Optimal routing of multimodal mobility systems with ride-sharing

Multimodal transportation systems are a combination of more environmentally friendly shared transport modes including public transport, ride-sharing, shuttle-sharing, or even completely carbon-free modes such as cycling to better meet customer needs. Multimodal mobility solutions are expected to contribute in mitigating traffic congestion and carbon emissions, and to result in savings in costs. They are also expected to improve access to transportation, more specifically for those in rural or low-populated communities (i.e., difficult to serve by public transportation only). Motivated by its benefits, in this study, we consider the combination of the ride-sharing and public transportation services and formulate a mixed integer programming model for the multimodal transportation planning problem. We propose a heuristic approach (i.e., angle-based clustering [AC] algorithm) and compare its efficiency with the exact solution for different settings. We find that the AC algorithm works well in both small and large settings. We further show that the multimodal transportation system with ride-sharing can yield significant benefits on travel distances and travel times.

Automated summary

Multimodal transportation systems combine various environmentally friendly transportation modes to meet customer needs, improve transportation efficiency, and save costs. By studying the combination of ride-sharing and public transportation services, it is found that multimodal transportation systems can significantly benefit travel distances and times.