Latent ringlike road traffic control system based on compound mechanism particle swarm optimisation algorithm

Urban traffic congestion is one of the most severe problems of everyday life in many cities. In an effort to deal with this problem, traffic control system technologies have concentrated in recent years on dealing with urban congestion. In the paper, a compound mechanism particle swarm optimisation (CMPSO) algorithm has been proposed, and the algorithm has been effectively used in dealing with the optimisation of city latent ringlike road traffic control system. In the algorithm, the tabu search algorithm and the particle swarm algorithm are combined effectively, and the tabu can offset the local optimums and avoid searching one solution repeatedly. Simulations show the CMPSO algorithm cannot only avoid premature convergence effectively, but also has powerful optimisation ability and higher precision. It makes the rate of delay and numbers of stopping reduce obviously.

[1]  Arjan Durresi,et al.  Real-time traffic routing over a multilayered satellite architecture , 2008, Int. J. Wirel. Mob. Comput..

[2]  Ganapathy Kanthaswamy,et al.  Control of dead-time systems using derivative free particle swarm optimisation , 2011, Int. J. Bio Inspired Comput..

[3]  Xianfang Wang,et al.  Hammerstein model identification using quantum delta-potential-well-based particle swarm optimisation , 2011, Int. J. Model. Identif. Control..

[4]  Ganzhao Yuan,et al.  Multilevel thresholding for image segmentation through Bayesian particle swarm optimisation , 2012, Int. J. Model. Identif. Control..

[5]  R Akcelik.  SIDRA 4.0 software status , 1991 .

[6]  Roman Prokop,et al.  Various approaches to control of systems with time-varying delay , 2011, Int. J. Model. Identif. Control..

[7]  Neeraj Sharma,et al.  Simulated annealing-based particle swarm optimisation with adaptive jump strategy for modelling of dynamic cerebral pressure autoregulation mechanism , 2011, Int. J. Bio Inspired Comput..

[8]  Tomoya Enokido,et al.  High-speed group communication protocol for exchanging real-time multimedia data , 2005, Int. J. Wirel. Mob. Comput..

[9]  Long Chen,et al.  Integrated control of semi-active suspension and electric power steering based on multi-agent system , 2012, Int. J. Bio Inspired Comput..

[10]  Zhihua Cui.  Performance-dependent attractive and repulsive particle swarm optimisation , 2009, Int. J. Model. Identif. Control..

[11]  Hongchi Shi,et al.  A two-level topology control strategy for energy efficiency in wireless sensor networks , 2010, Int. J. Wirel. Mob. Comput..

[12]  Z. Cui,et al.  A FAST PARTICLE SWARM OPTIMIZATION , 2006 .

[13]  Anirban Mukhopadhyay,et al.  An application of genetic algorithm method for solving patrol manpower deployment problems through fuzzy goal programming in traffic management system: a case study , 2012, Int. J. Bio Inspired Comput..

[14]  K Moller.  CALCULATIONS OF OPTIMUM FIXED-TIME SIGNAL PROGRAMS , 1987 .

[15]  Zheng Wang,et al.  Reconfiguration of shipboard power system using discrete particle swarm optimisation , 2012, Int. J. Model. Identif. Control..

[16]  Wang Chunlei.  Urban loop-road traffic-coordination-control system based on TWP-PSO , 2007 .

[17]  J P Silcock,et al.  SIGSIGN: A PHASE-BASED OPTIMISATION PROGRAM FOR INDIVIDUAL SIGNAL-CONTROLLED JUNCTIONS , 1990 .

[18]  Nagui M. Rouphail,et al.  SIMULTANEOUS OPTIMIZATION OF SIGNAL SETTINGS AND LEFT-TURN TREATMENTS , 1990 .

[19]  M. Chandrasekaran,et al.  Multimachine stability analysis using meta-heuristic PSO algorithm for HGTG and SGTG systems , 2012, Int. J. Model. Identif. Control..

[20]  Sugata Sanyal,et al.  To filter or to authorize , 2008 .

[21]  Amany M. Mohamed,et al.  Optimal sequencing of design projects' activities using discrete particle swarm optimisation , 2012, Int. J. Bio Inspired Comput..

[22]  Alaa F. Sheta,et al.  Evaluating software cost estimation models using particle swarm optimisation and fuzzy logic for NASA projects: a comparative study , 2010, Int. J. Bio Inspired Comput..

[23]  Giulio Erberto Cantarella,et al.  Control system design for an individual signalized junction , 1984 .

[24]  Jianchao Zeng,et al.  Recurrent hidden Markov models using particle swarm optimisation , 2011, Int. J. Model. Identif. Control..