A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles

A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles

Based on the 64-line lidar sensor, an object detection and classification algorithm with both effectiveness and real time is proposed. Firstly, a multifeature and multilayer lidar points map is used to separate the road, obstacle, and suspension object. Then, obstacle grids are clustered by a grid-c...

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Main Authors: Hai Wang, Xinyu Lou, Yingfeng Cai, Long Chen
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Scientific Programming
Online Access:http://dx.doi.org/10.1155/2018/6385104
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spelling doaj-622e06e757a34d8ab6cd3a8ff7fc29152021-07-02T08:47:37ZengHindawi LimitedScientific Programming1058-92441875-919X2018-01-01201810.1155/2018/63851046385104A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent VehiclesHai Wang0Xinyu Lou1Yingfeng Cai2Long Chen3Institute of Automotive Engineering, Jiangsu University, Zhenjiang 212013, ChinaInstitute of Automotive Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaBased on the 64-line lidar sensor, an object detection and classification algorithm with both effectiveness and real time is proposed. Firstly, a multifeature and multilayer lidar points map is used to separate the road, obstacle, and suspension object. Then, obstacle grids are clustered by a grid-clustering algorithm with dynamic distance threshold. After that, by combining the motion state information of two adjacent frames, the clustering results are corrected. Finally, the SVM classifier is used to classify obstacles with clustered object position and attitude features. The good accuracy and real-time performance of the algorithm are proved by experiments, and it can meet the real-time requirements of the intelligent vehicles.http://dx.doi.org/10.1155/2018/6385104
collection DOAJ
language English
format Article
sources DOAJ
author Hai Wang
Xinyu Lou
Yingfeng Cai
Long Chen
spellingShingle Hai Wang
Xinyu Lou
Yingfeng Cai
Long Chen
A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles
Scientific Programming
author_facet Hai Wang
Xinyu Lou
Yingfeng Cai
Long Chen
author_sort Hai Wang
title A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles
title_short A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles
title_full A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles
title_fullStr A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles
title_full_unstemmed A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles
title_sort 64-line lidar-based road obstacle sensing algorithm for intelligent vehicles
publisher Hindawi Limited
series Scientific Programming
issn 1058-9244
1875-919X
publishDate 2018-01-01
description Based on the 64-line lidar sensor, an object detection and classification algorithm with both effectiveness and real time is proposed. Firstly, a multifeature and multilayer lidar points map is used to separate the road, obstacle, and suspension object. Then, obstacle grids are clustered by a grid-clustering algorithm with dynamic distance threshold. After that, by combining the motion state information of two adjacent frames, the clustering results are corrected. Finally, the SVM classifier is used to classify obstacles with clustered object position and attitude features. The good accuracy and real-time performance of the algorithm are proved by experiments, and it can meet the real-time requirements of the intelligent vehicles.
url http://dx.doi.org/10.1155/2018/6385104
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AT yingfengcai a64linelidarbasedroadobstaclesensingalgorithmforintelligentvehicles
AT longchen a64linelidarbasedroadobstaclesensingalgorithmforintelligentvehicles
AT haiwang 64linelidarbasedroadobstaclesensingalgorithmforintelligentvehicles
AT xinyulou 64linelidarbasedroadobstaclesensingalgorithmforintelligentvehicles
AT yingfengcai 64linelidarbasedroadobstaclesensingalgorithmforintelligentvehicles
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