Optimizing Demand Responsive Transit: A Study on Fleet Size and Service Performance in Munich’s Northern Suburbs

The purpose of this study is to optimize the fleet size range of demand responsive transit (DRT) services for a given population density and service area in suburban regions. With the aim to reduce the use of private vehicles in the northern suburbs of Munich, specifically in the counties of Munich, Dachau, and Freising, over 400,000 origin–destination relationships were narrowed down to 349 high car demand inter-zonal relationships in Munich’s northern counties. A survey conducted among residents highlighted distinct mobility patterns and mode choices, revealing longer travel times to public transport services and higher car ownership in suburban areas compared to the city. DRT simulations were conducted at 1%, 2%, and 5% of car demand levels across multiple service areas categorized by area and population density, ensuring that each service area had a connection to a train station. Key performance metrics such as trips served, average detour factor, and average origin wait time were analyzed. Findings revealed that appropriate fleet sizing based on demand and population density is crucial for maintaining high service performance, with smaller areas requiring fewer vehicles and larger, densely populated regions requiring more. The results highlight the effectiveness of DRT in addressing last-mile connectivity and the drawbacks of infrequent bus services, enhancing public transport use, and reducing car dependency in suburban regions. Recommended optimum fleet size ranges for various combinations of service areas and population densities provides a framework for transport planners and authorities for the potential introduction of DRT services in suburban regions.