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Conference Paper
Highway Condition Analysis and Traffic Safety Monitoring System through Analysis of Time-Series Data from LiDAR-based Probe Vehicle
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- Authors
- Dohun Kim, Hongjin Kim, Sangjin Han, Wonjong Kim
- Issue Date
- 2023-10
- Citation
- International Conference on Systems, Man, and Cybernetics (SMC) 2023, pp.1-6
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Recently, various approaches have been developed for traffic analysis systems, ranging from Vehicle Detection Systems (VDS) to Mobile Detection Systems (MDS). However, VDS has limitations. For example, in actual driving situations such as intersections or exits, each lane may have different traffic conditions, revealing the limitations of traffic information provided by conventional VDS. In this paper, we propose a methodology to efficiently monitor the traffic condition and safety on the road by utilizing a LiDAR sensor installed on a vehicle to collect continuous traffic information about surrounding vehicles. To implement the Mobile Detection System (MDS), we collect point cloud data from LiDAR and detect the position and size of vehicles using a deep learning-based voxel-RCNN. We then convert the data into traffic information for analysis. Furthermore, we propose an efficient method for analyzing road hazards by introducing the MTTC method based on the TTC for hazard assessment. To evaluate the performance of the proposed method, we compare its reliability with that of conventional VDS and perform road hazards analysis using LiDAR-based probe vehicles with data collected directly from highways in Korea.
- KSP Keywords
- Condition analysis, Data collected, Hazards analysis, Intrusion detection system(IDS), Learning-based, LiDAR sensors, Monitoring system, Point Cloud Data, Probe vehicles, Road hazard, Safety Monitoring