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Incident ManagementIncident Management

Transportation Research CenterUniversity of Nevada, Las Vegas

UTC Technical DaySeptember 8, 2009

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Team MembersTeam Members

Project TeamProject Team Dr. Pushkin Dr. Pushkin

KachrooKachroo Neveen ShlayanNeveen Shlayan Vinod VasudevanVinod Vasudevan Rohit SaddiRohit Saddi Rita BrohmanRita Brohman

Sponsor TeamSponsor Team Adrian Gibby Adrian Gibby Brian HoeftBrian Hoeft Fred OheneFred Ohene Shital Patel Shital Patel

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Project ObjectivesProject Objectives

Incident ManagementIncident Management intends to improve intends to improve – the Incident Management Processthe Incident Management Process– first responders coordinationfirst responders coordination

Secondary CongestionsSecondary Congestions project intends to project intends to– Well define secondary incidents spatially and Well define secondary incidents spatially and

temporally temporally – investigate the full impact of freeway incidents investigate the full impact of freeway incidents

Bayesian Traffic Safety AnalyzerBayesian Traffic Safety Analyzer development development – estimates risks of various locationsestimates risks of various locations– traffic flow and Incident predictiontraffic flow and Incident prediction

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Methodology Methodology

Incident Management Incident Management – Discrete modeling Discrete modeling – Hybrid modelingHybrid modeling– Systems properties, safety and liveness, validation Systems properties, safety and liveness, validation

Secondary CongestionsSecondary Congestions – Case studiesCase studies– Data analysis Data analysis – Redefining the progression curve for queues due to Redefining the progression curve for queues due to

accidents accidents

Bayesian Traffic Safety AnalyzerBayesian Traffic Safety Analyzer– Crash data analysisCrash data analysis– System modelingSystem modeling– System implementation System implementation

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Anticipated BenefitsAnticipated Benefits

Reduce incidents clearance times Reduce incidents clearance times

Efficiently maximize the use of resources Efficiently maximize the use of resources

Better understand nature of incidents and its Better understand nature of incidents and its implications on traffic flow implications on traffic flow

Development of general models and Development of general models and methodologies that can be used in methodologies that can be used in transportationtransportation

Development software tools and applicationsDevelopment software tools and applications

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LVMPD and NHP Crash DataLVMPD and NHP Crash Data

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Incident Management Modeling Incident Management Modeling

Formal Language and Automata Formal Language and Automata Theory Theory – Finite State Processes (FSP) Models Finite State Processes (FSP) Models – Labeled Transition Systems (LTS) Labeled Transition Systems (LTS)

Diagrams for FSP Models Diagrams for FSP Models

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Accident FSP and LTS Models Accident FSP and LTS Models

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LVMPD FSP and LTS ModelsLVMPD FSP and LTS Models

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Tow Company FSP and LTS ModelsTow Company FSP and LTS Models

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Sequence Properties Sequence Properties

SafetySafety LivenessLiveness

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Secondary Incidents Vissim Simulations Secondary Incidents Vissim Simulations

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Moving Dynamic Progression Moving Dynamic Progression Curve for Incident Related Curve for Incident Related Freeway CongestionFreeway Congestion

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Freeway Travel Time Reliability Freeway Travel Time Reliability Using DMS Recording from FAST Using DMS Recording from FAST

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Normalized Standard Deviation Normalized Standard Deviation

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Travel Time Mean Estimations Travel Time Mean Estimations

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Reliability as a Measure of Non-Reliability as a Measure of Non-failurefailure

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Reliability Using Information Reliability Using Information Theory Based Approach Theory Based Approach

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Bayesian NetworksBayesian Networks

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SummarySummary

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Work in ProgressWork in Progress

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ThankThank you !!you !!

Questions?Questions?