Connected and automated vehicles Virtual room 4 Presentation
Nov 03, 2020 04:00 PM - Mar 01, 2021 05:30 PM(Europe/Amsterdam)
20201103T1600 20201103T1730 Europe/Amsterdam S1-5.1 - Connected and automated vehicles Virtual room 4 IEEE- Forum ISTS2020 n.fontein@tudelft.nl
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Understanding Stakeholders Evaluation of Autonomous Vehicle Services Complementing Public Transport in an Urban Context Watch Recording 0
04:00 PM - 04:20 PM (Europe/Amsterdam) 2020/11/03 15:00:00 UTC - 2021/03/01 15:20:00 UTC
Autonomous vehicles present opportunities for highly integrated multi-modal urban mobility services. This study reports on the evaluation of autonomous services that can be integrated with the existing public transport network. The autonomous services considered are first/last mile feeder services, on-demand point-to-point services, robo-taxis, and autonomous car-sharing and Bus Rapid Transit. In this evaluation, the views of users, public transport operators, public transport authorities and mobility service providers are taken into account. An in-depth understanding of the objectives for each stakeholder group is needed in order to assess the impact of new mobility services. Representatives from each stakeholder group were consulted to evaluate autonomous vehicle scenarios. Using the multi-actor multi-criteria analysis method, stakeholder criteria were weighted and used to calculate overall performance scores per scenario. The results indicate that users are positive towards all autonomous scenarios. For public transport operators all scenarios, except car-sharing, perform well. Public transport authorities believe more strongly in the benefits of on-demand point-to-point services, first/last mile feeders and bus rapid transport. Mobility service providers value flexible services most. These insights can be applied to evaluate the business models of public transport operators and mobility service providers and used to shape urban transport policies.
Presenters Manon Feys
Vrije Universiteit Brussel
Co-Authors Evy Rombaut
Post-doctoral Researcher, Vrije Universiteit Brussel
CM
Cathy Macharis
LV
Lieselot Vanhaverbeke
Examining the Acceptance for Autonomous Transit Feeders Using a Hybrid Choice Model Watch Recording 0
UndecidedConnected and Automated Vehicles 04:20 PM - 04:40 PM (Europe/Amsterdam) 2020/11/03 15:20:00 UTC - 2021/03/01 15:40:00 UTC
Acceptance is often claimed to be the crucial factor for autonomous vehicle success. In this study, we examine the factors that influence the acceptance of autonomous transit feeders using a hybrid choice model. Our research is based on data from a Germany-wide online survey with more than 1,000 respondents. The influence of gender, travel behavior, individual availability of mobility tools, such as car ownership or transit pass, and previous knowledge coincides with findings from previous studies. Further, we are able to explain a large part of the unexplained heterogeneity compared to a base ordered probit model with the latent variables simplification through autonomous minibuses and pro-transit-attitude. This indicates the relevance of considering attitudes in future research on the acceptance of autonomous vehicles in order to arrive at correct interpretation and to reduce the heterogeneity in predicting models.
Presenters Nadine Kostorz
Karlsruhe Institute Of Technology (KIT)
Co-Authors
MK
Martin Kagerbauer
Sv
Sascha Von Behren
PV
Peter Vortisch
A Contemporary Approach for Visualizing Temporal and Spatial Urban Freight Movement by Leveraging Mobility Portal Data Watch Recording 0
04:40 PM - 05:00 PM (Europe/Amsterdam) 2020/11/03 15:40:00 UTC - 2021/03/01 16:00:00 UTC
Analyzing and visualizing traffic data in order to better understand congestion trends, safety concerns, goods movement and capacity needs is a pressing need. Broadly speaking, there is a large amount of traffic data available today, including volume, lane occupancy, speed, and travel time, which can be used to manage transportation networks, provide traveler information and produce performance measures. This broadly disseminated data almost always treats all vehicles alike, without discriminating between trucks and passenger cars. Since trucks are critical and growing components of freeway traffic, monitoring and tracking their dynamics can reveal the impacts of freight movement on current freeway operations and over time will uncover trends useful for future planning and management. This study takes advantage of a unique data stream available for the freeway network of Portland, Oregon, USA. In addition to providing continuous vehicle count, speed and lane occupancies at 20-second intervals at more than 500 stations (1,300 individual detectors), the Portland system reports volume bins at 4 length-based classifications (< 20, 20-35, 36-30, >60 ft). Given that most vehicle classification studies are done over very short time intervals at an extremely limited number of locations, this nonstop data stream enables unprecedented insight into where and when trucks are traveling on Portlands freeways and a wealth of opportunities for performance measurement and diagnosis of their impacts. The objective of this paper is to exploit this new data stream and explore new visualization techniques that depict truck volume, truck percentage and volume-weighted average vehicle speeds along Portlands Interstate 5 corridor, an important north-south freight route between the Canada and
Presenters Eren Yuksel
Ph.D. Student, University Of South Florida
Co-Authors
SO
Seckin Ozkul
RB
Robert Bertini
Oregon State University
Vrije Universiteit Brussel
Karlsruhe Institute of Technology (KIT)
Ph.D. Student
,
University of South Florida
 Meiqi Liu
TU DELFT
 Evy Rombaut
Post-doctoral researcher
,
Vrije Universiteit Brussel
Dr. Eric Molin
TU Delft
Mr. Narith Saum
Presenter
,
Hokkaido University
 Gonçalo Santos
Department of Civil Engineering - University of Coimbra
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