TY - JOUR
T1 - On the joint network equilibrium of parking and travel choices under mixed traffic of shared and private autonomous vehicles
AU - Zhang, Zhuoye
AU - Liu, Wei
AU - Zhang, Fangni
N1 - Funding Information:
We are very grateful to the handling editor and three anonymous referees for their constructive comments that have led to a significant improvement of the paper. The work described in this paper was partially supported by the Research Grants Council of Hong Kong (No. 27202221 ), the National Natural Science Foundation of China (No. 72101222 ), The University of Hong Kong (No. 202009185002 ), and the Hong Kong Polytechnic University ( P0039246 , P0040900 ).
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/8
Y1 - 2023/8
N2 - This paper investigates the joint network equilibrium of parking and travel route choices in the future mobility paradigm with mixed traffic of private and shared autonomous vehicles. Specifically, we consider that private autonomous vehicle (PAV) travelers need to make both route and parking choices though the vehicle can drive itself to parking after dropping off the traveler. The origin–destination-based shared autonomous vehicle (OD-SAV) ride service allows multiple travelers with a common origin and destination (OD) pair to share the same vehicle, while the routing of OD-SAVs is determined by the operator. In this context, a bi-level model is developed which optimizes the OD-SAV service fare and OD-SAV flow in the upper-level, and specifies the travel demands, route and parking choices, and network traffic equilibrium in the lower-level. In particular, PAV travelers choose their route and parking location to minimize their own travel time or cost, while the routing of OD-SAVs is subject to the decision of the operator. The OD-SAVs controlled by the operator may minimize each vehicle’s travel time (user equilibrium, ‘UE’) or minimize the total travel time of all OD-SAVs operated by the operator (Cournot-Nash equilibrium, ‘CN’). The joint equilibrium of travel and parking under either UE or CN routing for OD-SAVs can be modeled as a Variational Inequalities (VI) problem. The uniqueness/non-uniqueness properties of the joint network equilibrium are investigated. Moreover, we examine the OD-SAV service operator’s optimal operation decisions subject to the lower-level network equilibrium. Solution approaches are introduced to solve the joint equilibrium and the proposed bi-level model. Numerical studies are conducted to illustrate the model and analytical results, and also to provide further understanding.
AB - This paper investigates the joint network equilibrium of parking and travel route choices in the future mobility paradigm with mixed traffic of private and shared autonomous vehicles. Specifically, we consider that private autonomous vehicle (PAV) travelers need to make both route and parking choices though the vehicle can drive itself to parking after dropping off the traveler. The origin–destination-based shared autonomous vehicle (OD-SAV) ride service allows multiple travelers with a common origin and destination (OD) pair to share the same vehicle, while the routing of OD-SAVs is determined by the operator. In this context, a bi-level model is developed which optimizes the OD-SAV service fare and OD-SAV flow in the upper-level, and specifies the travel demands, route and parking choices, and network traffic equilibrium in the lower-level. In particular, PAV travelers choose their route and parking location to minimize their own travel time or cost, while the routing of OD-SAVs is subject to the decision of the operator. The OD-SAVs controlled by the operator may minimize each vehicle’s travel time (user equilibrium, ‘UE’) or minimize the total travel time of all OD-SAVs operated by the operator (Cournot-Nash equilibrium, ‘CN’). The joint equilibrium of travel and parking under either UE or CN routing for OD-SAVs can be modeled as a Variational Inequalities (VI) problem. The uniqueness/non-uniqueness properties of the joint network equilibrium are investigated. Moreover, we examine the OD-SAV service operator’s optimal operation decisions subject to the lower-level network equilibrium. Solution approaches are introduced to solve the joint equilibrium and the proposed bi-level model. Numerical studies are conducted to illustrate the model and analytical results, and also to provide further understanding.
KW - Mixed traffic equilibrium
KW - Operation strategies
KW - Parking choice
KW - Private autonomous vehicles
KW - Route choice
KW - Shared autonomous vehicles
UR - http://www.scopus.com/inward/record.url?scp=85164294991&partnerID=8YFLogxK
U2 - 10.1016/j.trc.2023.104226
DO - 10.1016/j.trc.2023.104226
M3 - Journal article
SN - 0968-090X
VL - 153
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
M1 - 104226
ER -