The Effect of Target Features on Toyota’s Autonomous Emergency Braking System

2018-01-0533

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
The Pre-Collision System (PCS) in Toyota’s Safety Sense package includes an autonomous emergency braking feature that can stop or slow a vehicle independent of driver input if there is an impending collision. The goals of this study were to determine how hazard characteristics, specifically radar reflector size and degree of target edge contrast, affect the response of the PCS, as well as to scrutinize tests wherein the PCS failed to stop the vehicle before impact. We conducted 80 tests with a 2017 Toyota Corolla driven towards a car-like target in a straight line and under constant accelerator pedal position, reaching about 30 km/h at the PCS alarm. Vehicle speed and distance to target at the alarm flag (ALM) and at times corresponding to three other system flags (PBA, FPB, and PB) were read from the Vehicle Control History records. Time to impact (TTI) at each flag was calculated and the distance between the stopped vehicle and the target was measured for each test. The PCS detected the hazard in all tests. We found that when there was little or no driver input, the PCS stopped the vehicle autonomously in all but one test. Target radar size and contrast did not affect the speeds, distances or TTIs in these tests. In some tests, the PCS and ABS interacted in a way that increased the stopping distance. In a small number of tests, the PCS disengaged partway through its algorithm and returned control to the driver for reasons that we were unable to discern. This study provides some initial insights into the dynamic response of the Toyota PCS and identifies some factors that affect its performance.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-0533
Pages
9
Citation
Yang, M., Xing, P., Flynn, T., Tsuge, B. et al., "The Effect of Target Features on Toyota’s Autonomous Emergency Braking System," SAE Technical Paper 2018-01-0533, 2018, https://doi.org/10.4271/2018-01-0533.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0533
Content Type
Technical Paper
Language
English