Emissions Impact of Connected and Automated Vehicle Deployment in California

Circella, Giovanni; Jaller, Miguel; Sun, Ran; Qian, Xiaodong; Alemi, Farzad · 2021 · ROSA P / National Center for Sustainable Transportation (NCST) (UTC)

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Summary

This study investigates the potential impacts of Connected and Automated Vehicle (CAV) deployment on travel demand, vehicle miles traveled (VMT), energy consumption, and emissions in California by 2050. Motivated by the anticipated emergence of autonomous technology and the need to support the California Air Resources Board (CARB) in understanding these environmental and societal effects, the research addresses how CAVs might alter transportation supply, travel behavior, and pollutant emissions. The authors aim to quantify these impacts across various deployment scenarios to inform policy decisions regarding pricing, shared mobility, and zero-emission vehicle adoption. The methodology combines a comprehensive literature review with quantitative modeling using the California Statewide Travel Demand Model (CSTDM). The researchers modified the CSTDM to account for CAV-specific factors, including changes in driver’s license requirements, value of time, parking costs, vehicle operating costs, and highway network capacity. They simulated seven scenarios for 2050: a Baseline (no automation), Private CAV, Private CAV with Pricing, Private CAV with Zero Emission Vehicles (ZEV), Shared CAV, Shared CAV with Pricing, and Shared CAV with ZEV. Each scenario included lower and upper bound variations. The model outputs for travel demand and mode share were integrated with emission factors from the EMission FACtor (EMFAC) and Vision models to calculate energy consumption and criteria pollutant emissions. The results indicate that the relative convenience of CAVs leads to a sharp decrease in the mode shares of public transit and in-state air travel. Consequently, total VMT and vehicle hours traveled (VHT) are projected to increase across most CAV scenarios compared to the baseline, driving up greenhouse gas and criteria pollutant emissions. The study highlights that while shared CAVs and ZEV policies can mitigate some environmental impacts, they may not fully offset the increases in travel demand and road congestion caused by the induced demand from CAV convenience. Furthermore, the research identifies limitations in current travel demand models like the CSTDM, which rely heavily on sociodemographic factors and fail to fully capture the disruptive effects of CAVs on activity participation and tour patterns. The significance of this work lies in its demonstration that CAV deployment alone is likely to worsen environmental outcomes due to increased VMT. The findings suggest that policy interventions, such as congestion pricing and incentives for shared and electric fleets, are necessary to curb tailpipe emissions. However, even with these strategies, the study concludes that policies may not completely neutralize the negative impacts on travel demand and congestion. The report underscores the need for updated modeling frameworks that better account for the behavioral shifts induced by autonomous technology to effectively plan for sustainable future mobility.

Key finding

The deployment of connected and automated vehicles in California by 2050 is projected to sharply decrease public transit and air travel mode shares while increasing total vehicle miles traveled and emissions, although pricing and zero-emission policies can help mitigate these negative environmental impacts.

Methodology

modeling

Provenance

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