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Traffic incident related delays are estimated to contribute approximately 45% and 55% of total delay experienced by motorists in areas such as Las Vegas. This Project is intended to improve the Incident Management (IM) process by quantitatively studying existing situations of the IM process in the Las Vegas area, and developing a mathematical model that will be used for simulation taking into account all aspects of IM.
Finite State Processes (FSP) Models
Labeled Transition Systems (LTS) Diagrams for FSP Models
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When an incident occurs, each minute that it takes to respond to and clear the incident scence can add as much as 5 minutes of delay on the freeway while dramatically increasing likelihood of secondary incidents composing nearly 20% of all incidents. This project investigates the full impact of freeway incidents in order to better define secondary incidents which can be used in developing a systematical model reducing secondary events.
Proposed Novel Progression Curve for Congestion
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Reliability assessment is conducted using five different approaches. Variability based on normalized standard deviation, analysis of variance (ANOVA), average time mean estimation, reliability as a measure of non-failures, and information Theory based approach are proposed.
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A Bayesian network is a probabilistic model which represents relationships between uncertain variables and can be tweaked for a variety of purposes. In traffic studies, it can be used to analyze and predict traffic flow as well as accidents. It has been increasingly used in safety studies in order to analyze the relationships between various contributing factors in crash analyses. In this project, a Bayesian traffic safety analyzer will be developed using crash data and other surrogate information to estimate risks of various locations.
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Incident Management