A safety audit approach in ranking urban road crash hotspots using analytical hierarchy process (AHP). Case study: region 20 of Tehran

Abstract

Today existence of reliable crash data plays an important role in ranking hotspots and planningfor road crash prevention programs. Yet, so many Road Crash data-based models have beendeveloped for ranking hotspots. But crash data are rarely available in sufficient quantity oraccuracy to justify the approaches in many countries and this problem prohibits even usingordinary crash data-based ranking models. To compensate this, the methodology presented in this study, aims to introduce a method for ranking high potential crash risk locations instead of actual high crash risk locations (locations with actual high crash history). The methodology used,involves defining a Safety Deficiency Value (SD-Value) to rank urban hotspots. SD-Value isdefined as a number denoting the lack of safety in a distinct location and is measured by directfield inspection and measurement of crash contributing factors. The more the SD-Value is, the greater is the priority of location in the ranking. Road Crash contributing factors considered inthis study have been Lighting, Marking and Signing Inadequacy, Not provided enough sightdistances, Inadequate Drainage, Not Enough Pedestrian Facilities (if needed), Not ProvidingSafety Equipment (if needed), Existence of Effective Pavement Failures and Excessive Speeds of Vehicles. On the other hand, Road Crash contributing factors have different effects on lowering the safety level in crash hotspots. The importance weight of each factor has been calculated based on an analytical hierarchy approach (AHP). Moreover as the risk levels and the weights of contributing factors may be different in roadways and intersections, the hotspot type (the type of location) must also enter into the methodology. The total SD-Value of a location is calculated as the summation of the amount of each contributing factor times its respective weight of importance, regarding the location type. Finally to illustrate the methodology, an actual rankingproblem has been followed as a case study for 7 hotspots of region 20 of Tehran, Iran. In this case study, the reported hotspots by the local officials, have been carefully inspected by a RSA team and contributed factors have been measured and based on the results, the ranking methodology has been applied.Today existence of reliable crash data plays an important role in ranking hotspots and planningfor road crash prevention programs. Yet, so many Road Crash data-based models have beendeveloped for ranking hotspots. But crash data are rarely available in sufficient quantity oraccuracy to justify the approaches in many countries and this problem prohibits even usingordinary crash data-based ranking models. To compensate this, the methodology presented in this study, aims to introduce a method for ranking high potential crash risk locations instead of actual high crash risk locations (locations with actual high crash history). The methodology used,involves defining a Safety Deficiency Value (SD-Value) to rank urban hotspots. SD-Value isdefined as a number denoting the lack of safety in a distinct location and is measured by directfield inspection and measurement of crash contributing factors. The more the SD-Value is, the greater is the priority of location in the ranking. Road Crash contributing factors considered inthis study have been Lighting, Marking and Signing Inadequacy, Not provided enough sightdistances, Inadequate Drainage, Not Enough Pedestrian Facilities (if needed), Not ProvidingSafety Equipment (if needed), Existence of Effective Pavement Failures and Excessive Speeds of Vehicles. On the other hand, Road Crash contributing factors have different effects on lowering the safety level in crash hotspots. The importance weight of each factor has been calculated based on an analytical hierarchy approach (AHP). Moreover as the risk levels and the weights of contributing factors may be different in roadways and intersections, the hotspot type (the type of location) must also enter into the methodology. The total SD-Value of a location is calculated as the summation of the amount of each contributing factor times its respective weight of importance, regarding the location type. Finally to illustrate the methodology, an actual rankingproblem has been followed as a case study for 7 hotspots of region 20 of Tehran, Iran. In this case study, the reported hotspots by the local officials, have been carefully inspected by a RSA team and contributed factors have been measured and based on the results, the ranking methodology has been applied.