Assessing the Effectiveness of the Wyoming Connected Vehicle Pilot Program: New Traffic Safety Research Perspectives

Ahmed, Mohamed M.; Gaweesh, Sherif; Bakhshi, Arash Khoda · 2022 · ROSA P / Mountain-Plains Consortium

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Summary

This study addresses the challenge of evaluating the safety effectiveness of the Wyoming Connected Vehicle (CV) Pilot Program on Interstate 80, a rural corridor characterized by severe weather and high freight volume. Traditional safety evaluation methods, such as those in the Highway Safety Manual, are inadequate for this pilot due to the early deployment stage, low market penetration rates, and insufficient post-deployment crash data. To overcome these limitations, the authors developed a novel framework integrating real-time risk assessment, high-fidelity driving simulator experiments, and traffic microsimulation modeling to quantify the safety benefits of CV technologies. The methodology employs two complementary approaches: a before/after analysis to establish a pre-deployment baseline and a with/without analysis using an Analysis, Modeling, and Simulation (AMS) framework. The baseline development utilized matched-case control designs and advanced statistical modeling, including Random Forest feature selection and hierarchical logistic regression, on a dataset conflating crash reports, roadway geometry, weather conditions, and high-resolution real-time traffic observations from 51 speed sensors. The AMS framework quantified driver behavioral alterations through trajectory-level kinematic-based surrogate measures of safety (K-SMoS) derived from driving simulator experiments. These findings were integrated into microsimulation models using conflict-based surrogate measures of safety (C-SMoS) to assess impacts on the entire traffic stream under varying CV market penetration rates. The results identified statistically significant real-time traffic factors contributing to crashes and critical crashes during the pre-deployment phase. The with/without analysis demonstrated promising safety effects for several CV applications, including spot weather impact warnings, distress notifications, situational awareness, variable speed limits, work zone warnings, forward collision warnings, and rerouting. Trajectory-level analyses confirmed that CV notifications significantly altered driver behavior in safer directions. Furthermore, microsimulation results indicated enhanced traffic safety performance across various CV market penetration rates, particularly in mitigating risks associated with work zones and horizontal curves under adverse weather conditions. The study also established optimal thresholds for crash detection using extreme value theory and Bayesian inference. The significance of this research lies in providing a robust, data-driven framework for assessing CV safety effectiveness in environments where traditional crash-based evaluations are not feasible. By leveraging surrogate measures of safety and simulation, the study offers actionable insights for the Wyoming Department of Transportation and the Federal Highway Administration. It validates the potential of CV technologies to alleviate traffic safety concerns on rural corridors with challenging driving conditions, supporting strategic goals for improving freight mobility and reducing fatalities. The findings also provide specific recommendations for optimizing roadside unit placement and CV application deployment to maximize safety benefits.

Key finding

Connected vehicle applications demonstrated promising safety effects by altering driver behavior and enhancing traffic safety performance across varying market penetration rates, as validated through driving simulator experiments and microsimulation modeling.

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

Ranked by relevance to this paper. Hover a topic for its definition.

• naturalistic crash near crash
• induced exposure
• telematics crash prediction
• incidence prevalence
• regulatory evaluation
• exposure measurement

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes
• Methodological Resource: dataset resource
• Theoretical Contribution: computational model