Potentials of Autonomous Vehicles in a Changing Private Transportation System – a Case Study in the Stuttgart Region

Heilig, Michael; Hilgert, Tim; Mallig, Nicolai; Kagerbauer, Martin; Vortisch, Peter · 2017 · OpenAlex-citations

DOI: 10.1016/j.trpro.2017.07.004

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Summary

This study investigates the potential impacts of widespread autonomous vehicle (AV) adoption on private transportation systems, specifically focusing on the transition to Autonomous Mobility on Demand (AMOD) services. Motivated by the anticipated blurring of boundaries between private and public transport, the authors aim to quantify the effects of replacing private car ownership with a shared AMOD fleet. The research addresses gaps in existing literature by simultaneously modeling changes in travel behavior (mode and destination choice) and the operational requirements of an AMOD system, rather than treating them in isolation. The researchers employed the microscopic, agent-based travel demand model *mobiTopp* to simulate travel behavior for the Stuttgart region, representing 2.3 million agents over a one-week period. The methodology involved two steps. First, they simulated a future scenario where private car ownership is eliminated and replaced by an AMOD service, modeled with costs 70% lower than private cars to reflect operational efficiencies. This allowed the model to determine shifts in mode choice and destination selection. Second, using the resulting trip data, they calculated the infrastructure requirements for the AMOD service. This involved pooling trips with shared origins and destinations within 15-minute time slots, assuming a vehicle capacity of four passengers. The study also modeled vehicle relocation strategies, assuming empty vehicles are redistributed between zones only during nighttime hours to minimize traffic impact. The results indicate significant changes in travel patterns and resource utilization. While most travelers shifted to the AMOD service, some switched to walking, cycling, or public transportation, particularly for short trips under two kilometers. Consequently, the average length of car trips increased due to lower costs. The AMOD service reduced the total number of vehicle trips by approximately 46% and vehicle kilometers traveled by 20%. Crucially, the study found that only about 221,000 AMOD vehicles are needed to meet the region’s demand, compared to the approximately 1.565 million private cars currently registered. This suggests that roughly 85% of existing vehicles could be dispensable. However, the analysis revealed that trip reductions are not spatially uniform; originating car trips increased in the city center and areas with poor public transport coverage, indicating potential for localized congestion despite overall system efficiency. The significance of this work lies in its demonstration that AMOD services can drastically reduce the number of vehicles required in urban areas, freeing up street space and reducing emissions. However, the findings also highlight that cost reductions may induce longer trips and shift demand to specific zones, potentially exacerbating congestion in city centers. The study underscores the importance of integrating behavioral changes with operational modeling to accurately assess the impacts of autonomous mobility, suggesting that policy interventions may be necessary to manage localized traffic loads in a post-private-car society.

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