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Traffic light assistant system for optimized energy consumption in an electric vehicle

Emre Kural ; Stephen Jones ; Alejandro Ferreira Parrilla (Institutionen för signaler och system) ; Anders Grauers (Institutionen för signaler och system, Automation)
2014 International Conference on Connected Vehicles and Expo (ICCVE) p. 604-611. (2014)
[Konferensbidrag, refereegranskat]

Increasingly intelligent vehicle driving systems are rapidly being developed, and will in the future become a necessity for sustainable, convenient and safe mobility in our ever more urbanized world. This paper presents an innovative approach for the control of a fully electric vehicle approaching a road segment with Multiple Traffic Lights (TL). By utilizing Vehicle to Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, the energy consumption for the maneuver completion can be reduced. The problem is approached from a Model Predictive Control (MPC) framework. The performance of the system is evaluated using a complex simulation toolchain representing the vehicle, powertrain, driver, and road including the traffic conditions. The results have shown an overall energy consumption reduction of 29 % for an idealized case and 17 % for a real road simulated scenario as compared to ‘normal’ human driver behavior.

Nyckelord: Traffic Lights, Electric Vehicle, Model Predictive Control (MPC), Energy Consumption, Advanced Driver Assistance Systems (ADAS), Simulation, Vehicle-to-Infrastructure (V2I)

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Denna post skapades 2015-11-20. Senast ändrad 2016-08-18.
CPL Pubid: 226118


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Institutioner (Chalmers)

Institutionen för signaler och system (1900-2017)
Institutionen för signaler och system, Automation (2005-2017)



Chalmers infrastruktur