Energy saving and safe driving assistance system for light vehicles: Experimentation and analysis

Nouveliere, L.; Mammar, Saïd; Luu, Hong Tu · 2012 · OpenAlex-citations

DOI: 10.1109/icnsc.2012.6204942

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Summary

This paper presents the development and experimental validation of an Eco-Driving Assistance System (EDAS) designed for light vehicles to simultaneously reduce fuel consumption and enhance driving safety. The research is motivated by the need to lower greenhouse gas emissions from road transport, which remains a major contributor to CO2 emissions. While electric vehicles offer a long-term solution, the authors argue that immediate fuel savings can be achieved by modifying driver behavior through real-time assistance. The proposed system distinguishes itself by integrating infrastructure data, such as road geometry and legal speed limits, with real-time vehicle dynamics to compute optimal driving trajectories. The EDAS architecture combines a fuel consumption model, a safety module, and a Human-Machine Interface (HMI). Vehicle dynamics are modeled using a non-slip longitudinal model, while fuel consumption is estimated using a polynomial function of engine speed and torque, validated with an error margin of less than 2.5% for most data. The core optimization module employs Dynamic Programming to calculate optimal speed profiles and gear ratios. This optimization balances three criteria: minimizing fuel consumption, minimizing trip time, and ensuring driving smoothness. Safety constraints are integrated by enforcing legal speed limits and maintaining a safe headway spacing (based on a 2-second rule) relative to preceding vehicles. The HMI displays the current speed, optimal speed, and recommended gear ratio using a color-coded interface, providing immediate feedback to the driver. Experimental validation was conducted on a prototype Renault Clio Eco2 using eight voluntary drivers across two phases. Phase 1 involved free-circulating driving to assess fuel economy without traffic constraints, while Phase 2 introduced a preceding vehicle to evaluate performance under traffic conditions. Drivers performed trips both without the EDAS and with the HMI active. Results from Phase 1 showed fuel savings ranging from 1.8% to 9.7%, with significant reductions in legal speed overshoots (up to 79%). In Phase 2, which simulated real traffic, the system achieved an average fuel economy of 7.55% across all drivers, with individual gains ranging from 1.6% to 12.9%. Furthermore, the EDAS drastically improved safety metrics, reducing speed overlaps by more than 50% compared to legal limits. The analysis indicated that the system’s ability to anticipate road events allowed drivers to adopt smoother, more economical driving styles that were difficult to achieve manually. The study concludes that the EDAS is a promising solution for improving both the ecological and safety aspects of light vehicle driving. By providing anticipative guidance based on road infrastructure and traffic conditions, the system enables drivers to achieve significant fuel savings and safer driving behaviors without substantially increasing trip times. The findings suggest that such assistance systems can effectively bridge the gap between current conventional vehicles and future low-emission standards by optimizing driver behavior in real-time.

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• eco driving