TY - JOUR
T1 - Modeling the competition between multiple Automated Mobility on-Demand operators
T2 - An agent-based approach
AU - Wang, Senlei
AU - Correia, Gonçalo Homem de Almeida
AU - Lin, Hai Xiang
PY - 2022
Y1 - 2022
N2 - Automated Mobility-on-Demand (AMoD) systems, in which fleets of automated vehicles provide on-demand services, are expected to transform urban mobility systems. Motivated by the rapid development of AMoD services delivered by self-driving car companies, an agent-based model (ABM) has been developed to study the coexistence phenomena of multiple AMoD operators competing for customers. The ABM is used to investigate how changes in pricing strategies, assignment methods, and fleet sizes affect travelers’ choice of different AMoD services and the operating performance of competing operators in the case-study city of The Hague, in the Netherlands. Findings suggest that an optimal assignment algorithm can reduce the average waiting time by up to 24% compared to a simple heuristic algorithm. We also find that a larger fleet could increase demand but lead to higher waiting times for its users and higher travel times for competing operators’ users due to the added congestion. Notably, pricing strategies can significantly affect travelers’ choice of AMoD services, but the effect depends strongly on the time of the day. Low-priced AMoD services can provide high service levels and effectively attract more demand, with up to 64.7% of customers choosing the very early morning service [5:30 AM,7:20 AM]. In the subsequent morning hours, high-priced AMoD services are more competitive in attracting customers as more idle vehicles are available. Based on the quantitative analysis, policies are recommended for the government and service operators.
AB - Automated Mobility-on-Demand (AMoD) systems, in which fleets of automated vehicles provide on-demand services, are expected to transform urban mobility systems. Motivated by the rapid development of AMoD services delivered by self-driving car companies, an agent-based model (ABM) has been developed to study the coexistence phenomena of multiple AMoD operators competing for customers. The ABM is used to investigate how changes in pricing strategies, assignment methods, and fleet sizes affect travelers’ choice of different AMoD services and the operating performance of competing operators in the case-study city of The Hague, in the Netherlands. Findings suggest that an optimal assignment algorithm can reduce the average waiting time by up to 24% compared to a simple heuristic algorithm. We also find that a larger fleet could increase demand but lead to higher waiting times for its users and higher travel times for competing operators’ users due to the added congestion. Notably, pricing strategies can significantly affect travelers’ choice of AMoD services, but the effect depends strongly on the time of the day. Low-priced AMoD services can provide high service levels and effectively attract more demand, with up to 64.7% of customers choosing the very early morning service [5:30 AM,7:20 AM]. In the subsequent morning hours, high-priced AMoD services are more competitive in attracting customers as more idle vehicles are available. Based on the quantitative analysis, policies are recommended for the government and service operators.
KW - Agent-based modeling
KW - Automated vehicles
KW - Emerging urban mobility
KW - Future scenarios
KW - Multinomial logit
KW - Operating strategies
UR - http://www.scopus.com/inward/record.url?scp=85136583062&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2022.128033
DO - 10.1016/j.physa.2022.128033
M3 - Article
AN - SCOPUS:85136583062
SN - 0378-4371
VL - 605
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
M1 - 128033
ER -