A Data Mining Approach to Identify Key Factors of Traffic Injury Severity

Seventy percent of the traffic crash fatalities of Iran happen on rural roads, and a significant proportion of the rural roads network of this country is constituted of the main two-lane, two-way roads. The purpose of this study is to identify the most important factors which affect injury severity of drivers involved in traffic crashes on these roads, so that by eliminating or controlling such factors an overall safety improvement can be accomplished. Using the Classification and Regression Tree (CART), one of the powerful data mining tools, the crash data pertaining to the last three years (2006-2008) were analyzed. The variable selection procedure was carried out on the basis of Variable Importance Measure (VIM) which is one of the CART method outputs. The results revealed that not using the seat belt, improper overtaking and speeding are the most important factors associated with injury severity. KEYWORDS: injury severity; traffic safety; data mining; Classification and Regression Trees (CART); Variable Importance Measure (VIM

Head-on crashes on two-way interurban roads: a public health concern in road safety

AbstractObjectiveTo describe the magnitude and characteristics of crashes and drivers involved in head-on crashes on two-way interurban roads in Spain between 2007 and 2012, and to identify the factors associated with the likelihood of head-on crashes on these roads compared with other types of crash.MethodsA cross-sectional study was conducted using the National Crash Register. The dependent variables were head-on crashes with injury (yes/no) and drivers involved in head-on crashes (yes/no). Factors associated with head-on crashes and with being a driver involved in a head-on crash versus other types of crash were studied using a multivariate robust Poisson regression model to estimate proportion ratios (PR) and confidence intervals (95% CI).ResultsThere were 9,192 head-on crashes on two-way Spanish interurban roads. A total of 15,412 men and 3,862 women drivers were involved. Compared with other types of crash, head-on collisions were more likely on roads 7 m or more wide, on road sections with curves, narrowings or drop changes, on wet or snowy surfaces, and in twilight conditions. Transgressions committed by drivers involved in head-on crashes were driving in the opposite direction and incorrectly overtaking another vehicle. Factors associated with a lower probability of head-on crashes were the existence of medians (PR=0.57; 95%CI: 0.48-0.68) and a paved shoulder of less than 1.5 meters (PR=0.81; 95%CI: 0.77-0.86) or from 1.5 to 2.45 meters (PR=0.90; 95%CI: 0.84-0.96).ConclusionsThis study allowed the characterization of crashes and drivers involved in head-on crashes on two-way interurban roads. The lower probability observed on roads with median strips point to these measures as an effective way to reduce these collision

A control and surveillance ITS location model to improve safety

Traffic safety in rural highways can be considered as a constant source of concern in many countries. Nowadays, transportation professionals widely use Intelligent Transportation Systems (ITS) to address safety issues. However, compared to metropolitan applications, the rural highway (non-urban) ITS applications are still not well defined. This paper provides a comprehensive review on the existing ITS safety solutions for rural highways. This research is mainly focused on the infrastructure-based control and surveillance ITS technology, such as Crash Prevention and Safety, Road Weather Management and other applications, that is directly related to the reduction of frequency and severity of accidents. The main outcome of this research is the development of a ‘ITS control and surveillance device locating model’ to achieve the maximum safety benefit for rural highways. Using cost and benefits databases of ITS, an integer linear programming method is utilized as an optimization technique to choose the most suitable set of ITS devices. Finally, computational analysis is performed on an existing highway in Iran, to validate the effectiveness of the proposed locating model

An approximate reliability evaluation method for improving transportation network performance

Considering the importance of maintaining network performance at desired levels under uncertainty, network reliability, as a new approach to assessing the performance of degradable urban transportation networks, has become increasingly developed in two recent decades. In this paper, a method for optimizing resource allocation to meet the required levels of transportation network reliability is proposed. The worked out method consists of two stages: at stage one, a method for computing the reliability of network connectivity based on the reliability of computing arc performance with an assumption that capacities are random variables for each arc is presented. These random variables are assumed to be conformed to especial probability density functions which can be modified through investing to improve the performance reliability of the arcs. At stage two, a mixed integer nonlinear programming model is developed to optimize resource allocation in the network. Numerical results are also provided in a simple network to demonstrate the capability of the employed method. First published online: 27 Oct 201

A new approach for reliability assessment of urban transportation networks

Transport systems are subject to various types of short term incidents which affect their ordinary functions. Unlike the natural disasters in which the elements of the network would usually fail for long periods, short term incidents temporarily degrade the link capacities and often the network would not reach a new equilibrium before the normal functions return. This paper presents a method for a system level network reliability evaluation with a special attention to the role of network topology. The study is aimed at representing a framework for analyzing vulnerable networks first by introducing a reliability measure and secondly by applying a mathematical analysis method that efficiently executes the algorithm for a large network. The results of the proposed evaluation procedure for transportation system are promising. The study demonstrates that the reliability measure and network topology concepts can be included in the transportation network modeling process at a reasonable effort. Copyright ASCE 2006

A ROUTING METHODOLOGY FOR HAZARDOUS MATERIALS TRANSPORTATION TO REDUCE THE RISK OF ROAD NETWORK

Abstract: The shipments of hazardous materials (HAZMATs) induce various risks to the road network. Today, one of the major considerations of transportation system managers is HAZMATs shipments, due to the increasing demand of these goods (because it is more used in industry, agriculture, medicine, etc.), and the rising number of incidents that are associated to hazardous materials. This paper presents a tool for HAZMATs transportation authorities and planners that would reduce the risk of the road network by identifying safe and economic routes for HM transshipment. Using the proposed linear integer programming model, the HM management system could determine an optimal assignment for all origin–destination pairs for various hazardous materials in a transportation network and so reduce the vulnerability due to HAZMATs releases such as population and environmental vulnerability. The model is implemented and evaluated for the hazardous materials routing within Fars, Yazd, Isfahan, and Chaharmaha-o-Bakhtiyari provinces of Iran. The branch-and-bound algorithm is applied to solve the model using the Lingo software package

An approximate reliability evaluation method for improving transportation network performance

Considering the importance of maintaining network performance at desired levels under uncertainty, network reliability, as a new approach to assessing the performance of degradable urban transportation networks, has become increasingly developed in two recent decades. In this paper, a method for optimizing resource allocation to meet the required levels of transportation network reliability is proposed. The worked out method consists of two stages: at stage one, a method for computing the reliability of network connectivity based on the reliability of computing arc performance with an assumption that capacities are random variables for each arc is presented. These random variables are assumed to be conformed to especial probability density functions which can be modified through investing to improve the performance reliability of the arcs. At stage two, a mixed integer nonlinear programming model is developed to optimize resource allocation in the network. Numerical results are also provided in a simple network to demonstrate the capability of the employed method

Application of Particle Swarm Optimization to the Emergency Medical Services Location Problem

No abstract available

A Reliability-Based Resource Allocation Model for Transportation Networks Affected by Natural Disasters

This paper is concerned with the development of a resource allocation model for road networks under supply uncertainty caused by natural disasters. An optimization model is proposed to determine which links should be invested for the system to perform better while encountering natural disasters such as earthquake. The connectivity reliability and travel time reliability of origin-destinations (ODs) are selected as performance measures to do so. The Monte-Carlo simulation method is used to estimate the reliability measures and the model is solved by the genetic algorithm. The proposed model is implemented on a test network to demonstrate the results