Improved public transportation in rural areas with self-driving cars: A study on the operation of Swiss train lines

Public transport lines, especially train lines, have historically played an important role as economic lifelines of rural areas. They are one of the most important factors contributing to economic prosperity as they provide access to mobility for all the inhabitants of these regions. Maintaining such rural public transport lines can be a challenge due to the low utilization inherent to rural areas. Today, with the emergence of fully self-driving cars, on-demand mobility schemes in which autonomous robotic taxis transport passengers, are becoming possible. In this work, we analyze if rural public transport lines with low utilization can be replaced with autonomous mobility-on-demand systems. More specifically, we compare the existing public transportation infrastructure to hypothetical mobility-on-demand systems both in terms of cost and service level. We perform our analysis, which focuses on the operational aspects, using a simulation approach in which unit-capacity robotic taxis are operated in a street network taking into account congestion effects and state-of-the-art control (dispatching and rebalancing) strategies. Our study considers the case of four rural train lines in Switzerland that operate at low utilization and cost coverage. We show that a unit-capacity mobility-on-demand service with self-driving cars reduces both travel times and operational cost in three out of four cases. In one case, even a service with human driven vehicles would provide higher service levels at lower cost. The results suggest that centrally coordinated mobility-on-demand schemes could be a very attractive option for rural areas.