An Analysis of Highway-traffic Safety Based on Dynamic Risk Saturation
-
摘要:
为了反映高速公路运营安全状况,提出了动态风险饱和度理论,构建了动态风险饱和度模型和计算方法。依据路段不同交通饱和度下车辆的驾驶行为,以路段交通安全为约束,研究了跟车行驶和换道行驶2种驾驶状态下,考虑车速变化及雾天等特殊天气条件影响的路段平均最小安全车头时距计算方法,利用建立的安全车头时距与安全流量之间的转换关系,得到不同驾驶状态下的路段安全流量。在不同车辆驾驶状态切换阈值下,计算路段实际交通流量与路段安全流量的比值得到高速公路路段动态风险饱和度值。以G3高速公路某改扩建路段所在路网为例进行验证,计算得到了路网中各路段不同切换阈值下的动态风险饱和度值。动态风险饱和度随着交通饱和度的增大,呈现稳定的先增大后减小的规律,且在换道行驶状态时达到最大,在跟车行驶状态时开始下降,与现有交通安全状态分析相吻合。相较于交通饱和度,动态风险饱和度更能够反应出高速公路路段交通安全动态变化的规律。
Abstract:The study proposes a dynamic risk saturation theory and constructs a dynamic risk saturation model and a calculation method to reflect the safety operation status of highways. On the basis of the driving behavior of vehicles under different traffic saturation of the road section and the constraint of keeping the road section traffic safety, the calculation method of the average minimum safe headway of the road section takes into account the influence of vehicle speed changes and special weather conditions, such as vehicle speed and foggy in the two driving states of car-following and lane-changing. The established conversion relationship between safe headway and safe flow, is used to obtain the safe flow of road sections under different driving conditions. Under the switching thresholds of different driving states, the ratio of the actual traffic flow to the safe flow of the road section is calculated to obtain the dynamic risk saturation values for road sections. Taking a road network of a reconstructed and expanded section of the G3 expressway as a case study, the study calculates the dynamic risk saturation values of each section in the road network under different switching thresholds. It can be concluded that with the traffic saturation increases, the dynamic risk saturation shows a steady pattern of first increasing and then decreasing. It reaches the maximum in lane-changing driving state and starts to decrease in the following driving state, which is consistent with the existing analysis of traffic safety states. Compared with the factor of traffic saturation, dynamic risk saturation can better indicate the pattern of dynamic changes in traffic safety of highway sections.
-
Key words:
- traffic safety /
- highways /
- dynamic risk saturation /
- safe flow /
- following driving state /
- lane-change driving state
-
表 1 高速公路路网各路段动态风险饱和度
Table 1. Dynamic-risk saturation of each section in the expressway network
编号 起止段 车道数 设计速度/(km/h) 高峰小时交通量/(pcu/h) 基本通行能力/(pcu/h) 交通饱和度 1 G~A 4 120 1 422 2 200 0.65 2 B~E 4 120 1 054 2 200 0.48 3 E~F 4 120 996 2 200 0.45 4 C~D 8 120 1 800 2 200 0.82 5 B~H 4 100 478 2 100 0.23 6 H~I 4 100 478 2 100 0.23 7 I~J 4 100 476 2 100 0.23 8 J~K 4 100 473 2 100 0.23 9 K~L 4 100 542 2 100 0.26 表 2 不同流量下高速公路的车速值
Table 2. Speed value of expressway under different traffic
流量(pcu/h) 采用的车速值/(km/h) V85%车速 V15%车速 800 110 100 1 750 95 85 2 100 80 70 表 3 α, β 取值
Table 3. Values of α and β
序号 α β a 0.4 0.75 b 0.4 0.9 c 0.55 0.75 d 0.55 0.9 表 4 无特殊情况高速公路改扩建路网各路段风险饱和度
Table 4. Risk saturation of each section of the highway network for reconstruction and expansion without special circumstances
编号 起止段 交通饱和度 动态风险饱和度 a b c d 1 C~D 0.82 0.66 0.66 0.48 0.48 2 G~A 0.65 0.89 0.89 0.89 0.89 3 B~E 0.48 1.19 1.37 1.19 1.37 4 E~F 0.45 1.01 1.01 1.01 1.01 5 K~L 0.26 0.26 0.26 0.26 0.26 6 B~H 0.23 0.23 0.23 0.23 0.23 7 H~I 0.23 0.23 0.23 0.23 0.23 8 I~J 0.23 0.23 0.23 0.23 0.23 9 J~K 0.23 0.23 0.23 0.23 0.23 -
[1] 张晨琛, 贾利民. 高速公路网运营风险分析方法研究[J]. 中国安全科学学报, 2016, 26 (9): 135-139. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201609026.htmZHANG Chenchen, JIA Limin. Research on method for assessing expressway network operational risk[J]. China Safety Science Journal, 2016, 26 (9): 135-139. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201609026.htm [2] FRANCESCA L T, LORENZO D, ALESSANDRO N. Effects of stationary work zones on motorway crashes[J]. Safety Science, 2017 (92): 148-159. [3] 吴付威, 山岩, 付锐, 等. 高速公路干扰跟车时驾驶人注意力分配特性[J]. 中国安全科学学报, 2017, 27 (1): 25-29. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201701005.htmWU Fuwei, SHAN Yan, FU Rui, et al. Drivers' attention distribution characteristics in cutting-in process on freeway[J]. China Safety Science Journal, 2017, 27 (1): 25-29. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201701005.htm [4] 戴英, 罗云, 裴晶晶. 基于风险分级的道路限速设计方法研究[J]. 中国安全生产科学技术, 2017, 13 (8): 181-187. https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK201708030.htmDAI Ying, LUO Yun, PEI Jingjing, et al. Research on design method of road speed limit based on risk grading[J]. Journal of Safety Science and Technology, 2017, 13(8): 181-187. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK201708030.htm [5] 刘维民. 基于敏感性分析的改扩建高速公路安全性评价[J]. 公路, 2015, 60 (2): 131-138. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201502030.htmLIU Weimin. Safety evaluation of reconstructed and widened expressway based on sensitivity analysis[J]. Highway, 2015, 60 (2): 131-138. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201502030.htm [6] 杨奎, 余荣杰, 王雪松. 基于车道集计交通流数据的事故风险评估分析[J]. 同济大学学报(自然科学版), 2016, 44(10): 1567-1572. doi: 10.11908/j.issn.0253-374x.2016.10.014YANG Kui, YU Rongjie, WANG Xuesong. Application of aggregated lane traffic data from dualloop detector to crash risk evaluation[J]. Journal of Tongji University(Natural Science), 2016, 44 (10): 1567-1572. (in Chinese) doi: 10.11908/j.issn.0253-374x.2016.10.014 [7] 胡功宏, 林雨, 高建平. 高速公路交通流实时安全性评价[J]. 安全与环境学报, 2015, 15 (1): 57-63. https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201501014.htmHU Gonghong, LIN Yu, GAO Jianping. Real-time safety probability evaluation of the expressway traffic flow[J]. Journal of Safety and Environment, 2015, 15 (1): 57-63. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201501014.htm [8] 张存保, 彭汉辉, 张珊, 等. 雾天高速公路实时交通安全状态评价方法[J]. 中国安全科学学报, 2017, 27 (4): 110-115. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201704021.htmZHANG Cunbao, PENG Hanhui, ZHANG Shan, et al. Real-time traffic safety evaluation method for freeway in fog[J]. China Safety Science Journal, 2017, 27(4): 110-115. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201704021.htm [9] 孔令铮. 交通事故致因中的人为因素分析[J]. 中国安全科学学报, 2013, 23 (1): 28-34. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201301006.htmKONG Lingzheng. Human factors in causation of traffic accidents[J]. China Safety Science Journal, 2013, 23(1): 28-34. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201301006.htm [10] 孙剑, 孙杰. 城市快速路实时交通流运行安全主动风险评估[J]. 同济大学学报(自然科学版), 2013, 42 (6): 873-879. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201406008.htmSUN Jian, SUN Jie. Proactive assessed of real-time traffic flow accident risk on urban expressway[J]. Journal of Tongji University(Natural Science), 2013, 42 (6): 873-879. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201406008.htm [11] 吴焱, 钱振邦, 王建军. 高速公路交通安全风险评价与敏感性分析[J]. 长安大学学报(自然科学版), 2014, 34 (4), 134-141. doi: 10.3969/j.issn.1671-8879.2014.04.021WU Yan, QIAN Zhenbang, WANG Jianju. 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) doi: 10.3969/j.issn.1671-8879.2014.04.021 [12] 朱博雅, 符锌砂, 王晓飞. 基于模糊综合评判的高速公路改扩建工程作业区域交通安全评价[J]. 公路, 2018, 63(2): 249-254. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201802048.htmZHU Boya, FU Xinsha, WANG Xiaofei. Traffic safety evaluation in work zones of highway reconstruction and extension based on fuzzy comprehensive evaluation[J]. Highway, 2018, 63 (2): 249-254. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201802048.htm [13] 蒋锐, 郭忠印. 基于动态归类技术的交通流实时运营风险评价[J]. 同济大学学报(自然科学版), 2011, 39 (1): 57-61. doi: 10.3969/j.issn.0253-374x.2011.01.011JIANG Rui, GUO Zhongyin. Dynamic-classified method-based real-time risk audit of traffic flow[J]. Journal of Tongji University(Natural Science), 2011, 39 (1): 57-61. (in Chinese) doi: 10.3969/j.issn.0253-374x.2011.01.011 [14] 陈玲玲, 李凤, 杨家其, 等. 多因素影响下高速公路突发事件安全预警模型[J]. 中国安全科学学报, 2018, 28 (1): 50-55. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201801009.htmCHEN Lingling, LI Feng, YANG Jiaqi, et al. Safety early warning model of freeway emergency influenced by multiple factors[J]. China Safety Science Journal, 2018, 28(1): 50-55. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201801009.htm [15] 李曌, 王金安. 高速公路工程道路交通安全评价研究及工程应用[J]. 中国安全生产科学技术, 2011, 7 (7): 120-124. https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK201107026.htmLI Zhao, WANG Jinan. Study on evaluation of expressway traffic safety and engineering application[J]. Journal of Safety Science and Technology, 2011, 7 (7): 120-124. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK201107026.htm [16] MENG Q, WENG J. Evaluation of rear-end crash risk at work zone using work zone traffic data[J]. Accident Analysis & Prevention, 2011, 43 (4): 1291-1300. [17] DAVIS A, DORY E, LEE G P. Fatal fccidents in night-time vs day-time highway construction work zones[J]. Journal of Safety Research, 2007, 38 (4): 399-405. doi: 10.1016/j.jsr.2007.04.001 [18] 蒋锐, 郭忠印, 李振楠. 恶劣天气条件下车辆换车道的安全模型[J]. 同济大学学报(自然科学版), 2011, 39(4): 529-533. doi: 10.3969/j.issn.0253-374x.2011.04.011JIANG Rui, GUO Zhongyin, LI Zhennan. Lane-changing safety model for deteriorative weather[J]. Journal of Tongji University (Natural Science), 2011, 39 (4): 529-533. (in Chinese) doi: 10.3969/j.issn.0253-374x.2011.04.011 [19] 杜艳爽. 公路改扩建工程危险源辨识及安全评估技术研究[D]. 天津: 河北工业大学, 2017.DU Yanshuang. Study on hazard identification and safety assessment technology for highway reconstruction and extension project[D]. Tianjin: Hebei University of Technology, 2017. (in Chinese) [20] TAKAHASHI H, KAMEOKA H, WATANABE T, et al. Mitigation of expressway traffic congestion through TDM with toll discount[J]. Intelligent Transport Systems, IET, 2008, (41): 4238-4249.