Abstract
The prevention of secondary crashes is a high priority task in traffic incident management. However, the limited knowledge regarding the nature of secondary crashes largely impeded the development of established countermeasures. The primary goal of this paper is to improve the literature's understanding of secondary crashes. This goal is achieved in two steps: first, with an analysis framework that accurately identifies secondary crashes by integrating rich traffic-sensor data with statewide-crash data and, second, by carefully investigating the characteristics of these identified secondary crashes. To that end, secondary crashes within a 27-mile section of a major highway in New Jersey were mined using the developed analysis framework, and a thorough examination of their characteristics has been performed. Empirical findings on the frequency of secondary crashes, their spatio-temporal distributions, clearance time, crash type, severity, and major contributing factors have been highlighted. Taken together, these preliminary results could potentially help transportation agencies make more informed decisions on mitigating secondary crashes and improve their incident management operations. To complement the results, further in-depth investigations using more high-resolution sensor data and high-quality incident records are suggested.
Original language | English (US) |
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Article number | 04013024 |
Journal | Journal of Transportation Engineering |
Volume | 140 |
Issue number | 4 |
DOIs | |
State | Published - 2014 |
Keywords
- Crash characteristics
- Data mining
- Freeway
- Highway
- Safety
- Secondary crash
- Sensor data
ASJC Scopus subject areas
- Civil and Structural Engineering
- Transportation