Benefit Assessment of New Ecological and Safe driving Algorithm using Naturalistic Driving Data

A new Ecological and Safe (EcoSafe) driving control algorithm has been recently developed by the authors for controlling the longitudinal motion of the vehicle to minimize fuel consumption while respecting safety constraints. The algorithm uses a Model predictive control framework augmented with enhanced safety constraints based on Intervehicular Time (TIV) and the Time to Collision (TTC). This algorithm requires tuning to adapt to traffic condition. In this paper we propose a tuning method for EcoSafe algorithm which is deduced from driver preference and traffic flow information. In addition, to the best of our knowledge, the benefits of similar EcoSafe algorithms have not been tested with naturalistic data. Hence, we assessed the benefits of EcoSafe algorithm in terms of eco-driving and safety by using 1,100 km of naturalistic driving data. We use velocity profile extracted from the Australian Naturalistic Driving Study (ANDS) as the leading vehicle driving behaviour. The results show that our proposed strategy has a 14% reduction in fuel consumption on average while maintaining high safety levels without increasing travel time significantly.