Service Level Evaluation of Florida’s Highways Considering the Impact of Autonomous Vehicles

Mahdavian, Amirsaman; Shojaei, Alireza; Oloufa, Amr · 2019 · Crossref

DOI: 10.22260/isarc2019/0155

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Summary

This study addresses the critical need for long-term transportation planning in the face of emerging autonomous vehicle (AV) technologies and significant infrastructure investment gaps in the United States. Motivated by the American Society of Civil Engineers’ low infrastructure grade and the potential for AVs to revolutionize traffic dynamics, the research investigates the impact of AV market penetration on the service levels of Florida’s I-95 highway in District Five (Flagler, Volusia, and Brevard counties). The primary objective is to forecast traffic conditions from 2020 to 2040, providing government agencies and private investors with realistic plans to avoid infrastructure obsolescence and manage congestion. The methodology employs a data-driven fusion model that integrates traffic flow forecasts with capacity adjustments based on AV adoption. The study utilizes Florida Department of Transportation (FDOT) data for 38 stations along I-95, applying a weighting method to normalize Annual Average Daily Traffic. The model incorporates optimistic and pessimistic scenarios for AV market penetration, ranging from 0% in 2020 to 45% in 2040 under optimistic conditions. It evaluates six specific outputs affecting the volume-to-capacity (V/C) ratio: the impact of new user categories (e.g., seniors, disabled individuals), shifts from private to shared ownership, changes in vehicle time gaps due to automation, behavioral scenarios (baseline, adaptive, disruptive), and construction scenarios involving lane additions. The results indicate that while AVs increase roadway capacity through reduced headways and improved control precision, the increase in traffic flow exceeds the increase in capacity, leading to higher congestion levels. Specifically, the introduction of new user categories increases the V/C ratio by up to 18% by 2040. Conversely, shared vehicle ownership significantly mitigates congestion; a 75% shared ownership rate could delay highway overflow by six years. Shorter time gaps between AVs can improve capacity by up to 20%, though benefits are negligible at low penetration rates. Behavioral analysis reveals that without adaptive planning, disruptive scenarios lead to severe congestion gaps compared to baseline projections. Furthermore, constructing additional lanes is shown to be a viable short-term solution, with the first two added lanes providing the most significant utility in reducing the V/C ratio. The significance of this research lies in its demonstration that current infrastructure plans are insufficient to handle the projected surge in AV-related traffic demand. The study concludes that federal and local governments must adopt a proactive approach, utilizing such fusion models to optimize resource allocation and infrastructure timing. It highlights that without interventions like promoting shared mobility or timely lane expansions, the transition to autonomous vehicles will exacerbate congestion rather than alleviate it. The findings provide a framework for resilient transportation planning, emphasizing the need to account for both capacity expansion and induced demand in future highway development.

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