Browse > Article
http://dx.doi.org/10.12815/kits.2020.19.2.74

Development and Evaluation of Road Safety Information Contents Using Commercial Vehicle Sensor Data : Based on Analyzing Traffic Simulation DATA  

Park, Subin (Dept. of Transportation and Logistics Eng., Hanyang University)
Oh, Cheol (Dept. of Transportation and Logistics Eng., Hanyang University)
Ko, Jieun (Dept. of Transportation and Logistics Eng., Hanyang University)
Yang, Choongheon (Dept. of Infrastructure Safety Research Future Infrastructure Research Center, Korea Institute of Civil Engineering and Building Technology)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.19, no.2, 2020 , pp. 74-88 More about this Journal
Abstract
A Cooperative Intelligent Transportation System (CITS) provides useful information on upcoming hazards in order to prevent vehicle collisions. In addition, the availability of individual vehicle travel information obtained from the CITS infrastructure allows us to identify the level of road safety in real time and based on analysis of the indicators representing the crash potential. This study proposes a methodology to derive road safety content, and presents evaluation results for its applicability in practice, based on simulation experiments. Both jerk and Stopping Distance Index (SDI) were adopted as safety indicators and were further applied to derive road section safety information. Microscopic simulation results with VISSIM show that 5% and 20% samples of jerk and SDI are sufficient to represent road safety characteristics for all vehicles. It is expected that the outcome of this study will be fundamental to developing a novel and valuable system to monitor the level of road safety in real time.
Keywords
Commercial vehicle; Vehicle safety information; Road safety information; Traffic simulation;
Citations & Related Records
Times Cited By KSCI : 12  (Citation Analysis)
연도 인용수 순위
1 Wali B., Khattak A. J. and Karnowski T.(2019), "Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events-Concept of event-based driving volatility," Accident Analysis & Prevention, vol. 132, 105277, https://doi.org/10.1016/j.aap.2019.105277.
2 Wu K. F. and Jovanis P. P.(2013), "Defining and screening crash surrogate events using naturalistic driving data," Accident Analysis and Prevention, vol. 61, pp.10-22, https://doi.org/10.1016/j.aap.2012.10.004.   DOI
3 Zaki M. H., Sayed T. and Shaaban K.(2014), "Use of Drivers' Jerk Profiles in Computer Vision-Based Traffic Safety Evaluations," Transportation Research Record, vol. 2434, no. 1, pp.103-112, https://doi.org/10.3141/2434-13.   DOI
4 Allen B. L., Shin B. T. and Cooper P. J.(1978), "Analysis of traffic conflicts and collisions," Transportation Research Record: Journal of the Transportation Research Board, vol. 667, No. HS-025 846.
5 Cooper D. F., Ferguson N. and Traffic studies at T-Junctions.(1976), "A conflict simulation Record," Transportation Research Record: Traffic Engineering & Control, 17.
6 Bagdadi O. and Varhelyi A.(2013), "Development of a method for detecting jerks in safety critical events," Accident Analysis & Prevention, vol. 50, pp.83-91, https://doi.org/10.1016/j.aap.2012.03.032.   DOI
7 Cho W. H. and Choi E. M.(2015), "Rural Traffic Map Coverage Extension using DTG Big Data Processing," Journal of Information Technology and Architecture, vol. 12, no. 1, pp.51-57.
8 Choi S. and Oh C.(2016), "Proactive Strategy for Variable Speed Limit Operations on Freeways Under Foggy Weather Conditions," Transportation Research Record: Journal of the Transportation Research Board, vol. 2551, pp.29-36, doi:10.3141/2551-04.   DOI
9 Hayward J.(1971), Near misses as a measure of safety at urban intersections, Pennsylvania Transportation and Traffic Safety Center.
10 Jo Y., Oh C., Ko J., Kim Y. and Park J.(2019), "A Methodology for Evaluating Real-time Crash Risks in Driving Big Data Era," Journal of Korean Society of Transportation, vol. 37, no. 4, pp.350-364, https://doi.org/10.7470/jkst.2019.37.4.350.
11 Kang J. G., Kim Y. W. and Jun M. S.(2015), "Real-time Dangerous Driving Behavior Analysis Utilizing the Digital Tachograph and Smartphone," Journal of the Korea Society of Computer and Information, vol. 20, no. 12, pp.37-44, https://doi.org/10.9708/JKSCI.2015.20.12.037.   DOI
12 Kim J. and Kum K.(2016), "Development for City Bus Dirver's Accident Occurrence Prediction Model Based on Digital Tachometer Records," The Journal of The Korea Institute of Intelligent Transport Systems, vol. 15, no. 1, pp.1-15, https://doi.org/10.12815/kits.2016.15.1.001.   DOI
13 MOLIT, Ministry of land, Infrastructure and Transport(2013), Rules for Standard of Structure and Facilities of the Road (Explanation and Guideline).
14 Kim Y. W. and Kang J. G.(2015), "Implementation of Real-Time Dangerous Driving Behavior Analysis Utilizing the Digital Tachograph," Journal of The Korea Society of Computer and Information, vol. 20, no. 2, pp.55-62. https://doi.org/10.9708/JKSCI.2015.20.2.055.   DOI
15 Kim Y., Oh C., Choe B. and Choi S.(2018). "Development of a Methodology for Detecting Intentional Aggressive Driving Events Using Multi-agent Driving Simulations," Journal of Korean Society of Transportation, vol. 36, no. 1, pp.51-65, https://doi.org/10.7470/jkst.2018.36.1.051.
16 Lee S. J. and Lee C.(2012), "Short-term impact analysis of dtg installation for commercial vehicles," The Journal of The Korea Institute of Intelligent Transport Systems, vol. 11, no. 6, pp.49-59.   DOI
17 Nygard M.(1999), A Method for Analysing Traffic Safety with Help of Speed Profiles, Tampere University of Technology.
18 Oh C., Oh J. and Min J.(2009), "Real-Time Detection of Hazardous Traffic Events on Freeways," Transportation Research Record: Journal of the Transportation Research Board, vol. 2129, no. 1, pp.35-44, https://doi.org/10.3141/2129-05.   DOI
19 Oh C., Park S. and Ritchie S. G.(2006), "A method for identifying rear-end collision risks using inductive loop detectors," Accident Analysis & Prevention, vol. 38, no. 2, pp.295-301. https://doi.org/10.1016/j.aap.2005.09.009.   DOI
20 Oh M. S., Park H. J., Oh C. and Park S. M.(2018), "Analysis of Rear-end Collision Risks Using Weigh-in-Motion Data," The Journal of The Korea Institute of Intelligent Transport Systems, vol. 17, no. 2, pp.152-167, https://doi.org/10.12815/kits.2018.17.2.152.
21 Park H., Oh C., Moon J. and Kim S.(2018), "Development of a lane change risk index using vehicle trajectory data," Accident Analysis & Prevention, vol. 110, pp.1-8, https://doi.org/10.1016/j.aap.2017.10.015.   DOI
22 Park H., Oh C. and Moon J.(2017), "Evaluation of Freeway Mobile Work Zone Safety using Driving Simulations," The Journal of The Korea Institute of Intelligent Transport Systems, vol. 16, no. 6, pp.124-140, https://doi.org/10.12815/kits.2017.16.6.124.
23 Park H., Oh C. and Moon J.(2018), "Real-Time Estimation of Lane Change Risks Based on the Analysis of Individual Vehicle Interactions," Transportation Research Record: Journal of the Transportation Research Board, 036119811879034. doi:10.1177/0361198118790346.
24 Mclaughlim S, B., Hankey J. M. and Dingus T. A.(2008), "A method for evaluation collision avoidance systems using naturalistic driving data," Accident Analysis and Prevention, vol. 40, no. 1, pp.8-16, https://doi.org/10.1016/j.aap.2007.03.016.   DOI
25 Park J. Y. and Kim D. G.(2018), "Identifying the effects of advanced warning devices on the driving behaviors of commercial vehicle drivers," International Journal of Highway Engineering, vol. 20, no. 1, pp.137-146, https://doi.org/10.7855/ijhe.2018.20.1.137.
26 Seok J. S.(2014), "The Idea about Using Digital Tachograph Data for Improve the Urban Road Traffic Safety," Transportation Technology and Policy, vol. 11, no. 5, pp.52-61.
27 The Korea Transport Institute and Intelligent Transport Society of Korea(2013), Research on C-ITS technology trends and research on domestic adoption plans.
28 Traffic Accident Analysis System (TAAS), http://taas.koroad.or.kr/, 2020.03.01.