Autonomous driving and demand-oriented public transport for Sustainable cities

Abstract

Public transport is an important contributor to sustainable and smart cities. It is important for the general population to fulfill daily needs. Especially young and elderly people depend on the public transport system. They are using the system to get to work or go to school, to go shopping or the visit a doctor. Sustainability has different aspects however; a good utilization of public transport is usually considered a trait of sustainability. Achieving good utilization is especially challenging in rural areas. Low population density and a large area of operation are making it expensive to provide public transport with sufficiently attractive level of service. It is very important to avoid low utilization, because empty rides are both costly and not sustainable. However, reducing the amount of offered rides can reduce the attractiveness of the public transport system. It becomes too inflexible for the customers, especially compared to using a private car. A common approach to achieve both cost-effectiveness and flexibility is demand-oriented public transport. Trips are requested in advance and vehicle only operate in areas where they are needed and when they are needed. Empty rides are therefore avoided. This imposes new challenges for usability, once again especially for elderly people. In "Autonomous public driving" (emoin), a subproject of the project RealLabHH, such a system was implemented and tested in the region Hamburg-Bergedorf. Hamburg-Bergedorf is a suburb of Hamburg. This paper is going to provide an overview of the technical challenges and the steps involved of this project. It is going to focus on the technical aspects.