TY - GEN
T1 - On the Effects of Ride-Hailing and Ride-Pooling Stop Processes on Urban Network Capacities
AU - Hanekamp, Griffin
AU - Tilg, Gabriel
AU - Dandl, Florian
AU - Bogenberger, Klaus
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - With the introduction and expansion of mobility offerings, today's urban roadways are quickly becoming more multi-modal. Ride-sharing services, including ride-hailing and ride-pooling, interact with private cars in different ways based on their fleet characteristics, such as idling behavior and stop process allowance. Our understanding of these interactions from both an operational and a regulatory perspective will only become more important as city streets become more dense. This paper seeks to analyze the effects of ride-hailing and ride-pooling stop processes on the network capacity of a bi-modal network featuring private cars and a ride-sharing fleet. To do so, microscopic traffic simulations are conducted for a bi-modal traffic network in the Hamburg district of Harvestehude. The network capacity is estimated using the three-dimensional passenger Macroscopic Fundamental Diagram (3D-pMFD), a tool which displays the relationship between car accumulation, accumulation of a second mode, and passenger production for a given network. The performance of the network is evaluated given varying levels of both private car and ride-sharing vehicle demand. The results of the simulations show that the 3D-pMFD can be used to estimate the effects on traffic flow of bi-modal networks featuring small ride-sharing fleets. Additionally, our results indicate that ridepooling fleets in Harvestehude are able to offer a similar level of service to its passengers compared with ride-hailing fleets while accumulating fewer vehicle kilometers traveled. Finally, ride-sharing fleets featuring mid-edge off-street stop processes in Harvestehude appear more resilient to congestion effects based on their ability to continue serving trip requests. The results of this study are relevant to regulators, operators, and customers, as manipulating the operational characteristics of ride-sharing fleets has the potential to benefit all three groups and produce a more efficient, profitable, and useful service overall.
AB - With the introduction and expansion of mobility offerings, today's urban roadways are quickly becoming more multi-modal. Ride-sharing services, including ride-hailing and ride-pooling, interact with private cars in different ways based on their fleet characteristics, such as idling behavior and stop process allowance. Our understanding of these interactions from both an operational and a regulatory perspective will only become more important as city streets become more dense. This paper seeks to analyze the effects of ride-hailing and ride-pooling stop processes on the network capacity of a bi-modal network featuring private cars and a ride-sharing fleet. To do so, microscopic traffic simulations are conducted for a bi-modal traffic network in the Hamburg district of Harvestehude. The network capacity is estimated using the three-dimensional passenger Macroscopic Fundamental Diagram (3D-pMFD), a tool which displays the relationship between car accumulation, accumulation of a second mode, and passenger production for a given network. The performance of the network is evaluated given varying levels of both private car and ride-sharing vehicle demand. The results of the simulations show that the 3D-pMFD can be used to estimate the effects on traffic flow of bi-modal networks featuring small ride-sharing fleets. Additionally, our results indicate that ridepooling fleets in Harvestehude are able to offer a similar level of service to its passengers compared with ride-hailing fleets while accumulating fewer vehicle kilometers traveled. Finally, ride-sharing fleets featuring mid-edge off-street stop processes in Harvestehude appear more resilient to congestion effects based on their ability to continue serving trip requests. The results of this study are relevant to regulators, operators, and customers, as manipulating the operational characteristics of ride-sharing fleets has the potential to benefit all three groups and produce a more efficient, profitable, and useful service overall.
UR - http://www.scopus.com/inward/record.url?scp=85175403179&partnerID=8YFLogxK
U2 - 10.1109/MT-ITS56129.2023.10241763
DO - 10.1109/MT-ITS56129.2023.10241763
M3 - Conference contribution
AN - SCOPUS:85175403179
T3 - 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
BT - 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
Y2 - 14 June 2023 through 16 June 2023
ER -