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

页码：278 / 289

页数：12

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