01588977

Component

Traffic signals typically produce vehicle stops and thus increase vehicle fuel consumption levels. Eco-cooperative adaptive cruise control (Eco-CACC) systems can improve vehicle fuel efficiency by receiving Signal Phasing and Timing (SPaT) data from downstream signalized intersections via vehicle-to-infrastructure communication. The research presented in this paper develops an algorithm that provides advisory speed recommendations to drivers using received SPaT data to reduce vehicle fuel consumption levels. To construct an efficient algorithm, the authors first analyze the impact of different advisory speed limits and queue lengths on vehicle dynamics and their corresponding fuel consumption levels. The proposed eco-CACC algorithm with the consideration of vehicle queues is then proposed to provide the most fuel-efficient recommendation to connected vehicles (CVs). A simulation analysis demonstrates that the algorithm is able to reduce the vehicle fuel consumption level by as high as 40%. Moreover, the overall benefits of the proposed algorithm is evaluated for different intersection configurations and CV market penetration rates (MPRs). The results demonstrate that for single-lane approaches, the algorithm can reduce the overall fuel consumption levels and that higher MPRs result in larger savings. While for multi-lane approaches, lower MPRs produce negative impacts on fuel efficiency; only when the MPRs are greater than 30%, can the algorithm work effectively in reducing fuel consumption levels.

This paper was sponsored by TRB committee AHB30 Standing Committee on Vehicle-Highway Automation.

01584066

16-1593

English

28p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References

Algorithms; Autonomous intelligent cruise control; Ecodriving; Fuel consumption; Mobile communication systems; Queuing; Signalized intersections; Variable speed limits

Advisory speeds; Cooperative adaptive cruise control

Energy; Environment; Highways; Operations and Traffic Management; Vehicles and Equipment; I15: Environment; I73: Traffic Control; I90: Vehicles

Transportation Research Board Annual Meeting 2016 Paper #16-1593

TRIS, TRB, ATRI

Jan 12 2016 4:41PM