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 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.

Pedestrians, Autonomous Vehicles, and Cities

2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Neighborhoods ◽  
Urban Traffic ◽  
Risk Averse ◽  
Strategic Interactions ◽  
Road Users ◽  
Self Driving Cars ◽  
Time Autonomous

Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.

Examining the Equity Impacts of Autonomous Vehicles: A Travel Demand Model Approach

2019 ◽  
Vol 2673 (5) ◽  
pp. 23-35 ◽  
Author(s):  
Jesse Cohn ◽  
Richard Ezike ◽  
Jeremy Martin ◽  
Kwasi Donkor ◽  
Matthew Ridgway ◽  
...  
Keyword(s):  
Performance Measures ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Demand Model ◽  
The Status ◽  
Mode Share ◽  
Transit Agencies ◽  
Travel Demand Model

As investments in autonomous vehicle (AV) technology continue to grow, agencies are beginning to consider how AVs will affect travel behavior within their jurisdictions and how to respond to this new mobility technology. Different autonomous futures could reduce, perpetuate, or exacerbate existing transportation inequities. This paper presents a regional travel demand model used to quantify how transportation outcomes may differ for disadvantaged populations in the Washington, D.C. area under a variety of future scenarios. Transportation performance measures examined included job accessibility, trip duration, trip distance, mode share, and vehicle miles traveled. The model evaluated changes in these indicators for disadvantaged and non-disadvantaged communities under scenarios when AVs were primarily single-occupancy or high-occupancy, and according to whether transit agencies responded to AVs by maintaining the status quo, removing low-performing routes, or applying AV technology to transit vehicles. Across the performance measures, the high-occupancy AV and enhanced transit scenarios provided an equity benefit, either mitigating an existing gap in outcomes between demographic groups or reducing the extent to which that gap was expanded.

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 Vehicle Electrification Impacts on Energy Consumption for Different Connected-Autonomous Vehicle Scenario Runs

2019 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Ehsan Sabri Islam ◽  
Ayman Moawad ◽  
Namdoo Kim ◽  
Aymeric Rousseau
Keyword(s):  
Energy Consumption ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Transportation System ◽  
Regional Energy ◽  
Energy Impact ◽  
Potential Factors ◽  
The Impact ◽  
The City

Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.

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>

scholarly journals Exploring the correlations between spatiotemporal daily activity-travel patterns and stated interest and perception of risk with self-driving cars

2020 ◽  
Vol 1 ◽  
pp. 1-15
Author(s):  
Jingyi Xiao ◽  
Rongxiang Su ◽  
Elizabeth C. McBride ◽  
Konstadinos G. Goulias
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Daily Activity ◽  
Puget Sound ◽  
Travel Patterns ◽  
Multinomial Regression ◽  
Multinomial Regression Model ◽  
People’S Attitudes ◽  
Self Driving Cars

Abstract. The key to Autonomous Vehicles (AVs) successful penetration of markets lies in identifying specific needs that AVs satisfy for daily activity-travel participation of individuals. In this paper we explore whether and to what extent people’s exhibited spatiotemporal activity-travel patterns correlate with their stated perceptions about self-driving cars. We investigate the travel diaries of 3,411 survey respondents who live in the Puget Sound region of the U.S. in 2017 using sequence analysis. In parallel, we apply hierarchical clustering to identify people’s attitudes based on their stated interest and perception of risks about AVs. A multinomial regression model is built to examine the correlations between AV attitude clusters and daily activity-travel patterns. Statistically significant correlations are then identified. The model results suggest that people exhibiting different activity-travel behavior patterns also express distinct attitudes towards the uses of AVs. The model shows that people who travel to work during the day are more likely to be positive to AVs. In particular, the group traveling to work later than the regular 8-to-5 schedule shows stronger interest and less concerns to AVs, which can be partially explained by the diverse activities they do throughout the day, the variety of travel modes they use and presumably more schedule flexibility they need than the public transportation system offers.

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.

From driver assistance to fully-autonomous: examining consumer acceptance of autonomous vehicle technologies

2020 ◽  
Vol 37 (7) ◽  
pp. 883-894
Author(s):  
Michael A. Erskine ◽  
Stoney Brooks ◽  
Timothy H. Greer ◽  
Charles Apigian
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Consumer Acceptance ◽  
Unified Theory ◽  
Driver Assistance ◽  
Content Type ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Vehicle Technology ◽  
Vehicle Technologies

Purpose The purpose of this paper is to inform researchers who are examining the adoption of autonomous vehicle technology and to provide marketing insights for developers and manufacturers of such vehicles and their ancillary technologies. Design/methodology/approach This study assesses consumer attitudes and behavioral intentions regarding autonomous vehicles (AV) by applying the consumer version of the unified theory of acceptance and use of technology (UTAUT2). We validate the model through a behavioral research study (n = 1,154). Findings The findings suggest that attitude toward AV is primarily formed through performance expectancy, effort expectancy, social influence and hedonic motivation. Furthermore, the level of autonomy has limited effects on attitude. Originality/value This is the first study to examine attitudes toward AV through the theoretical lens of UTAUT2. Additionally, this study provides insights into consumer perceptions and the corresponding effects on attitude by moderating the level of autonomy.

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