Analysis, Modeling and Design for TrafficIncident Management Systems

The aim of incident management systems is to minimize the total delay experienced by travelers and also to keep the whole operation safe. In order to achieve these two goals, the system should make optimal choices and use optimal designs. For the design of optimal solutions, appropriate mathematical models are needed for various tasks, and then mathematical techniques need to be developed. The mathematical models, their analyses and the creation of optimal solutions can help to create a framework for a decision support system for overall incident management. The major aim of this project is to develop mathematical models, perform analyses, develop simulations, and then apply those to assist a decision support system for incident management in the Las Vegas area. In order to implement the system, this project helps gain an understanding on current local practices in incident management; evaluates alternate designs for incident management; and designs a system that focuses on the details of field implementations and operations locally.

[1]  Kaan Ozbay,et al.  Information Technology Requirements for Intelligent Evacuation Systems , 2009 .

[2]  Kaan Ozbay,et al.  FUZZY FEEDBACK CONTROL FOR REAL-TIME DYNAMIC TRAFFIC ROUTING: USER EQUILIBRIUM MODEL FORMULATIONS AND CONTROLLER DESIGN , 1996 .

[3]  Pushkin Kachroo,et al.  Modeling of Network Level System-Optimal Real-Time Dynamic Traffic Routing Problem Using Nonlinear H∞Feedback Control Theoretic Approach , 2006, J. Intell. Transp. Syst..

[4]  Pushkin Kachroo,et al.  Robust Feedback Control of a Single Server Queueing System , 1999, Math. Control. Signals Syst..

[5]  Kaan Ozbay,et al.  System dynamics and feedback control problem formulations for real time dynamic traffic routing , 1998 .

[6]  K. Ozbay,et al.  Wide-area incident management system on the Internet , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[7]  H. J. van Zuylen,et al.  Monitoring and predicting freeway travel time reliability , 2005 .

[8]  R A Raub SECONDARY CRASHES: AN IMPORTANT COMPONENT OF ROADWAY INCIDENT MANAGEMENT , 1997 .

[9]  Kaan Ozbay,et al.  Application of Stochastic Learning Automata for Modeling Departure Time and Route Choice Behavior , 2002 .

[10]  Timothy J Lomax,et al.  SELECTING TRAVEL RELIABILITY MEASURES , 2003 .

[11]  Kaan Ozbay,et al.  Feedback Control Theory for Dynamic Traffic Assignment , 1998 .

[12]  April Armstrong,et al.  Traffic Incident Management Handbook , 2010 .

[13]  Kaan Ozbay,et al.  INCIDENT MANAGEMENT IN INTELLIGENT TRANSPORTATION SYSTEMS , 1999 .

[14]  Kaan Ozbay,et al.  Solution to the user equilibrium dynamic traffic routing problem using feedback linearization , 1998 .

[15]  Pushkin Kachroo,et al.  Robust L2-gain control for nonlinear systems with projection dynamics and input constraints: an example from traffic control , 1999, Autom..

[16]  Kaan Ozbay,et al.  Feedback Ramp Metering in Intelligent Transportation Systems , 2003 .

[17]  Kaan Ozbay,et al.  Comprehensive Evaluation of Feedback-Based Freeway Ramp-Metering Strategy by Using Microscopic Simulation: Taking Ramp Queues into Account , 2004 .

[18]  Genevieve Giuliano,et al.  SECONDARY ACCIDENT RATES ON LOS ANGELES FREEWAYS , 2004 .

[19]  Myer Kutz,et al.  Handbook of Transportation Engineering , 2003 .

[20]  Samuel Labi,et al.  Incident Occurrence Models for Freeway Incident Management , 2003 .

[21]  Xin Wang,et al.  Are Incident Durations and Secondary Incidents Interdependent? , 2009 .

[22]  Pushkin Kachroo,et al.  Feedback Control Solutions to Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems , 2005 .

[23]  Sabiha Amin Wadoo,et al.  Pedestrian Dynamics: Feedback Control of Crowd Evacuation , 2008 .

[24]  Olivier Pourret,et al.  Bayesian networks : a practical guide to applications , 2008 .