Approach to Identifying Black Spots Based on Potential Saving in Accident Costs

In improving road safety, the identification of black spots based on potential saving in accident costs is an attempt to make the selection of black spots to treat out of the identified ones. This selection is based on a new approach in which safety potential is employed as a key parameter which has a dual function of identification and prioritization. With this approach, it is possible to find black spots where safety improvement measures are expected to have the greatest economical effectiveness. Therefore, the approach may be a practically suitable tool for developing countries in road traffic accident reduction effort. This paper intends to introduce the new approach to identify road accident black spots in detail. First, the evolution of criteria for black spot identification is reviewed. What follows is an analytical framework for identifying black spots based on potential saving in accident costs. Finally, a particular case of practical implementation is enclosed in order to illustrate the approach

Analysis of Transportation Networks Subject To Natural Hazards – insights from a Colombian case

ABSTRACT: This study provides an applied framework to derive the connectivity reliability and vulnerability of inter-urban transportation systems under network disruptions. The proposed model integrates statistical reliability analysis to find the reliability and vulnerability of transportation networks. Most of the modern research in this field has focused on urban transportation networks where the primary concerns are guaranteeing predefined standards of capacity and travel time. However, at a regional and national level, especially in developing countries, the connectivity of remote populations in the case of disaster is of utmost importance. The applicability of the framework is demonstrated with a case study in the state of Antioquia, Colombia, using historical records from the 2010-2011 rainy season, an aspect that stands out and gives additional support compared to previous studies that considers simulated data from assumed distributions. The results provide significant insights to practitioners and researchers for the design and management of transportation systems and route planning strategies under this type of disruptions

Evaluation and Design of Transport Network Capacity Under Demand Uncertainty

A flexible evaluation and design model for transport network capacity under demand variability is proposed. The future stochastic demand is assumed to follow a normal distribution. Traveler path choice behavior is assumed to follow the probit stochastic user equilibrium. The network reserve capacity is used to evaluate the performance of the network. Since the future demand is stochastic, the reserve capacity is measured by possible increases in both mean and standard deviation (SD) of the base demand distribution. The proposed model therefore represents the flexibility of the network in its robustness to origin-destination demand variation (i.e., high SD). The proposed model can also determine an optimal network design to maximize the reserve capacity of the network for both the mean and the SD of the increased demand distribution. The implicit programming approach is applied to solve the optimization problem. Sensitivity analysis is adopted to provide all necessary derivatives. The model and algorithm are tested with a hypothetical network to illustrate the merits of the proposed model

Intersection Safety Assessment Using Video-Based Traffic Conflict Analysis: The Case Study of Thailand

In the road transport network, intersections are among the most critical locations leading to a risk of death and serious injury. The traditional methods to assess the safety of intersections are based on statistical analyses that require crash data. However, such data may be under-reported and omit important crash-related factors. The conventional approaches, therefore, are not easily applied to making comparisons of intersection designs under different road classifications. This study developed a risk-based approach that incorporates video-based traffic conflict analysis to investigate vehicle conflicts under mixed traffic conditions including motorcycles and cars in Thailand. The study applied such conflict data to assess the risk of intersections in terms of time-to-collision and conflict speed. Five functional classes of intersections were investigated, including local-road/local-road, local-road/collector, collector/arterial, collector/collector, and arterial/arterial intersections. The results showed that intersection classes, characteristics, and control affect the behavior of motorists and the safety of intersections. The results found that the low-order intersections with stop/no control are high risks due to the short time-to-collision of motorcycle-related conflicts. They generate frequent conflicts with low chance of injury. The high-order intersections with signal control are high risks due to high conflicting speeds of motorcycle–car conflicts. They generate few conflicts but at a high chance of injury. The study presents the applicability of video-based traffic conflict analysis for systematically estimating the crash risk of intersections. The risk-based approach can be deemed as a supplement indicator in addition to limited crash data to evaluate the safety of intersections. However, future research is needed to explore the potential of other road infrastructure under different circumstances

Intersection Safety Assessment Using Video-Based Traffic Conflict Analysis: The Case Study of Thailand

In the road transport network, intersections are among the most critical locations leading to a risk of death and serious injury. The traditional methods to assess the safety of intersections are based on statistical analyses that require crash data. However, such data may be under-reported and omit important crash-related factors. The conventional approaches, therefore, are not easily applied to making comparisons of intersection designs under different road classifications. This study developed a risk-based approach that incorporates video-based traffic conflict analysis to investigate vehicle conflicts under mixed traffic conditions including motorcycles and cars in Thailand. The study applied such conflict data to assess the risk of intersections in terms of time-to-collision and conflict speed. Five functional classes of intersections were investigated, including local-road/local-road, local-road/collector, collector/arterial, collector/collector, and arterial/arterial intersections. The results showed that intersection classes, characteristics, and control affect the behavior of motorists and the safety of intersections. The results found that the low-order intersections with stop/no control are high risks due to the short time-to-collision of motorcycle-related conflicts. They generate frequent conflicts with low chance of injury. The high-order intersections with signal control are high risks due to high conflicting speeds of motorcycle–car conflicts. They generate few conflicts but at a high chance of injury. The study presents the applicability of video-based traffic conflict analysis for systematically estimating the crash risk of intersections. The risk-based approach can be deemed as a supplement indicator in addition to limited crash data to evaluate the safety of intersections. However, future research is needed to explore the potential of other road infrastructure under different circumstances

Large-scale road network vulnerability analysis: a sensitivity analysis based approach

Vulnerability analysis, Sensitivity analysis, Large-scale road network, Accessibility,

The evolution of criteria for identifying black spots and recommendations for developing countries

The general purpose of black spot identification is to identify high accident frequency locations on a road network to improve road safety. The next task is to sift through these locations to select the particular locations based on whose analysis the safety treatment is established. Thus, black spot treatment is a two-stage process: identification and safety analysis, with the former producing the enriched data for the detailed analysis done in the latter. Such analysis is to determine the true black spots, the safety aspects to improve, the cost of treatment, and the extent of the efficiency. Accordingly, the object of identification stage is to select sites that have a good chance of being in need of remedial action and also capable of being cost-effectively improved. This paper reviews the evolution of criteria for black spot identification in terms of scope and aspects. On the basis of this review, a number of suggestions are made for the cases of developing countries in terms of black spot identification aspects