On-demand (known also as flexible or demand responsive) services rely on algorithms that determine which vehicle to assign to which passenger travel request. This becomes especially relevant as developments in vehicle automation and the shared economy call for new developments in routing flexible transport services.
Together with colleagues from Applied Mathematics and Transdev (Connexxion) in the Netherlands, we propose a new type of insertion algorithm: an online dynamic insertion algorithm with demand forecasts. Hence, this algorithm beyond responsiveness by incorporating demand anticipatory capabilities. The performance of this algorithm is tested in a simulation model for a case study network located in vicinity to Amsterdam.
When combining the new insertion algorithm with empty vehicle rerouting, 98% of passenger rejections are eliminated and travel and waiting times are reduced by up to 10 and 46% respectively, compared to traditional insertion algorithms. A sensitivity analysis tested performance robustness to variations in operational and demand conditions including different fleet compositions.