Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic

被引：4
|
作者：
Gonzalez, Leonardo [1 ,2 ]
Marti, Enrique [1 ]
Calvo, Isidro [2 ]
Ruiz, Alejandra [1 ]
Perez, Joshue [1 ]
机构：
[1] Tecnalia Res & Innovat, Derio, Spain
[2] Univ Basque Country, Vitoria, Spain
来源：
COMPUTER SAFETY, RELIABILITY, AND SECURITY, SAFECOMP 2018 | 2018年 / 11094卷
基金：
欧盟地平线“2020”;
关键词：
Automated vehicles; Collision avoidance; Fuzzy logic; Time-to-collision; Driving behavior;
D O I：
10.1007/978-3-319-99229-7_24
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
As vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen.
引用
收藏
页码：278 / 289
页数：12
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