When and Where Are Dedicated Lanes Needed under Mixed Traffic of Automated and Non-automated Vehicles for Optimal System Level Benefits?

Guhathakurta, Subhrajit; Kumar, Amit · 2019 · ROSA P / Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC)

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Summary

This study addresses the infrastructure planning challenge of integrating automated vehicles (AVs) into existing road networks dominated by mixed traffic with non-automated vehicles (NAVs). As AV technology matures, the lack of physical and institutional infrastructure hinders widespread adoption. The research specifically investigates when and where dedicating specific road lanes to AVs yields optimal system-level benefits, such as reduced congestion and total system travel time. This is critical for determining the cost-effective timing and location of infrastructure investments, particularly to facilitate AV platooning, which is often disrupted by the presence of human-driven vehicles. To answer this, the authors developed a bi-level mathematical framework. The lower level employs a mixed equilibrium traffic assignment model to estimate network flows. This model treats AVs and NAVs on separate hypothetical network layers that interact through link cost functions. AVs are assigned using Deterministic User Equilibrium (DUE), assuming perfect information and rational routing, while NAVs are assigned using Stochastic User Equilibrium (SUE), accounting for varied driver perceptions. The upper level is an optimization model that determines the optimal subset of links to dedicate to AVs to minimize total system travel time. The decision variables are binary, indicating whether a link is dedicated or not. The framework was implemented using binary particle swarm optimization for the upper level and C++ for the lower level, tested on a small 15-node, 21-link network. Numerical experiments were conducted across 40 scenarios, varying AV market penetration from 1% to 40% in 1% increments. The results demonstrate that providing optimal dedicated lanes consistently reduces total system travel time compared to scenarios without dedicated lanes. Notably, the maximum savings in system travel time occurred at the lowest market penetration level (1%), with the magnitude of savings decreasing as AV penetration increased. The analysis also revealed that the number of links requiring dedication does not increase monotonically with market penetration; instead, specific links are identified as candidates for investment based on their contribution to system efficiency at various penetration levels. The study concludes that dedicated lanes can significantly improve network performance even at low levels of AV adoption, providing a strategic basis for phased infrastructure upgrades. By identifying critical market penetration thresholds and specific link locations, transportation planners can make focused, cost-effective investments to prepare road networks for AV integration. This approach bridges a gap in literature by addressing the specific routing behaviors of mixed traffic and the operational benefits of AV platooning, offering a practical decision-support tool for future transportation system planning.

Key finding

Dedicating specific links for automated vehicles reduces total system travel time across all tested market penetration levels, with the maximum travel time savings occurring at the lowest penetration rate of 1%.

Methodology

modeling

Provenance

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