An Analytical Model to Evaluate Traffic Impacts of On-Demand Ride Pooling

Ride pooling services have the possibility to enhance the traffic efficiency in our cities. The improvements on traffic conditions among other factors depend on the likelihood to find shareable trips in an operational area, a quantity called shareability. There are already available mathematical models, which show that shareability depends on service quality and city parameters, such as average velocity, which is considered to be constant. However, with the introduction of ride pooling services the average velocity is expected to increase as a result of fewer vehicles on the road due to shared trips. Current models are not able to estimate the modified shareability values for a dynamic velocity, which depends on the percentage of shared trips in an area. Therefore, this paper explores analytically the traffic impacts of ride pooling services and the influence that changed traffic conditions due to ride pooling have on the percentage of shared trips. The results could be beneficial for operators and cities for a quick estimation of the traffic impacts of ride pooling and the shareability that can be reached in an area due to these effects.