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Exploratory Analysis of Run-Off-Road Crash Patterns

Mohammad Jalayer, Huaguo Zhou, Subasish Das

Open publisher page 11 citations

Abstract

A roadway departure (RwD) crash is defined by the Federal Highway Administration as “a crash in which a vehicle crosses an edge line, a centerline, or otherwise leaves the traveled way.” These crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, tend to be more severe than other crash types. In 2013, RwD crashes accounted for 59 percent of all motor vehicle traffic fatalities. There are a number of reasons a driver may leave the travel lane such as an avoidance maneuver and inattention or fatigue. Roadway and roadside geometric design features (e.g., lane and shoulder widths, clear zones) play a significant role in whether human error results in a crash, which is the focus of this chapter. Given the fact that ROR crashes accounted for the majority of RwD events and due to the high fatality rate associated with ROR crashes, the factors contributing to this type of crash must be identified in order to implement effective safety countermeasures. Given the large and complex datasets, identifying the key factors contributing to crashes is a very challenging task. This paper identifies the significant contributing factors for ROR crashes on rural two-lane roads using multiple correspondence analysis (MCA), as an exploratory data analysis, using the United States Road Assessment Program (usRAP) database, roadway and roadside features of 4,500 300-ft roadway segments in Illinois were identified and five years (2009-2013) of ROR crashes were gathered. The study results provide policymakers with useful insight into ROR crashes for the development effective safety countermeasures.

About this research paper

What this paper is about

A roadway departure (RwD) crash is defined by the Federal Highway Administration as “a crash in which a vehicle crosses an edge line, a centerline, or otherwise leaves the traveled way.” These crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, tend to be more severe than other crash types. In 2013, RwD crashes accounted for 59 percent of all motor vehicle traffic fatalities. There are a number of reasons a driver may leave the travel lane such as an avoidance maneuver and inattention or fatigue. Roadway and roadside geometric design features (e.g., lane and shoulder widths, clear zones) play a significant role in whether human error results in a crash, which is the focus of this chapter. Given the fact that ROR crashes accounted for the majority of RwD events and due to the high fatality rate associated with ROR crashes, the factors contributing to this type of crash must be identified in order to implement effective safety countermeasures. Given the large and complex datasets, identifying the key factors contributing to crashes is a very challenging task. This paper identifies the significant contributing factors for ROR crashes on rural two-lane roads using multiple correspondence analysis (MCA), as an exploratory data analysis, using the United States Road Assessment Program (usRAP) database, roadway and roadside features of 4,500 300-ft roadway segments in Illinois were identified and five years (2009-2013) of ROR crashes were gathered. The study results provide policymakers with useful insight into ROR crashes for the development effective safety countermeasures.

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Available abstract

A roadway departure (RwD) crash is defined by the Federal Highway Administration as “a crash in which a vehicle crosses an edge line, a centerline, or otherwise leaves the traveled way.” These crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, tend to be more severe than other crash types. In 2013, RwD crashes accounted for 59 percent of all motor vehicle traffic fatalities. There are a number of reasons a driver may leave the travel lane such as an avoidance maneuver and inattention or fatigue. Roadway and roadside geometric design features (e.g., lane and shoulder widths, clear zones) play a significant role in whether human error results in a crash, which is the focus of this chapter. Given the fact that ROR crashes accounted for the majority of RwD events and due to the high fatality rate associated with ROR crashes, the factors contributing to this type of crash must be identified in order to implement effective safety countermeasures. Given the large and complex datasets, identifying the key factors contributing to crashes is a very challenging task. This paper identifies the significant contributing factors for ROR crashes on rural two-lane roads using multiple correspondence analysis (MCA), as an exploratory data analysis, using the United States Road Assessment Program (usRAP) database, roadway and roadside features of 4,500 300-ft roadway segments in Illinois were identified and five years (2009-2013) of ROR crashes were gathered. The study results provide policymakers with useful insight into ROR crashes for the development effective safety countermeasures.

Key concepts: Crash, Exploratory analysis, Computer science, Data science, Operating system

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