Demand-oriented mobility solutions for rural areas using autonomous vehicles

Abstract

Abstract Conventional public transport is facing major difficulties in rural parts of Germany due to current societal and demographical changes. Flexible mobility solutions, for example, carpooling, have been tried over and over in Germany. However, they have never caught on and most featured major financial problems. In the dawn of autonomous driving, these flexible mobility solutions surface again. New economically viable options for carpooling are appearing. Replacing personnel in transit vehicles can cut down on major parts of operation costs. The sharing economy is growing quickly and, as a part of this, sharing rides is becoming more popular again. Services like Uber and Lyft in the United States and car-sharing schemes in Germany are gaining attention for city transport. This study, however, will focus on pooling rides in rural areas, where there are very different conditions compared to inner city mobility. Average trip distance is longer and there are potentially fewer people that could share a ride. The goal of this study is to determine the feasibility of introducing flexible mobility solutions on a large scale in rural areas, using autonomous carpooling. Major trends for the next 30 years are taken into consideration to estimate public transport demand and supply in the future for rural areas in Germany. According to these changes, a model of a typical rural area in Germany is established to show the implementation of autonomous ride sharing and the feasibility of running a sound service. The demand is modeled depicting the real mobility demand of a sample administrative district in Germany. Our results show that ride pooling with autonomous vehicles is a feasible option for improving public transport in rural areas.