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基于相关向量机的换道安全性评估

贾小龙 宋定波 王畅 山岩 何爱生 贾丙硕

交通信息与安全2018,Vol.36Issue(2):10-17,8.
交通信息与安全2018,Vol.36Issue(2):10-17,8.DOI:10.3963/j.issn.1674-4861.2018.02.002

基于相关向量机的换道安全性评估

A Safety Evaluation of Lane Change Based on Relevance Vector Machine

贾小龙 1宋定波 1王畅 1山岩 1何爱生 1贾丙硕1

作者信息

  • 1. 长安大学汽车学院 西安710064
  • 折叠

摘要

Abstract

The accuracy and reliability are the major problems that have existed in traditional of lane change warning algorithms.Therefore,a test vehicle is set by using millimeter-wave radar,AWS vision sensor,vehicle gyroscope and other devices aiming at solving the above-mentioned problems.A field tests is conducted on highways and 19 subjects are recruited.Nearly 1 000 lane change samples are extracted from recorded driving test data.Based on a three-stage lane change trajectory model,the statistical value of yaw rate is regarded as the basis to determine radius of curvature in each stage.The upper limit for acceptable safety threshold is determined according to the yaw rate quantile when α=0.05.A series of control points are formed by analyzing lane change processes for which lasted more than 12s and the maximum value of lane change duration is selected as the benchmark.B-spline curve planning is adopted to determine the lower limit of the acceptable safety threshold.Parameters in lane change are estimated by Relevance Vector Machine(RVM),and 7th polynomial model is used to fit lane change trajectory.The area enclosed by the fitted trajectories and the upper(or lower)limit of the acceptable safety threshold is used as the warning parameters.The ratio is used as a warning parameter to evaluate safety of lane change.Actual data is used to verify this algorithm.The evaluation results of this algorithm can reflect actual safety level of the lane change,and have strong correlation with operating behaviors of drivers.

关键词

交通安全/换道安全/可接受安全域/相关向量机

Key words

traffic safety/lane change safety/acceptable safety domain/relevance vector machine

分类

交通工程

引用本文复制引用

贾小龙,宋定波,王畅,山岩,何爱生,贾丙硕..基于相关向量机的换道安全性评估[J].交通信息与安全,2018,36(2):10-17,8.

基金项目

国家自然科学基金项目(批准号:61473046,51775053)、长江学者和创新团队发展计划项目(批准号:IRT_17R95)、中央高校基本科研业务费专项资金项目(批准号:310822151028,310822172001)资助 (批准号:61473046,51775053)

交通信息与安全

OA北大核心CSCDCSTPCD

1674-4861

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