Safety evaluation method of freeway segment based on accident data and safety service level

MENG Xiang-hai; LI Xin; ZHENG Lai

Volume 14 Issue 6

Turn off MathJax

Article Contents

Article Navigation > Journal of Traffic and Transportation Engineering > 2014 > 14(6): 83-91

Next Previous

MENG Xiang-hai, LI Xin, ZHENG Lai. Safety evaluation method of freeway segment based on accident data and safety service level[J]. Journal of Traffic and Transportation Engineering, 2014, 14(6): 83-91.

Citation:

MENG Xiang-hai, LI Xin, ZHENG Lai. Safety evaluation method of freeway segment based on accident data and safety service level[J]. Journal of Traffic and Transportation Engineering, 2014, 14(6): 83-91.

Citation:

PDF( 951 KB)

Safety evaluation method of freeway segment based on accident data and safety service level

School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, Heilongjiang, China

More Information

Author Bio:
MENG Xiang-hai (1969-), male, professor, PhD, +86-451-86282116, mengxianghai100@126.com
Received Date: 2014-07-07
Publish Date: 2014-12-25

Abstract

Abstract

The basic division method of freeway segment was analyzed, the unequal-length division method of dynamic clustering segment based on the concentration and dispersion degrees of accident point was put forward.The accident prediction model was calibrated based on negative binomial distribution, the safety evaluation method of freeway segment based on negative binomial distribution was proposed.The concept of safety service level was introduced, the classification standard was determined, the safety evaluation method of freeway segment based on safety service level was proposed, and the example verification was carried out.Verification result indicates that when the 109 segments of Jingzhu Freeway are evaluated by using the two methods respectively, the 57.8% of segments have the same results, the segment amounts of safety conditions in great, good, normal, poor are 5, 63, 36 and 5 respectively by using the safety evaluation method based on negative binomial distribution, while the segment amounts of safety conditions in great, good, normal, poor are 1, 64, 26 and 18 respectively by using the safety evaluation method bassed on safety service level.The evaluation result of safety evaluationmethod based on negative binomial distribution is more in line with freeway actual safety situation.The safety evaluation method based on negative binomial distribution considers traffic volume and geometric alignment, and is more suitable for the freeway with complex geometric alignment conditions.The safety evaluation method based on safety service level considers traffic volume and accident frequency, and is more suitable for the freeway with better geometric alignment conditions..
- traffic safety,
- freeway,
- safety evaluation,
- segment division,
- dynamic cluster analysis,
- negative binomial distribution,
- safety service level

FullText(HTML)

References(20)

References

[1]	HAUER E, KONONOV J, ALLERY B, et al. Screening the road network for sites with promise[J]. Transportation Research Record, 2002 (1784): 27-32.
[2]	MENG Xiang-hai, LI Mei, MAI Qiang, et al. Research on identification of black spot and accident inducing factor for freeway[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11 (1): 114-120. (in Chinese). doi: 10.3969/j.issn.1009-6744.2011.01.019
[3]	HU Jiang-bi, WANG Wei-li, WANG Jian. Research on classification of various combined alignment section on expressway[J]. China Journal of Highway and Transport, 2010, 23 (S): 53-57. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL2010S1011.htm
[4]	AHMED M, HUANG H, ABDEL-ATY M, et al. Exploring a Bayesian hierarchical approach for developing safety performance functions for a mountainous freeway[J]. Accident Analysis and Prevention, 2011, 43 (4): 1581-1589. doi: 10.1016/j.aap.2011.03.021
[5]	CHEN Bi-wu, SHI Bao-lin, LEI Mao-jin. Traffic safety assessment for expressway based on matter element model[J]. Journal of Chang'an University: Social Science Edition, 2008, 10 (4): 20-24. (in Chinese). doi: 10.3969/j.issn.1671-6248.2008.04.005
[6]	MENG Xiang-hai, SHENG Hong-fei, CHEN Tian-en. Essence and an approach to identify the hazardous locations of urban arterial link based on BP artificial neural network[J]. Journal of Highway and Transportation Research and Development, 2008, 25 (3): 124-129. (in Chinese). doi: 10.3969/j.issn.1002-0268.2008.03.025
[7]	MENG Xiang-hai, HUANG Bao-an, SONG Chun-hua. Hazardous locations identification and causes analysis[J]. Journal of Transport Information and Safety, 2009, 27 (3): 108-111, 128. (in Chinese). doi: 10.3963/j.cn.42-1781.U.2009.03.028
[8]	ZHANG Chi, YANG Shao-wei, PAN Bing-hong, et al. Safety evaluation of expressway alignment based on spatial valid vision[J]. Journal of Highway and Transportation Research and Development, 2010, 27 (9): 132-137. (in Chinese). doi: 10.3969/j.issn.1002-0268.2010.09.024
[9]	MENG Xiang-hai, GUAN Zhi-qiang, ZHENG Lai. Safety evaluation of mountainous expressway based on geometric alignment indexes[J]. China Journal of Highway and Transport, 2011, 24 (2): 103-108. (in Chinese). doi: 10.3969/j.issn.1001-7372.2011.02.017
[10]	WU Yan, QIAN Zhen-bang, WANG Jian-jun, et al. Traffic safety risk assessment and sensitivity analysis on expressway[J]. Journal of Chang'an University: Natural Science Edition, 2014, 34 (4): 134-141. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201404022.htm
[11]	LIU Jian-bei, GUO Zhong-yin, HU Jiang-bi, et al. Safety evaluation method and standard of highway alignment design[J]. China Journal of Highway and Transport, 2010, 23 (S): 28-35. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL2010S1007.htm
[12]	DONG Cheng, ZOU Jing-rong, GAO Qiong, et al. Study on the highway alignment audit based on operating speed[J]. Highway Engineering, 2009, 34 (4): 64-67. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGL201305032.htm
[13]	FU Xin-sha, LONG Yu. Fuzzy synthetic evaluation of highway alignment safety[J]. Highway, 2009 (6): 88-92. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL200806023.htm
[14]	IVAN J N, WANG C, BERNARDO N R. Explaining two-lane highway crash rates using land use and hourly exposure[J]. Accident Analysis and Prevention, 2000, 32 (6): 787-795. doi: 10.1016/S0001-4575(99)00132-3
[15]	BERHANU G. Models relating traffic safety with road environment and traffic flows on arterial roads in Addis Ababa[J]. Accident Analysis and Prevention, 2004, 36 (5): 697-704. https://www.sciencedirect.com/science/article/pii/S0001457503000939
[16]	PARK E S, PARK J, LOMAX T J. A fully Bayesian multivariate approach to before-after safety evaluation[J]. Accident Analysis and Prevention, 2010, 42 (4): 1118-1127. https://www.sciencedirect.com/science/article/pii/S0001457509003406
[17]	QIN Xiao, IVAN J N, RAVISHANKER N, et al. Hierarchical Bayesian estimation of safety performance functions for two-lane highways using Markov chain Monte Carlo modeling[J]. Journal of Transportation Engineering, 2005, 131 (5): 345-351. doi: 10.1061/%28ASCE%290733-947X%282005%29131%3A5%28345%29
[18]	KONONOV J, ALLERY B K. Explicit consideration of safety in transportation planning and project scoping[J]. Transportation Research Record, 2004 (1897): 116-125. https://trid.trb.org/view.aspx?id=749628
[19]	ZHANG Lin, PREVEDOUROS P D. Signalized intersection level of service incorporating safety risk[J]. Transportation Research Record, 2003 (1852): 77-86. doi: 10.3141/1852-11
[20]	LU Jian, PAN Fu-quan, XIANG Qiao-jun. Level-of-safety service for safety performance evaluation of highway intersections[J]. Transportation Research Record, 2008 (2075): 24-33. https://trid.trb.org/view.aspx?id=848345