A Method for Quantitatively Analyzing Risks Associated with the Operation of Urban Buses Considering Chained Conflicts

LI Xiying; LIANG Jingru; HAO Tenglong

doi:10.3963/j.jssn.1674-4861.2022.03.003

Volume 40 Issue 3

Jun. 2022

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Article Navigation > Journal of Transport Information and Safety > 2022 > 40(3): 19-29

LI Xiying, LIANG Jingru, HAO Tenglong. A Method for Quantitatively Analyzing Risks Associated with the Operation of Urban Buses Considering Chained Conflicts[J]. Journal of Transport Information and Safety, 2022, 40(3): 19-29. doi: 10.3963/j.jssn.1674-4861.2022.03.003

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LI Xiying, LIANG Jingru, HAO Tenglong. A Method for Quantitatively Analyzing Risks Associated with the Operation of Urban Buses Considering Chained Conflicts[J]. Journal of Transport Information and Safety, 2022, 40(3): 19-29. doi: 10.3963/j.jssn.1674-4861.2022.03.003

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A Method for Quantitatively Analyzing Risks Associated with the Operation of Urban Buses Considering Chained Conflicts

doi: 10.3963/j.jssn.1674-4861.2022.03.003

LI Xiying^{1, 2, 3
,
,},
LIANG Jingru^{1, 2, 3},
HAO Tenglong^{1, 2, 3}

1.
School of Intelligent Systems Engineering, Sun Yat-Sen University, Guangzhou 510006, China
2.
Guangdong Provincial Key Laboratory of Intelligent Transportation System, Sun Yat-Sen University, Guangzhou 510006, China
3.
Key Laboratory of Video and Image Intelligent Analysis and Application Technology of Ministry of Public Security, Sun Yat-Sen University, Guangzhou 510006, China

Received Date: 2022-01-11
Available Online: 2022-07-25

Abstract

Abstract

A quantitative method for analyzing risks associated with the operation of buses in mixed traffic environment is studied by extracting data about traffic conflict and identifying a set of chain-conflicts. Regarding data collection, aerial video data are adopted based on which features of objects are extracted using YOLOv4 network. In this way, the trajectories with accurate attributes for buses and other related vehicles can be obtained. Regarding the identification of vehicle conflicts, the relative locations between pairs of vehicles which are likely to collide laterally in different lanes are set up as constraints. Based on the classic car-following model, the dynamic relationship of vehicle pairs in adjacent lanes is studied and added. With this, the classic time-to-collision(TTC)model is extended to a two-dimensional TTC model, which can identify lateral conflicts as well. Next, according to the Stimulus-Re-sponse Theory, the temporal and spatial scope caused by each conflicting vehicle who continuously disturb regional traffic is calibrated to study interrelationships between conflicted vehicles, and a time-series conflict tree model is established. With this, chained conflicts can be identified and the causal relationship between continuous risks can be traced using the conflict tree model. The risks of urban buses under different traffic settings are quantified from the following three aspects: ①the frequency of the conflicts is analyzed based on the two-dimensional TTC model; ②on this basis, the severity of conflicts is analyzed combined with cumulative frequency method; ③the probability and scope of conflicts are analyzed through ratio of chain conflicts and the length of conflict tree. Aerial video data of Guangzhou Bridge Road are collected for a case study. The results show that urban buses in frequently congested sections have high conflict risks, which reveal have high rate of severity and regional aggregation. The conflict frequency of buses in congested traffic flow exceeds 9 times per vehicle per minute. The average rate of serious conflicts of buses is 33.39%, which is much higher than the corresponding rate of regular passenger vehicles(i.e., 16.61%). The rate of regional chain-conflicts caused by buses is 30.75%, which is twice than that of cars(i.e., 14.67%)
- traffic safety,
- urban bus,
- traffic safety risk analysis,
- chain conflict recognition,
- traffic conflict technology

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References(24)

References

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