This document summarizes a research project called PROSPECT that aims to improve active safety systems for protecting vulnerable road users like cyclists and pedestrians. The project will develop and test new sensor and control technologies on three vehicle demonstrators. Key findings from accident analyses were used to identify the most common accident scenarios and develop test cases to evaluate the demonstrator vehicles. Naturalistic observations of vehicle-cyclist and vehicle-pedestrian interactions were also conducted. The demonstrator vehicles will feature expanded sensor fields of view, improved detection and classification of vulnerable road users, and controls that can automatically steer or brake to avoid collisions. The goal is to enhance safety and address limitations of current systems through innovative sensing and reaction capabilities.
Paper No.19-0277-O
Improving the Effectiveness of Active Safety Systems to Significantly Reduce Accidents with Vulnerable Road Users - The Project Prospect (Proactive Safety for Pedestrians and Cyclists)
ILONA CIEŚLIK
IDIADA Automotive Technology, Spain
JORDANKA KOVACEVA
Chalmers University of Technology, Sweden
MARIE-PIERRE BRUYAS
Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux (IFSTTAR), France
DAVID R. LARGE
University of Nottingham, United Kingdom
MARTIN KUNERT
Robert Bosch GmbH, Germany
SEBASTIAN KREBS
Daimler AG, Germany MAXIM ARBITMANN
Continental Teves AG & Co.OHG, Germany
Intelligent Transportation Systems (ITS) is the application of computer, electronics, and communication technologies and management strategies in an integrated manner to provide traveller information to increase the safety and efficiency of the surface transportation systems.
These systems involve vehicles, drivers, passengers, road operators, and managers all interacting with each other and the environment, and linking with the complex infrastructure systems to improve the safety and capacity of road systems.
ITS is an emerging transportation system which is comprised of an advanced information and Telecommunications network for users, roads and vehicles.
Paper No.19-0277-O
Improving the Effectiveness of Active Safety Systems to Significantly Reduce Accidents with Vulnerable Road Users - The Project Prospect (Proactive Safety for Pedestrians and Cyclists)
ILONA CIEŚLIK
IDIADA Automotive Technology, Spain
JORDANKA KOVACEVA
Chalmers University of Technology, Sweden
MARIE-PIERRE BRUYAS
Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux (IFSTTAR), France
DAVID R. LARGE
University of Nottingham, United Kingdom
MARTIN KUNERT
Robert Bosch GmbH, Germany
SEBASTIAN KREBS
Daimler AG, Germany MAXIM ARBITMANN
Continental Teves AG & Co.OHG, Germany
Intelligent Transportation Systems (ITS) is the application of computer, electronics, and communication technologies and management strategies in an integrated manner to provide traveller information to increase the safety and efficiency of the surface transportation systems.
These systems involve vehicles, drivers, passengers, road operators, and managers all interacting with each other and the environment, and linking with the complex infrastructure systems to improve the safety and capacity of road systems.
ITS is an emerging transportation system which is comprised of an advanced information and Telecommunications network for users, roads and vehicles.
A VISION-BASED REAL-TIME ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM USING VEHICULA...JANAK TRIVEDI
In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method.
TTI’s Connected and Automated Vision for the Future
The Texas A&M Transportation Institute (TTI) shares an industry vision where no vehicles collide and people can use connected and automated transportation to transform how they live, work and interact with their environment. To achieve this vision, research, development and testing are needed on how vehicles, users and transportation infrastructure all work together. While automated vehicles are emerging and connected vehicle research is progressing, TTI believes the most significant gains in safety and mobility will occur at the nexus of these areas. TTI is creating a world-class research environment on the Texas A&M University campus where researchers can collaborate, new transportation paradigms can be created, and future mobility and safety can be showcased.
A Synopsis of Simulation and Mobility Modeling in Vehicular Ad-hoc Networks (...IOSR Journals
Abstract : Vehicular communication is considered to be a backbone for many critical safety applications. In
order to achieve a better implementation of any vehicular communication scenario, an efficient, accurate and
reliable simulator is essential. Various open source and commercial simulating tools are available for this
purpose. One of the key issues in this regard is the selection of a reliable simulator which implements all
standard algorithms and paradigms giving accurate results. In this paper, we first present IEEE standard and
protocols for vehicular communication, IEEE 802.11p and IEEE 1609.x, also known as WAVE protocol stack.
The paper then discusses the necessary requirements for a generic discrete event simulator which can be used to
simulate Vehicular Ad-hoc Networks. Since not all the network simulators can be used in the scenario of
vehicular communication, we highlight the key features of some network simulators in the context of vehicular
ad-hoc networks. The paper also highlights some of the implementation limitations in these simulators.
Furthermore, the paper presents a discussion on traffic simulators by emphasizing on the underlying mobility
models used in order to generate the realistic traffic patterns. A comparative study of both network and traffic
simulators show the pros and cons of these simulation tools. The paper suggests the appropriate choice of a
network simulator to be used as a VANET simulator.
Keywords: VANET, IEEE 802.11p, WAVE-PHY, WAVE-MAC, Simulators, Modeling
Business Intelligence Computational Intelligence in Vehicle and Transportatio...ijtsrd
The Traffic and Transportation system is big problem in the world. So business intelligence in vehicle and transportation system solve this problem and solution with the help of new technologies. In the computational intelligence in vehicle and transportation system used computer electrical and electronic conversion technology management. Akshay Shrikant Nehre "Business Intelligence (Computational Intelligence in Vehicle and Transportation System)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30226.pdf Paper Url :https://www.ijtsrd.com/computer-science/artificial-intelligence/30226/business-intelligence-computational-intelligence-in-vehicle-and-transportation-system/akshay-shrikant-nehre
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.
This Presentation mentions the various ways in which transportation can be improved by use of "Intelligent Transportation System" and it also includes case study on "The Eastern Freeway, Mumbai."
Ontologies for Advanced Driver Assistance SystemsLihua Zhao
Many Advanced Driver Assistance Systems (ADAS) have been developed to improve car safety. A Knowledge Base is indispensable for autonomous vehicles to perceive driving environments and understand traffic regulations. In this paper, we introduce an ontology-based Knowledge Base, which contains maps and traffic regulations. By accessing to the Knowledge Base, the intelligent vehicles can aware overspeed situations and make decisions at intersections in comply with traffic regulations. Two simple ADAS systems are developed based on the Knowledge Base. We conducted field test with an intelligent vehicle to
evaluate the ADAS systems.
A Method for Predicting Vehicles Motion Based on Road Scene Reconstruction an...ITIIIndustries
The suggested method helps predicting vehicles movement in order to give the driver more time to react and avoid collisions on roads. The algorithm is dynamically modelling the road scene around the vehicle based on the data from the onboard camera. All moving objects are monitored and represented by the dynamic model on a 2D map. After analyzing every object’s movement, the algorithm predicts its possible behavior.
A multi-objective evolutionary scheme for control points deployment in intell...IJECEIAES
One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the Non dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the strength pareto evolutionary algorithm-II (SPEA-II); and the pareto envelope based selection algorithm-II (PESA-II). We performed the tests and compared these deployments using pareto front and performance indicators like the spread and hypervolume and the inverted generational distance (IGD). The results obtained show that the NSGA-II method is the most adequate in the deployment of these control points.
An Ontology-Based Intelligent Speed Adaptation System for Autonomous CarsLihua Zhao
Intelligent Speed Adaptation (ISA) is one of the key tech- nologies for Advanced Driver Assistance Systems (ADAS), which aims to reduce car accidents by supporting drivers to comply with the speed limit. Context awareness is indispensable for autonomous cars to perceive driving environment, where the information should be represented in a machine-understandable format. Ontologies can represent knowledge in a format that machines can understand and perform human-like reason- ing. In this paper, we present an ontology-based ISA system that can detect overspeed situations by accessing to the ontology-based Knowl- edge Base (KB). We conducted experiments on a car simulator as well as on real-world data collected with an intelligent car. Sensor data are converted into RDF stream data and we construct SPARQL queries and a C-SPARQL query to access to the Knowledge Base. Experimental re- sults show that the ISA system can promptly detect overspeed situations by accessing to the ontology-based Knowledge Base.
: This paper is aimed at designing a density based dynamic traffic signal system where the timing
of signal will change automatically on sensing the traffic density at any junction using the IoT technology. Traffic
congestion is a severe problem in most cities across the world and therefore it is time to shift more manual mode
or fixed timer mode to an automated system with decision making capabilities. To optimize this problem, we have
made a framework for an intelligent traffic control system. Sometimes higher traffic density at one side of the
junction demands longer green time as compared to standard allotted time. We therefore propose here a
mechanism in which the time period of green light and red light is assigned on the basis of the density of the
traffic present at the time. This is achieved by using LIDAR sensors.
A VISION-BASED REAL-TIME ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM USING VEHICULA...JANAK TRIVEDI
In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method.
TTI’s Connected and Automated Vision for the Future
The Texas A&M Transportation Institute (TTI) shares an industry vision where no vehicles collide and people can use connected and automated transportation to transform how they live, work and interact with their environment. To achieve this vision, research, development and testing are needed on how vehicles, users and transportation infrastructure all work together. While automated vehicles are emerging and connected vehicle research is progressing, TTI believes the most significant gains in safety and mobility will occur at the nexus of these areas. TTI is creating a world-class research environment on the Texas A&M University campus where researchers can collaborate, new transportation paradigms can be created, and future mobility and safety can be showcased.
A Synopsis of Simulation and Mobility Modeling in Vehicular Ad-hoc Networks (...IOSR Journals
Abstract : Vehicular communication is considered to be a backbone for many critical safety applications. In
order to achieve a better implementation of any vehicular communication scenario, an efficient, accurate and
reliable simulator is essential. Various open source and commercial simulating tools are available for this
purpose. One of the key issues in this regard is the selection of a reliable simulator which implements all
standard algorithms and paradigms giving accurate results. In this paper, we first present IEEE standard and
protocols for vehicular communication, IEEE 802.11p and IEEE 1609.x, also known as WAVE protocol stack.
The paper then discusses the necessary requirements for a generic discrete event simulator which can be used to
simulate Vehicular Ad-hoc Networks. Since not all the network simulators can be used in the scenario of
vehicular communication, we highlight the key features of some network simulators in the context of vehicular
ad-hoc networks. The paper also highlights some of the implementation limitations in these simulators.
Furthermore, the paper presents a discussion on traffic simulators by emphasizing on the underlying mobility
models used in order to generate the realistic traffic patterns. A comparative study of both network and traffic
simulators show the pros and cons of these simulation tools. The paper suggests the appropriate choice of a
network simulator to be used as a VANET simulator.
Keywords: VANET, IEEE 802.11p, WAVE-PHY, WAVE-MAC, Simulators, Modeling
Business Intelligence Computational Intelligence in Vehicle and Transportatio...ijtsrd
The Traffic and Transportation system is big problem in the world. So business intelligence in vehicle and transportation system solve this problem and solution with the help of new technologies. In the computational intelligence in vehicle and transportation system used computer electrical and electronic conversion technology management. Akshay Shrikant Nehre "Business Intelligence (Computational Intelligence in Vehicle and Transportation System)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30226.pdf Paper Url :https://www.ijtsrd.com/computer-science/artificial-intelligence/30226/business-intelligence-computational-intelligence-in-vehicle-and-transportation-system/akshay-shrikant-nehre
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.
This Presentation mentions the various ways in which transportation can be improved by use of "Intelligent Transportation System" and it also includes case study on "The Eastern Freeway, Mumbai."
Ontologies for Advanced Driver Assistance SystemsLihua Zhao
Many Advanced Driver Assistance Systems (ADAS) have been developed to improve car safety. A Knowledge Base is indispensable for autonomous vehicles to perceive driving environments and understand traffic regulations. In this paper, we introduce an ontology-based Knowledge Base, which contains maps and traffic regulations. By accessing to the Knowledge Base, the intelligent vehicles can aware overspeed situations and make decisions at intersections in comply with traffic regulations. Two simple ADAS systems are developed based on the Knowledge Base. We conducted field test with an intelligent vehicle to
evaluate the ADAS systems.
A Method for Predicting Vehicles Motion Based on Road Scene Reconstruction an...ITIIIndustries
The suggested method helps predicting vehicles movement in order to give the driver more time to react and avoid collisions on roads. The algorithm is dynamically modelling the road scene around the vehicle based on the data from the onboard camera. All moving objects are monitored and represented by the dynamic model on a 2D map. After analyzing every object’s movement, the algorithm predicts its possible behavior.
A multi-objective evolutionary scheme for control points deployment in intell...IJECEIAES
One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the Non dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the strength pareto evolutionary algorithm-II (SPEA-II); and the pareto envelope based selection algorithm-II (PESA-II). We performed the tests and compared these deployments using pareto front and performance indicators like the spread and hypervolume and the inverted generational distance (IGD). The results obtained show that the NSGA-II method is the most adequate in the deployment of these control points.
An Ontology-Based Intelligent Speed Adaptation System for Autonomous CarsLihua Zhao
Intelligent Speed Adaptation (ISA) is one of the key tech- nologies for Advanced Driver Assistance Systems (ADAS), which aims to reduce car accidents by supporting drivers to comply with the speed limit. Context awareness is indispensable for autonomous cars to perceive driving environment, where the information should be represented in a machine-understandable format. Ontologies can represent knowledge in a format that machines can understand and perform human-like reason- ing. In this paper, we present an ontology-based ISA system that can detect overspeed situations by accessing to the ontology-based Knowl- edge Base (KB). We conducted experiments on a car simulator as well as on real-world data collected with an intelligent car. Sensor data are converted into RDF stream data and we construct SPARQL queries and a C-SPARQL query to access to the Knowledge Base. Experimental re- sults show that the ISA system can promptly detect overspeed situations by accessing to the ontology-based Knowledge Base.
: This paper is aimed at designing a density based dynamic traffic signal system where the timing
of signal will change automatically on sensing the traffic density at any junction using the IoT technology. Traffic
congestion is a severe problem in most cities across the world and therefore it is time to shift more manual mode
or fixed timer mode to an automated system with decision making capabilities. To optimize this problem, we have
made a framework for an intelligent traffic control system. Sometimes higher traffic density at one side of the
junction demands longer green time as compared to standard allotted time. We therefore propose here a
mechanism in which the time period of green light and red light is assigned on the basis of the density of the
traffic present at the time. This is achieved by using LIDAR sensors.
Similar to Manuscript next generation advanced driver assistance systems towards the protection of vulnerable road users cyclists and pedestrians-prospect
Integrated tripartite modules for intelligent traffic light systemIJECEIAES
The traffic in urban areas is primarily controlled by traffic lights, contributing to the excessive, if not properly installed, long waiting times for vehicles. The condition is compounded by the increasing number of road accidents involving pedestrians in cities across the world. Thus, this work presents an integrated tripartite module for an intelligent traffic light system. This system has enough ingredients for success that can solve the above challenges. The proposed system has three modules: the intelligent visual monitoring module, intelligent traffic light control module, and the intelligent recommendation module for emergency vehicles. The monitor module is a visual module capable of identifying the conditions of traffic in the streets. The intelligent traffic light control module configures many intersections in a city to improve the flow of vehicles. Finally, the intelligent recommendation module for emergency vehicles offers an optimal path for emergency vehicles. The evaluation of the proposed system has been carried out in Al-Sader city/Bagdad/Iraq. The intelligent recommendation module for the emergency vehicles module shows that the optimization rate average for the optimal path was in range 67.13% to 92%, where the intelligent traffic light control module shows that the optimization ratio was in range 86% to 91.8%.
ESV - TECHNICAL CONFERENCEON THE ENHANCED SAFETY OF VEHICLES 2019;
Paper No.19-0277-O
Improving the Effectiveness of Active Safety Systems to Significantly Reduce Accidents with Vulnerable Road Users
PROGNOSTIC - ADAPTIVE INTELLIGENT DIAGNOSTIC SYSTEM FOR VEHICL.docxgertrudebellgrove
" PROGNOSTIC " - ADAPTIVE INTELLIGENT DIAGNOSTIC SYSTEM FOR VEHICLES
A. A. Poddubnaya, A. V. Keller
FSUE "NAMI", Moscow, Russian Federation
E-mail: [email protected]
Abstract. The article contains general information about promising vehicle diagnostic systems. Existing diagnostic systems, including those built into modern vehicles (TS), are not able to predict the moment of failure of components and assemblies, but only state the fact of a malfunction. To diagnose the current state and forecast the residual life of the vehicle in motion mode, it is proposed to use a mathematical model based on machine learning technologies and data from standard and additional sensors, vehicle detectors. Using this approach will make it possible to forecast the occurrence of a defect before its actual occurrence.
Keywords: advanced diagnostic systems, autonomous vehicle, connected cars, unmanned vehicles, technical condition monitoring, mechanical failure detection, fault prediction, sensors, detectors, digital data processing methods
Introduction
For autonomous transport and connected vehicles, diagnostic of the vehicle’s technical condition is a basic safety standard. * The issue of determining the mechanical failure of an autonomous vehicle is extremely relevant, due to the lack of a driver who can appreciate uncharacteristic noises or external vibrations. Errors received from the vehicle’s CAN bus are not sufficiently informative in assessing the current state of the vehicle and do not predict a breakdown or a failure. For a driverless vehicle, at the stage of its design, an expanded self-diagnosis system should be laid. During operation, onboard the vehicle, data from sensors and a reliability monitoring system should be processed and further data transferred to the ITS - intelligent transport system, as well as to the servers of owners and manufacturers. (* according to researches of the European Commission.)
Main part
Almost all modern cars are modified with a variety of full-time detecting devices and sensors, fixing faults and operation errors of some nodes by electrical parameters and fixing “extreme” system states in codes. Error icons appear on the vehicle dashboard when the system diagnoses a fault. If the driver notes the incorrect operation of certain nodes, systems and you need to make sure in what, really technical condition is the transport, then a specialized diagnosis is carried out. To clarify the technical condition, the computer diagnostics of the vehicle is performed by a certified technical specialist: a scanner with software is connected to the on-board systems, through special diagnostic connectors, CAN, which reads all the codes and errors transmitted by the car about possible malfunctions on the main nodes. Error codes are currently vendor specific, are set by OEM and are available for reading and monitoring in a limited list of codes. The received codes are decrypted by specialists, again using special ...
International Journal of Artificial Intelligence & Applications (IJAIA)gerogepatton
The conventional pedestrian crossing system's shortcomings require urgent reform to enhance the safety of
pedestrians and improve urban mobility. Issues such as insufficient time for pedestrians to cross, prolong
waiting times, neglection of emergency vehicles, and the absence of effective 24/7 response mechanisms at
traditional crosswalks present significant safety concerns in urban areas. Our primary intention is to
develop a cutting-edge pedestrian crossing system that relies on deep learning and image processing
technologies as its foundation. This research addresses to innovate an advanced smart crosswalk
consisting of four essential components: a real-time Pedestrian Detection and Priority System customized
for individuals with special needs, a responsive system for detecting road conditions, vehicle availability
and speed near crosswalks, a real-time Emergency Vehicle Detection and Priority System strengthened by
rigorous verification procedures, and a robust framework for identifying pedestrian accidents and
violations of crosswalk rules. The entire system has been meticulously designed not only to enhance
pedestrian safety by identifying potential dangers but also to optimize traffic flow. In essence, it aims to
provide an improved pedestrian crossing experience characterized by increased safety and efficiency.
SMART CROSSWALK: MACHINE LEARNING AND IMAGE PROCESSING BASED PEDESTRIAN AND V...gerogepatton
The conventional pedestrian crossing system's shortcomings require urgent reform to enhance the safety of
pedestrians and improve urban mobility. Issues such as insufficient time for pedestrians to cross, prolong
waiting times, neglection of emergency vehicles, and the absence of effective 24/7 response mechanisms at
traditional crosswalks present significant safety concerns in urban areas. Our primary intention is to
develop a cutting-edge pedestrian crossing system that relies on deep learning and image processing
technologies as its foundation. This research addresses to innovate an advanced smart crosswalk
consisting of four essential components: a real-time Pedestrian Detection and Priority System customized
for individuals with special needs, a responsive system for detecting road conditions, vehicle availability
and speed near crosswalks, a real-time Emergency Vehicle Detection and Priority System strengthened by
rigorous verification procedures, and a robust framework for identifying pedestrian accidents and
violations of crosswalk rules. The entire system has been meticulously designed not only to enhance
pedestrian safety by identifying potential dangers but also to optimize traffic flow. In essence, it aims to
provide an improved pedestrian crossing experience characterized by increased safety and efficiency.
The European Union is promoting eCall to reduce the number of roadway fatalities by minimizing the response time when an accident has occurred. eCall is a combination of an In Vehicle System (IVS), a device with a GSM cell phone and GPS location capability, and a corresponding infrastructure of Public Safety Answering Points (PSAPs) Intelligent Vehicle Safety Systems use Information and Communications Technologies for providing solutions for improving road safety in particular in the pre-crash phase when the accident can still be avoided or at least its severity significantly reduced. With these systems, which can operate either autonomously on-board the vehicle, or be based on vehicle-to-vehicle or vehicle-to-infrastructure communication (co-operative systems), the number of accidents and their severity can be reduced. Location-enhanced emergency calls like in-vehicle e-call have their primary benefit to society of saving lives and in offering an increased sense of security. The article presents the system eCall and how does it works.
Cisco Smart Intersections: IoT insights using video analytics and AICarl Jackson
In this trial, IoT, Video Analytics, Deep Learning (DL) and Artificial Intelligence (AI), for the purpose of traffic flow assessment and insights into road user behaviour, were evaluated at an intersection at the AIMES testbed in Melbourne¹ in partnership with: the University of Melbourne, Department of Transport (DOT), IAG and Cisco.
The International Journal of Management Research and Business Strategy is a international journal in English published every day in our life. It offers a fast publication schedule of maintaining rigorous peer review..The use of recommended electronic formats for article delivery the process and submitted research review articles and Case Studies are subjected to immediate screening by the editors.
Similar to Manuscript next generation advanced driver assistance systems towards the protection of vulnerable road users cyclists and pedestrians-prospect (20)
Why Is Your BMW X3 Hood Not Responding To Release CommandsDart Auto
Experiencing difficulty opening your BMW X3's hood? This guide explores potential issues like mechanical obstruction, hood release mechanism failure, electrical problems, and emergency release malfunctions. Troubleshooting tips include basic checks, clearing obstructions, applying pressure, and using the emergency release.
What Does the PARKTRONIC Inoperative, See Owner's Manual Message Mean for You...Autohaus Service and Sales
Learn what "PARKTRONIC Inoperative, See Owner's Manual" means for your Mercedes-Benz. This message indicates a malfunction in the parking assistance system, potentially due to sensor issues or electrical faults. Prompt attention is crucial to ensure safety and functionality. Follow steps outlined for diagnosis and repair in the owner's manual.
Symptoms like intermittent starting and key recognition errors signal potential problems with your Mercedes’ EIS. Use diagnostic steps like error code checks and spare key tests. Professional diagnosis and solutions like EIS replacement ensure safe driving. Consult a qualified technician for accurate diagnosis and repair.
Ever been troubled by the blinking sign and didn’t know what to do?
Here’s a handy guide to dashboard symbols so that you’ll never be confused again!
Save them for later and save the trouble!
Core technology of Hyundai Motor Group's EV platform 'E-GMP'Hyundai Motor Group
What’s the force behind Hyundai Motor Group's EV performance and quality?
Maximized driving performance and quick charging time through high-density battery pack and fast charging technology and applicable to various vehicle types!
Discover more about Hyundai Motor Group’s EV platform ‘E-GMP’!
Things to remember while upgrading the brakes of your carjennifermiller8137
Upgrading the brakes of your car? Keep these things in mind before doing so. Additionally, start using an OBD 2 GPS tracker so that you never miss a vehicle maintenance appointment. On top of this, a car GPS tracker will also let you master good driving habits that will let you increase the operational life of your car’s brakes.
𝘼𝙣𝙩𝙞𝙦𝙪𝙚 𝙋𝙡𝙖𝙨𝙩𝙞𝙘 𝙏𝙧𝙖𝙙𝙚𝙧𝙨 𝙞𝙨 𝙫𝙚𝙧𝙮 𝙛𝙖𝙢𝙤𝙪𝙨 𝙛𝙤𝙧 𝙢𝙖𝙣𝙪𝙛𝙖𝙘𝙩𝙪𝙧𝙞𝙣𝙜 𝙩𝙝𝙚𝙞𝙧 𝙥𝙧𝙤𝙙𝙪𝙘𝙩𝙨. 𝙒𝙚 𝙝𝙖𝙫𝙚 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙥𝙡𝙖𝙨𝙩𝙞𝙘 𝙜𝙧𝙖𝙣𝙪𝙡𝙚𝙨 𝙪𝙨𝙚𝙙 𝙞𝙣 𝙖𝙪𝙩𝙤𝙢𝙤𝙩𝙞𝙫𝙚 𝙖𝙣𝙙 𝙖𝙪𝙩𝙤 𝙥𝙖𝙧𝙩𝙨 𝙖𝙣𝙙 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙛𝙖𝙢𝙤𝙪𝙨 𝙘𝙤𝙢𝙥𝙖𝙣𝙞𝙚𝙨 𝙗𝙪𝙮 𝙩𝙝𝙚 𝙜𝙧𝙖𝙣𝙪𝙡𝙚𝙨 𝙛𝙧𝙤𝙢 𝙪𝙨.
Over the 10 years, we have gained a strong foothold in the market due to our range's high quality, competitive prices, and time-lined delivery schedules.
"Trans Failsafe Prog" on your BMW X5 indicates potential transmission issues requiring immediate action. This safety feature activates in response to abnormalities like low fluid levels, leaks, faulty sensors, electrical or mechanical failures, and overheating.
Fleet management these days is next to impossible without connected vehicle solutions. Why? Well, fleet trackers and accompanying connected vehicle management solutions tend to offer quite a few hard-to-ignore benefits to fleet managers and businesses alike. Let’s check them out!
What Exactly Is The Common Rail Direct Injection System & How Does It WorkMotor Cars International
Learn about Common Rail Direct Injection (CRDi) - the revolutionary technology that has made diesel engines more efficient. Explore its workings, advantages like enhanced fuel efficiency and increased power output, along with drawbacks such as complexity and higher initial cost. Compare CRDi with traditional diesel engines and discover why it's the preferred choice for modern engines.
In this presentation, we have discussed a very important feature of BMW X5 cars… the Comfort Access. Things that can significantly limit its functionality. And things that you can try to restore the functionality of such a convenient feature of your vehicle.
Comprehensive program for Agricultural Finance, the Automotive Sector, and Empowerment . We will define the full scope and provide a detailed two-week plan for identifying strategic partners in each area within Limpopo, including target areas.:
1. Agricultural : Supporting Primary and Secondary Agriculture
• Scope: Provide support solutions to enhance agricultural productivity and sustainability.
• Target Areas: Polokwane, Tzaneen, Thohoyandou, Makhado, and Giyani.
2. Automotive Sector: Partnerships with Mechanics and Panel Beater Shops
• Scope: Develop collaborations with automotive service providers to improve service quality and business operations.
• Target Areas: Polokwane, Lephalale, Mokopane, Phalaborwa, and Bela-Bela.
3. Empowerment : Focusing on Women Empowerment
• Scope: Provide business support support and training to women-owned businesses, promoting economic inclusion.
• Target Areas: Polokwane, Thohoyandou, Musina, Burgersfort, and Louis Trichardt.
We will also prioritize Industrial Economic Zone areas and their priorities.
Sign up on https://profilesmes.online/welcome/
To be eligible:
1. You must have a registered business and operate in Limpopo
2. Generate revenue
3. Sectors : Agriculture ( primary and secondary) and Automative
Women and Youth are encouraged to apply even if you don't fall in those sectors.
5 Warning Signs Your BMW's Intelligent Battery Sensor Needs AttentionBertini's German Motors
IBS monitors and manages your BMW’s battery performance. If it malfunctions, you will have to deal with an array of electrical issues in your vehicle. Recognize warning signs like dimming headlights, frequent battery replacements, and electrical malfunctions to address potential IBS issues promptly.
5 Warning Signs Your BMW's Intelligent Battery Sensor Needs Attention
Manuscript next generation advanced driver assistance systems towards the protection of vulnerable road users cyclists and pedestrians-prospect
1. Next Generation Advanced Driver Assistance Systems towards the
protection of Vulnerable Road Users - cyclists and pedestrians.
-The project PROSPECT (PROactive Safety for PEdestrians and CyclisTs)-
Jordi Bargalló 1)
Ilona Cieslik 1)
Martin Kunert 2)
Johann Stoll 3)
Fabian Flohr 4)
Maxim Arbitmann 5)
Gary Burnett 6)
Dariu Gavrila 7)
Patrick Seiniger 8)
1) Advanced Driver Assistance Systems, IDIADA Automotive Technology, Santa Oliva 473710, Spain
2) Advanced Engineering Sensor Systems, Robert Bosch GmbH, 71226 Leonberg, Germany
3) Automated Driving, Audi, Ingolstadt D-85045, Germany
4) Environment Perception, Daimler AG, Ulm D-89081, Germany
5) Enhanced ADAS & Tire Interactions, Continental Teves, 60488 Frankfurt/Main, Germany
6) Human Factors, University of Nottingham, NG7 2RD Nottingham, the United Kingdom
7) Intelligent Perception Systems, University of Amsterdam, 1012 WX Amsterdam, The Netherland
8) Active Vehicle Safety and Driver Assistance Systems, Bundesanstalt für Straßenwesen, D-51427 Bergisch Gladbach, Germany
ABSTRACT: PROSPECT - PROactive Safety for PEdestrians and CyclisTs is a collaborative research project funded by the
European Commission. Its main objective is to significantly improve the effectiveness of active VRU safety systems and address well-
known barriers of current AEB systems: limited sensors field-of-view, unreliable intent recognition and slow reaction times for
actuations. New concepts for sensors and control systems will be shown in three vehicle demonstrators and mobile driving simulator
and tested using extensive validation methodologies. The introduction of a new generation ADAS systems will enhance the New Car
Assessment Programme roadmap in 2020-2025 and contribute to the Vision Zero.
KEY WORDS: safety, protection for vulnerable road users, statistical accident analysis, test/evaluation, sensor technology (C1)
1. INTRODUCTION AND MOTIVATION
Accidents involving Vulnerable Road Users (VRU) remain a
significant issue for road safety, accounting for more than 25%
of road fatalities in the European Union(1)
. These percentages
show the magnitude of the problem and the need to take action in
order to reduce these figures (see Fig. 1).
Fig. 1 Road traffic deaths by type of road user in Europe (Source:
WHO, 2015).
The White Paper (Roadmap to a Single European Transport
Area - Towards a Competitive and Resource Efficient Transport
System) contains European Union goals on the area of traffic
safety(2)
. „By 2050, move close to zero fatalities in road transport.
In line with this goal the European Union aims at halving road
casualties by 2020.”
Advanced Driver Assistance Systems (ADAS) are the basis
for the development of automated cars. Putting the focus on
active safety features, the introduction of Autonomous
Emergency Braking (AEB) functions will be a must for vehicles
sold in the United States and in the European Union by 2020,
since AEB Systems have the potential to increase safety for
drivers as well as for VRU.
´PROactive Safety for PEdestrians and CyclisTs´ is a
collaborative research project funded by the European
Commission. The project pursues an integrated approach
comprising in-depth and multiple European accident studies
involving VRUs, combined with results from urban naturalistic
observation. A vast variety of data collected at European level,
where vehicles and VRU interact in real traffic situations, helped
to understand critical situations, identify factors that lead to
conflicts and better anticipate possible accidents. As the output,
the Accident Scenarios were identified for pedestrians and cyclist
with a special focus on urban environments, where indeed the
majority of accidents involving VRU occur. Further on, the most
important ´Use Cases´ were derived as basis for the development
of Test Scenarios for the ADAS systems. Proposed ´Test Cases´
are more detailed than the defined ´Use Cases´ - they are a
description of how to reproduce a specific use case on test tracks.
Finally, this accident analysis represents a key input for the
system specifications, integration and demonstration to the
public in three project prototype vehicles. These demo-vehicles
are extensively tested in realistic scenarios. PROSPECT broad
2. testing methodology goes beyond what has currently been used:
VRU intention detection (dummies with additional degrees-of-
freedom), intersection driving style (natural driving style using
robots by analysis of human driving) and transferability to real
life (testing in realistic traffic scenarios, user acceptance tests).
The concept for realistic testing includes an intersection marking
which allows the efficient testing of all test cases, mobile and
light obstruction elements and realistic surroundings like traffic
signs or lights. The PROSPECT project technical approach is
presented herein below (see
Fig. 2).
Fig. 2 The PROSPECT project technical approach.
In PROSPECT, just like other functions implemented in
automated driving, vehicle-based sensors (i.e. video, radar)
survey the vehicle surroundings; advanced algorithms enable
safety related decision-making, and the system will act actively
when necessary. Being an active safety solutions focused on
VRU, the system developed in PROSPECT will take action
when a critical situation with a VRU occurs. Moreover, each of
the demonstrators will have its unique focus:
- I demonstrator is equipped with stereo vision camera and
high resolution radars, featuring high dynamic brake system
combined with power assisted steering actuator.
- II demonstrator will feature improvements in earlier, accurate
and more robust detection of VRUs where sensor fusion with
radar / lidar technologies is planned to extract VRU
intention-related features.
- III demonstrator integrates enlarged FOV radar sensors
including side and rear coverage and avoids critical
situations or collisions by steering and/or braking in complex
urban scenarios.
- Additionally, one driving simulator will include advanced
warning/HMI and control strategies to evaluate interaction
between the driver and the vehicle inside PROSPECT.
- Advanced realistic pedestrian and cyclist dummies including
platform propulsion system will improve realistic testing by
extending dummies trajectories, organic materials,
kinematics and physical behavior.
AEB Systems have the high-potential to improve VRU
safety. The findings within the PROSPECT contribute not only
to the generation of state-of-the-art knowledge of VRU-vehicle
behavior but as well to technical innovations i.e. assessment
methodologies and tools for testing of next generation VRU
active safety systems.
Besides, in terms of the impact, the introduction of a new
generation safety system in the market will enhance VRU road
safety in the 2020-2025 timeframe, contributing to the ‘Vision
Zero’ objective of no fatalities or serious injuries in road traffic
set out in the Transport White Paper. Test methodologies and
tools shall be considered as well for 2020-2024 Euro NCAP
road-maps(3)
.
2. ACCIDENT ANALYSIS: “ACCIDENT SCENARIOS”
AND “USE CASES”
The first stage of the project included macro statistical and
in-depth accident studies involving VRUs, performed in Europe
and focused mainly in pedestrians and cyclists. An overview and
an in-depth understanding of the characteristics of road traffic
crashes involving vehicles (focus on passenger cars) and VRUs
(i.e. pedestrians, cyclists, riders of mopeds, e-bikes or scooters)
was provided for different European countries.
The in-depth understanding of the crashes includes the
identification of the most relevant road traffic “accident
scenarios” and levels of injury severity sustained, as well as the
transport modes that represent a higher risk for VRUs. Besides
extensive literature studies, comprehensive data analyses have
been performed including information from recent years.
Several crash databases have been analysed: CARE database
(Europe), the German, Swedish and Hungarian national road
traffic statistics as well as the in-depth databases IGLAD
(Europe), GIDAS (Germany), from Central Statistical Office
(Központi Statisztikai Hivatal – KSH) and the Volvo Cars
Cyclist Accident Database (Sweden).
The focus of the project is on crashes with two participants.
Regarding the injury severity of the vulnerable road users two
groups were considered: first “slightly, seriously injured and
3. killed (SSK) VRU” and second “killed and seriously injured
(KSI) VRU”. Early investigations have shown that the crashes
between passenger cars and pedestrians or cyclists are from
highest relevance for Europe.
Fig. 3 shows a summary of the most relevant accident
scenarios related to car-to-cyclist crashes were generated from
this study(4)
.
Fig. 3 Most relevant car-to-cyclist scenarios.
In the analysis of car-to-pedestrian accidents, the Accident
Scenarios introduced in the European project AsPeCSS (5-6)
were
considered as basis. Regarding crashes between cars and
pedestrians, all databases confirmed that the Accident Scenario 1
“Crossing a straight road from nearside; no obstruction” was
ranked highest regarding killed or seriously injured pedestrians,
and the Accident Scenario 2 “Crossing a straight road from the
offside; no obstruction” was ranked highest regarding all
pedestrian injury severities. An additional Accident Scenario
“Driving backwards” has been considered. The car-to-pedestrian
accident scenarios can be seen in Fig. 4.
Fig. 4 Pedestrian accident scenarios.
The ‘Accident Scenarios’ obtained from the studies describe
the type of road users involved in the accident, their motions
(e.g., the motion of the cyclist or pedestrian relative to the
vehicle) expressed as ‘accident types’ and further contextual
factors like the course of the road, light conditions, weather
conditions and view obstruction. More information is available
on the project deliverable “Accident Analysis, Naturalistic
Driving Studies and Project Implications”(7)
. The most relevant
accident scenarios have been clustered in “Use Cases” or “Target
Scenarios” addressed by the project.
3. NATURALISTIC OBSERVATIONS
Complementary to accident studies which have derived the
most relevant use cases to study, naturalistic observations have
been carried out to provide information that cannot be inferred
from accident data bases, since these usually do not contain
detailed information about the time before the accident happened
(the so-called “pre-crash phase”).
The first goal has been to acquire data about indicators of
VRU’s behaviours that sign their intent in the near future.
Naturalistic observations were also used to look for correctly
managed situations by the road users that could have led to false
alarms for an active safety system.
As seen in Fig. 5, two types of naturalistic observations were
carried out in three countries. A first data set (France and
Hungary) was collected from on-site observations by
infrastructure-mounted cameras. A second data set was collected
by cars equipped with sensors and cameras (Hungary and Spain)
to observe interactions with surrounding VRUs.
Fig. 5 Two types of naturalistic observations were carried out:
(a) Video data from in-vehicle camera (b) View from
infrastructure-mounted cameras.
A set of parameters have been coded for the traffic conflicts
identified in the acquisition. They describe (1) the general
environmental conditions of the conflict (light, precipitation,
road surface, traffic density), (2) the infrastructure (layout,
dedicated lanes, speed limit), (3) the characteristics of the VRU
(type, equipment), (4) the encounter characteristics (visibility,
right of way, yielding, conflict management, estimated impact
point), (5) the intents of the VRU (head/torso orientation,
gesture), (6) kinematics and trajectories of both car and VRU.
PROSPECT_UC_PD_x
(x=1…8)
Pictogram in % Description
PROSPECT_UC_PD_1
PROSPECT_UC_PD_2
23%
22%
Crossing a straight road
from near-side / off-side;
No obstruction
PROSPECT_UC_PD_3a
PROSPECT_UC_PD_3b
5,5%
5,5%
Crossing at a junction from
the near-side / off-side;
vehicle turning across
traffic
PROSPECT_UC_PD_4a 4%
Crossing at a junction from
the near-side / off-side;
vehicle not turning across
traffic
PROSPECT_UC_PD_5
PROSPECT_UC_PD_6
10%
7%
Crossing a straight road
from near-side / off-
side;With obstruction
PROSPECT_UC_PD_7a
PROSPECT_UC_PD_7b
3%
Along the carriageway on a
straight road away from
vehicle / towards vehicle;
No Obstruction
PROSPECT_UC_PD_8 No Pictogram 6% Driving Backwards
Others 14% Others
4. Analyses performed on each use case provide descriptions of
a battery of VRUs’ behaviour when involved in a specific
conflict that helped to identify the clues that can predict VRUs’
behaviour in the near future.
4. SYSTEM SPECIFICATION AND DEMONSTRATORS -
CHALLENGES FOR ADDRESSING BARRIERS OF
CURRENT ADAS SYSTEMS
Based on the derived Use Cases, the sensor specification was
achieved including hardware characteristics (e.g. stereo vision
base line, image resolution, microwave radar sensitivity/accuracy,
field of views) and items that relate to the sensor processing e.g.
VRU detection area, correct vs. false recognition rates,
localization accuracy, and computational latencies.
PROSPECT focusses on active safety solutions, where the
vehicle survey surroundings based on video and radar sensing.
The developed sensors intend to support a larger coverage of
accident scenarios by means of an extended sensor field of view
(e.g. frontal stereo vision coverage increased to about 90°, radar
coverage increased up to 270° covering vehicle front and one
side), high-resolution and sensitive microwave radar sensors with
enhanced micro-Doppler capabilities for a better radar-based
VRU classification.
For automated driving however, the system should not only
detect VRUs, but also predict their trajectories to anticipate and
avoid potentially dangerous situations. In this case, advanced
algorithms enable safety related decision-making and the
systems developed within PROSPECT will take action in case of
a critical situation with a VRU, increasing the effectiveness of
current active safety systems.
Improved VRU sensing and situational analysis functions
(enlarged sensor coverage; earlier and more robust VRU
detection and classification; sophisticated path prediction and
reliable intent recognition) will be shown in three vehicle
demonstrators at the final project event at proving ground
(Spain) in October 2018. All vehicles will be able to
automatically steer and / or brake to avoid accidents. Special
emphasis will be placed on balancing system performance in
critical scenarios and avoiding undesired system activations.
Information about the demonstrators developed in the project is
available in the appropriate PROSPECT deliverables (8)
.
This section provides an overview of the applied
methodology pursued in this project in relation to PROSPECT
car demonstrators. The ´Use Case selection´ (cyclists and
pedestrians) for the three car demonstrators inside the project is
presented in Fig 6(9)
.
Fig. 7 The addressed use cases by three demo-cars (cyclists and
pedestrians).
4.1 . Demonstrator car I
Demonstrator car I is able to quickly detect and classify
VRU from -90° to 90° with respect to the vehicle center line with
three RADAR sensors, additionally detect the lane markings
with a lane camera. There are actuators for the steering and the
brake. Especially the brake actuator can increase brake force
much quicker than current production brake systems (approx.
150 ms from start of braking to fully cycling ABS). Due to
shorter reaction time a prediction horizon can be reduced and the
prediction error is lower. The reduction of false activations
improves overall driver acceptance and usability. Fig. 7 shows
utilized sensors of the demonstrator.
a
b
Fig. 7 Demonstrator car I - vehicle with functional setup: (a)
Sensors integration site RADARS, (b) Radar sensor setup (3x
Long Range Radar for VRU detection & classification >180°).
4.2 . Demonstrator car II
To handle the defined use cases (car moving straight with
VRU crossing/moving straight, car turning right/left with VRU
crossing) the II demo-car is equipped with a front facing stereo
camera and two side-mounted cameras. By this camera setup a
horizontal FOV of approx. 210° is covered, which is suitable for
most of proposed use cases (see Fig. 8 with the sensor setup). In
5. the near range (longitudinal distance up to ~ 40 m) a more
detailed analysis of the VRUs will be executed. Based on this
detailed information intention recognition can be performed. The
correct estimation of VRU’s intention helps to increase the
possible prediction time horizon, allowing much earlier warnings
and interventions without increasing the false-positive rate.
a
b
Fig. 8 Demonstrator car II: (a) Calibrated and synchronized
stereo camera and lidar system, (b) Sensor setup consisting of
one front facing stereo camera (~60m, 75° ) and two side-
oriented cameras covering a horizontal FOV of roughly 210°.
4.3 . Demonstrator car III
Demonstrator car III will focus on high resolution RADAR
sensors with a coverage of the regions in the front, rear and at
least at one side of the vehicle: especially accidents with crossing
or rewards approaching, quick-running bicycles in combination
with a relatively slow or stopped car require a sufficient large
field-of-view zone for a sound detection and appropriate vehicle
action (e.g. for a stopped car in a parking lot and an approaching
cyclist from the rear a warning or even the blocking of the door
is needed to avoid an accident). See Fig. 9 for more details.
Fig. 9 Demonstrator car III - high resolution radar sensors: (a)
Radar sensor mounting positions and FOV, (b) The demo-car
equipped with radar sensor.
4.4. Mobile driving simulator
Within the project, a mobile driving demonstrator is used to
present and evaluate the results of PROSPECT in a realistic
setting applying a real car as a mock-up. Based on the results of
the accident analysis(7)
it was possible to integrate common
accident scenarios between car drivers and cyclists into the
driving simulator in order to demonstrate the circumstances of
car-to-cyclist-accidents. Moreover, the results of the accident
analysis contributed fundamentally to the establishment of
hypotheses which outlined why car drivers fail to manage these
common crash situations with cyclists.
As a next step, studies will be carried out with PROSPECT
driving simulator in order to evaluate these hypotheses. One of
the planned studies deals with the role of sensory conspicuity of
cyclists within the detection of cyclists in specific scenarios by
car drivers. The results of these studies will account for a better
understanding of possible reasons why car drivers often fail to
handle such situations properly. Fig. 10 shows the driving
simulator, which was equipped with two additional monitors (for
a better side view in order to improve the demonstration of
crossing cyclists) with Simulation Tool.
Fig. 10 PROSPECT Mobile driving simulator presentation.
5. NEXT GENERATION TESTING
A sound benefit assessment of the prototype vehicle's
functionality requires a broad testing methodology which goes
beyond what has currently been used. A collection of ‘test
scenarios’, representative for all accident scenarios, was required
to be defined and specified within the project, resulting in a
preliminary test protocol(10)
. A key aspect of the test
methodology is the provision of exact copies of natural driving
styles on the test track with driving robots. For this task, data
from real driving studies with subjects in a suburb of Munich,
Germany and from Barcelona was used.
5.1. Test methodologies and assessment protocols
Apart from technology demonstrators that will help to
maintain and extend the leadership of European car
manufacturers in intelligent vehicles and for autonomous driving,
PROSPECT will take a step forward in defining test and
6. assessment methods for Euro NCAP AEB VRU systems. Euro
NCAP will directly benefit from the project’s findings and
results, especially by being supplied with deliverables including
test protocol as a proposal for consumer testing (final deliverable
under preparation), the below mentioned dummy and verification
testing. Since Euro NCAP is the leading NCAP in the world
regarding active vehicle safety, this helps to keep the European
automotive industry in the pole position of active safety.
At this stage, Euro NCAP has published a roadmap
document that outlines the strategy for the timeframe 2016 to
2020, however more important with respect to PROSPECT will
be the roadmap 2020 to 2024 which announces several
requirements for e.g. steering intervention and cross-junction
AEB systems that need specifically conditioned VRUs.
PROSPECT results will be an early input for the definition of all
these requirements.
5.2. Testing tools
PROSPECT focuses on functions that avoid collisions with
other traffic participants, so at least one other traffic participant
will be part of the test as well. Active safety functions might or
might not be able to avoid a collision, so the “other” traffic
participant will need to be an impactable dummy, a surrogate
either for a bicycle or a pedestrian. Both objects (Vehicle-Under-
Test (VUT) and impact partner) will initially be moved on a
predefined track and with predefined speeds so that a critical
situation develops. Active safety functions in the VUT might
intervene and avoid the collision.
In the context of testing tools development, advanced
articulated dummies - Pedestrian and Cyclist - prototypes are
already completed to obtain higher degrees of freedom (head
rotation, torso angle, pedaling, side leaning, etc.) and an
improved behavior during the acceleration- and stopping-phase
(see Fig. 11). The demonstrator vehicles will make use of novel
realistic VRU dummy specimen features for a better object
classification and prediction of intended VRU movements. The
dummies are mounted on fully self-driving platforms to take into
account even complex test scenarios with different arbitrary
movements.
Fig. 11 Examples of advanced dummy features: (a) Pedestrian
dummy full stop and rotate head towards approaching car, (b)
Pedaling cyclist dummy with rotating wheels.
A reproducible movement of the VUT is achieved by using
driving robots that are able to follow a path with a lateral
tolerance as low as 5 centimeter, see Fig. 12 for examples. The
use of driving robots is standard in active safety tests. The
opponent (bicycle or pedestrian) on the other hand is controlled
completely with a time-synchronized propulsion system.
Fig. 12 Examples of instrumented car with equipment: (a)
Control equipment (b) Measurement equipment.
In various accidents that had been analyzed for the use case
definition, the VRU (bicycle or pedestrian) was hidden to the
VUT for a significant amount of time. To reflect this, some test
cases are defined with an obstruction that initially hides the
pedestrian or the bicycle to the VUT, and it will be necessary to
have an appropriate obstruction tool for these test cases.
Further elements of the PROSPECT test methodology are a
standard intersection marking to be implemented on the test track
which allows the efficient testing of all PROSPECT test cases
and a concept for tests in realistic surroundings. The concept is
shown in Fig. 13.
3,5m
0,25m
50m
Non dimensioned
object are symmetric
3m
2m
5,5m
2m
R=8m
8m
11m
16m
9m
R=8m
13m
4m
3m
2m
150m
3/3m
0,5m
4m
A
F
B D
C
E
1m
G H
16m
Fig. 6 PROSPECT intersection with tracks.
Since the exact same test tools will be used on a test track and
in realistic surroundings by both Euro NCAP laboratories, all
tests will be repeatable (test results measured in the same
condition will be comparable) and test results from a test track
will be reproducible (test results from different test tracks, but
same vehicle and test setup are comparable). Test results on real
7. city streets however are not reproducible (they cannot be
reproduced on another intersection, in another city etc.).
5.3. Types of testing activities
PROSPECT considers of special relevance the following
testing activities:
- Vehicle-based functional tests: production vehicles will be
tested against the first PROSPECT test program to: a)
generate baseline data and b) refine the test procedures.
These represent the baseline for the state-of-the-art of AEB
systems.
- Simulator testing: testing the designed safety measures in
real traffic with normal drivers induces risks that cannot be
afforded at such early stages of the system development.
Nevertheless, driver reaction and response is of vital
importance since these measures will ultimately be applied in
normal vehicles. Full motion driving simulators will be used
for the collection of data regarding the interaction between
the driver and the safety function. The driving simulator
studies aim specifically to evaluate HMI/warning in
combination with automatic intervention by braking and/or
steering with the driver in the loop.
- User acceptance: it is also crucial for the success of all active
safety systems - if the systems are unacceptable for the
drivers (e.g. annoying), they could be permanently turned off
and would then have no effect on traffic safety. Moreover,
interventions of active systems being rare, they may lead to
unpredictable reactions from non-aware drivers i.e. being
potentially frightened. A methodology for user acceptance
was developed within the project, focusing on the balance
between performance and unjustified activations of the
system.
Moreover, the test results will be used for benefit estimation
of the PROSPECT systems. An important aspect of the project
will be to estimate the real-world benefit of the developed
systems, i.e. the improvement for traffic safety in terms of saved
lives or serious injuries and the resulting overall benefit - not
only the system performance measured in terms of detection rate
or speed reduction.
At this stage the project consortium implements the benefit
estimation methodology that includes an assessment of the
combined effect of active and passive safety measures (i.e.
integrated safety). The results from this analysis depend strongly
on testing activities that will take place in 2018 and will be
extrapolated to the EU-28 level. Finally, the expected fleet
penetration rates for 2020-2025 will be analysed.
5.4. Test results
In July 2017 a pre-testing event was organized at testing
tracks in Germany. The idea was to give all demo-car developers
the opportunity to get an impression of the new dummy design.
Furthermore, they could verify whether the methods for "hiding"
the dummy from vehicle sensors at the beginning of the various
test scenarios perform as expected.
What now follows is the next round of baseline tests
according to the PROSPECT test methodology that started in
September 2017 with four most advanced production vehicles
from European manufacturers. These tests represent the baseline
for the state-of-the-art of AEB systems and will focus on testing
dummy-vehicle interactions. The other objectives of testing
production vehicles against the first PROSPECT draft test
program are to generate not only baseline data but as well to
refine the test procedures(10)
. In the final stage of the project,
these results will be compared with the prototype performance.
The hypothesis that will be deeply studied is that current vehicles
from the market are able to address only a limited number of
PROSPECT scenarios.
The final tests of the three prototype vehicles developed
within PROSPECT will be conducted in the first half of 2018; in
surroundings and conditions as realistic as possible to real urban
roads.
6. CONCLUSION REMARKS AND NEXT STEPS
The proliferation and performance of ADAS systems has
increased in recent years. PROSPECT's primary goal is the
development of novel active safety features to prevent accidents
with VRUs such as pedestrians and cyclists in intersections. The
know-how obtained in the accident analysis and the derivation of
the PROSPECT use cases enable the development of improved
VRU sensing, modelling and path prediction capabilities. These
facilitate novel anticipatory driver warning and vehicle control
strategies, which will significantly increase system effectiveness
without increasing the false alarm/activation rate.
Multiple PROSPECT demonstrators (three vehicles, one
corresponding vehicle / simulator, one mobile simulator, dummy
specimen) will integrate the different technologies including
sensor setup position and orientation, sensor fusion, environment
information evaluation and processing, actuators and HMI
required covering the selected relevant use cases. Information
about the demonstrators to be developed in the project is
available on Deliverable D3.2.(8)
. Disruptive AEB systems will
be finally demonstrated to the public in three prototype vehicles
with the use of realistic dummy specimen during the final
PROSPECT event in October 2018 at testing tracks in Spain.
8. A driving simulator fulfilling the required characteristics has
already been implemented in order to be able to execute a first
subset of the PROSPECT use cases.
In the context of testing tools development, advanced
articulated dummies – Pedestrian and Cyclist – are already
developed to obtain higher degrees of freedom (head rotation,
torso angle, pedaling, side leaning, etc.) and an improved
behaviour during the acceleration- and stopping-phase.
What is known is that the European New Car Assessment
Program (Euro NCAP) will include the testing of Cyclist-AEB
systems from 2018 onwards in their safety assessment(11)
. The
CATS project (Cyclist-AEB Testing System) has worked on the
introduction of Cyclist-AEB systems and the corresponding
consumer tests in order to obtain a test setup and test protocol
and results have been shared with Euro NCAP for their 2018
protocols(12-13)
. With respect to CATS, more complex car-to-
cyclist scenarios will be implemented in demonstrators and
assessed through testing activities within the PROSPECT project.
The test methodologies generated in this project will be proposed
to Euro NCAP for standardization. The test methodologies and
tools shall be considered for 2020-2024 Euro NCAP test
programmes, supporting the European Commission goal of
halving the road toll.
The impact of the developed system is expected to increase
in about 36% the effectiveness respect to the state-of-the-art
VRU AEB systems, representing a significant reduction in terms
of VRU accidents. An important aspect of the project will be to
estimate the real-world benefit of the developed systems, i.e. the
improvement for traffic safety in terms of saved lives or
reduction of serious injuries taking into account the overall
benefit - not only the system performance measured in detection
rate or speed reduction.
The findings within the project that are presented in this
paper will contribute especially to the state-of-the-art about
accident analysis, advanced sensing, decision-making and
control technologies, assessment methodologies and tools for
advancing Advanced Driver Assistance Systems towards the
safety of VRUs.
Moreover, the project results will also enable the
improvement of today’s ADAS features and will be useful to
solve some of the challenges for the development and
deployment of increasingly automated vehicles towards fully
autonomous vehicles.
ACKNOWLEDGMENTS
PROSPECT is a collaborative research project funded by the
EC under Grant Agreement nº 634149. The authors would like to
thank partners of PROSPECT who contributed to the work
described in this paper: Applus IDIADA, BASt, Audi, BMW,
Bosch, Continental, Volvo, TNO, VTI, University of Nottingham,
University of Budapest, University of Amsterdam, IFSTTAR,
4activeSystems, TME, Daimler, and Chalmers.
REFERENCES
(1) World Health Organization (WHO) : Global status report on
road safety (2015).
(2) The European Commission, Vision Zero European
Commission : White Paper on Transport (2011).
(3) European New Car Assessment Programme Euro NCAP :
Test Protocol - AEB VRU systems Version 1.0.1 (2015).
(4) Gohl, A. Schneider, J. Stoll, M. Wisch, V. Nitsch: Car-to-
cyclist accidents from the car driver’s point of view, ICSC -
International Cycling Safety Conference (2016).
(5) M. Wisch, P. Seiniger, M. Edwards, T. Schaller, M. Pla, A.
Aparicio, S. Geronimi and N. Lubbe: European project AsPeCSS
- Interim result: Development of test scenarios based on
identified accident scenarios, 23rd ESV (Enhanced Safety of
Vehicles) Conference, Seoul, Paper Number 13-0405 (2013).
(6) M. Wisch, P. Seiniger, C. Pastor, M. Edwards, C. Visvikis
and C. Reeves: Scenarios and weighting factors for pre-crash
assessment of integrated pedestrian safety systems, EC FP7
AsPeCSS project Deliverable 1.1 (2013).
(7) PROSPECT Deliverable D2.1 : Accident Analysis,
Naturalistic Observations and Project Implications (2016).
(8) PROSPECT Deliverable D3.2 : Specification of the
PROSPECT demonstrators (2016).
(9) PROSPECT Deliverable D3.1 : The addressed VRU
scenarios within PROSPECT and associated test catalogue
(2016).
(10) PROSPECT Deliverable D7.4 : Draft Test protocol as a
proposal for consumer testing (2016).
(11) Euro NCAP. 2020 ROADMAP :
www.euroncap.com/en/about-euro-ncap/timeline/ (accessed 17
November 2017).
(12) O. Op den Camp, A. Ranjbar, J. Uittenbogaard, E. Rosen
and S. Buijssen : Overview of main accident scenarios in car-to-
cyclist accidents for use in AEB-system, test protocol,
International Cycling Safety Conference, Sweden (2014).
(13) Uittenbogaard, J., Op den Camp, O., van Montfort :
Overview of main accident parameters in car-to-cyclist accidents
for use in AEB-system test protocol (2016).