Autonomous Electric Vehicle Sharing System Design

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Namwoo Kang ◽  
Fred M. Feinberg ◽  
Panos Y. Papalambros
Keyword(s):  
System Design ◽  
Electric Vehicle ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Transportation Systems ◽  
Fleet Size ◽  
Gasoline Engines ◽  
Ann Arbor ◽  
Vehicle Technologies ◽  
System Design Optimization

Car sharing services promise “green” transportation systems. Two vehicle technologies offer marketable, sustainable sharing: autonomous vehicles (AVs) eliminate customer requirements for car pick-up and return, and battery electric vehicles entail zero emissions. Designing an autonomous electric vehicle (AEV) fleet must account for the relationships among fleet operations, charging station (CS) operations, electric powertrain performance, and consumer demand. This paper presents a system design optimization framework integrating four subsystem problems: fleet size and assignment schedule; number and locations of charging stations; vehicle powertrain requirements; and service fees. We also compare an AEV service and autonomous vehicle (AV) service with gasoline engines. A case study for an autonomous fleet operating in Ann Arbor, MI, is used to examine AEV and AV sharing systems profitability and feasibility for a variety of market scenarios. The results provide practical insights for service system decision makers.

Autonomous Electric Vehicle Sharing System Design

2015 ◽  
Author(s):  
Namwoo Kang ◽  
Fred M. Feinberg ◽  
Panos Y. Papalambros
Keyword(s):  
System Design ◽  
Electric Vehicle ◽  
Autonomous Vehicles ◽  
Transportation Systems ◽  
Fleet Size ◽  
Charging Station ◽  
Ann Arbor ◽  
Vehicle Technologies ◽  
System Design Optimization ◽  
Charging Stations

Car-sharing services promise “green” transportation systems. Two vehicle technologies offer marketable, sustainable sharing: Autonomous vehicles eliminate customer requirements for car pick-up and return, and battery electric vehicles entail zero-emissions. Designing an Autonomous Electric Vehicle (AEV) fleet must account for the relationships among fleet operations, charging station operations, electric powertrain performance, and consumer demand. This paper presents a system design optimization framework integrating four sub-system problems: Fleet size and assignment schedule; number and locations of charging stations; vehicle powertrain requirements; and service fees. A case study for an autonomous fleet operating in Ann Arbor, Michigan, is used to examine AEV sharing system profitability and feasibility for a variety of market scenarios.

scholarly journals Platoon Signal Priority in Connected-Autonomous Vehicle Environments: Algorithm Development and Testing

2019 ◽  
Vol 65 (4) ◽  
pp. 1-9
Author(s):  
Milan Zlatkovic ◽  
Andalib Shams
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Transportation Systems ◽  
Vehicle Technologies ◽  
Measures Of Effectiveness ◽  
Urban Corridor ◽  
Intersection Control ◽  
Day By Day

As traffic congestion increases day by day, it becomes necessary to improve the existing roadway facilities to maintain satisfactory operational and safety performances. New vehicle technologies, such as Connected and Autonomous Vehicles (CAV) have a potential to significantly improve transportation systems. Using the advantages of CAVs, this study developed signalized intersection control strategy algorithm that optimizes the operations of CAVs and allows signal priority for connected platoons. The algorithm was tested in VISSIM microsimulation using a real-world urban corridor. The tested scenarios include a 2040 Do-Nothing scenario, and CAV alternatives with 25%, 50%, 75% and 100% CAV penetration rate. The results show a significant reduction in intersection delays (26% - 38%) and travel times (6% - 20%), depending on the penetration rate, as well as significant improvements on the network-wide level. CAV penetration rates of 50% or more have a potential to significantly improve all operational measures of effectiveness.

scholarly journals An Open-Source Scale Model Platform for Teaching Autonomous Vehicle Technologies

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3850
Author(s):  
Bastien Vincke ◽  
Sergio Rodriguez Rodriguez Florez ◽  
Pascal Aubert
Keyword(s):  
Open Source ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Constrained Systems ◽  
Scale Model ◽  
Technical Students ◽  
Vehicle Technologies ◽  
Model Platform ◽  
High Level ◽  
Time And Energy

Emerging technologies in the context of Autonomous Vehicles (AV) have drastically evolved the industry’s qualification requirements. AVs incorporate complex perception and control systems. Teaching the associated skills that are necessary for the analysis of such systems becomes a very difficult process and existing solutions do not facilitate learning. In this study, our efforts are devoted to proposingan open-source scale model vehicle platform that is designed for teaching the fundamental concepts of autonomous vehicles technologies that are adapted to undergraduate and technical students. The proposed platform is as realistic as possible in order to present and address all of the fundamental concepts that are associated with AV. It includes all on-board components of a stand-alone system, including low and high level functions. Such functionalities are detailed and a proof of concept prototype is presented. A set of experiments is carried out, and the results obtained using this prototype validate the usability of the model for the analysis of time- and energy-constrained systems, as well as distributed embedded perception systems.

scholarly journals Towards a Severity Assessment Method for Potential Cyber Attacks to Connected and Autonomous Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Qiyi He ◽  
Xiaolin Meng ◽  
Rong Qu
Keyword(s):  
Cyber Security ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Assessment Method ◽  
Transportation Systems ◽  
Cyber Attacks ◽  
Large Set ◽  
Security Attacks ◽  
Physical Damage

CAV (connected and autonomous vehicle) is a crucial part of intelligent transportation systems. CAVs utilize both sensors and communication components to make driving decisions. A large number of companies, research organizations, and governments have researched extensively on the development of CAVs. The increasing number of autonomous and connected functions however means that CAVs are exposed to more cyber security vulnerabilities. Unlike computer cyber security attacks, cyber attacks to CAVs could lead to not only information leakage but also physical damage. According to the UK CAV Cyber Security Principles, preventing CAVs from cyber security attacks need to be considered at the beginning of CAV development. In this paper, a large set of potential cyber attacks are collected and investigated from the aspects of target assets, risks, and consequences. Severity of each type of attacks is then analysed based on clearly defined new set of criteria. The levels of severity for the attacks can be categorized as critical, important, moderate, and minor. Mitigation methods including prevention, reduction, transference, acceptance, and contingency are then suggested. It is found that remote control, fake vision on cameras, hidden objects to LiDAR and Radar, spoofing attack to GNSS, and fake identity in cloud authority are the most dangerous and of the highest vulnerabilities in CAV cyber security.

scholarly journals How virtue signalling makes us better: Moral preferences with respect to autonomous vehicle type choices

2019 ◽  
Author(s):  
Robin Kopecky ◽  
Michaela Košová ◽  
Daniel D. Novotný ◽  
Jaroslav Flegr ◽  
David Černý
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Biological Species ◽  
Transportation Systems ◽  
Personal Choice ◽  
Moral Issues ◽  
Web Based ◽  
The Public ◽  
Vehicle Type ◽  
Research Questions

Autonomous vehicles (henceforth AVs) are expected to significantly benefit our transportation systems, their safety, efficiency, and impact on environment. However, many technical, social, legal, and moral questions and challenges concerning AVs and their introduction to the mass market still remain. One of the pressing moral issues has to do with the choice between AV types that differ in their built-in algorithms for dealing with situations of unavoidable lethal collision. In this paper we present the results of our study of moral preferences with respect to three types of AVs: (1) selfish AVs that protect the lives of passenger(s) over any number of bystanders; (2) altruistic AVs that minimize the number of casualties, even if this leads to death of passenger(s); and (3) conservative AVs that abstain from interfering in such situations even if it leads to the death of a higher number of subjects or death of passenger(s). We furthermore differentiate between scenarios in which participants are to make their decisions privately or publicly, and for themselves or for their offspring. We disregard gender, age, health, biological species and other characteristics of (potential) casualties that can affect the preferences and decisions of respondents in our scenarios. Our study is based on a sample of 2769 mostly Czech volunteers (1799 women, 970 men; age IQR: 25-32). The data come from our web-based questionnaire which was accessible from May 2017 to December 2017. We aim to answer the following two research questions: (1) Whether the public visibility of an AV type choice makes this choice more altruistic and (2) which type of situation is more problematic with regard to the altruistic choice: opting for society as a whole, for oneself, or for one’s offspring.Our results show that respondents exhibit a clear preference for an altruistic utilitarian strategy for AVs. This preference is reinforced if the AV signals its strategy to others. The altruistic preference is strongest when people choose software for everybody else, weaker in personal choice, and weakest when choosing for one’s own child. Based on the results we conclude that, in contrast to a private choice, a public choice is considerably more likely to pressure consumers in their personal choice to accept a non-selfish solution, making it a reasonable and relatively cheap way to shift car owners and users towards higher altruism. Also, a hypothetical voting in Parliament about a single available program is less selfish when the voting does not take place in secret.

scholarly journals NEW SOURCE OF GEOSPATIAL DATA: CROWDSENSING BY ASSISTED AND AUTONOMOUS VEHICLE TECHNOLOGIES

2018 ◽  
Vol XLII-4/W8 ◽  
pp. 211-216 ◽  
Author(s):  
C. K. Toth ◽  
Z. Koppanyi ◽  
M. G. Lenzano
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Data Science ◽  
Information Dissemination ◽  
Autonomous Vehicle ◽  
Weather Conditions ◽  
Traffic Monitoring ◽  
Geospatial Data ◽  
Object Space ◽  
Vehicle Technologies

<p><strong>Abstract.</strong> The ongoing proliferation of remote sensing technologies in the consumer market has been rapidly reshaping the geospatial data acquisition world, and subsequently, the data processing as well as information dissemination processes. Smartphones have clearly established themselves as the primary crowdsourced data generators recently, and provide an incredible volume of remote sensed data with fairly good georeferencing. Besides the potential to map the environment of the smartphone users, they provide information to monitor the dynamic content of the object space. For example, real-time traffic monitoring is one of the most known and widely used real-time crowdsensed application, where the smartphones in vehicles jointly contribute to an unprecedentedly accurate traffic flow estimation. Now we are witnessing another milestone to happen, as driverless vehicle technologies will become another major source of crowdsensed data. Due to safety concerns, the requirements for sensing are higher, as the vehicles should sense other vehicles and the road infrastructure under any condition, not just daylight in favorable weather conditions, and at very fast speed. Furthermore, the sensing is based on using redundant and complementary sensor streams to achieve a robust object space reconstruction, needed to avoid collisions and maintain normal travel patterns. At this point, the remote sensed data in assisted and autonomous vehicles are discarded, or partially recorded for R&amp;amp;D purposes. However, in the long run, as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies mature, recording data will become a common place, and will provide an excellent source of geospatial information for road mapping, traffic monitoring, etc. This paper reviews the key characteristics of crowdsourced vehicle data based on experimental data, and then the processing aspects, including the Data Science and Deep Learning components.</p>

Modeling Individual Preferences for Ownership and Sharing of Autonomous Vehicle Technologies

2017 ◽  
Vol 2665 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Patrícia S. Lavieri ◽  
Venu M. Garikapati ◽  
Chandra R. Bhat ◽  
Ram M. Pendyala ◽  
Sebastian Astroza ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Network Performance ◽  
Transportation Network ◽  
Autonomous Vehicle ◽  
Puget Sound ◽  
Heterogeneous Data ◽  
Model System ◽  
Vehicle Technologies ◽  
The One

Considerable interest exists in modeling and forecasting the effects of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle (AV) future, individuals may privately own such vehicles, use mobility-on-demand services provided by transportation network companies that operate shared AV fleets, or adopt a combination of those two options. This paper presents a comprehensive model system of AV adoption and use. A generalized, heterogeneous data model system was estimated with data collected as part of the Puget Sound, Washington, Regional Travel Study. The results showed that lifestyle factors play an important role in shaping AV usage. Younger, urban residents who are more educated and technologically savvy are more likely to be early adopters of AV technologies than are older, suburban and rural individuals, a fact that favors a sharing-based service model over private ownership. Models such as the one presented in this paper can be used to predict the adoption of AV technologies, and such predictions will, in turn, help forecast the effects of AVs under alternative future scenarios.

scholarly journals Macroscopic Traffic Simulation of Autonomous Vehicle Effects

Vehicles ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 187-196
Author(s):  
Mohammed Obaid ◽  
Arpad Torok
Keyword(s):  
Autonomous Vehicles ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Transportation Systems ◽  
Road Transportation ◽  
Total Delay ◽  
Urban Road ◽  
Vehicle Mobility ◽  
Network Speed ◽  
Restrictive Measures

The increasing worldwide demand on urban road transportation systems requires more restrictive measures and policies to reduce congestion, time delay and pollution. Autonomous vehicle mobility services, both shared and private, are possibly a good step towards a better road transportation future. This article aims to study the expected impact of private autonomous vehicles on road traffic parameters from a macroscopic level. The proposed methodology focuses on finding the different effects of different combinations of autonomous vehicle penetration and Passenger Car Units (PCU) on the chosen road traffic model. Four parameters are studied: traveled daily kilometers, daily hours, total daily delay and average network speed. The analysis improves the four parameters differently by implementing autonomous vehicles. The parameter total delay has the most significant reduction. Finally, several mathematical models are developed for the percentage of improvement for each chosen parameter.

scholarly journals Autonomous Vehicle Use and Urban Space Transformation: A Scenario Building and Analysing Method

2021 ◽  
Vol 13 (6) ◽  
pp. 3008
Author(s):  
Dahlen Silva ◽  
Dávid Földes ◽  
Csaba Csiszár
Keyword(s):  
Urban Space ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Scenario Building ◽  
Space Management ◽  
Fleet Size ◽  
Space Transformation ◽  
Novel Method ◽  
Environmental Savings ◽  
Parking Demand

The use of autonomous vehicles (AVs) has the potential to transform users’ behaviour and urban space management. Quantitative and qualitative analyses of impacts require a scenario building method. We considered the fleet size, modal share, car ownership, parking preferences, and urban space repurposing during the elaboration of a novel method. Existing scenarios and results of a questionnaire survey have been used as sources. The method was applied to build scenarios in a case study in Budapest, Hungary. The results were used to calculate the impacts on urban space management, including environmental savings. The key findings are: scenarios with significant shared AV use show that parking demand may be minimised (almost 83%) and urban space repurposing has the highest potential; furthermore, AV use and sharing acceptability may decrease the fleet size and alter the type of shared mode to multiple occupancies. The developed scenario building method serves as a base for future studies. The produced scenarios allow the researchers to focus on the analysis of the impacts caused.

scholarly journals A Research Platform for Autonomous Vehicles Technologies Research in the Insurance Sector

2020 ◽  
Vol 10 (16) ◽  
pp. 5655
Author(s):  
Miguel Ángel de Miguel ◽  
Francisco Miguel Moreno ◽  
Pablo Marín-Plaza ◽  
Abdulla Al-Kaff ◽  
Martín Palos ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Use Cases ◽  
Self Awareness ◽  
Insurance Company ◽  
High Level Architecture ◽  
Human Machine Interaction ◽  
Insurance Sector ◽  
Vehicle Technologies ◽  
High Level

This work presents a novel platform for autonomous vehicle technologies research for the insurance sector. The platform has been collaboratively developed by the insurance company MAPFRE-CESVIMAP, Universidad Carlos III de Madrid and INSIA of the Universidad Politécnica de Madrid. The high-level architecture and several autonomous vehicle technologies developed using the framework of this collaboration are introduced and described in this work. Computer vision technologies for environment perception, V2X communication capabilities, enhanced localization, human–machine interaction and self awareness are among the technologies which have been developed and tested. Some use cases that validate the technologies presented in the platform are also presented; these use cases include public demonstrations, tests of the technologies and international competitions for self-driving technologies.

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