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. 2017 Sep 8;12(9):e0184564.
doi: 10.1371/journal.pone.0184564. eCollection 2017.

The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation

Junhua Wang  1 , Yumeng Kong  1 , Ting Fu  2 , Joshua Stipancic  2
Affiliations

The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation

Junhua Wang et al. PLoS One. .

Abstract

This paper presents the use of the Aimsun microsimulation program to simulate vehicle violating behaviors and observe their impact on road traffic crash risk. Plugins for violations of speeding, slow driving, and abrupt stopping were developed using Aimsun's API and SDK module. A safety analysis plugin for investigating probability of rear-end collisions was developed, and a method for analyzing collision risk is proposed. A Fuzzy C-mean Clustering algorithm was developed to identify high risk states in different road segments over time. Results of a simulation experiment based on the G15 Expressway in Shanghai showed that abrupt stopping had the greatest impact on increasing collision risk, and the impact of violations increased with traffic volume. The methodology allows for the evaluation and monitoring of risks, alerting of road hazards, and identification of hotspots, and could be applied to the operations of existing facilities or planning of future ones.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Vehicle collision distance-time-velocity diagram.
Fig 2
Fig 2. Methodology framework.
Fig 3
Fig 3. API module application flowchart.
Fig 4
Fig 4. SDK module application flowchart.
Fig 5
Fig 5. Descriptions of distance-time-velocity relationship in the four situations in the rear-end collision model.
Fig 6
Fig 6. Aimsun interface of the simulated section.
Fig 7
Fig 7. Largest cluster center value (VC) with different cluster number for different volume conditions.
Fig 8
Fig 8. Comparisons of different types of violation.
Fig 9
Fig 9. Influence of violation under different traffic volume.
Fig 10
Fig 10. Space-time diagram under different traffic condition with no violations.
Fig 11
Fig 11. Space-time diagram of traffic flow risk for different violation types.
See this image and copyright information in PMC

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