On The Impact of Replacing Private Cars with Autonomous Shuttles: An Agent-Based Approach

TL;DR

This paper uses an agent-based framework to evaluate the sustainability implications of replacing private cars with shared autonomous shuttles across Berlin-Brandenburg under the European Green Deal. It integrates 2050 travel-demand forecasts with a MATSim Open Berlin baseline and tests 12 regulatory scenarios (SAV bans in inner city, city, and metro areas) using the DRT SAV module, coupled with lifecycle assessments that separate driving-related and non-driving-related emissions. The study finds modest life-cycle emission reductions from 0.4% to 9.6% and energy savings from 1.5% to 12.2%, with substantially larger gains (up to 59%) achievable when SAVs are fully electrified. The results underscore the potential of zone-based SAV deployment but also highlight the dominant role of electrification and the need for more realistic demand-shaping, infrastructure assumptions, and optimization of ride-sharing in future work.

Abstract

The European Green Deal aims to achieve climate neutrality by 2050, which demands improved emissions efficiency from the transportation industry. This study uses an agent-based simulation to analyze the sustainability impacts of shared autonomous shuttles. We forecast travel demands for 2050 and simulate regulatory interventions in the form of replacing private cars with a fleet of shared autonomous shuttles in specific areas. We derive driving-related emissions, energy consumption, and non-driving-related emissions to calculate life-cycle emissions. We observe reduced life-cycle emissions from 0.4% to 9.6% and reduced energy consumption from 1.5% to 12.2%.

Figures (11)

• Figure 1: One of our simulated deployment strategies for shared autonomous shuttles. Here, private cars are banned in the city of Berlin, as indicated by the green streets. Red lines indicate streets for private cars and blue lines public transport routes. All trips need to be done with shared autonomous shuttles, bicycles, public transportation, or on foot. Adapted from Karsch_Sustainability_2023_MA.
• Figure 2: Conservative and optimistic travel demand forecasts of population growth (dotted lines) and travel demand (solid lines) for 2030 and 2050. Adapted from Karsch_Sustainability_2023_MA.
• Figure 3: Delta of car-based travel with SAV introduction compared to the original OpenBerlin scenario, where green shows a reduced vehicle count per street and red an increased count. Brighter colors indicate higher values. Best viewed at 600%.
• Figure 4: Waiting times per SAV scenario. Adapted from Karsch_Sustainability_2023_MA.
• Figure 5: Vehicle occupancy of SAV fleets. Adapted from Karsch_Sustainability_2023_MA.