Effectiveness of the Autonomous Braking and Evasive Steering System OPREVU-AES in Simulated Vehicle-to-Pedestrian Collisions
Author:
Losada Ángel1ORCID, Páez Francisco Javier1ORCID, Luque Francisco2ORCID, Piovano Luca2ORCID
Affiliation:
1. Department of Accidentology, University Institute for Automobile Research Francisco Aparicio Izquierdo (INSIA-UPM), Universidad Politécnica de Madrid, 28031 Madrid, Spain 2. Center for Energy Efficiency, Virtual Reality, Optical Engineering and Biometry (CEDINT-UPM) Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Spain
Abstract
This paper proposes a combined system (OPREVU-AES) that integrates optimized AEB and Automatic Emergency Steering (AES) to generate evasive maneuvers, and it provides an assessment of its effectiveness when compared to a commercial AEB system. The optimized AEB system regulates the braking response through a collision prediction model. OPREVU is a research project in which INSIA-UPM and CEDINT-UPM cooperate to improve driving assistance systems and to characterize pedestrians’ behavior through virtual reality (VR) techniques. The kinematic and dynamic analysis of OPREVU-AES is conducted using CarSim© software v2020.1. The avoidance trajectories are predefined for speeds above 40 km/h, which controls the speed and lateral stability during the overtaking and lane re-entry process. In addition, the decision algorithm integrates information from the lane and the blind spot detectors. The effectiveness evaluation is based on the reconstruction of a sample of vehicle-to-pedestrian crashes (INSIA-UPM database), using PCCrash© software v. 2013, and it considers the probability of head injury severity (ISP) as an indicator. The incorporation of AEB can avoid 53.8% of accidents, with an additional 2.5–3.5% avoided by incorporating automatic steering. By increasing the lateral activation range, the total avoidance rate is increased to 61.8–69.8%. The average ISP reduction is 65%, with significant reductions achieved in most cases where avoidance is not possible.
Funder
Project OPREVU Project VULNEUREA Community of Madrid
Subject
Electrical and Electronic Engineering,Automotive Engineering
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