TY - JOUR
T1 - Modelling and managing the integrated morning-evening commuting and parking patterns under the fully autonomous vehicle environment
AU - Zhang, Xiang
AU - Liu, Wei
AU - Waller, S. Travis
AU - Yin, Yafeng
N1 - Funding Information:
We thank the handling editor, Prof. Robin Lindsey, and the anonymous reviewers for their thoughtful comments, which helped improve both the technical quality and exposition of this paper. This research is partially supported by a grant from the Australian Research Council (LP160101021), and is partially supported by funding from the UNSW Digital Grid Futures Institute, UNSW, Sydney, under a cross disciplinary fund scheme. Yafeng Yin would like to thank the support from the National Science Foundation via CMMI-1740865 and the USDOT Center of Connected and Automated Transportation at University of Michigan.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/10
Y1 - 2019/10
N2 - This study is the first in the literature to analytically investigate the traffic dynamics of the integrated morning and evening commutes when daily trips are completed with autonomous vehicles (AVs). Given the parking locations of AVs resulting from the morning commute, firstly we analyse the evening commuting pattern, at which no traveller can reduce the individual travel cost given other AVs’ times of departures from the parking spaces. The equilibrium traffic pattern at the evening commute is then integrated with the morning commute, where equilibrium choices of departure time from home and parking location are derived and analysed. We then study the integrated morning-evening commuting pattern at the system optimum and develop the road tolling scheme to achieve the system optimum. Furthermore, this study analyses the optimal AV parking supply strategy to minimise the total system cost, which is comprised of the total social parking cost and the total daily travel cost under either user equilibrium or system optimum traffic pattern. We also illustrate the modelling insights through numerical studies regarding relationship among traffic efficiency, tolling schemes and AV parking supply plans. This study highlights the differences in daily commuting and parking patterns between the AV situation and the non-AV situation, and sheds light on how traffic and parking should be managed or planned in the future.
AB - This study is the first in the literature to analytically investigate the traffic dynamics of the integrated morning and evening commutes when daily trips are completed with autonomous vehicles (AVs). Given the parking locations of AVs resulting from the morning commute, firstly we analyse the evening commuting pattern, at which no traveller can reduce the individual travel cost given other AVs’ times of departures from the parking spaces. The equilibrium traffic pattern at the evening commute is then integrated with the morning commute, where equilibrium choices of departure time from home and parking location are derived and analysed. We then study the integrated morning-evening commuting pattern at the system optimum and develop the road tolling scheme to achieve the system optimum. Furthermore, this study analyses the optimal AV parking supply strategy to minimise the total system cost, which is comprised of the total social parking cost and the total daily travel cost under either user equilibrium or system optimum traffic pattern. We also illustrate the modelling insights through numerical studies regarding relationship among traffic efficiency, tolling schemes and AV parking supply plans. This study highlights the differences in daily commuting and parking patterns between the AV situation and the non-AV situation, and sheds light on how traffic and parking should be managed or planned in the future.
KW - Autonomous vehicles
KW - Bottleneck model
KW - Dynamic user equilibrium
KW - Morning-evening commute
KW - Parking supply
UR - http://www.scopus.com/inward/record.url?scp=85071239070&partnerID=8YFLogxK
U2 - 10.1016/j.trb.2019.08.010
DO - 10.1016/j.trb.2019.08.010
M3 - Journal article
AN - SCOPUS:85071239070
VL - 128
SP - 380
EP - 407
JO - Transportation Research, Series B: Methodological
JF - Transportation Research, Series B: Methodological
SN - 0191-2615
ER -