Safety and Energy Assessment of Electric Vehicles Equipped with Adaptive Cruise Control System

This work focuses on the assessment of safety and energy performance of an ACC-equipped electric vehicle under different driving conditions. Variability in vehicle dynamics and ACC settings introduces complexities in analysing the performance of the considered system. To address this challenge, an evaluation methodology that integrates stochastic simulation with the PAWN sensitivity technique is employed. This approach enables the evaluation of the impact of variations in driving conditions on both safety and energy efficiency. The extensive analysis denotes and quantifies the effect of driving condition variables on the performance of the vehicle. Results also prove that different goals (safety and consumption) are affected by different variables. The outcome of such operation is crucial for optimizing ACC system design and operation to enhance both safety and energy efficiency in electric vehicles.

I. Introduction

The transportation sector is confronted with the critical challenge of reducing its environmental impact, given that it accounted for approximately 22% of greenhouse gas (GHG) emissions in Europe in 2020, according to data reports. In this context, vehicle electrification has emerged as one of the best technological solutions to adopt for decreasing both energy consumption and the pollutant emissions associated with conventional vehicles. [1], [2]. Besides Electric Vehicles (EVs), the deployment of Automated Driving Systems (ADSs) is expected to enhance road efficiency, safety, and energy performance [3], [4]. However, the design of ADSs yielding positive effects on both safety and energy consumption is still an open challenge. Numerous studies have investigated the performance of ACC-equipped vehicles [5], [6]. For instance, [7] evaluated seven commercially available ACC systems to understand if they were string stable, while [8] carried out a simulation study on the impact of ACC-equipped vehicles on road safety and traffic efficiency under realistic driving conditions (e.g., imperfect communication, large reaction time, imperfect vehicle modelling and heterogeneous traffic demand). Field experiment investigating the consumption of vehicles following an ACC-equiped one were carried out in [9] and [6]. The studies results indicate that following an ACC-equipped vehicle results in higher consumption compared to following a human-driven one. Recently, some studies focused on the evaluation of different kind of performance of ACC-equipped vehicles at the same time [10], [11]. For instance, the results of [11] are in line with the previous findings in terms of string instability of the ACC, highlighting that current ACC implementations may increase energy consumption and safety risks with higher penetration rates in fleets. Most studies assume vehicle and consumption model parameters are set at nominal values or omit them entirely from the ACC system model. However, these parameter variations should not be overlooked, as they significantly impact vehicle performance and test outcomes.