Pavement Life Comparison for Different Traffic Scenarios

Zhou, Fujie; Hu, Sheng; Xue, Wenjing; Flintsch, Gerardo W · 2019 · ROSA P / Safety through Disruption (Safe-D) University Transportation Center (UTC)

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Summary

This study investigates the impact of automated vehicle (AV) lateral positioning on pavement durability and roadway safety, specifically addressing the risks of accelerated pavement deterioration and hydroplaning. The research is motivated by the observation that AVs are programmed to maintain a precise lateral position within lanes, resulting in significantly less lateral wandering than human-driven vehicles. This concentrated traffic loading is hypothesized to cause severe pavement rutting and cracking, which in turn increases the risk of hydroplaning due to deeper water accumulation in wheel paths. The methodology involved quantifying AV lateral wandering patterns using data collected from a Texas A&M University AV operating at 20 mph on a straight test track. These empirical measurements were compared with established data for human-driven vehicles. The researchers then utilized the Texas Mechanistic-Empirical Flexible Pavement Design System (TxME) to simulate pavement performance under two scenarios: 100% human-driven truck traffic and 100% AV truck traffic. The simulations modeled lateral wandering as a normal distribution, using a standard deviation of 250 mm for human drivers and 75 mm for AVs. Additionally, hydroplaning potential was evaluated using established prediction models that account for water film thickness, rut depth, and pavement cross slope. Finally, the study tested an optimized AV wandering pattern using a uniform distribution across the lane width. The results demonstrated that AV lateral wandering is at least three times narrower than that of human-driven vehicles. This narrow wandering significantly degrades pavement performance, shortening fatigue life by 22% (178 months vs. 228 months) and increasing rut depth by 30%, reaching critical safety thresholds 39% sooner than human-driven traffic. Consequently, AVs face a much higher risk of hydroplaning; for example, at a rut depth of 7.5 mm, the hydroplaning speed for AVs drops to 48 mph compared to 64 mph for human-driven vehicles, due to greater water film thickness in the narrower, deeper ruts. However, when AVs were programmed to follow an optimal uniform lateral wandering distribution, pavement performance improved substantially. This optimized pattern extended fatigue life by 16% beyond human-driven traffic levels and increased rutting life by 24%, while significantly raising the critical rut depths required to trigger hydroplaning. The study concludes that the default narrow lateral wandering of AVs poses significant risks to infrastructure longevity and safety. To mitigate these effects, the authors recommend implementing a uniform lateral wandering pattern for AVs, which distributes traffic loads evenly across the lane. This approach not only eliminates the negative impacts of concentrated loading but also enhances pavement life and reduces hydroplaning potential. The findings imply that AV control algorithms should be adjusted to prioritize infrastructure preservation and safety, and that current lane widths should be maintained or expanded to accommodate this wider, uniform wandering pattern.

Key finding

Automated vehicles with narrow lateral wandering shorten pavement fatigue life by 22 percent and increase rut depth by 30 percent compared to human-driven vehicles, but adopting a uniform lateral wandering pattern extends fatigue life by 16 percent relative to human traffic and reduces hydroplaning risk.

Methodology

mixed_methods

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

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

Topics

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• road surface friction