Field Testing of Eco-Speed Control Using V2I Communication

Rakha, Hesham A.; Chen, Hao; Almannaa, Mohammed; Kamalanathsharma, Raj Kishore; El-Shawarby, Ihab; Loulizi, Amara · 2016 · ROSA P / Connected Vehicle/Infrastructure University Transportation Center

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Summary

This study addresses the need to reduce petroleum consumption and greenhouse gas emissions in the surface transportation sector by developing and field-testing an Eco-Cooperative Adaptive Cruise Control (Eco-CACC) system. While previous research focused on simulation-based Eco-Speed Control (ESC) algorithms, this work tackles practical implementation challenges such as communication latency, data errors, and driver reaction times. The primary objective was to validate an ESC algorithm that explicitly minimizes fuel consumption by optimizing vehicle speed profiles using Signal Phasing and Timing (SPaT) data received via vehicle-to-infrastructure (V2I) communication. The research team developed an ESC algorithm using dynamic programming to compute optimal speed trajectories for vehicles approaching signalized intersections. The algorithm incorporated vehicle dynamics and the VT-CPFM-1 fuel consumption model, accounting for two cases: passing through the intersection without decelerating or decelerating to cross during the green phase. The system was tested on the Virginia Smart Road Connected Vehicle Test Bed in Blacksburg, Virginia, using a 2014 Cadillac SRX equipped with V2I communication capabilities. The field test involved 32 participants who completed 64 trips each, totaling 2,048 trips across various signal timing offsets (10, 15, 20, and 25 seconds) and road grades (3% uphill and downhill). Four scenarios were evaluated: a baseline uninformed drive, an informed drive with a red-light countdown, a manual Eco-CACC scenario where drivers followed audio-alerted speed recommendations, and an automated Eco-CACC scenario where the system controlled longitudinal motion. The results demonstrated that the Eco-CACC system significantly improved driving smoothness and efficiency compared to the baseline. Fuel consumption and travel times consistently decreased from the baseline scenario to the automated scenario. Specifically, the longitudinally automated Eco-CACC system achieved average fuel consumption savings of approximately 37.8% and travel time reductions of 9.3% compared to the uninformed baseline. The automated scenario consistently yielded the lowest fuel consumption and travel times across all tested conditions, including varying red phase offsets and road grades. Additionally, post-run surveys indicated that participants perceived the automated system as enhancing safety, comfort, and decision-making ability at intersections. The study concludes that integrating V2I communication with automated speed control offers substantial benefits for fuel efficiency and travel time reduction at signalized intersections. By addressing real-world implementation issues such as latency and driver perception, the Eco-CACC system proves viable for practical application. The findings support the adoption of connected vehicle technologies to promote environmental sustainability and operational efficiency in transportation systems, highlighting the potential for automated eco-driving strategies to outperform manual driver adjustments.

Key finding

The longitudinally automated Eco-CACC system reduced fuel consumption by approximately 37.8% and travel times by 9.3% compared to the uninformed baseline driving scenario.

Methodology

field_study

Sample size: 32

Provenance

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

Topics

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• eco driving