Multimodal route planning with public transport and carpooling

Abstract

Increasing mobility demands raise the pressure on existing transport networks. As the most used mode of transport, private cars have a particularly strong environmental impact and produce congestion. Ridesharing or carpooling, where a driver and several riders form a carpool, can help to address these issues by increasing the number of persons per car. Therefore, recent years have seen a strong interest in carpooling. However, there exists no effective method of integrating carpooling into transport trip planners as of now, mainly due to the fuzzy and flexible nature e.g., no fixed stops, possibility of making detours of carpooling. This hinders the acceptance of carpooling by the general public. This paper proposes a new method to merge public transport and carpooling networks for multimodal route planning, considering the fuzziness and flexibility brought by carpooling. It is based on the concept of drive-time areas and points of action. The evaluation with real-world data sets shows that, compared with the state-of-the-art method, the proposed method merges static i.e., public transport and dynamic/fuzzy i.e., carpooling networks better, while retaining the desired flexibility offered by the latter, and thus creates a higher interconnectivity between the networks. Meanwhile, the merged network enables multimodal route planning, which can provide users with trips from an origin to a destination using different combinations of modes.