Automated Vehicles are Expected to Increase Driving and Emissions Without Policy Intervention [Policy Brief]

Rodier, Caroline; Jaller, Miguel; Pourrahmani, Elham; Bischoff, Joschka; Freedman, Joel; Pahwa, Anmol · 2020 · ROSA P / National Center for Sustainable Transportation (NCST) (UTC)

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Summary

This policy brief addresses the potential system-level impacts of automated vehicles (AVs) on travel behavior and greenhouse gas emissions, motivated by concerns that AV adoption could increase driving distances and congestion despite promises of improved safety and efficiency. The study aims to provide public and private sectors with methods to understand these effects, specifically focusing on the San Francisco Bay Area. The research was conducted by simulating two distinct future scenarios: a 100% personal automated vehicle future and the introduction of an automated taxi service with plausible per-mile fares. To execute these simulations, researchers utilized the Metropolitan Transportation Commission’s activity-based travel demand model (MTC-ABM) alongside MATSim, an agent-based transportation model. These tools allowed for the assessment of how AV technologies affect conventional personal vehicle use, transit travel, and overall system performance. The findings indicate that without policy intervention, automated vehicle technology is likely to significantly increase vehicle miles traveled (VMT) and associated greenhouse gas emissions. This increase stems from efficient AV operations creating more roadway capacity and lowering the perceived cost of driving by allowing passengers to perform other tasks. In the simulations, VMT increased by 11% in the personal AV scenario and 18% in the automated taxi scenario compared to the base case. Furthermore, the study found that automated taxis could undermine existing sustainable modes; in outer regional areas, automated taxis provided faster and cheaper service than transit, leading to a reduction in regional transit share by approximately half. While efficient AV operations might theoretically improve congestion, the induced travel demand creates an unclear net result, with current models potentially overestimating congestion benefits. The brief concludes that road pricing policies are necessary to counteract these negative impacts. Simulations showed that implementing a per-mile road user charge mitigated the increase in VMT, increased transit use, and promoted bicycling and walking. However, the reduction in VMT was largely driven by a decrease in shared vehicle trips, suggesting that traditional carpooling incentives, such as lane access, may be ineffective against the travel time benefits of AVs. Consequently, the authors argue that new incentives are required to promote shared vehicle trips. The significance of this work lies in its demonstration that AVs will not automatically lead to sustainable outcomes; rather, proactive policy interventions, particularly pricing mechanisms, are essential to prevent increased emissions and to maintain the viability of public transit and shared mobility options.

Key finding

Simulated automated vehicle adoption increased vehicle miles traveled by 11% in a personal-vehicle scenario and 18% in an automated-taxi scenario, and cut regional transit share by about half.

Methodology

simulation_modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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