Interrelated trips in the rural dial-a-ride problem with autonomous vehicles

Abstract

Nowadays, the rural population is still dependent on motorized individual transportation due to the little offers of public transport there. Autonomous vehicles have the potential to close this mobility gap as shifting the task of driving from humans to machines facilitates new possibilities for vehicle sharing and lifts economical and service time limitations (e.g., labor costs and working hour regulations). However, mobility service operators are then probably responsible for serving the holistic travel demands of users. This might involve interrelated trips, where users ask for simultaneous arrival at meeting locations, where round trips involve a stay time at some destination locations, or the like. Accordingly, in this work, we present a problem variant of the dial-a-ride problem that allows for interrelated trips. We formulate the problem as a mixed-integer program and propose an adaptive variable neighborhood search heuristic (AVNS) based on a sophisticated solution representation. Our computational results for instances considering characteristics of rural areas reveal that the heuristic performs very well and that it is clearly superior to standard MIP solvers. We further investigate the impact of different types of trip interrelations on the solvability of the problem, service quality, and total transportation costs of the solutions.