This study aims to determine if autonomous vehicles (AV) for last-mile deliveries are sustainable from three perspectives: social, environmental, and economic. Because of the relevance of AV application for last-mile delivery, safety was only addressed for the sake of societal sustainability. According to this study, it is rather safe to deploy AVs for delivery since current society’s speed restriction and decent road conditions give the foundation for AVs to run safely for last-mile delivery in metropolitan areas. Furthermore, AV has a distinct advantage in the event of a pandemic. The biggest worry for environmental sustainability is the emission problem. In terms of a series of emissions, it is established that AV has a substantial benefit in terms of emission reduction. This is mostly due to the differences in driving behaviour between autonomous cars and human vehicles. Because of AV’s commercial character, this research used a quantitative approach to highlight the economic sustainability of AV. The
study demonstrates the economic benefit of AV for various carrying capacities.
This research is aimed at confirming whether the autonomous vehicles (AV) for last-mile delivery is sustainable in terms of three aspects – social sustainability, environmental sustainability, and economic sustainability. The safety was solely considered for the social sustainability because of its importance of AV application for lastmile delivery. This study finds that it is relatively safe to use AVs for delivery because of the speed limit of actual society and the good road conditions provide the ground that AV runs safely for last-mile delivery in urban areas. Besides, AV has a special advantage when facing pandemic. For environmental sustainability, the emission problem
is the main concern. It is concluded that AV has a significant advantage in emission reduction in terms of a series of emissions. This mainly results from the driving behaviors difference between AV and human vehicles. As for the economic sustainability of AV, this research adopted a quantitative way to illustrate because the cost of AV is essential to consider because of AV’s commercial nature. The research reveals the cost advantage of AV under different
carrying capabilities.
White Paper on Transport Safety in the Era of Digital MobilityCarl Jackson
While remarkable progress has been made with technological, operational and behavioral improvements in the century-old, automotive-based transport systems used around the world, rapid technological changes are occurring that could amount to a reset in outcomes for transport users.
This research is aimed at confirming whether the autonomous vehicles (AV) for last-mile delivery is sustainable in terms of three aspects – social sustainability, environmental sustainability, and economic sustainability. The safety was solely considered for the social sustainability because of its importance of AV application for lastmile delivery. This study finds that it is relatively safe to use AVs for delivery because of the speed limit of actual society and the good road conditions provide the ground that AV runs safely for last-mile delivery in urban areas. Besides, AV has a special advantage when facing pandemic. For environmental sustainability, the emission problem
is the main concern. It is concluded that AV has a significant advantage in emission reduction in terms of a series of emissions. This mainly results from the driving behaviors difference between AV and human vehicles. As for the economic sustainability of AV, this research adopted a quantitative way to illustrate because the cost of AV is essential to consider because of AV’s commercial nature. The research reveals the cost advantage of AV under different
carrying capabilities.
White Paper on Transport Safety in the Era of Digital MobilityCarl Jackson
While remarkable progress has been made with technological, operational and behavioral improvements in the century-old, automotive-based transport systems used around the world, rapid technological changes are occurring that could amount to a reset in outcomes for transport users.
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 technology is in place to build more efficient, convenient and safer transport solutions. But there will be challenges to overcome, in terms of industry cooperation and trust on a sharing ecosystem.
Connectivity is causing a shift in business models from products to services, with data being the key asset affecting this change. As such, the transport industry is experiencing a seismic shift in technology, regulation and user behavior, which will force all key actors to reassess their business models.
Connectivity has already started to make an impact in the world of transport. The first phase focused on transactional connectivity, where data would be sent in the case of a traffic incident. Now, the focus of the second phase is on being connected, including sending and receiving data, and the ability to share it between companies and industries.
The technology is in place to build more efficient, convenient and safer transport solutions based on passenger vehicle-centric ecosystems. But there will be challenges to overcome, in terms of cooperating with new partners from different industries, gaining user trust, ensuring quality, reliability and security of data and controlling its flow in a highly shared environment. This paper takes a closer look at these challenges, and what will be required to move past them.
The importance of the Car hauling industry for safe and efficient vehicle transportation is Ongoing transformative changes in the car-hauling industry due to advancing technology and changing consumer demands. Explore the emerging trends and innovations shaping the future of car hauling.
It is important to understand the role of transporting vehicles from manufacturers to dealerships and consumers. We explore the advancements in technology driving transformative changes, meeting increasing consumer demands, safe and efficient vehicle transportation, and future-shaping trends and innovations in the car-hauling industry.
Investigating willingness to pay for congestion pricing in peshawar universit...EditorIJAERD
Congested road is a perfect example of tragedy of the commons as there is no restriction for drivers not to
exploit it. Car users are independent in their traveling decisions but their decisions have negative consequences for
others for which they do not pay rather the non-users pay for them in the form of hard cash, inconvenience and lack of
safety. This unwanted but widely practiced phenomena has over-shadowed the livable environment even in universities
all across Pakistan particularly in Peshawar university campus (case study) where the environment is exacerbated by
minimum personalized vehicle holders for the maximum non-car commuters resulting from the free vehicular entrance
and biased provision of infrastructure. This leads to huge social divide, inequality and gender disparity. In addition to
finding appropriate rent for provision of new equitable, environment and gender friendly modes of transport like rental
bikes and golf carts, Willingness to pay for congestion pricing as proposed solution is investigated through online webbased questionnaire survey from 580 respondents and statistical analysis is used for selecting most feasible mode(s) of
alternate in-campus transportation. Results showed that 67.6% respondents were WTP for congestion charging and
55.3% selected golf carts as their preferred mode in campus followed by rental bike with 27.6%. Appropriate rent chosen
for golf cart was PKR 20 and less than PKR 20 for rental bikes by more than half of the respondents. Congestion pricing
was perceived as effective solution and proposed modes were opted as the preferred modes for traveling in campus.
Electric Mobility and Development Worldbank UITP EVConsultEVConsult
The report, prepared by the World Bank and UITP—the International Association of Public Transport, and ESMAP—the Energy Sector Management Assistance Program, lays out basic principles for eMobility programs that respond to the climate, economic, fiscal, technical, institutional, and policy circumstances of different countries.
Sustainable Last mile delivery- challenges & opportunities.pdfHamid Saeedi
Due to urbanization trends, and megacities, the main part of the last mile happens in urban areas. The cost of providing last-mile services accounts for around 40% of overall supply chain costs. This is more than double compared to any other operations, such as parceling or warehousing in a supply chain. It’s a challenge not just in terms of costs, but also in terms of environmental impact. Transportation in the last mile is accountable for around 25% of GHG emissions in urban areas, and it is expected a 32% jump in carbon emissions from urban delivery by 2030. Last-mile delivery is the most inefficient part of the supply chain, because of small order sizes, lack of consolidation, network conditions, short lead times, and many constantly changing and geographically dispersed locations.
The recent focus on how to internalize the external costs of commuting have open a frontier of researches in estimating the private cost of commuting, however, there is still the dearth of knowledge on what constitute social cost of transportation in developing countries. This study estimates the private costs of commuting in Metropolitan Lagos. Data were collected on the socio-economic characteristics of commuting households (income, wages, modal choice,
Last-mile delivery is the final stage in the network of courier, express, and parcel companies
(CEP). It is an entire ecosystem that brings a variety of goods to consumers’ doorsteps (or
very close). In 2016, we looked at the transport market – and in particular last-mile delivery –
from two industry perspectives: commercial vehicles (advanced industries sector) and CEP
(logistics sector). Our analyses revealed three main insights
The present paper developed an integrated closed-loop supply chain model by considering social responsibility. The novelty of this research is considering social responsibility in the model. In order to achieve this goal, a three-objective mathematical model was presented with the following aims: 1) Minimizing the costs, 2) Maximizing social responsibility or social benefits of the model, and 3) Minimizing the adverse environmental effects. The mathematical method which is applied proves the validity of the model.
Autonomous vehicles for smart and sustainable cities an in-depth exploratio...Araz Taeihagh
Amidst rapid urban development, sustainable transportation solutions are required to meet the increasing demands for mobility whilst mitigating the potentially negative social, economic, and environmental impacts. This study analyses autonomous vehicles (AVs) as a potential transportation solution for smart and sustainable development. We identified privacy and cybersecurity risks of AVs as crucial to the development of smart and sustainable cities and examined the steps taken by governments around the world to address these risks. We highlight the literature that supports why AVs are essential for smart and sustainable development. We then identify the aspects of privacy and cybersecurity in AVs that are important for smart and sustainable development. Lastly, we review the efforts taken by federal governments in the US, the UK, China, Australia, Japan, Singapore, South Korea, Germany, France, and the EU, and by US state governments to address AV-related privacy and cybersecurity risks in-depth. Overall, the actions taken by governments to address privacy risks are mainly in the form of regulations or voluntary guidelines. To address cybersecurity risks, governments have mostly resorted to regulations that are not specific to AVs and are conducting research and fostering research collaborations with the private sector.
Future of transport An initial perspective - Professor Glenn Lyons, UWE, Br...Future Agenda
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General Overview and Forecasting of Factors Affecting the Use of Electric Veh...ijtsrd
Electric vehicles are being promoted in a number of countries as a way to reduce greenhouse gas emissions and fossil fuel depletion. The rate of adoption of electric vehicles, on the other hand, varies per country. The studys goals were to compare factors that influence electric car uptake and to generate policy suggestions. The design of electric vehicles EVs is an example of a successful policy. It has been demonstrated that there is no single appropriate policy or country specific scenario for supplying electric vehicles. Because electric vehicles are becoming more popular, a policy mix that promotes their proliferation in many countries is required. Government support for EV and charging station adoption appears to dwindle when EV and charging station designs advance beyond a certain point, maybe due to dwindling customer demand. Reduce the cost of electric car charging as well as the cost of license plate registration is one of the most essential things the many countries can do. Abdussalam Ali Ahmed | Mohamed Belrzaeg "General Overview and Forecasting of Factors Affecting the Use of Electric Vehicles" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-2 , February 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49405.pdf Paper URL: https://www.ijtsrd.com/engineering/automotive-engineering/49405/general-overview-and-forecasting-of-factors-affecting-the-use-of-electric-vehicles/abdussalam-ali-ahmed
Air quality forecasting using convolutional neural networksBIJIAM Journal
Air pollution is now one of the biggest environmental risks, which causes more than 6 million premature deathseach year from heart diseases, stroke, diabetes, respiratory disease, and so on. Protecting humans from thedamage which is caused by air pollution is one of the major issues for the global community. The prediction ofair pollution can be done by machine learning (ML) algorithms. ML combines statistics and computer science tomaximize the prediction power. ML can be also used to predict the air quality index (AQI). The aim of this researchis to develop a convolutional neural network (CNN) model to predict air quality from the unseen data set, whichincludes concentration of nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2). The proposedsystem will be implemented in two steps; the first step will focus on data analysis and pre-processing, includingfiltering, feature extraction, constructing convolutional neural network layers, and optimizing the parameters ofeach layer, while the second step is used to evaluate its model accuracy. The output is predicted as AQI for thedeveloped CNN model. The developed CNN model achieves a root-mean-square error of 13.4150 and a highaccuracy of 86.585%. The overall model is implemented using MATLAB software.
Prevention of fire and hunting in forests using machine learning for sustaina...BIJIAM Journal
Deforestation, illegal hunting, and forest fires are a few current issues that have an impact on the diversity andecosystem of forests. To increase the biodiversity of species and ecosystems, it becomes imperative to preservethe forest. The conventional techniques employed to prevent these issues are costly, less effective, and insecure.The current systems are unreliable and use more energy. By utilizing an Internet of Things (IOT) system, thistechnology offers a more practical and economical method of continuously maintaining and monitoring the statusof the forest. To guarantee excellent security, this system combines a number of sensors, alarms, cameras, lights,and microphones. It aids in reducing forest loss, animal trafficking, and forest fires. In the suggested system,sensors are used for monitoring, and cloud storage is used for data storage. Through the use of machine learning,the raspberry pi camera module significantly aids in the prevention of unlawful wildlife hunting as well as thedetection and prevention of forest fires.
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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 technology is in place to build more efficient, convenient and safer transport solutions. But there will be challenges to overcome, in terms of industry cooperation and trust on a sharing ecosystem.
Connectivity is causing a shift in business models from products to services, with data being the key asset affecting this change. As such, the transport industry is experiencing a seismic shift in technology, regulation and user behavior, which will force all key actors to reassess their business models.
Connectivity has already started to make an impact in the world of transport. The first phase focused on transactional connectivity, where data would be sent in the case of a traffic incident. Now, the focus of the second phase is on being connected, including sending and receiving data, and the ability to share it between companies and industries.
The technology is in place to build more efficient, convenient and safer transport solutions based on passenger vehicle-centric ecosystems. But there will be challenges to overcome, in terms of cooperating with new partners from different industries, gaining user trust, ensuring quality, reliability and security of data and controlling its flow in a highly shared environment. This paper takes a closer look at these challenges, and what will be required to move past them.
The importance of the Car hauling industry for safe and efficient vehicle transportation is Ongoing transformative changes in the car-hauling industry due to advancing technology and changing consumer demands. Explore the emerging trends and innovations shaping the future of car hauling.
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Investigating willingness to pay for congestion pricing in peshawar universit...EditorIJAERD
Congested road is a perfect example of tragedy of the commons as there is no restriction for drivers not to
exploit it. Car users are independent in their traveling decisions but their decisions have negative consequences for
others for which they do not pay rather the non-users pay for them in the form of hard cash, inconvenience and lack of
safety. This unwanted but widely practiced phenomena has over-shadowed the livable environment even in universities
all across Pakistan particularly in Peshawar university campus (case study) where the environment is exacerbated by
minimum personalized vehicle holders for the maximum non-car commuters resulting from the free vehicular entrance
and biased provision of infrastructure. This leads to huge social divide, inequality and gender disparity. In addition to
finding appropriate rent for provision of new equitable, environment and gender friendly modes of transport like rental
bikes and golf carts, Willingness to pay for congestion pricing as proposed solution is investigated through online webbased questionnaire survey from 580 respondents and statistical analysis is used for selecting most feasible mode(s) of
alternate in-campus transportation. Results showed that 67.6% respondents were WTP for congestion charging and
55.3% selected golf carts as their preferred mode in campus followed by rental bike with 27.6%. Appropriate rent chosen
for golf cart was PKR 20 and less than PKR 20 for rental bikes by more than half of the respondents. Congestion pricing
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Electric Mobility and Development Worldbank UITP EVConsultEVConsult
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Sustainable Last mile delivery- challenges & opportunities.pdfHamid Saeedi
Due to urbanization trends, and megacities, the main part of the last mile happens in urban areas. The cost of providing last-mile services accounts for around 40% of overall supply chain costs. This is more than double compared to any other operations, such as parceling or warehousing in a supply chain. It’s a challenge not just in terms of costs, but also in terms of environmental impact. Transportation in the last mile is accountable for around 25% of GHG emissions in urban areas, and it is expected a 32% jump in carbon emissions from urban delivery by 2030. Last-mile delivery is the most inefficient part of the supply chain, because of small order sizes, lack of consolidation, network conditions, short lead times, and many constantly changing and geographically dispersed locations.
The recent focus on how to internalize the external costs of commuting have open a frontier of researches in estimating the private cost of commuting, however, there is still the dearth of knowledge on what constitute social cost of transportation in developing countries. This study estimates the private costs of commuting in Metropolitan Lagos. Data were collected on the socio-economic characteristics of commuting households (income, wages, modal choice,
Last-mile delivery is the final stage in the network of courier, express, and parcel companies
(CEP). It is an entire ecosystem that brings a variety of goods to consumers’ doorsteps (or
very close). In 2016, we looked at the transport market – and in particular last-mile delivery –
from two industry perspectives: commercial vehicles (advanced industries sector) and CEP
(logistics sector). Our analyses revealed three main insights
The present paper developed an integrated closed-loop supply chain model by considering social responsibility. The novelty of this research is considering social responsibility in the model. In order to achieve this goal, a three-objective mathematical model was presented with the following aims: 1) Minimizing the costs, 2) Maximizing social responsibility or social benefits of the model, and 3) Minimizing the adverse environmental effects. The mathematical method which is applied proves the validity of the model.
Autonomous vehicles for smart and sustainable cities an in-depth exploratio...Araz Taeihagh
Amidst rapid urban development, sustainable transportation solutions are required to meet the increasing demands for mobility whilst mitigating the potentially negative social, economic, and environmental impacts. This study analyses autonomous vehicles (AVs) as a potential transportation solution for smart and sustainable development. We identified privacy and cybersecurity risks of AVs as crucial to the development of smart and sustainable cities and examined the steps taken by governments around the world to address these risks. We highlight the literature that supports why AVs are essential for smart and sustainable development. We then identify the aspects of privacy and cybersecurity in AVs that are important for smart and sustainable development. Lastly, we review the efforts taken by federal governments in the US, the UK, China, Australia, Japan, Singapore, South Korea, Germany, France, and the EU, and by US state governments to address AV-related privacy and cybersecurity risks in-depth. Overall, the actions taken by governments to address privacy risks are mainly in the form of regulations or voluntary guidelines. To address cybersecurity risks, governments have mostly resorted to regulations that are not specific to AVs and are conducting research and fostering research collaborations with the private sector.
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Electric vehicles are being promoted in a number of countries as a way to reduce greenhouse gas emissions and fossil fuel depletion. The rate of adoption of electric vehicles, on the other hand, varies per country. The studys goals were to compare factors that influence electric car uptake and to generate policy suggestions. The design of electric vehicles EVs is an example of a successful policy. It has been demonstrated that there is no single appropriate policy or country specific scenario for supplying electric vehicles. Because electric vehicles are becoming more popular, a policy mix that promotes their proliferation in many countries is required. Government support for EV and charging station adoption appears to dwindle when EV and charging station designs advance beyond a certain point, maybe due to dwindling customer demand. Reduce the cost of electric car charging as well as the cost of license plate registration is one of the most essential things the many countries can do. Abdussalam Ali Ahmed | Mohamed Belrzaeg "General Overview and Forecasting of Factors Affecting the Use of Electric Vehicles" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-2 , February 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49405.pdf Paper URL: https://www.ijtsrd.com/engineering/automotive-engineering/49405/general-overview-and-forecasting-of-factors-affecting-the-use-of-electric-vehicles/abdussalam-ali-ahmed
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Air pollution is now one of the biggest environmental risks, which causes more than 6 million premature deathseach year from heart diseases, stroke, diabetes, respiratory disease, and so on. Protecting humans from thedamage which is caused by air pollution is one of the major issues for the global community. The prediction ofair pollution can be done by machine learning (ML) algorithms. ML combines statistics and computer science tomaximize the prediction power. ML can be also used to predict the air quality index (AQI). The aim of this researchis to develop a convolutional neural network (CNN) model to predict air quality from the unseen data set, whichincludes concentration of nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2). The proposedsystem will be implemented in two steps; the first step will focus on data analysis and pre-processing, includingfiltering, feature extraction, constructing convolutional neural network layers, and optimizing the parameters ofeach layer, while the second step is used to evaluate its model accuracy. The output is predicted as AQI for thedeveloped CNN model. The developed CNN model achieves a root-mean-square error of 13.4150 and a highaccuracy of 86.585%. The overall model is implemented using MATLAB software.
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An Internet – of – Things Enabled Smart Fire Fighting SystemBIJIAM Journal
Fire accident is a mishap that could be either man made or natural. Fire accident occurs frequently and can be controlled but may at time result in severe loss of life and property. Many a times fire fighters struggle to sort out the exact source of fire as it is continuously flammable and it spreads all over the area. On this concern, we have designed an Internet – of – Things (IoT) based device which sorts out the exact source of fire through a software and
hardware devices and also the complete detail of an area can be visualized by fire fighters which are preinstalled in the software itself. Because of our system’s intelligence in decision making during fire fighting, the proposed system is claimed as ‘Smart Fire Fighting System’. The implementation of the smart fire fighting system can make
the fire fighters to analyze the current situation immediately and make the decision quicker in an effective manner. Because of this system, fire losses in a building can be greatly reduced and many lives can be rescued immediately and moreover fire spread can also be restricted.
Automation Attendance Systems Approaches: A Practical ReviewBIJIAM Journal
Accounting for people is the first step of every manpower-based organization in today’s world. Hence, it takes up a signification amount of energy and value in the form of money from respective organizations for both
implementing a suitable system for manpower management as well as maintaining that same system. Although this amount of expenditure for big organizations is near to nothing, rather just a formality, it does not hold as much truth for small organizations such as schools, colleges, and even universities to a certain degree. This is the first point. The second point for discussion is that much work has been done to solve this issue. Various technologies like Biometrics, RFID, Bluetooth, GPS, QR Code, etc., have been used to tackle the issues of attendance collection. This study paves
the path for researchers by reviewing practical methods and technologies used for existing attendance systems.
Transforming African Education Systems through the Application of IOTBIJIAM Journal
The project sought to provide a paradigm for improving African education systems through the use of the IOT. The created IOT model for Africa will enable African countries, notably Namibia, to exchange educational content and resources with other African countries. The objective behind the IOT paradigm in Africa’s education sectors is to provide open access to knowledge and information. The study revealed that there are no recognised platforms in African education systems that are utilised by African governments to interact, communicate, and share educational material directly with African institutions. As a result, the current research developed a model for
transforming African education systems using the IOT in the Namibian context, which will serve as a centralised online platform for self-study, new skill acquisition, and self-improvement using materials provided by African institutions of higher learning. Everyone is welcome to use the platform, including students, instructors, and
members of the general public.
Deep Learning Analysis for Estimating Sleep Syndrome Detection Utilizing the ...BIJIAM Journal
Manual sleep stage scoring is frequently performed by sleep specialists by visually evaluating the patient’s neurophysiological signals acquired in sleep laboratories. This is a difficult, time-consuming, & laborious process. Because of the limits of human sleep stage scoring, there is a greater need for creating Automatic Sleep Stage Classification (ASSC) systems. Sleep stage categorization is the process of distinguishing the distinct stages of sleep & is an important step in assisting physicians in the diagnosis & treatment of associated sleep disorders. In this research, we offer a unique method & a practical strategy to predicting early onsets of sleep disorders, such as restless leg syndrome & insomnia, using the Twin Convolutional Model FTC2, based on an algorithm composed of two modules. To provide localised time-frequency information, 30 second long epochs of EEG recordings are subjected to a Fast Fourier Transform, & a deep convolutional LSTM neural network is trained for sleep stage categorization. Automating sleep stages detection from EEG data offers a great potential to tackling sleep irregularities on a
daily basis. Thereby, a novel approach for sleep stage classification is proposed which combines the best of signal
processing & statistics. In this study, we used the PhysioNet Sleep European Data Format (EDF) Database. The code
evaluation showed impressive results, reaching accuracy of 90.43, precision of 77.76, recall of 93,32, F1-score of 89.12 with the final mean false error loss 0.09. All the source code is availlable at https://github.com/timothy102/eeg.
Robotic Mushroom Harvesting by Employing Probabilistic Road Map and Inverse K...BIJIAM Journal
A collision-free path to a destination position in a random farm is determined using a probabilistic roadmap (PRM) that can manage static and dynamic obstacles. The position of ripening mushrooms is a result of picture processing. A mushroom harvesting robot is explored that uses inverse kinematics (IK) at the target
position to compute the state of a robotic hand for grasping a ripening mushroom and plucking it. The DenavitHartenberg approach was used to create a kinematic model of a two-finger dexterous hand with three degrees of freedom for mushroom picking. Unlike prior experiments in mushroom harvesting, mushrooms are not planted in a grid or design, but are randomly scattered. At any point throughout the harvesting process, no human interaction is necessary
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.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
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.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptx
Evaluate Sustainability of Using Autonomous Vehicles for the Last-mile Delivery Industry
1. BOHR International Journal of Internet of Things, Artificial Intelligence and Machine Learning
2022, Vol. 1, No. 1, pp. 32–43
https://doi.org/10.54646/bijiam.006
www.bohrpub.com
Evaluate Sustainability of Using Autonomous Vehicles for the
Last-mile Delivery Industry
Linghan Huang
Coventry Business School, Coventry University, Coventry, United Kingdom
E-mail: huanglinghan0@gmail.com
Abstract. This study aims to determine if autonomous vehicles (AV) for last-mile deliveries are sustainable from
three perspectives: social, environmental, and economic. Because of the relevance of AV application for last-mile
delivery, safety was only addressed for the sake of societal sustainability. According to this study, it is rather safe to
deploy AVs for delivery since current society’s speed restriction and decent road conditions give the foundation
for AVs to run safely for last-mile delivery in metropolitan areas. Furthermore, AV has a distinct advantage in
the event of a pandemic. The biggest worry for environmental sustainability is the emission problem. In terms
of a series of emissions, it is established that AV has a substantial benefit in terms of emission reduction. This is
mostly due to the differences in driving behaviour between autonomous cars and human vehicles. Because of AV’s
commercial character, this research used a quantitative approach to highlight the economic sustainability of AV. The
study demonstrates the economic benefit of AV for various carrying capacities.
Keywords: Supply Chain Management, Logistics, Sustainability, Autonomous Vehicles.
INTRODUCTION
The income in the E-commerce market is US$2,237,481m in
2020 and this figure is anticipated to grow 7.6% annually
(CAGR 2020–2024), a trend that results in market value of
US$3,003,971m in 2024. The E-commerce market’s largest
part is made up of fashion, which occupies US$717,993m in
2020. Moreover, E-commerce user penetration is estimated
to increase from 56.1% in 2020 to 65.5% in 2024. The aver-
age revenue per user (ARPU) currently is US$535.70 [43].
The customers in the e-commerce market rose gradually
during the past few years and this number was estimated
to go up to 5,060.3m by 2024.
Express delivery is a necessary support for online shop-
ping so that the delivery market was boomed significantly
with such a flourishing worldwide e-commerce market.
The courier, express, and parcel (CEP) market volume in
the world increased stably from 2009 to 2018 and reached
306.18 billion euros [27]. In addition, the global CEP market
is expected to grow by USD 90.63 billion during 2019-2023,
progressing at a compound annual growth rate of over
5% (Businesswire 2019). There are three main companies
-namely, DHL, FedEx Corp, UPS- to share the couriers
and local delivery service. For example, the three delivery
giants account for more than 90% of the delivery service
business in the world in 2018. Another research (Allied
Market Research 2019) shows that the world autonomous
last-mile delivery market volume is estimated to reach
$11.13 billion by 2021, and is anticipated to increase to
$75.65 billion by 2030, progressing a compound average
growth rate of 23.7%. North America is expected to be
the highest revenue contributor, which accounts for $4.5
billion by 2021, and this number is projected to climb to
$35.67 billion by 2030, with a compound average growth
rate of 25.9%. Europe and North America are predicted to
collectively account for approximately 71.1% in 2021, with
the former constituting roughly 40.6%. Europe and North
America are estimated to witness considerable compound
average growth rates of 25.9% and 24.5%, respectively,
during the forecast period. The cumulative share of these
two parts is expected to be 71.1% in 2021 and is projected
to ascend to 79.1% by 2030.
Overall, the rapid growth of urbanization and the rise
in the disposable income of consumers is booming the
e-commerce industry. An inclination toward online ser-
vices because the rise in usage of smartphone devices has
32
2. Evaluate Sustainability of Using Autonomous Vehicles for the Last-mile Delivery Industry 33
caused the growth of trade through online portals. This
phenomenon, in turn, has been flourishing the worldwide
express delivery industry. The rise in internet penetration
led to an increase in last-mile delivery services. Addi-
tionally, multinational e-commerce organizations – such as
Amazon – are paying attention to the progress of their
speed of delivery and reach. Therefore, these firms are
investing remarkably in express delivery businesses. Last-
mile delivery is the last step in the network of CEP. It is an
entire ecosystem that brings various goods to customers’
doors (or very close). According to a survey conducted
by Mckinsey [28], there are three insights in this industry:
consumer expectations are high and these expectations
are going up, automation potential is high, competitive
dynamics are changing [28].
The research aims to identify the sustainability of
autonomous drive for last-mile delivery from three per-
spectives: social sustainability, environmental sustainabil-
ity, and economic sustainability. Moreover, this research
also aims to put forward suggestions for the using strategy
of autonomous vehicles (AV) for delivery. To analyze the
sustainability, the three pillars – social sustainability, envi-
ronmental sustainability, and economic sustainability –
were discussed step by step. This research first qualita-
tively analyzes the social and environmental sustainability
through identifying the current status of safety status
and the emission of AVs. For social sustainability, even
though social sustainability has four main components
theoretically, the safety was solely discussed because of
its importance of AV application for last-mile delivery.
The safety issue was divided into context safety, driving
behavior safety, and technology safety. For environmental
sustainability, the main topic in this part is the emission
of AV because the emission is the most significant part of
AV related to the environment. This research cites a large
number of data and research to show the emission status
of AV. Then this research tries to quantitatively analyze the
economic sustainability through building a quantitative
model to calculate the average expenditure of AVs and
conducts a comparison between the cost of self-piloting
automobiles and the cost of manned vehicles, in order to
analyze and discuss the cost advantage of the two types of
vehicles for delivery. Based on the cost advantages of AVs,
this research finally proposes some recommendations for
the use of AVs.
This paper is mainly organized in light of objectives.
After a general introduction about the delivery industry
status, research aims, and research objectives, a literature
review is presented in the second stage, which includes
the background of the autonomous drive for the last-
mile delivery and the sustainability of this transportation.
Sustainability is divided into three parts – namely, social
sustainability, environmental sustainability, and economic
sustainability. The following three sections are the analysis
and discussion of social, environmental, and economic sus-
tainability. In addition, the findings of each sustainability
are carried out at the end of each section. Finally, the
main body of this research ends up with a conclusion,
which is made up of a research overview, key findings,
recommendation, limitation of the research, future research
suggestions, and conclusion. The reference list and the
ethics certificate are placed in the last.
LITERATURE REVIEW
The Application of AVs in Delivery
It is believed that the combination of intelligent ordering
methods-such as telephone and internet-and up to date
supply chain management techniques supports companies
to serve their customers in innovative ways. These ways
are convenient, of high quality, customized, and enjoyable
experiences in the commercial context that has increas-
ingly been dominated by the importance of cheap service
and any meaningful connection with customers [8]. In
addition, Gramatikov et al. [18] stated that the amount
of online orders is increasing stably; accordingly, it is
necessary to deliver goods to the customer efficiently and
environmentally friendly. The AVs are obviously becoming
the next revolution of the goods delivery-should be the
background.
Schröder et al. (2018) argued in the research of fast-
forwarding last-mile delivery that consumer expectations
are high and rising, automation potential is high and
that competitive dynamics are changing. The three main
insights in this research provided the fundamental needs of
the autonomous drive for delivery; accordingly, it is neces-
sary to conduct further research in terms of autonomous
drive sustainability. However, Michael and Delila (2018)
pose some questions on this advanced technology in terms
of safety concerns, environmental risks, and economic
issues. They illustrated the problems in general circum-
stances but did not consider the details of a specific
scenario. These potential problems could have decisive
impacts on the implementation of AVs in the ‘last mile’.
Moreover, if these problems can be probed, the correspond-
ing conclusions can be used to illustrate the sustainability
of autonomous delivery. This research is going to research
the sustainability of the autonomous drive of last-mile
delivery in terms of those risks mentioned above.
Sustainability
The definition Portney [37, 3] provided by the World Com-
mission on Environment and Development in 1987 argued
that sustainability is an economic-development activity
that meets the current requirements without impairing the
ability of future generations to satisfy their requirements.
However, Robert et al. [41] contend that sustainability is
meeting basic human needs while protecting the earth’s
life support systems. Besides, Lim and Taeihagh [24] sup-
pose that sustainability is not an objective but a course
3. 34 Linghan Huang
of continuous advance according to the needs and the
context, which can change in space and time. Moreover,
the organization corporate finance institute (CFI) defines
sustainability as the capability to provide for the needs of
the current generation using available resources without
adversely impacting future generations [9]. It seems that
they have a reasonable perspective to define sustainability.
The three opinions, however, cannot generalize sustain-
ability separately. However, it is realistic to utilize them
individually when facing a specific issue.
The three-pillar – social, environmental, and economic –
conception of sustainability, normally described by three
intersecting circles with sustainability at the centre, has
become pervasive [39]. Furthermore, Chokshi [10] sup-
poses that economic, environmental, and social pillars are
foremost in assessing sustainability and if any one of
the three pillars is weak, the overall system can become
unsustainable. As a result, when the AV emerges, the
three-pillars theory is exacting standard to assess the sus-
tainability of this innovative means of transportation. This
research is going to analyze whether this transportation for
delivery is sustainable by applying this theory. The follow-
ing sections are divided into three parts to analyze social
sustainability, environmental sustainability, and economic
sustainability respectively.
Social Sustainability
There is little literature that pays attention to social sus-
tainability so that a detailed interpretation of this concept
is still lacking [11]. However, a study by the OECD [22]
supports the idea that social sustainability is dealt with
in connection with the social influences of environmental
politics rather than regarded as an equal component of
sustainable development. Moreover, Assefa and Frostell [4]
believe that social sustainability is the outcome of develop-
ment while environmental and economic sustainability are
both the objectives of sustainable development and tools to
its realization.
Overall, even though the past definitions of social sus-
tainability are few and unclear, it is easy to connect
the social sustainability with the autonomous drive. For
example, the potential social impact generated by AVs is
correlating with social sustainability. For example, if an
AV launches an accident and hurt people, it indisputably
impacts society. Thus, this research chooses safety as, one
of the social issues, a topic to analyze the sustainability of
AV for delivery.
Environmental Sustainability
A simple and traditional explanation of environmental
sustainability is meeting human needs without jeopar-
dizing the health of ecosystems [30]. Similarly, Moldan
et al. [29] suppose that environmental sustainability is the
preservation or improvement to the integrity of the earth’s
Figure 1. Three pillars of sustainability.
life operating systems. Environmental sustainability is the
second pillar, which is one of the main concerns of the
future of humanity. It indicates how we should study and
preserve the ecosystems, air quality, sustainability of our
natural resources and focus on the components that ham-
per our environment [10]. Overall, most of the definition
of environmental sustainability is focused on its biogeo-
physical aspects. When it comes to the environmental
sustainability of autonomous drive for last-mile delivery,
this research pays attention to the vehicle’s emission in the
process of transportation.
Economic Sustainability
Economic sustainability is the motivation of businesses
and organizations, which is aimed at observing and obey-
ing sustainability guidelines beyond their normal legal
requirements. It should also encourage the average person
to play their roles wherever they can; an individual rarely
achieves much, but a group can go further [10]. As shown
in following Figure 1, the three pillars theory is a relatively
comprehensive definition of sustainability.
Based on the discussion of sustainability, this research
is going the apply the three pillars model to analyze the
autonomous drive delivery of last-mile. For the economic
aspect, this research is going to investigate the cost of
autonomous drive and compare it with the traditional
delivery of last-mile. When it comes to social sustainabil-
ity, this research focuses on the risks that could impact
customers. The emission will be the theme in terms of the
environmental part.
SUSTAINABILITY ANALYSIS
Social Sustainability (Safety)
The social influence of business is easy to identify but
difficult to assess, however, understanding the effects on
4. Evaluate Sustainability of Using Autonomous Vehicles for the Last-mile Delivery Industry 35
Figure 2. Conceptual framework of social sustainability [13].
society and the environment is important to achieve sus-
tainability [44]. Eizenberg and Jabareen [13] proposed a
general conceptual framework (see Figure 2) of Social
Sustainability, a framework comprises four associated con-
cepts of socially oriented practices, where each concept
has a particular function in the framework and incorpo-
rates primary social aspects. The concept of safety in this
framework is the ontological foundation of sustainability
in general and social sustainability in particular. The con-
cept refers to the right to not only be safe but also take
all methods of security and adaptation to prevent future
casualties and physical injury. This framework and the
corresponding definition provide the evidence that it is
essential to analyze the safety issues of the autonomous
drive for delivery before implementation. Hence, safety
issues related to autonomous drive will be discussed and
analyzed in the following paragraphs.
Context Safety
The last-mile delivery is usually the final part of the entire
delivery and the environment is probably complicated and
of high risk, especially in the crowded urban area, which
has a large number of pedestrians, trucks, cyclists, buses,
cars, and different barriers. Those subjects have different
moving directions at different times. This circumstance
makes the context of last-mile delivery suffer huge safety
risks. However, the driving speed limit of cities is normally
low. For example, the UK national speed limit is 30 miles
per hour in built-up areas [16], a limit applied to all kinds
of automobiles such as cars, vans, motorcycles, coaches,
buses, and goods vehicles. If the AVs are designed with
relatively low speed as well, the vehicles would have
sufficient time to judge, respond, and control themselves.
Therefore, it can be expected that the safety risk from a
speed perspective is relatively low. Second, most areas
that need last-mile delivery are located in urban areas,
which has a relatively good road condition. AV could
be safer when running in those roads compared to bad
road condition. For example, AV is not likely to create an
overturned accident running on flat roads.
Driving Behaviour Safety
It is true that the misoperation while driving can hardly be
prevented such as drink-driving, seatbelt use, and fatigue-
driving. Most countries have established a set of very strict
regulations and legislation to prevent improper and law-
less driving. For example, according to UK drink-driving
penalties rules [17], those people who drive or attempt
to drive while above the legal regulation through drink
may get: 6 months’ imprisonment, an unlimited fine, and a
driving ban for at least 1 year (3 years if convicted twice in
10 years)
Despite such rigorous legislation, approximately 1.2 mil-
lion people die and millions more are harmed or disabled
resulted from road accidents all over the world each
year [45]. Besides, another study (OECD 2017) shows that
an anticipated 20–28% (25% average) of all road casualties
in Europe correlate with alcohol use. Furthermore, fatigue
driving contributes to 10–20% of road crashes worldwide
(European Road Safety Observatory 2018), and 4% of fatal
crashes in Britain are caused by tiredness (GOV.UK 2015).
These data show manned driving has severe disadvan-
tages in terms of the process of manual driving. Also, Araz
Taeihagh & Hazel Si Min Lim [3] stated that more than 90%
of road tragedies are projected to be the consequence of
human fault; consequently, choosing AVs can potentially
reduce or eliminate the largest cause of traffic accidents and
also outperform human drivers in execution, perception,
and decision-making.
A study by McKinsey & Company [6] expects that in
a future where all cars are AVs, people could witness
an accident rate that reduces up to 90%. The important
reason for this reduction is that AV can eliminate the
occurrence of human faults: from loss of attention to delay
of reaction and failure to conform to the regulations of the
road because AV does not get tired, angry, frustrated, or
drunk [5]. Notably, delivery divers for manned vehicles –
who work long times with few rests – could be more
vulnerable to these faults. Another possible reason why AV
is safer is the AV drive system probably performs driving
better than humans. For example, human has a visual
blind point when driving while AV can avoid this through
programming.
Technology Safety
The implementation of AV for delivery is unrealistic with-
out enough support from unmanned drive technology.
Litman [25] stated the impacts on self-driving as well as
5. 36 Linghan Huang
Figure 3. COVID-19 confirmed cases statistic (Johns Hopkins University 2020).
their implications for various planning issues. It investi-
gated the speed of self-driving, costs and benefits, and
how they are likely to influence travel needs. Although
this analysis is not focusing on the autonomous drive for
delivery, the estimated implication in the future suggests
that the viability of autonomous drive is fulfilled in terms
of the technology aspect.
However, Lim and Taeihagh [24] argue that despite the
removal of driver mistake, risks may generate from a myr-
iad of elements, such as system mistakes, cyber-attacks on
safety systems, and incautious behavior from passengers
and pedestrians. Moreover, it is believed that vehicles have
become increasingly heavy during the past years to meet
stricter crash test standards and that no AV will be released
to use without meeting those strict test standards.
Response to COVID-19
Since the first Corona Virus (COVID-19) confirmed in
Wuhan city, China On 31 December 2019, there are
3,271,892 confirmed cases (see Figure 3) worldwide on
30 April 2020 (Johns Hopkins University 2020).
During such pandemic, autonomous vehicles have a
significant advantage when running on the road because
it creates no infected risk while servicing people. Thus,
it could be utilized to service delivery, healthy materials
transportation, and any transportation task related to fight-
ing COVID-19. For example, autonomous vehicles move
COVID-19 tests in Florida [15].
Environmental Sustainability
Environmental protection is more and more important in
modern society. Any kind of transportation for last-mile
delivery should consume less and environment-friendly
energy. The emission conducted by transportation is
becoming more and more noteworthy. For instance, a
carbon dioxide emission figure [36] shows that America’s
trucks, automobiles, and aircraft emit more carbon dioxide
than its power plants do since February 2016. Accordingly,
it is necessary to find out whether the autonomous drive
harms the environment to assess the sustainability of AV
last-mile delivery. In the last-mile delivery scenarios, the
first environmental issue that is easy to come into mind is
the emission problems. Therefore, an emission analysis of
AV in the process of last-mile delivery will be conducted in
the following sections.
Greenblatt and Saxena [19] found that small, shared
electric-driven AVs in combination with a future low-
carbon electricity grid could lessen per-mile (km) green-
house gas emissions by 90% compared to current auto-
mobiles. Besides, Igliñski and Babiak [20] conclude that
precise anticipation of the possibility of AV in the decrease
of greenhouse gas emission is very difficult because of a
set of variable factors that condition the operation of the
future transport system. It may, however, be estimated that
the total decrease will be roughly 40–60%. Moreover, they
found that the drop of emissions will only happen after AV
becomes more prevalent, and this requires their creators to
reach the 5th level of autonomy, at which people will be
freed from controlling cars.
A research [40] shows that adopting more efficient driv-
ing patterns is a method to decrease emissions from AVs.
Reducing human interaction with driving would decrease
repetitive acceleration and braking and even permit cars
to run closer together which is known to enhance aero-
dynamics. Thereafter, a quantitative analysis, aimed at
expecting the emission impacts of AV, carried out by Liu
et al. [26] conclude that AV runs smoother than manned
vehicle because AV is projected to be faster and more
6. Evaluate Sustainability of Using Autonomous Vehicles for the Last-mile Delivery Industry 37
Figure 4. Automation levels (National Highway Traffic Safety Administration 2017).
accurate than human drivers in terms of reaction times and
driving skills. They believe that human drivers are likely to
conduct drastic and continual speed fluctuations (i.e. hard
brakes and fast accelerations) and have a long reaction
time (e.g. 1.5 seconds) while AV technologies may rarely
be influenced by such fluctuations, allowing for smoother
driving. Therefore, they contend that hard braking and
rapid acceleration actions correlate with increased emis-
sions, so, by smoothing human vehicles’ existing driving
cycles, this work expects the emission advantages of AVs.
Furthermore, Liu et al. [26] found that the results from
their modeling and calculation show that, normally, if
human vehicles are substituted by AVs, greater emission
benefits (up to 14% emission decrease) are estimated in
driving conditions where there are much hard acceleration
and braking events, and for drivers with bad driving
styles. The outcomes of Austin cycle signify the average
emission drops are 10.89% for volatile organic compounds
(VOC), 19.09% for fine particulate matter (PM2.5), 13.23%
for carbon monoxide (CO), 15.51% for nitrogen oxides
(NOx), and 6.55% for sulfur dioxide (SO2) and carbon
dioxide (CO2). They also found that the road links with
higher mean speeds have greater emission decreases in
all emission items. This quantitative analysis presents the
specific values of each emission that AV can reduce when
compared to manned vehicles. It justified the advantage of
AV in terms of emission reduction.
However, it is still hard to say that the emission will
drop if the manned vehicle is replaced by AV. The reason is
some researches show that the traveled vehicle miles will
increase so that the total emission will rise [1] – they believe
the automation reduces the opportunity cost of driving.
This probably encourages people to take more automobile
journeys or accept longer commutes because people would
be able to multitask in cars rather than concentrating on
the road. Besides, AV technology could permit groups of
people who are currently unable to drive—such as the
aged, young people, and disabled people—to travel alone
in AVs, making more people on the road. Hence, the total
emission will increase.
On the other hand, AVs may also contribute to solv-
ing the parking problems in the long run. In addition
to the environmental issues of energy production and
consumption, the existing cars impact much of the living
environment. Traditional car occupies a considerable acre
for parking even in the crowded city center. However,
being able to drive and park themselves at some distant
location from their users, AVs may need no nearby park-
ing lot for residents, workers, or business establishments,
which may be able to restructure the urban environment
and allow new construction development because nearby
parking lots are unnecessary.
Economic Sustainability
Newman et al. [32] argue that qualitative analysis vir-
tually reflects some sort of individual phenomenological
perspective. Most quantitative research, however, tends
to emphasize the common reality that people can agree.
Therefore, sole qualitative can not illustrate sustainability
sufficiently and it is necessary to carry out a quantitative
analysis. The following sections apply several mathematic
methods to supplement the qualitative analysis to demon-
strate sustainability.
To investigate the cost of the autonomous drive for
the last-mile, this research simulates a model based on
a real scenario. This scenario depicts the process that
goods transportation from a storefront of Lidl to a city
7. 38 Linghan Huang
center (Hub). There are two transport methods that will
be applied to this route including autonomous drive and
manual drive.
First, this route is stipulated as from Lidl supermarket
to the courier locker at Hub (L-H). Then, the distance
and transport time of this route are calculated from the
OPENROUTESERVICE software, OPENROUTESERVICE
is an open-source route planner with plenty of features for
cars, heavy vehicles, hiking, and cycling. The distance of
this route (dL−H) is 4.2 km and the delivery time of manual
vehicles (t2) is 22.5 min.
Develop Assumptions
All the calculations and formulas are conducted based
on the real context; hence, it is necessary to follow basic
requirements from the actual transportation practice. As
a result, the mathematic models are established on the
following assumptions and existing data values.
1. The daily operating cost of AVs mainly comprises
electricity consumption.
2. Both autonomous and manual vehicles operated
250 working days per year. However, AVs operated
24 hours per day while manual vehicles operated
8 hours per day because of the legal limitation on
driver’s daily working time.
3. The service life of an AV (TA) is 8 years.
4. The cost of manual vehicles is amortized into their
daily cost while the cost of AVs is not included in the
daily cost and is an initial investment.
5. The maximum capacity of one manual vehicle (WM)
is 5,000 kg [12].
6. The maximum capacity of one AV (WM) is less than
or equals to the maximum capacity of one manual
vehicle (WM)
7. The average running speed of one AV (vA) is
6.4 km/h [23].
8. The running cost of manual vehicles per kilometer is
1 pound [12].
9. Both autonomous and manual vehicles run at their
full capacity.
10. In the UK, the average electricity price for electromo-
bile (PoE) is £0.25 per kWh (Power Compare 2020),
and the electricity consumption per kilometer (Epk)
is 0.19 kWh [2].
11. The cost of electric vehicles is composed of power
only.
12. In one day, an AV can deliver the same weight of
shipments as a manual vehicle can.
13. The initial purchasing cost of one AV (Ci) is
£24,000 [7].
14. During the service life of each AV, the sum of ini-
tial purchasing cost and accumulated operation cost
should be lower than the accumulated operating cost
of a manual vehicle, otherwise, there is no need to use
AVs.
Calculation
The daily operating cost of running AVs (CA) can be
calculated through:
CA = x1 × dL−H × Epk × PoE
where x1 refers to how many times on the route L-H
can an AV runs during one working day, dL−H refers
to the distance of this route, Epk refers to the electricity
consumption per kilometer, and PoE refers to the price of
electricity.
Input data values presented in assumption 10,
CA = x1 × 4.2 km × 0.19 kWh/km × £0.25/kWh = 0.2x1
The daily cost of running manual vehicles (Cm) can be
calculated through:
CM = x2 × dL−H × Ppk
where x2 refers to how many times on the route L-H can a
manual vehicle runs during one working day, dL−H refers
to the distance of this route, and Ppk refers to the running
cost of manual vehicles per kilometer. This cost includes
the fixed cost (cost for the truck and the insurance), main-
tenance (including tires), the cost for the driver, and fuel
costs.
Input data values in assumption 8,
CM = x2 × 4.2 km × £1/km = 4.2x2
Define ∆C = Ci + 250 days × CA − 250 days × CM =
24, 000 + 50x1 − 1050x2, and ∆C means the difference of
the accumulated cost between AVs and manual vehicles
during the service life of an AV. This research aims to find
the appropriate x1 and x2 that can lead to a minimum
∆C, which is an indicator of the cost between autonomous
drive and manual drive. If these optimization values exist,
AVs are sustainable in terms of daily operating costs.
Finding minimum ∆C is subjected to the following
model constrains:
1. In the real context, the number that an AV runs on the
route in a working day must not less than 0 and the
number cannot be a decimal.
So:
x1, x2 ≥ 0, and both are integers (1)
2. The total time that an AV spends on the route per
day is no more than 24 hours, which is indicated by
the product of a daily operating number and time
amount per operation.
x1 × t1 = x1 ×
dL−H
vA
= 0.66x1 ≤ 24 ⇒ x1 ≤ 36
(2)
8. Evaluate Sustainability of Using Autonomous Vehicles for the Last-mile Delivery Industry 39
Figure 5. The route from Lidl supermarket to a target locker at Coventry center.
3. Like the time algorithm of an AV, the time that
a manual vehicle spends on the same route can
be expressed as the following formula. However,
according to assumption 2, the operating time of a
manual vehicle is 8 hours a day.
x2 × t2 = 0.38x2 ≤ 8 ⇒ x2 ≤ 21 (3)
4. According to assumption 12, the weight that an AV
transports is as much as that of a manual vehicle.
Then, it can be expressed by:
WA × x1 = WM × x2: x1
=
WM
WA
x2 (4)
Thus, the aim is to a minimum 24, 000 +50x1 −1050x2. This
formula can be rewritten as 24, 000 + 50(x1 − 21x2). There-
fore, ∆C can achieve its minimum value when achieving
the minimum value of x1 − 21x2. The following simula-
tion focuses on the calculation of the minimum value of
x1 − 21x2 using statistical analysis software.
Simulation
To get the minimum value, let n represents WM
WA
, which is
the rate of the weight of one manual vehicle (MV) to the
weight of one AV. This research analyzes four scenarios in
terms of different values of n from 1 to 25.
Because the formula includes two independent vari-
ables, its result cannot be calculated and analyzed manu-
ally. However, MATLAB can be used to solve this mathe-
matical problem.
Figure 6. The relationship between cost and n of AV.
First,
min(x1 − 21x2) subject to
x1, x2 are integers
0 ≤ x1 ≤ 36
0 ≤ x2 ≤ 21
x1 − nx2 = 0
Then, input the variables in MATLAB, and the outcomes
will be carried out. The following figures show the out-
comes of all processes of the MATLAB.
Figure 6 was generated by MATLAB after inputting the
data. It depicts how the cost advantage changes with the
change of n. The cost unit is pound while n unit is 1. It can
9. 40 Linghan Huang
Figure 7. 3D modeling for the relationship between AV and MV.
Figure 8. Statistic portfolio of solutions.
be seen that the relationship between cost and n is a linear
relation.
MATLAB provides a series of solutions (see Figure 8) for
the formula, and the optimized cost advantage has been
listed in the figure. However, considering the context, those
scenarios that the times of manual vehicle run less than
8 times should be ignored because it is unrealistic that
a manual vehicle operates only 8 times in 8 hours. As a
result, it is reasonable to choose the solutions that n = 1, 2,
3, 4 respectively, which means a manual vehicle runs more
than 8 times a per day.
As the bottom part of Figure 8 shows, the four statis-
tics are effective solutions; accordingly, the optimized cost
advantage value can be utilized to assess the outcome
of using an AV. It shows that an AV has a significant
advantage in terms of cost when transporting goods on this
route.
KEY FINDINGS
Social Sustainability
For social sustainability – safety consideration, this
research result shows that AV has an overall better per-
formance in safety so that it could have good social
sustainability. Firstly, for AV running context, it is relatively
safe because of the speed limit of actual society and the
good road conditions provide the ground that AV runs
safely for last-mile delivery in urban areas. Secondly, for
driving behavior aspect, AV has a significant advantage
than a manned vehicle. The main reason is that AV has no
human behavior so that it is impossible to make human
behavior mistakes when moving. Thirdly, for technology
safety, AV’s safety technology level is the same as tradi-
tional vehicles because their test standards are extremely
high and because of the procedure that no vehicle can come
into use without passing the strict test. Finally, AV has a
special advantage when facing pandemic periods, a result
that is in line with the research finding of Xuan Feng [47].
Environmental Sustainability
Through the quantitative analysis for the emission gener-
ated by AV, the AVs has a significant advantage in emission
reduction in terms of a series of emissions. This mainly
results from the driving behaviors difference between AV
and human vehicles. Some researches show that the total
emission will rise because of the use of AV. The phe-
nomenon generates by the side effect of AV’s use rather
than the vehicle itself. So this kind of side effect could
be sorted into the management of AV. Then, looking at
the quantitative analysis outcome and management aspect
outcome of AV simultaneously, it cannot be calculated
how much the emission will be reduced or increased.
Even though the emission reduction is clear, the amount
of increase from the rising rate that people drive with
AV cannot be confirmed. As a result, the total emission
changing trend is uncertain based on the present analysis.
Finally, I found that the AVs can to a large extent miti-
gate the pressure from the scarcity of parking places in
urban areas.
Economic Sustainability
The result of quantitative analysis shows that the cost
advantage of AV in this route is approximately −475, the
smallest value in the meantime when n equals 1, i.e., one
AV and carry the dame weight as one traditional vehicle.
This point means that the cost of AV is 475 less than that
of MV. Accordingly, AV can save 475 pounds when AV
transports the weight as much as that of MV. 475 pounds
is the maximum cost advantage of AV compared to MV in
this context. The value of the ratio of weighting capacity
of one Av to that of one traditional vehicle matters. From
10. Evaluate Sustainability of Using Autonomous Vehicles for the Last-mile Delivery Industry 41
n = 1 to n = 8, this figure rises significantly along with
the increase of n. This means when the weight of MV is
1 to 8 times as that of AV, the weight impacts the cost
advantage markedly. The more MV can transport than AV,
the less AV can save in this range. From n=9 to n=19, the
figure goes up gradually accompanied by the increase of
n. This phenomenon proves that when the weight of MV
is 9 to 19 times as that of AV, the weight impacts the cost
advantage of AV slightly. From n = 20 to n = 25, the figure
keeps unchanged no matter how n changes. This means
that when the weight of MV is 20 to 25 times as that of
AV, MV has the same cost as that of AV. More specifically,
when the manual vehicle is big enough, AV has no cost
advantage anymore. Over the change range of n, the figure
does not exceed 0, which means the same cost of the two
drive types. Consequently, autonomous drive cost in this
route is no more than that of manual drive through the
range of chosen weight rate.
In all, the autonomous drive for the last-mile delivery is
sustainable because it can save money compared to manual
drive for the last-mile delivery.
Recommendation
The result of this research has important practical implica-
tions for real business. Firstly, to achieve safer road traffic,
corporates should replace manned vehicles with AVs as
many as possible for last-mile delivery. This replacement
keeps pace with the audit procedure of AV. Moreover,
increasing the number of AV runs for last-mile deliv-
ery is helpful for reducing the emission. Furthermore,
when the manned vehicle capability is 1 to 25 times as
AV’s and the manned vehicle runs more than 8 times
per day, using AVs to replace manned vehicles can save
cost. It is also possible to achieve more AVs by some
financial methods. For example, gaining fund from Invest-
ment banks such as Goldman Sachs, an international
leading investment bank despite various management
issues [46].
CONCLUSION
This research is aimed at confirming whether the AVs for
last-mile delivery is sustainable. Several objectives were set
up to address the aim. This research introduced a classical
framework, which is three pillars of sustainability. This
theory was regarded as the ground of this research and the
following structure following the framework. To analyze
the sustainability, the three pillars – social sustainability,
environmental sustainability, and economic sustainabil-
ity – were discussed step by step. First, even though social
sustainability has four main components theoretically, the
safety was solely discussed because of its importance of
AV application for last-mile delivery. The safety issue was
divided into context safety, driving behavior safety, and
technology safety. The result shows that the AV’s safety
status is relatively good. Besides, a brief and special part
about the response to COVID-19 was discussed in the
last. Second, because the emission is the most significant
part of AV related to the environment, the main topic in
this part is the emission of AV. This research cites a large
number of data and research to show the emission status
of AV. Noticeably, quantitative research of AV emission
was cited to analyze. However, because of the adverse
impact of AV that cannot be figured out thoroughly, the
outcome is uncertain. Lastly, a brief living environment
influenced by AV was discussed. Third, as for the economic
sustainability of AV, this research adopted a quantitative
way to illustrate because the cost of AV is essential to
consider because of AV’s commercial nature. To figure out
the cost of AV, this research built a mathematical model
and used statistic software to calculate, combining a set
of assumptions, reality, and actual values of AV. Several
portfolios were finally confirmed to compare with manned
vehicle cost. The result shows that the AVs can save
more cost.
In all, the result of this research shows that the AV’s
sustainability for last-mile delivery is high. In addition,
three suggestions are conducted in terms of how to use AV.
Overall, AV is encouraged to replace the manual vehicle for
the delivery. Even though the process of analysis may not
be thorough, this research still conducts a relative right and
objective conclusion – namely, AV is sustainable for last-
mile delivery. Several recommendations are also carried
out completely and the main point is that more AVs are
encouraged to use.
However, this research is not flawless due to limited
research time and research conditions. Firstly, this research
covers only the safety of social sustainability while do not
mention the other three aspects of the social framework;
therefore, the analysis outcome of social sustainability may
not be objective enough. Secondly, this research does not
find a solution to expect the trend of choice after people
using AV so that the total amount of emission cannot be
acquired. Finally, the quantitative model designed to find
the cost of AV does not include all the potential variables
that could exist in actual scenarios such as insurance cost;
thus, the result could not be precise. Before building the
model, we can interview the financial stuff of the delivery
company to get all the cost variables. Thus, a precise
outcome could be expected.
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