Predictive fuel efficiency optimization using traffic light timings and fuel consumption model

Energy efficiency has become a major issue in trade, transportation and environment protection. While the next generation of zero emission propulsion systems are still under development, it is already possible to increase fuel efficiency in regular vehicles by applying a more fuel efficient driving behaviour. Fuel efficiency depends on vehicle specific characteristics, e.g. engine efficiency and transmission configuration. It also depends on current and future events in the environment, e.g. traffic lights or other traffic participants. This paper proposes an approach to make predictive use of traffic light timings while also incorporating knowledge about the vehicle's power-train. The optimization is largely based on dynamic programming. The results are a velocity and gear shift guidance for the driver to follow. Results based on simulations show that a system assisted driver can achieve significant fuel savings compared to an unassisted driver.