부산대학교 도서관

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 ride-pooling 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.