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  4. The morning commute problem with endogenous shared autonomous vehicle penetration and parking space constraint
 
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The morning commute problem with endogenous shared autonomous vehicle penetration and parking space constraint

Journal
Transportation Research Part B: Methodological
Journal Volume
123
Pages
258-278
Date Issued
2019
Author(s)
Tian L.-J.
JIUH-BIING SHEU  
Huang H.-J.
DOI
10.1016/j.trb.2019.04.001
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/472113
URL
https://www2.scopus.com/inward/record.uri?eid=2-s2.0-85064067810&doi=10.1016%2fj.trb.2019.04.001&partnerID=40&md5=6e10d9d00590f0ef99c523139e517634
Abstract
Morning commuting trips commonly involve a number of transportation modes and departure times. This study extends the standard bottleneck model by considering both regular and shared autonomous vehicles with and without parking space constraint, taking into account the travel time-dependent fuel cost that is associated with each vehicle. In this study the parking space constraint has no effect on shared autonomous vehicles and only commuters who share autonomous vehicles exhibit ridesharing behavior, differing from those utilizing regular vehicles. The dynamic departure patterns and endogenous penetration rates associated with shared autonomous vehicles are determined with respect to parking capacity. Analytical results not only provide several important propositions, but also include the optimal solutions for parking capacity and ridesharing occupancy from the perspective of the system optimum in terms of various indicators, under which parking capacity is a binding constraint, and the first shared autonomous vehicle arrives at the bottleneck as the last regular vehicle leaves. This work is expected not only to motivate related research, but also to promote the development of new strategies and methods for allocating a limited number of parking spaces and regulating the travel behavior of commuters in urban areas. © 2019 Elsevier Ltd
Subjects
Autonomous vehicle; Bottleneck congestion; Parking space constraint; Ridesharing behavior
SDGs

[SDGs]SDG9

[SDGs]SDG11

Other Subjects
Traffic congestion; Travel time; Analytical results; Bottleneck congestion; Bottleneck models; Optimal solutions; Parking spaces; Ride-sharing; Transportation mode; Vehicle penetration; Autonomous vehicles; commuting; computer simulation; numerical model; parking; traffic congestion; transportation mode; travel behavior; travel time
Type
journal article

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