Driving Simulation for Energy Efficiency Studies: Analyzing Electric Vehicle Eco-Driving With EcoSimLab and the EcoDrivingTestPark

Driving simulators often lack fundamental components needed for accurate simulation of energy dynamics. We introduce EcoSimLab, a comprehensive electric vehicle driving simulation framework consisting of (1) a simulation of electric vehicle energy dynamics, (2) an optimization-based approach of structuring eco-driving behaviors, (3) a synthetic driver module as versatile benchmark model to analyze human behavior. Guided by fundamentals of energy modeling and considerations on human action regulation, we further present the development of the EcoDrivingTestPark, an exemplary set of energy-relevant scenarios to enable the analysis of individual differences in eco-driving and intervention effects (e.g., HMIs). To generate a first characterization of driving behavior, we conducted two empirical studies with human (𝑁S1 = 31, 𝑁S2a = 41) and synthetic drivers (𝑁S2b = 3). Results indicate substantial variations in driver behavior and considerable challenges for human drivers to achieve synthetic driver performance. Implications for augmenting human action regulation in eco-driving are discussed.