Description
Passengers value reliable travel times but are often faced with delays in intermodal urban traffic. To improve their mobility experience, we propose a robust route planning tool that provides routes guaranteeing a certain probability of on-time arrival and satisfying additional constraints. The constraints can limit the number of transfers, time-dependent trip costs and other relevant resources. To find such routes, we extend the time-dependent reliable shortest path problem by adding constraints on time-dependent and stochastic edge weights. An exact solution method based on multi-objective A* search is proposed to solve this problem. By applying our algorithm to a showcase featuring an actual city, we hope to answer relevant questions for policy-makers and contribute to smarter mobility in the future.
Robust Route Planning in Intermodal Urban Traffic
Passengers value reliable travel times but are often faced with delays in intermodal urban traffic. To improve their mobility experience, we propose a robust route planning tool that provides routes guaranteeing a certain probability of on-time arrival and satisfying additional constraints. The constraints can limit the number of transfers, time-dependent trip costs and other relevant resources. To find such routes, we extend the time-dependent reliable shortest path problem by adding constraints on time-dependent and stochastic edge weights. An exact solution method based on multi-objective A* search is proposed to solve this problem. By applying our algorithm to a showcase featuring an actual city, we hope to answer relevant questions for policy-makers and contribute to smarter mobility in the future.