Integrating ridesharing services with automated vehicles into macroscopic travel demand models

Abstract

As the introduction of fully automated vehicles enhances the attractiveness of carsharing and ridesharing systems, cities and regions may want to examine the effects of this development. This paper presents a framework for how to integrate those services in traditional macroscopic travel demand models, which are commonly used to evaluate the impacts of changed transport supply. Addressed topics are (1) the implementation of direct and intermodal ridesharing into the demand modeling process, presenting two approaches for the latter, (2) the pooling of ridesharing trips and (3) the scheduling of automated and shared vehicles. The first approach for integrating intermodal ridesharing includes ridesharing as an additional transport system, which uses the road network and which is integrated in the timetable-based public transport assignment. The second approach uses direct-link connections between traffic zones and suitable public transport transfer stops for the ridesharing feeder trips instead. Using the second approach, preliminary results of a test scenario for the Stuttgart region are presented.

Implementing a Ride-sharing Algorithm in the German National Transport Model (DEMO)

“…In order to match the supplier and demander paths, there is an iteration over all demander paths where the current path is compared to longer supplier paths. The algorithm follows the following steps, based on Friedrich et al (8) and Richter et al (10):…”

“…It regards non-discrete demand and matches trip trajectories based on crossed TAZs with the trips’ network-based paths. This approach has been successfully implemented for regional modeling studies in the context of automated driving ( 9 , 10 ). Applying the scheduling algorithm by Hartleb et al ( 11 ), it is possible to determine relocation trips and fleet sizes.…”

“…To summarize, the approach of Friedrich et al ( 8 ) provides a framework that stands out with its straightforward implementation into existing macroscopic travel demand models and produces good results with reasonable computational effort. For these reasons, the approach has already been applied and further developed in different research works ( 9 , 10 ). It is suggested that this approach is suitable for a large-scale implementation, too.…”

“…In Richter et al ( 10 ), this algorithm is implemented for autonomous ride-sharing where suppliers are vehicles of a commercial service provider. Since the suppliers’ tours in this case solely depend on the demanders’ trips, the demander paths are matched with themselves following the previously described steps.…”

Vehicle scheduling for on-demand vehicle fleets in macroscopic travel demand models

“…Examples of microscopic approaches including on-demand services in existing travel demand models are presented by Azevedo et al (2016) for SimMobility, Maciejewski (2016), Hörl (2017) for MATSim, Heilig et al (2018), Wilkes et al (2019) for mobi-Topp and Martínez et al (2017) for an agent-based model for Lisbon. A macroscopic approach is described by Richter et al (2019).…”