Crash Classification by Congestion Type for Highways

Abstract

Effective management of highway networks requires a thorough understanding of the conditions under which vehicular crashes occur. Such an understanding can and should inform related operational and resource allocation decisions. This paper presents an easily implementable methodology that can classify all reported crashes in terms of the operational conditions under which each crash occurred. The classification methodology uses link-based speed data. Unlike previous secondary collision identification schemes, it neither requires an a priori identification of the precipitating incident nor definition of the precipitating incident’s impact area. To accomplish this objective, the methodology makes use of a novel scheme for distinguishing between recurrent and non-recurrent congestion. A 500-crash case study was performed using a 274 km section of the I-40 in North Carolina. Twelve percent of the case study crashes were classified as occurring in non-recurrent congestion. Thirty-seven percent of the crashes in non-recurrent congestion classified were identified within unreported primary incidents or crashes influence area. The remainder was classified as primary crashes occurring in either uncongested conditions (84%) or recurrent congestion (4%). The methodology can be implemented in any advanced traffic management system for which crash time and link location are available along with corresponding archived link speed data are available.

Point-process modeling of secondary crashes

“…Salek et al [ 19 ] presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes. Song et al [ 20 ] present a methodology using link-based speed data to classify all reported crashes based on operational conditions, without prior identification of the cause. A case study on a 274 km section of I-40 revealed 12% of crashes in non-recurrent congestion, with 37% linked to unreported primary incidents, while the rest were classified as primary crashes in uncongested conditions (84%) or recurrent congestion (4%).…”

Traffic Flow Density Model and Dynamic Traffic Congestion Model Simulation Based on Practice Case with Vehicle Network and System Traffic Intelligent Communication

“…The traffic scheme and the analysis of an intersection take into account elements of traffic, systematizing the whole process by synchronizing the signal with the control assembly of the traffic management system [12,13]. Thus, in order to create the simulation scenarios, additional direct simulation tools were used, including macro backgrounds, adjustment of directions and ground, and arrangement of intersections in order to render a real transport system reproduced with the defining elements imposed by legislation [14][15][16].…”