Prediction of traffic accidents hot spots using fuzzy logic and GIS

被引:0
作者
Aslam Al-Omari
Nawras Shatnawi
Taisir Khedaywi
Tasneem Miqdady
机构
[1] Jordan University of Science and Technology,Civil Engineering Department
[2] Al-Balqa Applied University,Surveying and Geomatics Engineering Department
来源
Applied Geomatics | 2020年 / 12卷
关键词
Traffic accidents; Hot spots; Fuzzy logic; AHP; GIS; Transportation;
D O I
暂无
中图分类号
学科分类号
摘要
The purpose of the current study is to predict accident hot spots in different locations using Geographic Information System (GIS) and fuzzy logic. The data used contained accident types and occurrence time. Fatality and injury were also studied with spatial-temporal analysis. Moreover, accident hot spots were predicted performing Weighted Overlay Method (WOM) and Fuzzy Overlay Method (FOM), which are widely used in decision making and alternatives analysis based on the results obtained from Analytic Hierarchy Process (AHP). Point Density (PD) method was used to verify hot spots in urban region that resulted from the mentioned two methods. Traffic accidents’ hot spots were predicted for Irbid City in Jordan using the data of the accidents that occurred between 2013 and 2015. Both WOM and FOM proved to be successful in identifying hot spots in parts of study area when verified to PD surface. Final results showed that eight hot spots were pointed out; three are road sections and five are major intersections, which were analyzed to get accident-contributing factors and suggest the proper remedies.
引用
收藏
页码:149 / 161
页数:12
相关论文
共 35 条
  • [1] Balist J(2016)Fuzzy modeling to determine the optimum location of fire stations, with network analyst and ANP (case study: sixth district of Tehran) International Journal of Emerging Research in Management & Technology 5 2278-9359
  • [2] Karimi S(2018)Traffic crash evolution characteristic analysis and spatiotemporal hotspot identification of urban road intersections Sustainability 2019 160-214
  • [3] Noraisefat I(2014)Application of Bayesian techniques for the identification of accident-prone sections DYNA Journal 81 209-303
  • [4] Mirkarimi A(2014)A geospatial neuro-fuzzy approach for identification of hazardous zones in regional transportation corridors International Journal of Civil Engineering 12 289-59
  • [5] Cheng Z(2010)Identification of accident hot spots: a GIS based implementation for Kannur District, Kerala International journal of Geomatics and Geosciences 1 51-285
  • [6] Zu Z(2007)A GIS-based Bayesian approach for analyzing spatial-temporal patterns of intra-city motor vehicle crashes J Transp Geogr 15 274-22
  • [7] Lu J(2013)GIS and f-AHP integration for locating a new textile manufacturing facility FIBRES & TEXTILES in Eastern Europe 5 18-325
  • [8] Edison T(2011)Spatio-temporal clustering of road accidents GIS based analysis and assessment Procedia Soc Behav Sci 21 317-110
  • [9] Castro G(2015)Safety classification using GIS in decision-making process to define priority road interventions J Transp Geogr 43 101-247
  • [10] Effati M(2016)GIS tools for analyzing accidents and road design: a review Transportation Research Procedia 18 242-542