Autonomous vehicles have been invented to increase the safety of transportation users. These vehicles can sense their environment and make decisions without any external aid to produce an optimal route to reach a destination. Even though the idea sounds futuristic and if implemented successfully, many current issues related to transportation will be solved, care needs to be taken before implementing the solution. This paper will look at the pros and cons of implementation of autonomous vehicles. The vehicles depend highly on the sensors present on the vehicles and any tampering or manipulation of the data generated and transmitted by these can have disastrous consequences, as human lives are at stake here. Various attacks against the different type of sensors on-board an autonomous vehicle are covered.
Automotive Cybersecurity Challenges for Automated Vehicles: Jonathan PetitSecurity Innovation
July 2016: Jonathan Petit, Principal Scientist at Security Innovation, discusses cybersecurity challenges for automated vehicles at the Automotive Vehicles Symposium.
Vision-based real-time vehicle detection and vehicle speed measurement using ...JANAK TRIVEDI
In recent trends, digital information to the industrial integration for the intelligent transportation system (ITS)
field is gaining importance for the researcher, academia, and industrial persons. Visual information helps to
manage traffic systems in the industrial forum to build smart cities in developed countries. This paper presents
vision-based real-time vehicle detection and Vehicle Speed Measurement (VSM) using morphology operation and
binary logical process for an unplanned traffic scenario using image processing techniques. Vehicle detection and
VSM help to reduce the number of accidents and improve road network efficiency. The bounding box size for
vehicle detection is flexible according to vehicles’ sizes on the road. We test this system with different colors and
dimensions for a selected Region of Interest (ROI). The ROI sets using the two-line approach. Here, we compare
the proposed system with the inter-frame difference method and the blob analysis method with recall, precision,
and F1 performance parameters.
'' Internet of Vehicles (IoV) ,,
IoV is basically INTERNET of VEHICLES, a strong network between vehicles and living.
IoT is a proposed development of the Internet in which everyday objects have network connectivity, allowing them to send and receive data.
The new era of the Internet of Things is driving the evolution of conventional Vehicle Ad-hoc Networks into the Internet of Vehicles (IoV).
Being in generation of Internet connectivity, there is a need to stay in safe and hassle free environment.
According to recent predictions, 25 billion “things” will be connected to the Internet by 2020, of which vehicles will constitute a significant portion.
Objectives
IoV – distributed transport fabric capable of making its own decisions about driving customers to their destinations
IoV should have communications, processing, storage, intelligence, learning and strong security capabilities .
To be integrated in IoT framework and smart cities technologies.
Extended business models and the range of applications ( including mediaoriented) current vehicular networks.
Types Of Communication IoV
The IoV includes mainly five types of vehicular communications
1.Vehicle-to-Vehicle (V2V).
2.Vehicle to-Roadside Unit (V2R).
3.Vehicle-to-Infrastructure of cellular networks (V2I) .
4.Vehicle-to-Personal devices (V2P)
5.Vehicle-to-Sensors (V2S).
Network elements of IoV
A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs
With the rapid development of Internet and communication technologies, vehicles that often quickly move in cities or suburb have strong computation and communication abilities. IoV is emerging as an important part of the smart or intelligent cities being proposed and developed around the world. IoV is complex integrated network system that interconnects people within and around vehicles,intelligent systems on board vehicles, and various cyber-physical systems in urban environments.
This project first gives a network model of IoV, and later provides an abstract taxonomy of IoV activation, maintenance, and applications. Finally, an analysis of challenges and future study directions in IoV is also provided.
we have analyzed the existing problems andhave given new approaches for the implementation of urban loTs. Researchers are heading towards big projects which aim at making complex architectures and networks for an advanced future.
Automotive Cybersecurity Challenges for Automated Vehicles: Jonathan PetitSecurity Innovation
July 2016: Jonathan Petit, Principal Scientist at Security Innovation, discusses cybersecurity challenges for automated vehicles at the Automotive Vehicles Symposium.
Vision-based real-time vehicle detection and vehicle speed measurement using ...JANAK TRIVEDI
In recent trends, digital information to the industrial integration for the intelligent transportation system (ITS)
field is gaining importance for the researcher, academia, and industrial persons. Visual information helps to
manage traffic systems in the industrial forum to build smart cities in developed countries. This paper presents
vision-based real-time vehicle detection and Vehicle Speed Measurement (VSM) using morphology operation and
binary logical process for an unplanned traffic scenario using image processing techniques. Vehicle detection and
VSM help to reduce the number of accidents and improve road network efficiency. The bounding box size for
vehicle detection is flexible according to vehicles’ sizes on the road. We test this system with different colors and
dimensions for a selected Region of Interest (ROI). The ROI sets using the two-line approach. Here, we compare
the proposed system with the inter-frame difference method and the blob analysis method with recall, precision,
and F1 performance parameters.
'' Internet of Vehicles (IoV) ,,
IoV is basically INTERNET of VEHICLES, a strong network between vehicles and living.
IoT is a proposed development of the Internet in which everyday objects have network connectivity, allowing them to send and receive data.
The new era of the Internet of Things is driving the evolution of conventional Vehicle Ad-hoc Networks into the Internet of Vehicles (IoV).
Being in generation of Internet connectivity, there is a need to stay in safe and hassle free environment.
According to recent predictions, 25 billion “things” will be connected to the Internet by 2020, of which vehicles will constitute a significant portion.
Objectives
IoV – distributed transport fabric capable of making its own decisions about driving customers to their destinations
IoV should have communications, processing, storage, intelligence, learning and strong security capabilities .
To be integrated in IoT framework and smart cities technologies.
Extended business models and the range of applications ( including mediaoriented) current vehicular networks.
Types Of Communication IoV
The IoV includes mainly five types of vehicular communications
1.Vehicle-to-Vehicle (V2V).
2.Vehicle to-Roadside Unit (V2R).
3.Vehicle-to-Infrastructure of cellular networks (V2I) .
4.Vehicle-to-Personal devices (V2P)
5.Vehicle-to-Sensors (V2S).
Network elements of IoV
A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs
With the rapid development of Internet and communication technologies, vehicles that often quickly move in cities or suburb have strong computation and communication abilities. IoV is emerging as an important part of the smart or intelligent cities being proposed and developed around the world. IoV is complex integrated network system that interconnects people within and around vehicles,intelligent systems on board vehicles, and various cyber-physical systems in urban environments.
This project first gives a network model of IoV, and later provides an abstract taxonomy of IoV activation, maintenance, and applications. Finally, an analysis of challenges and future study directions in IoV is also provided.
we have analyzed the existing problems andhave given new approaches for the implementation of urban loTs. Researchers are heading towards big projects which aim at making complex architectures and networks for an advanced future.
Traffic congestion has become one of the largest annoyances to countries like the United States and China when it comes to economic competitiveness, livability, safety, and long-term environmental sustainability. Congestion on freeways and roads is a major component of and contributor to delay. Emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), and connected vehicles provide opportunities to mitigate traffic congestion.
As one of the largest technology providers in China, Asiainfo Data is leading a city-scale Smart Transportation project in City of Wuxi, one of the national centers for IoT innovation in China. In this talk, we would like to share our real-world experiences in using AI and big data technologies to implement cutting-edge technologies transformation of Wuxi’s transportation systems. In this project, we collaborate with China Telecom, the Traffic Management Research Institute, smart vehicle makers, and many influential researchers on traffic management worldwide. We will showcase scenarios on public transportation prioritization, car-road coordination, and region-wide traffic signal optimization by utilizing AI modeling and the most advanced IoT technologies.
Speaker
Jian Chang, AsiaInfo, Chief Technology Officer
2015 D-STOP Symposium session by CTR's Mike Walton. Watch the presentation at http://youtu.be/yd0DJWndSmo?list=PLWQCGQLl10mwkino_uNmTO4JXOg5oCWtU
Get symposium details: http://ctr.utexas.edu/research/d-stop/education/annual-symposium/
Wearables, IoT and consumer robotics are amongst the hottest topics highlighted at Startup Village 2014. They attract both younger generation teams and investors with international track, promising significant growth potential in future.
The use of traffic lights to control traffic flow at intersections is a long-standing means to promote traffic safety and efficiency. While traffic lights and intersection-based signs are the predominant means of controlling traffic flow, other systems of intersection-based traffic management have been the subject of some experimentation. US20140278029 illustrates the self-organizing smart traffic control system. The self-organizing smart traffic control system exploits vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. V2V and V2I communication enables development of the dynamic traffic control plan (DTCP) by the central city traffic planner that can resolve the travel-priority conflict in the potential-conflict zone and optimize the traffic flow.
Vehicle detection by using rear parts and tracking systemeSAT Journals
Abstract Vision of Indian government; of making 100 smart cities, attracts our attention to intelligent transport system. Traffic flow analysis is a part of intelligent transport system. It mainly contains three parts: vehicle detection, classification and vehicle tracking par t. Recently, there are different detection and tracking methods like computer vision based, magnetic frequency wave based etc. With the rapid development of computer vision techniques, visual detection has become increasingly popular in the transportation field. In urban traffic video monitoring systems, traffic congestion is a common scene that causes vehicle occlusion and is a challenge for current vehicle detection methods.In practical traffic scenarios, occlusion between vehicles often occurs; therefore, it is unreasonable to treat the vehicle as a whole. To overcome this problem we can use part based detection model. In our system the vehicle is treated as an object composed of multiple salient parts, including the license plate and rear lamps. These parts are localized using their distinctive color, texture, and region feature. Furthermore, the detected parts are treated as graph nodes to construct a probabilistic graph using a Markov random field model. After that, the marginal posterior of each part is inferred using loopy belief propagation to get final vehicle detection. Finally, the vehicles’ trajectories are estimated using a Kalman filter and a tracking-based detection technique is realized. This method we can use in daytime as well as night time and in any bad weather condition. Keywords vehicle detection, kalman filter, Markov model, tracking, rear lamps
Connected & Autonomous vehicles: cybersecurity on a grand scale v1Bill Harpley
A presentation which was given at 'How the Internet of Things is Changing Cyber Security - an event organised by Optimise Hub (Portsmouth University) on January 26th 2017 at Havant.
- This talk describes the issues relating to cybersecurity of Connected Cars and Autonomous Vehicles. It begins with an introduction to technology and standards. It then looks at the key security challenges and asks how prepared we are to deal with the future risks.
- It is a perfect case study in the challenge of achieving cybersecurity on a massive scale.
The Internet of Cars - Towards the Future of the Connected CarJorgen Thelin
No doubt you have heard the phrase “Internet of Things” and the new buzzword “IoT” been used more and more these days, but what does that mean in practice? The Tesla Model S is probably the most well-connected car on the planet at the moment, and in this presentation we will use that vehicle as a case study of some practical usage of IoT concepts and technology that is already being applied to modern automobiles.How far away are we from a future “Internet of Cars” and what will be the social and privacy impacts of more connected-car scenarios?
Artificial Intelligence in Autonomous Vehiclesijtsrd
An autonomous vehicle is one that uses a combination of sensors, cameras, radar, and artificial intelligence AI to travel between destinations without a human operator. It is designed to be able to detect objects on the road, maneuver through the traffic without human intervention, and get to the destination safely. It is fitted with AI based functional systems such as voice and speech recognition, gesture controls, eye tracking, and other driving monitoring systems. Several companies have announced their plan to get involved in autonomous or driverless and electric vehicle technology. This paper presents uses of AI technology in autonomous vehicles. Matthew N. O. Sadiku | Sarhan M. Musa | Abayomi Ajayi-Majebi "Artificial Intelligence in Autonomous Vehicles" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38514.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/38514/artificial-intelligence-in-autonomous-vehicles/matthew-n-o-sadiku
Blockchain and ai__architectures__challenges_and_future_directions_for_enabli...Hani Sami
Nowadays, nobody neglects the fact that #autonomous_vehicles are the future. Nevertheless, many problems stem from letting machines take control of the streets without embedding a sophisticated decision-making process within. This column spotlights the importance of #security in the smart #Internet_of_Vehicles paradigm, and the integration of #Blockchain and #Artificial_Intelligence for acquiring safety on the road by investigating in an #Edge-based architecture that benefits from the decentralized authority and network topology of a hybrid Blockchain in order to leverage highly accurate decision models. Challenges and future directions of such a combination are listed and discussed in the following article.
The full paper is available from:
https://www.researchgate.net/publication/340999407_AI_Blockchain_and_Vehicular_Edge_Computing_for_Smart_and_Secure_IoV_Challenges_and_Directions
Implementing Secured and Comport Transportation using Vehicular Ad-Hoc Networ...ijtsrd
VANET is the largest wireless communications research area. VANETs of rapidly moving vehicles can be inefficient or unreliable. With the passing of time, VANET technology advances via inter vehicle interaction, but many problems need to be resolved in order to strengthen the network. This paper simulates road traffic simulators in a way that ensures safe communication between different types vehicles and prevents traffic based congestion in the cities of India. Ms. Pooja Deshpande | Mrs. Vrushali Uttarwar | Ms. Ekta Choudhari "Implementing Secured and Comport Transportation using Vehicular Ad-Hoc Network for Realistic City Scenario" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29771.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/29771/implementing-secured-and-comport-transportation-using-vehicular-ad-hoc-network-for-realistic-city-scenario/ms-pooja-deshpande
Traffic congestion has become one of the largest annoyances to countries like the United States and China when it comes to economic competitiveness, livability, safety, and long-term environmental sustainability. Congestion on freeways and roads is a major component of and contributor to delay. Emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), and connected vehicles provide opportunities to mitigate traffic congestion.
As one of the largest technology providers in China, Asiainfo Data is leading a city-scale Smart Transportation project in City of Wuxi, one of the national centers for IoT innovation in China. In this talk, we would like to share our real-world experiences in using AI and big data technologies to implement cutting-edge technologies transformation of Wuxi’s transportation systems. In this project, we collaborate with China Telecom, the Traffic Management Research Institute, smart vehicle makers, and many influential researchers on traffic management worldwide. We will showcase scenarios on public transportation prioritization, car-road coordination, and region-wide traffic signal optimization by utilizing AI modeling and the most advanced IoT technologies.
Speaker
Jian Chang, AsiaInfo, Chief Technology Officer
2015 D-STOP Symposium session by CTR's Mike Walton. Watch the presentation at http://youtu.be/yd0DJWndSmo?list=PLWQCGQLl10mwkino_uNmTO4JXOg5oCWtU
Get symposium details: http://ctr.utexas.edu/research/d-stop/education/annual-symposium/
Wearables, IoT and consumer robotics are amongst the hottest topics highlighted at Startup Village 2014. They attract both younger generation teams and investors with international track, promising significant growth potential in future.
The use of traffic lights to control traffic flow at intersections is a long-standing means to promote traffic safety and efficiency. While traffic lights and intersection-based signs are the predominant means of controlling traffic flow, other systems of intersection-based traffic management have been the subject of some experimentation. US20140278029 illustrates the self-organizing smart traffic control system. The self-organizing smart traffic control system exploits vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. V2V and V2I communication enables development of the dynamic traffic control plan (DTCP) by the central city traffic planner that can resolve the travel-priority conflict in the potential-conflict zone and optimize the traffic flow.
Vehicle detection by using rear parts and tracking systemeSAT Journals
Abstract Vision of Indian government; of making 100 smart cities, attracts our attention to intelligent transport system. Traffic flow analysis is a part of intelligent transport system. It mainly contains three parts: vehicle detection, classification and vehicle tracking par t. Recently, there are different detection and tracking methods like computer vision based, magnetic frequency wave based etc. With the rapid development of computer vision techniques, visual detection has become increasingly popular in the transportation field. In urban traffic video monitoring systems, traffic congestion is a common scene that causes vehicle occlusion and is a challenge for current vehicle detection methods.In practical traffic scenarios, occlusion between vehicles often occurs; therefore, it is unreasonable to treat the vehicle as a whole. To overcome this problem we can use part based detection model. In our system the vehicle is treated as an object composed of multiple salient parts, including the license plate and rear lamps. These parts are localized using their distinctive color, texture, and region feature. Furthermore, the detected parts are treated as graph nodes to construct a probabilistic graph using a Markov random field model. After that, the marginal posterior of each part is inferred using loopy belief propagation to get final vehicle detection. Finally, the vehicles’ trajectories are estimated using a Kalman filter and a tracking-based detection technique is realized. This method we can use in daytime as well as night time and in any bad weather condition. Keywords vehicle detection, kalman filter, Markov model, tracking, rear lamps
Connected & Autonomous vehicles: cybersecurity on a grand scale v1Bill Harpley
A presentation which was given at 'How the Internet of Things is Changing Cyber Security - an event organised by Optimise Hub (Portsmouth University) on January 26th 2017 at Havant.
- This talk describes the issues relating to cybersecurity of Connected Cars and Autonomous Vehicles. It begins with an introduction to technology and standards. It then looks at the key security challenges and asks how prepared we are to deal with the future risks.
- It is a perfect case study in the challenge of achieving cybersecurity on a massive scale.
The Internet of Cars - Towards the Future of the Connected CarJorgen Thelin
No doubt you have heard the phrase “Internet of Things” and the new buzzword “IoT” been used more and more these days, but what does that mean in practice? The Tesla Model S is probably the most well-connected car on the planet at the moment, and in this presentation we will use that vehicle as a case study of some practical usage of IoT concepts and technology that is already being applied to modern automobiles.How far away are we from a future “Internet of Cars” and what will be the social and privacy impacts of more connected-car scenarios?
Artificial Intelligence in Autonomous Vehiclesijtsrd
An autonomous vehicle is one that uses a combination of sensors, cameras, radar, and artificial intelligence AI to travel between destinations without a human operator. It is designed to be able to detect objects on the road, maneuver through the traffic without human intervention, and get to the destination safely. It is fitted with AI based functional systems such as voice and speech recognition, gesture controls, eye tracking, and other driving monitoring systems. Several companies have announced their plan to get involved in autonomous or driverless and electric vehicle technology. This paper presents uses of AI technology in autonomous vehicles. Matthew N. O. Sadiku | Sarhan M. Musa | Abayomi Ajayi-Majebi "Artificial Intelligence in Autonomous Vehicles" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38514.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/38514/artificial-intelligence-in-autonomous-vehicles/matthew-n-o-sadiku
Blockchain and ai__architectures__challenges_and_future_directions_for_enabli...Hani Sami
Nowadays, nobody neglects the fact that #autonomous_vehicles are the future. Nevertheless, many problems stem from letting machines take control of the streets without embedding a sophisticated decision-making process within. This column spotlights the importance of #security in the smart #Internet_of_Vehicles paradigm, and the integration of #Blockchain and #Artificial_Intelligence for acquiring safety on the road by investigating in an #Edge-based architecture that benefits from the decentralized authority and network topology of a hybrid Blockchain in order to leverage highly accurate decision models. Challenges and future directions of such a combination are listed and discussed in the following article.
The full paper is available from:
https://www.researchgate.net/publication/340999407_AI_Blockchain_and_Vehicular_Edge_Computing_for_Smart_and_Secure_IoV_Challenges_and_Directions
Implementing Secured and Comport Transportation using Vehicular Ad-Hoc Networ...ijtsrd
VANET is the largest wireless communications research area. VANETs of rapidly moving vehicles can be inefficient or unreliable. With the passing of time, VANET technology advances via inter vehicle interaction, but many problems need to be resolved in order to strengthen the network. This paper simulates road traffic simulators in a way that ensures safe communication between different types vehicles and prevents traffic based congestion in the cities of India. Ms. Pooja Deshpande | Mrs. Vrushali Uttarwar | Ms. Ekta Choudhari "Implementing Secured and Comport Transportation using Vehicular Ad-Hoc Network for Realistic City Scenario" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29771.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/29771/implementing-secured-and-comport-transportation-using-vehicular-ad-hoc-network-for-realistic-city-scenario/ms-pooja-deshpande
Taking into consideration the drivers’ state might be a serious challenge for designing new advanced driver
assistance systems. During this paper we present a driver assistance system strongly coupled to the user. Driver
Assistance by Augmented Reality for Intelligent Automotive is an augmented reality interface informed by a several
sensors. Communicating the presence of pedestrians or bicyclists to vehicle drivers may end up in safer interactions
with these vulnerable road users. Advanced knowledge about the presence of these users on the roadway is
particularly important when their presence isn't expected or when these users are out of range of the advanced safety
systems that are becoming a daily feature in vehicles today. For example, having advanced knowledge of a pedestrian
walking along a rural roadway is important to increasing driver awareness through in-vehicle warning messages that
provide an augmented version of the roadway ahead. Voice recognition system through an android platform adds
some good flavour during this project. The strategy of voice recognition through this platform is achieved by
converting the input voice signal into text of string and subsequently it's transmitted to embedded system which
contains an arduino atmega328 microcontroller through Bluetooth as a technique of serial communication between an
android application and a control system. The received text string on an arduino is also displayed on the AR Glass. As
connected vehicles start to enter the market, it's conceivable that when the vehicle sensors detect a pedestrian on a
rural roadway, the pedestrian presence is also communicated to vehicles upstream of the pedestrian location that
haven't reached the destination. This paper presents a survey of studies related to perception and cognitive attention
of drivers when this information is presented on Augmented Reality
Self driving Vehicles An Overview of Their Influence on Tech Societyijtsrd
Autonomous vehicles have emerged as a transformative technology that promises to revolutionize how we travel and interact with transportation systems. This article aims to provide a comprehensive introduction to autonomous vehicles, exploring their definition, underlying technologies, the current state of development, and their potential impact on society. By delving into autonomous vehicles benefits, challenges, and prospects, we can better understand this rapidly evolving field and its implications for various sectors, including transportation, urban planning, safety, and the economy. Sanath D Javagal "Self-driving Vehicles: An Overview of Their Influence on Tech Society" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd60012.pdf Paper Url: https://www.ijtsrd.com/engineering/automotive-engineering/60012/selfdriving-vehicles-an-overview-of-their-influence-on-tech-society/sanath-d-javagal
Design and Implementation of an Intelligent Safety and Security System for Ve...Hamzamohammed70
In recent years, the surge in car theft cases, often linked to illicit activities, has become a growing concern. Simultaneously, countries grappling with oil shortages have shifted towards converting vehicles to run on liquid propane gas, presenting new safety challenges for car owners. This paper introduces a novel integrated intelligent system designed to address the challenges of car theft and safety concerns associated with gas-based vehicles. By seamlessly integrating these concerns into a single system, it aims to achieve significantly improved performance compared to traditional alarm systems. The proposed system consists of three primary parts: the car security subsystem, an Internet of Things (IoT)-based real-time car tracking subsystem, and the car safety subsystem. Utilizing key technologies such as the Arduino Microcontroller, Bluetooth module, vibration sensor, keypad, solenoid lock, GSM module, NodeMCU microcontroller, GPS module, MQ-4 gas sensor, flame sensor, temperature sensor, and Bluetooth module, the system aims to provide a comprehensive solution for the mentioned issues. Furthermore, the vibration sensor plays a crucial role in identifying unauthorized vehicle operations. Its significance lies in detecting the vibrations emanating from the running engine. Concurrently, other modules and sensors are utilized for real-time tracking and enhancing vehicle safety. These measures include safeguarding against incidents like fire outbreaks or gas leaks within the gas container. Finally, the system was compiled and practically tested, with results that worked well. This work provides some basic steps to enhance vehicle safety and security, as well as to prevent theft and overcome safety concerns related to gas leaks
Advancements and Hurdles in the Evolution of Automotive Wireless Interfaces: ...IJCI JOURNAL
The integration of wireless interfaces into vehicles has posed some challenges for the automotive industry over the years. While manufacturers strive to impress consumers with cutting-edge features, these features also bring security risks that cannot be ignored. To prevent potentially fatal incidents, a thorough protocol must be established to address system vulnerabilities. As the modern century moves towards an era of autonomous vehicles, security must be a top priority to avoid compliance breaches and delays in feature development. The significance of vehicle interfaces in the modern automotive industry cannot be overstated.
The present study aims to explore the prospective advantages and challenges associated with the integration of wireless interfaces in the automotive industry. This analysis will primarily focus on the latest technological advancements in vehicle technology and the critical need to secure against possible cyber-attacks. A wide range of topics will be covered in this paper, from the evolution of vehicle interfaces to the industry’s hurdles and strategies to minimize the risks associated with cyber threats. The objective of this study is to provide a comprehensive understanding of wireless interfaces in the automotive sector, including the benefits of implementing such technology, the challenges that it poses, and the measures needed to maintain the security and safety of vehicles, as well as the passengers.
Problems in Autonomous Driving System of Smart Cities in IoTijtsrd
This paper focuses on the problems and challenges during self driving. In the modern era, technologies are getting advanced day by day. The field of smart city has introduced a new technology called ""Autonomous Driving"". Autonomous driving can be defined as Self Driving, Automated Vehicle. Google has started working on this type of system since 2010 and still in the phase of making changes in this technology to take it to a higher level. Any technology can reach up to an advanced level but it cannot provide a full fledged result. This paper facilitates the researchers to understand the problems, challenges and issues related to this technology. Shweta S. Darekar | Dr. Anandhi Giri ""Problems in Autonomous Driving System of Smart Cities in IoT"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30079.pdf
Paper Url : https://www.ijtsrd.com/computer-science/other/30079/problems-in-autonomous-driving-system-of-smart-cities-in-iot/shweta-s-darekar
Global autonomous vehicle market size is projected to reach around US$ 200.31 Billion by 2030. The dream of seeing fleets of driverless cars efficiently delivering people to their destinations has captured consumers' imaginations and fuelled billions of dollars in investment in recent years.
12 part framework to structure safety assessment for autonomous drivingZiaullah Mirza
NHTSA: National Highway Traffic Safety Administration
An agency of the Executive Branch of the U.S. government who has developed a 12-part framework to structure safety assessment for autonomous driving.
Algorithmic decision-making in AVs: understanding ethical and technical conce...Araz Taeihagh
Autonomous Vehicles (AVs) are increasingly embraced around the world to advance smart mobility and more broadly, smart and sustainable cities. Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently and more safely than human drivers and offering various economic, social and environmental benefits. However, algorithmic decision-making in AVs can also introduce new issues that create new safety risks and perpetuate discrimination. We identify bias, ethics and perverse incentives as key ethical issues in the AV algorithms’ decision-making that can create new safety risks and discriminatory outcomes. Technical issues in the AVs’ perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance of the AV system. This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public. We discuss steps taken to address these issues and increase the accountability of AV stakeholders, highlight the existing research gaps and the need to mitigate these issues through the design of AV’s algorithms and of policies and regulations to fully realise AVs’ benefits for smart and sustainable cities.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
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The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
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Autonomous vehicles: A study of implementation and security
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 11, No. 4, August 2021, pp. 3013~3021
ISSN: 2088-8708, DOI: 10.11591/ijece.v11i4.pp3013-3021 3013
Journal homepage: http://ijece.iaescore.com
Autonomous vehicles: A study of implementation and security
Firoz Khan1
, R. Lakshmana Kumar2
, Seifedine Kadry3
, Yunyoung Nam4
, Maytham N. Meqdad5
1
Higher Colleges of Technology, United Arab Emirates
2
Hindusthan College of Engineering and Technology, Coimbatore, India
3
Faculty of Applied Computing and Technology, Noroff University College, Kristiansand, Norway
4
Department of Computer Science and Engineering, Soonchunhyang University, South Korea
5
Al-Mustaqbal University College, Hillah, Iraq
Article Info ABSTRACT
Article history:
Received Aug 1, 2020
Revised Dec 21, 2020
Accepted Jan 13, 2021
Autonomous vehicles have been invented to increase the safety of
transportation users. These vehicles can sense their environment and make
decisions without any external aid to produce an optimal route to reach a
destination. Even though the idea sounds futuristic and if implemented
successfully, many current issues related to transportation will be solved,
care needs to be taken before implementing the solution. This paper will look
at the pros and cons of implementation of autonomous vehicles. The vehicles
depend highly on the sensors present on the vehicles and any tampering or
manipulation of the data generated and transmitted by these can have disastrous
consequences, as human lives are at stake here. Various attacks against the
different type of sensors on-board an autonomous vehicle are covered.
Keywords:
Autonomous vehicles
Cooperative driving
LiDAR
Security
Ultrasonic sensors
This is an open access article under the CC BY-SA license.
Corresponding Author:
Yunyoung Nam
Department of Computer Science and Engineering
Soonchunhyang University
Asan 31538, South Korea
Email: ynam@sch.ac.kr
1. INTRODUCTION
Over the years the automobile industry has been technologically improving and growing
significantly. The developments in incorporating computer systems and computerization of mechanical and
manual functions have improved the features of vehicles. More and more new cars are incorporating driver
assisting features like adaptive cruise-control, lane departure warning systems and self-parking systems
among other features [1, 2]. These features have reduced human dependency for the vehicles and given rise
to vehicles that are partly autonomous in nature. Additional features with the help of sensors and on-board
cameras have given rise to self-driving cars. Pushing this envelope further is the development of autonomous
vehicles. These are a step further where the vehicles can navigate from a source to a destination by the use of
various technologies, without any human intervention. These autonomous vehicles have the potential to
significantly alter transportation and how humans travel in the future on the roads. The benefits of
autonomous vehicles are significant, be it in use for transporting the elderly and disabled, or in the use in
dangerous war zones where human life loss can be expected [3]. Other benefits can include reduction in
traffic congestion, reduction in fuel consumption and optimal usage of the road infrastructure. These vehicles
further aid in reducing traffic accidents which in turn provides cascading benefits like reduction in insurance
costs, reducing loss of human life. Other benefits include reduction in carbon emissions and lesser air
pollution. Autonomous vehicles have various technologies like radars, sensors, global positioning system
(GPS) and on-board cameras that help it to detect the surroundings and navigate. The parts of an autonomous
vehicle are highlighted in Figure 1. The data which is sensed using these technologies are fed into advanced
2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 11, No. 4, August 2021 : 3013 - 3021
3014
control systems present in these vehicles. These systems make relevant decisions regarding navigation and
interpreting obstacles that may be present. Also interpreted are traffic signals and signage that help the
vehicle to have a smooth movement from a source to a destination while accounting for the nearby vehicles
on the road. Even though there are various benefits of using autonomous vehicles, there are also issues
related to these vehicles. The costs of these vehicles will generally be higher than the comparable non-
autonomous vehicles. This is due to the high amount of technology present in these vehicles [4]. The
technology itself is not mature enough and still at its early stages, where developments are happening by the
day. Other issues include accountability of accidents, security issues of technologies used, privacy issues
related to consumer data, insurance regulation issues.
Figure 1. Autonomous vehicle components
Many companies including Google are involved in the development of these autonomous cars and
several of the Google cars have competed around 2 million miles across various cities in the United States
(US). But other companies like Uber technologies and Tesla motors are fast catching up and introducing their
own autonomous vehicles on the roads [5]. This paper will be looking at the market penetration of
autonomous vehicle and security issues related to the adoption of autonomous vehicle. Technological and
non-technological issues related security of autonomous vehicles implementation will be looked at. The first
section of the paper will address the benefits of autonomous vehicles, and the later part will cover the
implementation issues with a specific look at security attacks against autonomous vehicles. The paper will be
finished off by policy recommendations to address these issues with related to security and general
adoptability of autonomous vehicles.
2. BENEFITS OF AUTONOMOUS VEHICLES
The automation system of automated vehicles follows three phases depicted in Figure 2 (i.e. `Sense',
`Understand', `Act'). The automotive sector is going to be revolutionized by the adoption of autonomous
vehicles. It needs to be seen if the adoption of these vehicles will outweigh and counteract the negatives
associated with it. There are several benefits associated with the use of autonomous vehicles in
transportations. The technology can be used in different type of vehicles like buses, where they can co-exist
with a smart city to offer adaptive routes based on low and high-demand routes. They can also be used as
taxis which can cater to people’s needs. Another area of use is, heavy hauling trucks on long distance
transportation between far reaching cities. These vehicles can also be effectively used in the military so that
soldiers’ lives are not put at risk while encountering dangerous warzones [6]. The following section will look
at some of the far reaching benefits associated with autonomous vehicles and associated use [7].
2.1. Safety
These vehicles can be used to reduce the number of crashes on the road. It has been found that
drivers are getting increasingly distracted behind the wheel with respect to drunk driving, speeding and
increased usage of smartphones. This in effect is contributing to large losses in terms of currency, human
lives and human injuries. The autonomous vehicles are programmed to avoid accidents and cause less
disruptions in road traffic. However, having said that it was recently found that a driverless car from Uber
went through a red light in San Francisco without stopping [8]. The autonomous vehicles are designed to
navigate through any road infrastructure and has been successful to do so, so far. Advancements in
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technologies used in these vehicles have made them much more dependable and safer even though the
maturity of this technology has been challenging. Humans comprehending objects and traffic while driving is
easier than autonomous vehicles and these have to be explicitly programmed and the evasive behavior
depends on the object encountered by the vehicle. The vehicle has to successfully understand the situation at
hand and come with a suitable counter-measure. If loss of human life is inevitable, then an important
question to be asked is whether the safety of the vehicle occupants is more important than the safety of the
pedestrians. These types of liabilities can be a huge hindrance for successful adoption. Another aspect of
safety can be brought about by the creation of an ecosystem of cooperative vehicles on the roads [9]. For
autonomous vehicles to be successful, an ecosystem consisting of road-side units (RSUs) and vehicle to
vehicle (V2V) communication infrastructure needs to be developed. There needs to be a high level of
interaction between these devices which will give rise to cooperative driving to increase the safety and
functional benefits of autonomous vehicles.
Figure 2. Data flow in an autonomous vehicle
2.2. Congestion and traffic management
The current state of road infrastructure is facing a huge amount of traffic congestion and tailback
during peak times. These are primarily due to human’s not anticipating slow upcoming traffic and normal
stop and go durations. Another contributing factor is the low level of patience of drivers, where they change
lanes frequently. The use of autonomous vehicles can help in coordinating traffic on highways and reduce
tailbacks [9]. Autonomous vehicles can reduce the distances between themselves to have more vehicles on
the road and the stop and go durations are considerably reduced. These in effect produces more efficient use
of the roads infrastructure. Another benefit due to this, is the reduction in fuel consumption as the vehicle
slowdown is reduced and thus carbon emissions are also reduced. Parking issues can also be considerably
reduced in highly commercial areas. The autonomous cars can drop off their passengers where needed and go
and self-park at a further parking area without human intervention. These vehicles can then be summoned to
pick up its passengers when needed. These can give rise to parking savings on a large scale.
2.3. Human behavior
The autonomous cars can be a huge advantage for the people too young to drive, elderly and
physically disabled [10]. These populations can be effectively transported from one location to another
without any external person or aid. The cars can be used as mobile offices for working professionals and can
provide entertainment while on a long distance commute. The benefit includes reduction of driver fatigue and
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a smoother travel experience. A recent survey has found that more and more young people are opting to use
public transportation rather than driving, as they would have more time to engage in other activities like
browsing the internet or reading books. These people could be early adopters of autonomous vehicles. If
there is an absence of public transportation in a city, shared autonomous vehicles can support the need of the
residents of these cities. Humans depending on older technologies of mass transportation like trains can thus
be reduced. Another potential benefit is avoiding the need to have private chauffeurs or the need to get
driving licenses. Human error which can cause accidents, will be efficiently negated by the use of
autonomous vehicles.
2.4. Adoption by specific sectors
The autonomous vehicle technology is being more and more adopted by various sectors like mining,
freight transportation and the military among other industries. The trucking industry is adopting autonomous
vehicle technologies to aid transportation over a large distance [11]. The adoption has reduced the need for
drivers and increased fuel economy of these trucks. A behavior called as platooning is being used to by these
trucking companies using a large number of autonomous vehicles which travel in tandem. In the mining
industry, large autonomous earth movers are being used highly effectively. These earth movers have a fixed
route from a source to a destination and are being very effective. The autonomous vehicles assist in
improving the safety of humans as there are lesser number of people working around heavy equipment [12].
With autonomous mining vehicles, specialized equipment operators are not needed, which in turn improves
productivity. The military sector is a huge embracer of autonomous vehicle technology. The military
considers the autonomous vehicles as a huge enabler for its soldier protection [13]. Driverless military trucks
can be deployed in sensitive areas to deliver essential items and commodities without human intervention.
3. IMPLEMENTATION ISSUES
Even though there are many advantages to implementing autonomous vehicles, its adaptability on a
large scale is still in question. Studies on large scale implementations and its ramifications are still being
done in real life environments and continuous further research is needed. The success of implementing
autonomous vehicles depends highly on the costs associated with manufacturing, liability when accidents
occur and licensing issues. Furthermore, as these are vehicles are operating using computing technologies,
the security and privacy aspects is a very important field of study [14]. The following section will look some
of the major inhibitors of adopting autonomous vehicles in a major scale.
3.1. Technology issues
The autonomous vehicles depend solely on its onboard sensors, GPS, light imaging detection and
ranging (LiDAR) and camera systems. Any failure of these devices can contribute to serious consequences.
Failures in sensors will need to be efficiently communicated and should be easy to detect and replace. Not
just sensors, but computer and systems malfunctions can bring about disastrous consequences. These could
be a major failure or even a minor glitch for essential items of an autonomous vehicles, like its braking
system. All technologies on the autonomous vehicles have responded well during optimal conditions. But
during extreme weather conditions, like hail storms, heavy rains or snowy conditions, the system will not
operate perfectly and will interfere with the sensors and camera systems. Sufficient research on these areas
still needs to be done to ascertain the reaction of these vehicles. Even if the autonomous vehicles can self-
drive from a location to another, human intervention would still be needed to operate it safely. This could be
an issue, as the future drivers could be heavily reliant on the technology and may have forgotten the
necessary skills to successfully drive a vehicle. Pre-programming is done on the autonomous vehicles and the
presence of artificial intelligence technologies help the vehicles to get accustomed to newer environments
and situations on the road. A known limiting factor is that the vehicles are not programmed to interpret hand
signals shown by other drivers or situations where the traffic is controlled by police officer manually using
hand signals. Another issue is the reliability of dependency on GPS systems. Various examples have been found
where people have been navigated to non-existent roads and bridges due to the inaccuracy of the technology.
3.2. Vehicle costs
A large scale adoption of autonomous vehicles will be seriously impeded due to the manufacturing
costs of these vehicles. Various technologies including sensors, global positioning systems, communications
from the vehicles and artificial intelligence software are needed for each vehicle. An essential piece of
equipment, LiDAR, is very expensive currently and so are the processing requirement equipment. These
prices put the autonomous vehicles cost beyond the purchasing power of average people who own cars. The
success of autonomous vehicles can only be successful, if adopted on a large scale, which cascades on to
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lower prices of the same vehicles in the future. This is like any technological adoptions, be it computers or
electric cars, future prices can be reduced only with technological advances and large scale production. Even
though early adopters may pay higher prices, the costs can be brought down in the future. This will remain a
significant implementation challenge for the foreseeable future.
3.3. Liability and law issues
Even though autonomous cars have been tested for many thousand kilometers on public roads, still
there are chances of accidents happening. This raises the concern of liability in case of such accidents. Who
is at fault? Is it the person in the driver seat of the vehicle, the manufacturer or the algorithm developer?
Another aspect is the insurance issues for such accidents [15]. In most cases humans are exempted from
penalty when accident occur beyond the control of the driver. Legal precedents are also not existing in most
countries where autonomous vehicles may be deployed. These are no existing laws or legalities around
accidents involving autonomous cars. There are no central regulatory bodies existing country-wide to
regulate the use of autonomous vehicles. Laws and rules applicable in one state may be different from
another state.
3.4. Security and privacy issues
The most major issue with autonomous vehicles is in the field of security as there are numerous
computing devices and communications occurring from the vehicle to other vehicles or various components
within the vehicle itself. Hackers can get into the system and manipulate the operations of the vehicle [16].
This can be extremely dangerous as the vehicle can be controlled by people to do nefarious activities.
Terrorist can use the vehicle loaded with bombs to target key establishments [17]. They can be also used as
rolling missiles to target and create chaos on the roads. As vehicles are interconnected and communicate with
each other, any malware can spread quickly through the entire vehicular network to penetrate a large number
of vehicles. These malwares can be dangerous and can be used to do controlled and coordinated attacks.
A security breach of autonomous vehicles will allow a hacker to do simple attacks like relaying false
information from the sensors to taking complete control over all the operations of the vehicle. Security
attacks against autonomous vehicles will be looked at in more detail in the next section. For the successful
operation of an autonomous vehicle, lots of personal data is collected and stored. These data are shared
among other vehicles and RSUs. The ecosystem of cooperative vehicles is built on the principle of sharing
data [18]. This is a major concern for privacy advocates. Questions have been raised about what type of data
will be stored, what will be shared, who will it be shared to, and what will the data be used for? Most humans
do not want share the vehicular data as the data may be used against them in case of accidents and a court
case. Also, the driving mannerisms will be used by insurance providers to increase the insurance costs if
erratic driving behavior is observed. Location data is also tracked and shared by autonomous vehicles. This
could enable tracking of users and can be misused by hackers for monitoring or even worse, can be used by
criminals to track the location of victims.
3.5. Ethical issues
There are several non-technical ethical issues with the use of autonomous cars. Issues are being
raised as to what to do in case of an emergency. Should the vehicle protect the occupants of the car or the
pedestrians? Should the vehicle try to avoid animals crossing the street which may cause injuries to the
passengers? How should the programming be done in such cases and who takes the decision during these
programming? If the passenger is being robbed or being attacked by a criminal involving a carjacking, how
should the autonomous vehicle respond? Can the vehicle run a red light or break traffic laws in an
emergency? Other ethical issues faced would be how the vehicle to responds to rough, ignorant other non-
autonomous drivers on the road. Should the vehicle take evasive measure when confronted with such
situations? Ethical issues can be handled sufficiently by human drivers, but may not be handled in a humane
way by the autonomous cars as, in the end, they are just machines running on programmed code. A high level
of maturity is needed in the built-in processing software before the widespread implementation of
autonomous vehicles.
3.6. Increased traffic
One of the major issue of convenience is the success and furthermore its overall usage. A major
issue with the success of autonomous vehicles is its convenience. The more convenient it is, the more the
number of people who will use it. This will give rise to increase in traffic due to unnecessary usage [19].
Earlier, with normal vehicles, when humans were feeling lazy for less critical travels, they would avoid the
travel. But now, with autonomous vehicles, these may happen more often.
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4. SECURITY ATTACKS
The manufacturers have been constantly working to improve the dependability of autonomous
vehicles. These are primarily achieved by increasing the accuracy of data sensed by the various sensors on
these vehicles. Tesla is considered to be a market leader in autonomous vehicles and even one of their cars, a
Model S, crashed onto a truck and caused a death [20]. This accident highlights the importance of having
accurate sensors that perform in normal road conditions. Even more important is the fact is that the sensors
should not be vulnerable to external inputs and hacks. If external inputs or hacks are successful, then the
sensors may produce false readings and sensor malfunctions [21]. This in effect will produce disastrous
consequences on the road. The major categories of sensors used in autonomous vehicle are ultrasonic
sensors, millimeter wave radars (MMW), on-board cameras, LiDAR and GPS [22]. Various attacks have
been conducted against, both in- lab and in the external environment to test contactless attacks against these
sensors. The attacks and its effects against each category of sensors will be reviewed in the following sections.
4.1. Attacks against ultrasonic sensors
The ultrasonic sensors are used to monitor the front and back of vehicle to detect obstacles and aid
in the parking of a vehicle. The ultrasonic sensors work on the principle of emitting ultrasonic pulses and if
an obstacle is present, these pulses are reflected back. The time taken to receive this reflected waves are
measured, which is used to measure the distance of the obstacle from the sensor [23]. Following are some of
the attacks conducted against ultrasonic sensors. Jamming attack-in a jamming attack an ultrasonic signal is
created in the same frequency range as the vehicle’s sensor operate and continually transmits the signal. Due
to this the ultrasonic sensors does not detect obstacles and the vehicle collides with them. Spoofing attack-the
same equipment used for jamming can be used to send ultrasonic signals, but instead of sending the signal
continually, the spoofing signal is sent a specific time to trick the sensors. Due to this, the ultrasonic sensor
detects an obstacle, even when one does not exist. Acoustic quieting method is used to hide the obstacles
from being detected by an ultrasonic sensor. The sensors do not detect sound absorption materials like plastic
foams and fur. If an object is covered with this material, the detection is avoided as the echoes as not returned
by the material.
4.2. Attacks against MMW radars
MMW radars works using millimeter waves, which are considered to be waves whose frequencies
are lesser than visible light but higher than the radio frequencies. These waves are transmitted out as probes
and the reflections are measures to find various parameters including but not limited to examples like time
and frequency difference. There are primary three types of MMW radars used on autonomous vehicles; Short
range MMW radars used for blind spot detection, Medium range MMW radars used for collision avoidance
and on road people detection, and long range MMW radars are used in adaptive cruise control systems at
high speeds. A jamming attack against MMW radars are their effects are as seen below. Jamming attacks-a
signal generator is used to send out constant signals in the same frequency range of the actual MMW radars
on the vehicles. The jamming signals generated increases the noise levels and signal to noise ratio is
considerably reduced. Due to this, the radar system existing on the vehicle fails and does not detect any
vehicle or obstacle in front of it. This could lead to disastrous consequences where an autonomous vehicle
may run into an obstacle in front of it.
4.3. Attacks against on-board cameras
On-board cameras use visible light and optics to comprehend visual recognition of the environment
where the autonomous vehicle is being used. The cameras are especially useful in detection lanes, traffic
signals and road signs. This data is used to enhance the driving and stopping capabilities of autonomous
vehicles. The most major attack against on-board cameras is called as conducting a blinding attack. The goal
of the attack is to affect the sensor of the camera by exposing it to a strong intensity light that temporarily
blinds the camera from recognizing actual traffic signals or objects. Many type of light emitting devices can
be used to conduct this attacks. Laser pointers and LED light sources are some of such prominent light
emitting devices. It takes 4 to 5 seconds before the camera recovers from such a blinding attack. The attack
can be done as a constant light source hitting the camera or exposing the camera to a burst of light. The latter
is considered to be more effectively as the attacks cannot be easily detected and by the time the camera
recovers, it is attacked again.
4.4. Attacks against the LiDAR system
LiDAR’s are devices which use rotating laser beams. The device is used in the detection of obstacles
and helps to navigate the autonomous vehicle through its surroundings. The data generated by the LiDAR
system provides information about where obstacles exist in an environment and the position of the
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autonomous vehicle with respect to the obstacle [24]. LiDAR data can show curvatures in roads, roadside
infrastructure and vegetation and elevation of roads. Attacks on LiDAR system can create noise, fake
reflections and spoof fake objects. Some attacks that can make this possible are highlighted below. Relay
attack-the purpose of this attack is to relay the original reflected signal from an object to be coming from
another position. This way the autonomous vehicle is tricked into understanding the false position of a real
object as being either closer of farther away. The attack is conducted by using transceivers which receive the
original reflected signal and retransmits it. This way the same reflected data is made to appear as coming and
being detected in many locations. Spoofing attack-the previous attack can be extended further to generate non-
existent objects and spoofed to trick the LiDAR system. The system detects several instances of the same object
existing throughout its environment, which will hamper the optimal behavior of the autonomous vehicle.
4.5. Attacks against the GPS
GPS satellites are used by autonomous vehicles to identify geographic locations of themselves [25].
The geographic locations and vehicle identities provided by these satellites are a very important element for
the success of autonomous vehicle implementation. Positioning attack-in this attack, a malicious user can
exploit the behavior by using a GPS satellite simulator. This device can be used to provide false information
about locations to unsuspecting vehicles, if the signal from this device is stronger than the authentic GPS
satellites [26]. The vehicles are deceived to think they are in a different location than they actually are which
will hamper the effective behavior of the autonomous vehicles. Also, another variant of the positioning attack
is the tunnel attack, where GPS signals are temporarily not available in tunnels. An attacker provides false
information about geographic positions once the vehicle leaves the tunnel and before it receives authentic
GPS signals.
4.6. Attacks against the communication system
Denial of Service attacks is a very serious attack where the main aim is to prevent the authentic
users from accessing the network and network resources [27]. The attackers transmit dummy messages into
the network to overwhelm the current users, thus reducing the efficiency and performance of the network.
This attack is very significant in nature such that, even if the attack is detected, it is very difficult to correct.
In an ecosystem of cooperative vehicles, a vehicle can falsify a large number of fake identities and transmit
dummy messages to other vehicles and RSUs [28]. These dummy messages can be misleading and can cause
other vehicles to respond in unforeseen ways. Distributed denial of service (DDoS) attacks is a variant of the
DoS attack where multiple vehicles collude and attack on a legitimate vehicle at one time from different
locations. Multiple vehicles can attack a single vehicle from different locations and time, so that the target
vehicle cannot communicate to other vehicles or the RSU. The wireless medium used in autonomous vehicle
network, increases the possibilities of these attacks. Furthermore, the rapid change in topology and high
mobility of vehicles aids in more instances of these attacks and detection becomes difficult.
5. RECOMMENDATIONS FOR SUCCESSFUL IMPLEMENTATION
Further detailed research needs to be done on autonomous vehicles and the technologies used in it.
This will aid further expansion of autonomous vehicles and its penetration in the market. Guidelines needs to
be created by government which aid the development and usage of autonomous vehicles. One such rule
specified by the US Department of Transportation states that every vehicle on the roads of US should have
V2V communications enabled by 2023 [29]. Successful V2V communication will enable autonomous
vehicles to warn each other about traffic disturbances and obstacles [30]. Standards needs to be created for
data storage and data communication which will aid development of unified standards [31]. These will in
turn help manufacturers create autonomous vehicles without worrying about liabilities in case of failure.
6. CONCLUSION
Autonomous vehicles are not a distant future and vehicle manufacturers are embracing the
technology where leading manufacturers are foraying into this field. These vehicles depend on on-board
sensors and technical equipment for successful navigation and understanding the environment it is present in.
Valid and accurate sensor data is critical for the successful router planning, emergency maneuvers and route
calculations. In this paper, the major success factors and inhibitors of autonomous vehicles have been
discussed. The paper also discusses a critical aspect of security of autonomous vehicles and why security is
important. Security attacks on various sensors and on-board cameras have exposed several vulnerabilities of
the autonomous vehicles. Also critical for autonomous vehicles success is the presence of wireless
technologies for cooperative driving. The autonomous vehicles collect a variety of data from other vehicles
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and their surroundings. The wireless connectivity exposes the vehicles to DoS and malware attacks. For
efficient implementation, a secure wireless technology which encompasses the highest level of privacy and
security is critical.
ACKNOWLEDGEMENTS
This work was supported by the Soonchunhyang University Research Fund.
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