Title

An Investigation of Incident Frequency, Duration and Lanes Blockage for Determining Traffic Delay

Document Type

Article

Publication Date

7-2009

Publication Title

Journal of Advanced Transportation

Volume

43

Issue

3

First page number:

275

Last page number:

299

Abstract

Traffic delay caused by incidents is closely related to three variables: incident frequency, incident duration, and the number of lanes blocked by an incident that is directly related to the bottleneck capacity. Relatively, incident duration has been more extensively studied than incident frequency and the number of lanes blocked in an incident. In this study, we provide an investigation of the influencing factors for all of these three variables based on an incident data set that was collected in New York City (NYC). The information about the incidents derived from the identification can be used by incident management agencies in NYC for strategic policy decision making and daily incident management and traffic operation.

In identifying the influencing factors for incident frequency, a set of models, including Poisson and Negative Binomial regression models and their zero-inflated models, were considered. An appropriate model was determined based on a model decision-making tree. The influencing factors for incident duration were identified based on hazard-based models where Exponential, Weibull, Log-logistic, and Log-normal distributions were considered for incident duration. For the number of lanes blocked in an incident, the identification of the influencing factors was based on an Ordered Probit model which can better capture the order inherent in the number of lanes blocked in an incident. As identified in this study, rain is the only factor that significantly influenced incident frequency. For incident duration and the number of lanes blocked in an incident, various factors had significant impact. As concluded in this study, there is a strong need to identify the influencing factors in terms of different types of incidents and the roadways where the incidents occured.

Keywords

Negative binomial distribution; Poisson distribution; Traffic congestion; Traffic congestion—Management; Traffic flow

Disciplines

Civil and Environmental Engineering | Civil Engineering | Construction Engineering and Management | Environmental Engineering | Structural Engineering

Language

English

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

Identifier

DOI: http://dx.doi.org/10.1002/atr.5670430303

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