The Role Of ITS In Evacuation RouteOptimization For Emergency Vehicles

In this paper the application of ITS (Intelligent Transportation Systems) in road evacuation in the case of route optimization for emergency vehicles is reported. The ITS are usually used in transport to analyse the data and improve the system performances. In road evacuation, the ITS can be used at three levels: survey and transmission, control and user information. This structure allows managing an evacuation starting from the network monitoring and defining the optimal strategies to apply to speed up the evacuation procedure.

[1]  Francesco Russo,et al.  Planning in road evacuation: classification of exogenous activities , 2011 .

[2]  Asad J. Khattak,et al.  Selection of Source and Use of Traffic Information in Emergency Situations , 2011 .

[3]  G. Chilà,et al.  Safety of users in road evacuation: demand models , 2007 .

[4]  Zimin Zhang.  AN OPEN URBAN EMERGENCY DECISION SUPPORT SYSTEM , 2008 .

[5]  Francesco Russo,et al.  Demand Models in Road Evacuation: A Synopsis of Recent Contributions , 2011 .

[6]  Eiichi Taniguchi,et al.  INTELLIGENT TRANSPORTATION SYSTEM BASED DYNAMIC VEHICLE ROUTING AND SCHEDULING WITH VARIABLE TRAVEL TIMES , 2004 .

[7]  Paul Beynon-Davies,et al.  Human error and information systems failure: the case of the London ambulance service computer-aided despatch system project , 1999, Interact. Comput..

[8]  Kien A. Hua,et al.  Leveraging e-transportation in real-time traffic evacuation management , 2007, Electron. Commer. Res. Appl..

[9]  Antonino Vitetta,et al.  Safety of Users in Road Evacuation: Design of Path Choice Models for Emergency Vehicles , 2007 .

[10]  Kay W. Axhausen,et al.  The potential of information provision in a simulated road transport network with non-recurrent congestion , 1995 .

[11]  Brian Wolshon,et al.  Alternative Methods to Increase the Effectiveness of Freeway Contraflow Evacuation , 2004 .

[12]  Serge P. Hoogendoorn,et al.  Evacuation modeling including traveler information and compliance behavior , 2010 .

[13]  Eiichi Taniguchi,et al.  Travel Time Reliability in Vehicle Routing and Scheduling with Time Windows , 2006 .

[14]  Francesco Russo,et al.  A Statistical Approach to Analyze User Behaviour in Road Evacuation , 2011 .

[15]  F. Russo,et al.  An assignment model with modified Logit, which obviates enumeration and overlapping problems , 2003 .

[16]  Flavien Balbo,et al.  Using intelligent agents for Transportation Regulation Support System design , 2010 .

[17]  William H. K. Lam,et al.  A model for assessing the effects of dynamic travel time information via variable message signs , 2001 .

[18]  Jyh-Hone Wang,et al.  Disseminating Information with Variable Message Signs during Natural or Human-Caused Disasters , 2007 .

[19]  Joaquín de Cea Ch.,et al.  Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion , 2009 .

[20]  Francesco Russo,et al.  Safety of Users in Road Evacuation: the Logical Framework Approach in Evacuation Planning , 2008 .

[21]  Antonino Vitetta,et al.  Risk evaluation in a transportation system , 2006 .

[22]  Liping Fu,et al.  Decomposing Travel Times Measured by Probe-based Traffic Monitoring Systems to Individual Road Segments , 2008 .

[23]  Srinivas Peeta,et al.  Identification of vehicle sensor locations for link-based network traffic applications , 2009 .

[24]  A. Tsakalidis,et al.  Integrating GIS, GPS and GSM technologies for the effective management of ambulances , 2001 .

[25]  Francesco Russo,et al.  Safety of Users in Road Evacuation: Planning Internal Processes and Guidelines , 2007 .

[26]  Francesco Russo,et al.  The planning process and logical framework approach in road evacuation: a coherent vision , 2011 .

[27]  Giuseppe Musolino,et al.  Safety of Users in Road Evacuation: Supply ad Demand-Supply Interaction Models for Users , 2007 .

[28]  W. Wallace,et al.  Decision Support Systems for Disaster Management , 1985 .

[29]  Kouichi Taji,et al.  Group decision support for hazards planning and emergency management: A Group Analytic Network Process (GANP) approach , 2007, Math. Comput. Model..

[30]  G. Chilà,et al.  Safety of Users in Road Evacuation: Modelling and DSS for Demand , 2009 .

[31]  Antonino Vitetta,et al.  Reverse assignment: calibrating link cost functions and updating demand from traffic counts and time measurements , 2011 .

[32]  M Hallenbeck,et al.  EQUIPMENT FOR COLLECTING TRAFFIC LOAD DATA , 2004 .

[33]  Ted Smith,et al.  Evacuation Management Operations Modeling Assessment: Transportation Modeling Inventory , 2008 .

[34]  Suleyman Tufekci,et al.  An integrated emergency management decision support system for hurricane emergencies , 1995 .

[35]  Antonio Iera,et al.  An experimental station for real-time traffic monitoring on a urban road , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[36]  Martin Trépanier,et al.  Road network monitoring: algorithms and a case study , 2006, Comput. Oper. Res..

[37]  Tiejun Wang,et al.  Research on the Method of Dynamic Emergency Rescue Vehicle Routing Based on Real-time Information , 2010, ICE-B 2010.

[38]  Francesco Russo,et al.  Safety of Users in Road Evacuation: Modelling and DSS for LFA in the Planning Process , 2009 .

[39]  Yasuhiro Shiomi,et al.  Model for Location of Medical Facility and Evaluation of Vulnerability and Accessibility of Road Network , 2011 .

[40]  E. Gutiérrez,et al.  A network-based analysis of the impact of structural damage on urban accessibility following a disaster: the case of the seismically damaged Port Au Prince and Carrefour urban road networks , 2011 .

[41]  G. Chilà,et al.  Safety Of Users In Road Evacuation:RP Vs. SP Surveys In Demand Analysis , 2008 .

[42]  Hai-Jun Huang,et al.  A multiclass, multicriteria logit-based traffic equilibrium assignment model under ATIS , 2007, Eur. J. Oper. Res..

[43]  Li Jie,et al.  Monitoring travel times in an urban network using video, GPS and Bluetooth , 2011 .