城市道路网络特征对交通事故作用机理的研究进展

doi:10.18306/dlkxjz.2022.10.014

Abstract

Abstract:

With the rapid development of motor traffic, urban traffic safety problems are becoming increasingly serious. As a key factor influencing the characteristics of regional traffic flow and travel behavior, the characteristics of urban road network have an important impact on the frequency, type, and spatial distribution of regional traffic accidents. Based on the theoretical analysis of the relationship between urban built environment and traffic accidents, this article summarized the mechanism of impact of urban road network characteristics on traffic accidents from two aspects: road network patterns and geometric-topological characteristics. The potential mechanism of impact of urban road network characteristics on traffic accidents was analyzed by exploring the relationship between urban road network and travel behavior. Existing studies indicate that there are differences in spatial scale effects on the type, frequency, and severity of traffic accidents caused by road network patterns such as grid-iron, warped parallel, and loops-lollipops, as well as road network topology indicators such as centrality and connectivity. Furthermore, reasonable geometric characteristics of road network such as intersection density, road network density, and block density play an important role in improving traffic safety. Future research needs to further characterize the structure, function, and other characteristics of road network using complex network theory, and to provide in-depth analyses on the driving mechanism and non-linear effects of complex road network characteristics on traffic accidents from the perspective of travel behavior by controlling the effect of residential self-selection. Future research also needs to consider the potential interaction between road network characteristics and the built environment on traffic accidents.

Key words: traffic accident, road network, travel behavior, complex network

XIE Bo, XIAO Yangmou. Progress of research on the mechanism of impact of urban road network characteristics on traffic accidents[J].PROGRESS IN GEOGRAPHY, 2022, 41(10): 1956-1968.

Figures/Tables 7

Fig.1

Tab.1

Tab.2

Characteristics of road network topology

道路网络拓扑特征	指标理论内涵
接近中心性 (closeness centrality)	网络中某一节点与其他节点的邻近程度^[46],反映了道路网络中某点到其余各点的难易程度,即可达性
中间中心性 (betweenness centrality)	网络中某一节点或连线的重要性,反映了某条道路被穿行的可能性,即作为出行必经之路的潜力^[47]
连通性(α指数)	网络中实际圈数和最大圈数的比值,又称网状系数(meshedness coefficient),系数越大意味着路网的集聚性、成网性越强^[14]
连通性(β指数)	网络中连线数量与节点数量的比值,又称链节比(link-node ratio),用于度量道路网络中某一节点与其他节点的联系程度,即节点通达度^[48]
连通性(γ指数)	网络中的实际连线数与它可能存在的最大连线数之比^[48],值越接近于1,道路网络越接近最大平面网络
绕行性(绕行率)	网络中某对起止点之间的最短网络距离与欧几里得距离之比^[49],用于衡量道路网络通行效率
异配性 (disassortativity)	一个节点倾向于与具有不同节点度的其他节点相连^[50],这种特性被称为异配性,道路网络中体现为不同功能等级道路的衔接,常用洛伦兹曲线、基尼系数等进行量化^[51]
平均测地距离 (average geodesic distance)	网络中任意两个节点之间最短连接路径的边数的平均值^[52],值越小,表示任意节点之间的拓扑距离越小,道路网络的整体可达性越好^[53]
集聚系数 (clustering coefficient)	网络中节点的邻点之间也互为邻点的比例,即小集团结构的完美程度^[54],值越大,表示道路网络中相邻节点内部联系的紧密程度越高^[53],网络中所有节点集聚系数的平均值即为该网络的整体集聚系数
富人俱乐部指数 (rich-club coefficient)	道路网络中任一节点与富节点(节点度高的节点)连接的可能性^[55]

Tab.2

Tab.3

Tab.4

Fig.2

Fig.3

References 76

[1]	World Health Organization. Global status report on road safety 2018[M]. Geneva, Switzerland: WHO Press, 2018: 4-6.
[2]	国家统计局. 中国统计年鉴[M]. 北京: 中国统计出版社, 2020: 771.
	[National Bureau of Statistics. China statistical yearbook. Beijing, China: China Statistics Press, 2020: 771. ]
[3]	国家卫生健康委员会. 中国卫生健康统计年鉴[M]. 北京: 中国协和医科大学出版社, 2019: 286.
	[National Health Commission. China health statistical yearbook. Beijing, China: Peking Union Medical College Press, 2019: 286. ]
[4]	Naghavi M, Abajobir A A, Abbafati C, et al. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: A systematic analysis for the Global Burden of Disease Study 2016[J]. The Lancet, 2017, 390: 1151-1210. doi: 10.1016/S0140-6736(17)32152-9
[5]	王雪松, 游世凯. 基于多项罗吉特模型的路网形态判别[J]. 同济大学学报(自然科学版), 2014, 42(1): 64-70.
	[Wang Xuesong, You Shikai. Street patterns distinction based on logit model. Journal of Tongji University (Natural Science), 2014, 42(1): 64-70. ]
[6]	徐向远, 石飞, 徐建刚, 等. 西方城市街道模式与居民出行方式关系探析[J]. 现代城市研究, 2015(9): 118-125.
	[Xu Xiangyuan, Shi Fei, Xu Jiangang, et al. A study of the relationship between western city street pattern and traffic mode. Modern Urban Research, 2015(9): 118-125. ]
[7]	Luca D A. The mathematics of urban morphology[M]// Boeing G. The morphology and circuity of walkable and drivable street networks. Basel, Switzerland: Birkhäuser, 2019: 271-287.
[8]	Rifaat S, Tay R, Perez A, et al. Effects of neighborhood street patterns on traffic collision frequency[J]. Journal of Transportation Safety & Security, 2009, 1(4): 241-253.
[9]	Wang X S, Yuan J H, Schultz G G, et al. Investigating the safety impact of roadway network features of suburban arterials in Shanghai[J]. Accident Analysis & Prevention, 2018, 113: 137-148. doi: 10.1016/j.aap.2018.01.029
[10]	Rifaat S M, Tay R, de Barros A. Effect of street pattern on the severity of crashes involving vulnerable road users[J]. Accident Analysis & Prevention, 2011, 43(1): 276-283. doi: 10.1016/j.aap.2010.08.024
[11]	Marshall W E, Garrick N W. Does street network design affect traffic safety?[J]. Accident Analysis and Prevention, 2011, 43(3): 769-781. doi: 10.1016/j.aap.2010.10.024
[12]	Ewing R, Cervero R. Travel and the built environment[J]. Journal of the American Planning Association, 2010, 76(3): 265-294. doi: 10.1080/01944361003766766
[13]	Rifaat S M, Tay R. Effects of street patterns an injury risks in two-vehicle crashes[J]. Transportation Research Record, 2009, 2102(1): 61-67. doi: 10.3141/2102-08
[14]	Wang X S, Wu X W, Abdel-Aty M, et al. Investigation of road network features and safety performance[J]. Accident Analysis and Prevention, 2013, 56: 22-31. doi: 10.1016/j.aap.2013.02.026
[15]	Marshall W E, Garrick N W. Street network types and road safety: A study of 24 California cities[J]. Urban Design International, 2010, 15(3): 133-147. doi: 10.1057/udi.2009.31
[16]	Sun J, Lovegrove G. Comparing the road safety of neighbourhood development patterns: Traditional versus sustainable communities[J]. Canadian Journal of Civil Engineering, 2013, 40(1): 35-45. doi: 10.1139/cjce-2012-0002
[17]	Liu C H, Sharma A. Exploring spatio-temporal effects in traffic crash trend analysis[J]. Analytic Methods in Accident Research, 2017, 16: 104-116. doi: 10.1016/j.amar.2017.09.002
[18]	Adeyemi O J, Arif A A, Paul R. Exploring the relationship of rush hour period and fatal and non-fatal crash injuries in the U.S.: A systematic review and meta-analysis[J]. Accident Analysis & Prevention, 2021, 163: 106462. doi: 10.1016/j.aap.2021.106462. doi: 10.1016/j.aap.2021.106462
[19]	Zou W, Wang X K, Zhang D P. Truck crash severity in New York City: An investigation of the spatial and the time of day effects[J]. Accident Analysis and Prevention, 2017, 99: 249-261. doi: 10.1016/j.aap.2016.11.024
[20]	周素红, 郑重, 柳林. 城市交通消散期事故高峰现象及成因[J]. 地理科学, 2012, 32(6): 649-657. doi: 10.13249/j.cnki.sgs.2012.06.649
	[Zhou Suhong, Zheng Zhong, Liu Lin. Spatio-Temporal analysis of peak traffic accidents in the city of Huizhou. Scientia Geographica Sinica, 2012, 32(6): 649-657. ] doi: 10.13249/j.cnki.sgs.2012.06.649
[21]	Zeng Q, Huang H L. Bayesian spatial joint modeling of traffic crashes on an urban road network[J]. Accident Analysis & Prevention, 2014, 67: 105-112. doi: 10.1016/j.aap.2014.02.018
[22]	Marshall W E, Coppola N, Golombek Y. Urban clear zones, street trees, and road safety[J]. Research in Transportation Business and Management, 2018, 29: 136-143. doi: 10.1016/j.rtbm.2018.09.003
[23]	Saha D, Dumbaugh E, Merlin L A. A conceptual framework to understand the role of built environment on traffic safety[J]. Journal of Safety Research, 2020, 75: 41-50. doi: 10.1016/j.jsr.2020.07.004 pmid: 33334491
[24]	Azimian A, Dimitra Pyrialakou V, Lavrenz S, et al. Exploring the effects of area-level factors on traffic crash frequency by severity using multivariate space-time models[J]. Analytic Methods in Accident Research, 2021, 31: 100163. doi: 10.1016/j.amar.2021.100163. doi: 10.1016/j.amar.2021.100163
[25]	柳林, 宋广文, 周素红, 等. 城市空间结构对惠州市中心城区交通事故影响的时间差异分析[J]. 地理科学, 2015, 35(1): 75-83. doi: 10.13249/j.cnki.sgs.2015.01.75
	[Liu Lin, Song Guangwen, Zhou Suhong, et al. Temporally impact of urban structure on city traffic accidents in Huizhou. Scientia Geographica Sinica, 2015, 35(1): 75-83. ] doi: 10.13249/j.cnki.sgs.2015.01.75
[26]	Greenwald M J. The relationship between land use and intrazonal trip making behaviors: Evidence and implications[J]. Transportation Research Part D: Transport and Environment, 2006, 11(6): 432-446. doi: 10.1016/j.trd.2006.09.003
[27]	van Acker V, van Wee B, Witlox F. When transport geography meets social psychology: Toward a conceptual model of travel behaviour[J]. Transport Reviews, 2010, 30(2): 219-240. doi: 10.1080/01441640902943453
[28]	曹新宇. 社区建成环境和交通行为研究回顾与展望:以美国为鉴[J]. 国际城市规划, 2015, 30(4): 46-52.
	[Cao Xinyu.Examining the relationship between neighborhood built environment and travel behavior: A review from the US perspective. Urban Planning International, 2015, 30(4): 46-52. ]
[29]	Hanson C S, Noland R B, Brown C. The severity of pedestrian crashes: An analysis using Google Street View imagery[J]. Journal of Transport Geography, 2013, 33: 42-53. doi: 10.1016/j.jtrangeo.2013.09.002
[30]	Cantillo V, Márquez L, Díaz C J. An exploratory analysis of factors associated with traffic crashes severity in Cartagena, Colombia[J]. Accident Analysis & Prevention, 2020, 146: 105749. doi: 10.1016/j.aap.2020.105749. doi: 10.1016/j.aap.2020.105749
[31]	Wang X S, Zhou Q Y, Yang J G, et al. Macro-level traffic safety analysis in Shanghai, China[J]. Accident Analysis & Prevention, 2019, 125: 249-256. doi: 10.1016/j.aap.2019.02.014
[32]	Chen P, Zhou J P. Effects of the built environment on automobile-involved pedestrian crash frequency and risk[J]. Journal of Transport & Health, 2016, 3(4): 448-456.
[33]	Ewing R, Hamidi S, Grace J B. Urban sprawl as a risk factor in motor vehicle crashes[J]. Urban Studies, 2016, 53(2): 247-266. doi: 10.1177/0042098014562331
[34]	Chen P, Shen Q. Built environment effects on cyclist injury severity in automobile-involved bicycle crashes[J]. Accident Analysis & Prevention, 2016, 86: 239-246. doi: 10.1016/j.aap.2015.11.002
[35]	Ewing R, Dumbaugh E. The built environment and traffic safety: A review of empirical evidence[J]. Journal of Planning Literature, 2009, 23(4): 347-367. doi: 10.1177/0885412209335553
[36]	Saha D, Dumbaugh E. Use of a model-based gradient boosting framework to assess spatial and non-linear effects of variables on pedestrian crash frequency at macro-level[J]. Journal of Transportation Safety & Security, 2022, 14(8): 1419-1450.
[37]	Ding C, Chen P, Jiao J F. Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach[J]. Accident Analysis & Prevention, 2018, 112: 116-126. doi: 10.1016/j.aap.2017.12.026
[38]	An R, Tong Z M, Ding Y M, et al. Examining non-linear built environment effects on injurious traffic collisions: A gradient boosting decision tree analysis[J]. Journal of Transport & Health, 2022, 24: 101296. doi: 10.1016/j.jth.2021.101296. doi: 10.1016/j.jth.2021.101296
[39]	谢波, 庞哲, 安子豪. 基于交通安全视角的城市土地混合利用模式研究[J]. 城市发展研究, 2020, 27(8): 19-24.
	[Xie Bo, Pang Zhe, An Zihao. Exploring the mixed land use pattern from the perspective of transportation safety. Urban Development Studies, 2020, 27(8): 19-24. ]
[40]	王成, 谢波. 土地利用视角下城市交通事故驱动机理的研究进展[J]. 地理科学进展, 2020, 39(9): 1597-1606.
	[Wang Cheng, Xie Bo. Research progress on the driving mechanism of traffic accidents from the perspective of land use. Progress in Geography, 2020, 39(9): 1597-1606. ]
[41]	Najaf P, Thill J C, Zhang W J, et al. City-level urban form and traffic safety: A structural equation modeling analysis of direct and indirect effects[J]. Journal of Transport Geography, 2018, 69: 257-270. doi: 10.1016/j.jtrangeo.2018.05.003
[42]	Harvey C, Aultman-Hall L. Urban streetscape design and crash severity[J]. Transportation Research Record, 2015, 2500(1): 1-8. doi: 10.3141/2500-01
[43]	Ukkusuri S, Miranda-Moreno L F, Ramadurai G, et al. The role of built environment on pedestrian crash frequency[J]. Safety Science, 2012, 50(4): 1141-1151. doi: 10.1016/j.ssci.2011.09.012
[44]	Li J, Wang X S. Safety analysis of urban arterials at the meso level[J]. Accident Analysis & Prevention, 2017, 108: 100-111. doi: 10.1016/j.aap.2017.08.023
[45]	Masoud A R, Lee A, Faghihi F, et al. Building sustainably safe and healthy communities with the Fused Grid development layout[J]. Canadian Journal of Civil Engineering, 2015, 42(12): 1063-1072. doi: 10.1139/cjce-2015-0086
[46]	Freeman L C. Centrality in social networks conceptual clarification[J]. Social Networks, 1978, 1(3): 215-239. doi: 10.1016/0378-8733(78)90021-7
[47]	宋小冬, 陶颖, 潘洁雯, 等. 城市街道网络分析方法比较研究: 以Space Syntax、sDNA和UNA为例[J]. 城市规划学刊, 2020(2): 19-24.
	[Song Xiaodong, Tao Ying, Pan Jiewen, et al. A comparison of analytical methods for urban street network: Taking space syntax, sDNA and UNA as examples. Urban Planning Forum, 2020(2): 19-24. ]
[48]	高洁. 交通运输网络连通性评价指标分析[J]. 交通运输工程与信息学报, 2010, 8(1): 35-38.
	[Gao Jie. Analysis of transportation network connectivity evaluation index. Journal of Transportation Engineering and Information, 2010, 8(1): 35-38. ]
[49]	Sarkar C, Webster C, Kumari S. Street morphology and severity of road casualties: A 5-year study of Greater London[J]. International Journal of Sustainable Transportation, 2018, 12(7): 510-525. doi: 10.1080/15568318.2017.1402972
[50]	Newman M E J. Assortative mixing in networks[J]. Physical Review Letters, 2002, 89: 208701. doi: 10.48550/arXiv.cond-mat/0205405. doi: 10.48550/arXiv.cond-mat/0205405
[51]	Hu H B, Wang X F. Unified index to quantifying heterogeneity of complex networks[J]. Physica A: Statistical Mechanics and Its Applications, 2008, 387(14): 3769-3780. doi: 10.1016/j.physa.2008.01.113
[52]	Zhang Y Y, Bigham J, Ragland D, et al. Investigating the associations between road network structure and non-motorist accidents[J]. Journal of Transport Geography, 2015, 42: 34-47. doi: 10.1016/j.jtrangeo.2014.10.010
[53]	莫辉辉, 王姣娥, 金凤君. 交通运输网络的复杂性研究[J]. 地理科学进展, 2008, 27(6): 112-120. doi: 10.11820/dlkxjz.2008.06.016
	[Mo Huihui, Wang Jiao'e, Jin Fengjun. Complexity perspectives on transportation network. Progress in Geography, 2008, 27(6): 112-120. ] doi: 10.11820/dlkxjz.2008.06.016
[54]	徐凤, 朱金福, 杨文东. 复杂网络在交通运输网络中的应用研究综述[J]. 复杂系统与复杂性科学, 2013, 10(1): 18-25.
	[Xu Feng, Zhu Jinfu, Yang Wendong. The complex networks applications in transportation networks: A survey. Complex Systems and Complexity Science, 2013, 10(1): 18-25. ]
[55]	Zhou S, Mondragon R J. The rich-club phenomenon in the Internet topology[J]. IEEE Communications Letters, 2004, 8(3): 180-182. doi: 10.1109/LCOMM.2004.823426
[56]	Guo Q, Pei X, Yao D Y, et al. Role of street patterns in zone-based traffic safety analysis[J]. Journal of Central South University, 2015, 22(6): 2416-2422. doi: 10.1007/s11771-015-2768-3
[57]	龙雪琴, 关宏志. 基于交通安全的城市路网结构优化方法[J]. 公路交通科技, 2012, 29(4): 107-113.
	[Long Xueqin, Guan Hongzhi. Urban road network structure optimization method based on traffic safety. Journal of Highway and Transportation Research and Development, 2012, 29(4): 107-113. ]
[58]	Kamel M B, Sayed T. The impact of bike network indicators on bike kilometers traveled and bike safety: A network theory approach[J]. Environment and Planning B: Urban Analytics and City Science, 2021, 48(7): 2055-2072. doi: 10.1177/2399808320964469
[59]	Moeinaddini M, Asadi-Shekari Z, Zaly Shah M. The relationship between urban street networks and the number of transport fatalities at the city level[J]. Safety Science, 2014, 62: 114-120. doi: 10.1016/j.ssci.2013.08.015
[60]	申凤, 李亮, 翟辉. “密路网,小街区”模式的路网规划与道路设计: 以昆明呈贡新区核心区规划为例[J]. 城市规划, 2016, 40(5): 43-53.
	[Shen Feng, Li Liang, Zhai Hui. Road network planning and street design based on the planning pattern of "high street density, small block size": A case study of central district planning in Chenggong new town of Kunming. City Planning Review, 2016, 40(5): 43-53. ]
[61]	Masoud A R, Idris A O, Lovegrove G. Modelling the impact of fused grid network design on mode choice behaviour[J]. Journal of Transport & Health, 2019, 15: 100627. doi: 10.1016/j.jth.2019.100627. doi: 10.1016/j.jth.2019.100627
[62]	蔡军, 路晓东. 路网密度对城市公共汽车交通发展的影响[J]. 城市交通, 2016, 14(2): 1-9, 58.
	[Cai Jun, Lu Xiaodong. Impact of road network density on promoting bus traffic development. Urban Transport of China, 2016, 14(2): 1-9, 58. ]
[63]	Marshall W E, Garrick N W. Effect of street network design on walking and biking[J]. Transportation Research Record: Journal of the Transportation Research Board, 2010, 2198(1): 103-115. doi: 10.3141/2198-12
[64]	Rifaat S M, Pasha M, Tay R, et al. Effect of community road infrastructure, socio-demographic and street pattern in promoting walking as sustainable transportation mode[J]. The Open Transportation Journal, 2019, 13(1): 25-34. doi: 10.2174/1874447801913010025
[65]	Berrigan D, Pickle L W, Dill J. Associations between street connectivity and active transportation[J]. International Journal of Health Geographics, 2010, 9(1): 20. doi: 10.1186/1476-072X-9-20. doi: 10.1186/1476-072X-9-20
[66]	蒋应红, 沈雷洪, 刘宙, 等. 街道机动车车道宽度缩窄的合理取值研究[J]. 城市规划, 2022, 46(2): 62-70.
	[Jiang Yinghong, Shen Leihong, Liu Zhou, et al. A study on the reasonable value for narrowing the width of motor vehicle lane. City Planning Review, 2022, 46(2): 62-70. ]
[67]	Parthasarathi P. Network structure and metropolitan mobility[J]. Journal of Transport and Land Use, 2014, 7(2): 153-170. doi: 10.5198/jtlu.v7i2.494
[68]	Pasha M, Rifaat S M, Tay R, et al. Effects of street pattern, traffic, road infrastructure, socioeconomic and demographic characteristics on public transit ridership[J]. KSCE Journal of Civil Engineering, 2016, 20(3): 1017-1022. doi: 10.1007/s12205-016-0693-6
[69]	Huang J, Levinson D M. Circuity in urban transit networks[J]. Journal of Transport Geography, 2015, 48: 145-153. doi: 10.1016/j.jtrangeo.2015.09.004
[70]	车冠琼, 仇保兴, 杨滔. 街道网络结构与土地利用布局对人流分布的影响[J]. 西部人居环境学刊, 2021, 36(2): 87-94.
	[Che Guanqiong, Qiu Baoxing, Yang Tao. The effects of street network structure and land use distribution on pedestrian flow. Journal of Human Settlements in West China, 2021, 36(2): 87-94. ]
[71]	Guan X D, Wang D G, Cao X J. The role of residential self-selection in land use-travel research: A review of recent findings[J]. Transport Reviews, 2020, 40(3): 267-287. doi: 10.1080/01441647.2019.1692965
[72]	Lin T, Wang D G, Guan X D. The built environment, travel attitude, and travel behavior: Residential self-selection or residential determination?[J]. Journal of Transport Geography, 2017, 65: 111-122. doi: 10.1016/j.jtrangeo.2017.10.004
[73]	van Wee B. Self-selection: A key to a better understanding of location choices, Travel behaviour and transport externalities?[J]. Transport Reviews, 2009, 29(3): 279-292. doi: 10.1080/01441640902752961
[74]	Cao X Y, Mokhtarian P L, Handy S L. Examining the impacts of residential self-selection on travel behaviour: A focus on empirical findings[J]. Transport Reviews, 2009, 29(3): 359-395. doi: 10.1080/01441640802539195
[75]	Deng Y L, Zhao P J. Quantifying residential self-selection effects on commuting mode choice: A natural experiment[J]. Transportation Research Part D: Transport and Environment, 2022, 104: 103197. doi: 10.1016/j.trd.2022. doi: 10.1016/j.trd.2022

[76]	Wang D G, Lin T. Built environment, travel behavior, and residential self-selection: A study based on panel data from Beijing, China[J]. Transportation, 2019, 46(1): 51-74. doi: 10.1007/s11116-017-9783-1

道路网络布局形式	描述	交通安全特性
格网型	路网呈现方格网式或近似方格网式,多为四岔路口	交通冲突点多,但有利于分散地区交通流量,减缓地区平均车速
平行曲线型	由平行或近似平行的曲线道路组成,多为三岔路口	美学效果好,但曲线式的道路线型可能影响司机正常驾驶行为
回路尽端型	由尽端路结合回路式路网构成,多呈树状、鱼骨状	穿越型交通流量较低,限制性的设计特征可以促进司机谨慎驾驶,但也可能影响司机正常驾驶行为
融合网格型	格网作为路网的整体框架,内部应用限制通行的尽端式道路	居住单元内部非机动车网络连通性好,机动车网络连通性差,可以有效保障非机动车群体通行安全

道路网络几何特征	测度指标	作用方式
宏观尺度特征	交叉口密度	影响交通冲突、交通速度,影响驾驶行为
	路网密度	影响交通冲突、交通流量,影响驾驶行为
	街区密度	影响交通冲突,影响行人出行环境
	道路总长度	影响交通流量
微观尺度特征	道路宽度	影响交通流量、交通速度,影响行人出行环境
	道路段长度	影响交通速度
	交叉口类型	影响交通冲突

Progress of research on the mechanism of impact of urban road network characteristics on traffic accidents

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 76

Related Articles 15

Metrics

Comments

Recommended 0

道路网络拓扑特征	测度指标	作用方式
中心性	接近中心性	影响交通流量,影响驾驶行为
中心性	中间中心性	影响交通流量,影响行人、骑行者出行环境
连通性	α、β、γ指数	影响交通冲突、交通流量,影响驾驶行为
绕行性	绕行率	影响交通冲突、交通速度
异配性	—	影响交通冲突
平均测地距离	平均测地距离	影响交通速度
集聚系数	整体集聚系数	影响行人、骑行者出行环境
富人俱乐部指数	富人俱乐部指数	影响骑行者出行环境

[1]	ZHANG Wenjia, NIU Caicheng, ZHU Jiancheng. Progress of regional spatial structure research from the perspective of behavior network [J]. PROGRESS IN GEOGRAPHY, 2022, 41(8): 1504-1515.
[2]	WANG Anqi, PENG Jiandong, REN Peng, YANG Hong, DAI Qi. Impact of the built environment of rail transit stations on the travel behavior of persons with disabilities: Taking 189 rail transit stations in Wuhan City as an example [J]. PROGRESS IN GEOGRAPHY, 2021, 40(7): 1127-1140.
[3]	WANG Cheng, XIE Bo. Research progress on the driving mechanism of traffic accidents from the perspective of land use [J]. PROGRESS IN GEOGRAPHY, 2020, 39(9): 1597-1606.
[4]	GUO Jianke, HOU Yajie, HE Yao. Characteristics of change of the China-Europe port shipping network under the Belt and Road Initiative [J]. PROGRESS IN GEOGRAPHY, 2020, 39(5): 716-726.
[5]	MAO Shuaiyong, JIAO Limin, XU Gang, LI Zehui. Identification of the polycentric spatial structure in Wuhan City based on multisource data [J]. PROGRESS IN GEOGRAPHY, 2019, 38(11): 1675-1683.
[6]	Wenyan HU, Mengya LI, Jun WANG, Qingyu HUANG. Urban traffic congestion caused by rainstorms and innudation [J]. PROGRESS IN GEOGRAPHY, 2018, 37(6): 772-780.
[7]	Jianke GUO, Yao HE, Yajie HOU. Spatial connection and regional difference of the coastal container port shipping network of China [J]. PROGRESS IN GEOGRAPHY, 2018, 37(11): 1499-1509.
[8]	Sihui GUO, Congcong WEN, Yun HE, Tao PEI. Relationship between travel behavior and income level of urban residents:A case study in Shanghai Municipality [J]. PROGRESS IN GEOGRAPHY, 2017, 36(9): 1158-1166.
[9]	Kun QIN, Qing ZHOU, Yuanquan XU, Wenting XU, Ping LUO. Spatial interaction network analysis of urban traffic hotspots [J]. PROGRESS IN GEOGRAPHY, 2017, 36(9): 1149-1157.
[10]	Jing MA, Yanwei CHAI, Tingting FU. Progress of research on the health impact of people's space-time behavior and environmental pollution exposure [J]. PROGRESS IN GEOGRAPHY, 2017, 36(10): 1260-1269.
[11]	Yueer GAO, Shuting CHEN, Chengyu ZHENG, Jingwei BIAN. Road network capacity of tourist site's periphery based on FCD: Taking Xiamen Island as an example [J]. PROGRESS IN GEOGRAPHY, 2016, 35(12): 1529-1537.
[12]	Limin JIAO, Xin TANG, Xiaoping LIU. Spatial linkage and urban expansion:An urban agglomeration perspective [J]. PROGRESS IN GEOGRAPHY, 2016, 35(10): 1177-1185.
[13]	Wei ZHENG. Research progress and development trend in urban economic network study based on complexity theory [J]. PROGRESS IN GEOGRAPHY, 2015, 34(6): 676-686.
[14]	Jianxi FENG, Zhenshan YANG. Factors influencing travel behavior of urban elderly people in Nanjing [J]. PROGRESS IN GEOGRAPHY, 2015, 34(12): 1598-1608.
[15]	Xiaoyan HUANG, Shuang ZHANG, Xiaoshu CAO. Spatial-temporal evolution of Guangzhou subway accessibility and its effects on the accessibility of public transportation services [J]. PROGRESS IN GEOGRAPHY, 2014, 33(8): 1078-1089.