Intersection Group Dynamic Subdivision and Coordination at Intraregional Boundaries in Sudden Disaster

This paper aims at the traffic flow agglomeration effect characteristics and rapid evacuation requirement in sudden disaster; operation time of intraregional boundaries traffic signal coordination was presented firstly. Then intraregional boundaries intersection group dynamic subdivision and consolidation method based on relative similarity degree and similarity coefficient of adjacent intersections was put forward. As to make the traffic control strategy adapt to traffic condition of different intraregional boundaries intersection groups, this paper proposes an intraregional boundaries traffic signal coordination and optimization technology based on organic computing theory. Finally, this paper uses Delphi 7.0, MapX, and Oracle developing a software package, combined with Paramics V6 Simulator to validate the methods of this paper. The result shows that it can obviously improve disaster affected regional traffic signal control efficiency which reduces average traffic delay by 30–35%, decreases vehicle queue by more than 20% and reduces evacuation time more than 13.06%.

[1]  James E. Moore,et al.  Statistical designation of traffic control subareas , 1985 .

[2]  Marcel Urner Complex Decision Making Theory And Practice , 2016 .

[3]  Yiming Bie,et al.  An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections , 2013 .

[4]  Cengiz Kahraman,et al.  Fuzzy Multi-Criteria Decision Making: Theory and Applications with Recent Developments , 2008 .

[5]  Markos Papageorgiou,et al.  Applications of the urban traffic control strategy TUC , 2006, Eur. J. Oper. Res..

[6]  Henrikas Pranevicius,et al.  Knowledge based traffic signal control model for signalized intersection , 2012 .

[7]  Michael M. Richter,et al.  Intelligence and Artificial Intelligence , 1998, Springer Berlin Heidelberg.

[8]  Yu-Ting Hsu,et al.  Risk-based spatial zone determination problem for stage-based evacuation operations , 2014 .

[9]  Soon-Chul Kim,et al.  Structure of attractive and repulsive hard-core Yukawa fluids: Density functional perturbation theory , 2011 .

[10]  J H Chandler THE ORGANISATION OF TRAFFIC CONTROL IN METROPOLITAN AREAS , 1984 .

[11]  Shing Chung Josh Wong,et al.  Group-based optimisation of signal timings using the TRANSYT traffic model , 1996 .

[12]  James L Pline Traffic engineering handbook , 2009 .

[13]  Jörg Hähner,et al.  Decentralised Progressive Signal Systems for Organic Traffic Control , 2008, 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems.

[14]  Brian Wolshon,et al.  Traffic Engineering Handbook: Institute of Transportation Engineers , 2015 .

[15]  Jörg Hähner,et al.  Organic Traffic Control , 2011, Organic Computing.

[16]  Yang Zhaosheng,et al.  Interregional traffic signal coordination control under sudden disaster based on game theory , 2011 .

[17]  Baher Abdulhai,et al.  Real-Time Optimization for Adaptive Traffic Signal Control Using Genetic Algorithms , 2005, J. Intell. Transp. Syst..

[18]  Cengiz Kahraman,et al.  Fuzzy Multi-Criteria Decision Making , 2008 .

[19]  Navid Kalantari,et al.  The Optimization of Traffic Signal Timing for Emergency Evacuation using the Simulated Annealing Algorithm , 2011 .