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Research On Key Technologies Of Large-scale Strategic Traffic Coordination And Control System

Posted on:2010-08-27Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:1102360272996159Subject:Traffic Information Engineering & Control
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With the rapid development and urbanization of cities, traffic congestion become heavier and have inverse influence on the function of cities.With the deeper research of traffic subject, the mode of allieviate traffic congestion is changed from infrastruce construction to management, for example:traffic signal control system and traffic guidance system, to inhance the operation potential of infrastructure.Worldwide experts ,scholars and engineering technicians are paying more attention to the two system.After several decades of research, some achievement are obtained,such as TRANSYT of USA and UK,SCATS of Austrilia,SCOOT of UK, RHODES and OPEC of USA, KYOSAN of Japan and ITACA of Spain.Several tens of big cities in China imported and applied these advanced systems.These system have some effect on the allievating traffic congestion to some extent, however,it could not efficiently avoid traffic congestion and allieviate traffic congestion.Meanwhile, countries all around the world have construted traffic guidance sytem, such as VICS and DRGS of Japan, TRAVTEK of USA,ALI-SCOUT of Europe. In our country, the guidance by broadcast and VMS on freeway, expressway and some urban road are constructed, but there isn't a shaping and complete traffic guidance system.Acoordig to the above analysis, within the research of traffic signal control and traffic guidance system, some questions still exist, which are as follows:(1)The two systems are constructed isolately, it is difficult for the information to share with each other and the strategies to coordinate with each other;(2)The existed traffic signal control system is designed without considering the saturated traffic flow. Facing current saturated traffic flow, for the congestion caused by saturated flow, the existing signal control system is unable to solve.(3)The existed traffic signal control system only have the function of adaption, they do not have intelligence and self-organization. The signal timing is ajusted within small step as the traffic flow changes, they do not have the ability to coordinate the traffiic flow of all node within the roadnetwork macroscopicly;(4)In the existed traffic signal control system, the regional control strategies are fixed, they could not adapte to the traffic flow flexiblely;what'more, the control strategies could coordinate among regions, so it could not adjust traffic flow by space resource and time resource, which aggravate traffic congestion and could not rapidly evacuate traffic congestion;(5)The existed traffic information infrastructure could not meet the needs, which are variety of information, high accuracy and low cost, of traffic signal control and traffic guidance.Under this backgroud, the national science and technology department establish"863 plan"project.Jilin University and Shanghai Baokang cooperated to develop Novel Intelligent Traffic Control System(NITCS).Large-scale Strategic Traffic Coordination System(LSTCS) is the central subsystem of NITCS.It is also the subsystem with higher intelligence and function of macrosopic decision The research on the key technology of LSTCS offers technical guarantee for NITCS. It has strong theory value and big significance. Therefore, depending on the national"863 plan"project( 2006AA11Z228, 2007AA11Z245 and 2007AA12Z242), this disseration aims to research on LSTCS. The dissertation is divided into 7 chapters. The 2nd,3rd,4th,5th,6th chapter is the focuse. The 1stand 7th chapter introduces the backgourd, significance, research clues and the whole disseration summery and prospects.The main key technologies of this disseration involves:Achitecture desgin of LSTCS, Travel time extraction tehnology based on cellular phone probe car, Traffic information fusion technology based on fixed detector and probe car,Dyanmic OD estimation technology based on cellular phone probe car and Large-scale strategic traffic coordination control strategies and models, which are as follows:(1) Achitecture desgin of LSTCSFirstly, this disseration establish the system composition and logical architecture of NITCS based on dynamic hierachical coordination theory of large-scale system. Comparing to the traditional traffic signal control system, the difference and characteristic are proposed. Meanwhile, the system composition, physical architecture, logical architecture and system functions of LSTCS are mainly proposed, which break through the limitation of tradtional signal control system, which only has center supervising function.(2) Travel time extraction tehnology based on cellular phone probe carAnalysis and introduction of state-of-art of this technology and cellular phone location technology are offered.The travel time extraction process based on cellular phone hand over is introduced. The travel time extraction process based on cellular phone latitude and longitude information is mainly proposed. Different from GPS, the celllar phone location has the charateristis of long sampling interval and low accuracy of location. Considering these questions, the travel time extraction process, the pretreatment methods, the map matching method under long sampling interval and single car travel time assignment method based on probability. What else, the link average travel time statistical method under sufficient samples and unsufficient sample are proposed.The field position data and simulation data of Changchun roadnetwork are applied to test the above methods.It is conluded that the above methods have good accuracy and efficiency.(3) Traffic information fusion technology based on fixed detector and probe car Analysis and introduction of state-of-art of this technology is offered. The travel time estimation based on g factor of single loop detector is proposed. In this dissertation, the estimated travel time from fixed loop detector and probe car are fused. A fusion method based on adaptive weighed average are proposed, in which the adaptive weight is computed by the dynamic error; Futhermore, the wavelet analysis are applied to the travel time fusion.Then, the result of the above method are used as the input, the nonlinear combination fusion method based on BP neural network is proposed. VISSIM simulated data of Changchun roadnetwork are applied to test the above methods.The results show that both of above methods have good accuracy. The fusion accaracy based on BP neural network has higher accuracy. The fusion method inhances the accuracy of the single resouce data.(4) Dyanmic OD estimation technology based on cellular phone probe car According to classification by the time dimension, OD mapping method, model estimation level, operation modes, the used roadnetwork and data collection method, the OD estimation state-of-art are analyzed. The prior OD collection process based on cellular phone base station is introduced. The prior OD collection method based on cellular phone longitude and latitude is maily proposed,including cellular phone probe car runing situation identification based on labelling algorithm, the OD sampling expansion method based on simple coefficients and fillment and reference method.What'more, the state space model of dynamic OD estimation based on kalman filter are established.The assignment matrix estimation method and kalman filter algorithm are also proposed. The field data and simulated data of Changchun roadnetwork are applied to test these methods.The results analysis show that the above methods has good accuracy and efficiency and could meet the need of real-time dynamic OD application.(5) Large-scale strategic traffic coordination control strategies and models The state-of-art of this technology is offered.According to requirement of the real saturated traffic flow, the Large-scale strategic traffic coordination control strategies are made up of region strategic traffic control strategies, traffic coordination control strateiges among regions and traffic coordination control strateiges of regional boundaries. This dissertation analyzes the influence factor of regional strategic traffic control strategies and establishs a regional strategic traffic control strategies optimization method based on hierachical support vector machine;Then, the running opportunity of traffic coordination control strateiges among regions and the traffic coordination control models among regions based on dynamic OD are proposed. On basis of regional boundary traffic situation identification, a regional boundary coordination control model based on fuzzy control is proposed. The VISSIM simulated data of Changchun roadnetwork are applied to test these methods.It comes to conclusion that the proposed strategies and methods have good efficiency and feasibility.It could inhance the control benefit of the whole system and efficiently allieviate traffic congestion.This disseration aims to break through traditional traffic signal control system's limitation, enrich traffic information collection methods, enhance traffic information accuarcy, faster the integration of traffic signal control and traffic guidance, decrease traffic congestion and improve travel environment. Using several advanced methods, such as probability method, statistics method and artificial method, to research on the key technologies of LSTCS.It offers key technology basis for the construction of LSTCS and NITCS.At present, the ownership of cellular phone is already 0.608 billion.In the future, the ownership will be incresed.Therefore, the traffic collection technology based on cellular phone probe car will have large market prospect.Meanwhile, with the ehanced understanding of traffic manager and increased signal control nodes, the LSTCS, which has the characteristics of intelligence and macrosopic coordination, will achieve widely engineeing application and improve traffic congestion of cities.
Keywords/Search Tags:large-scale, strategic traffic coordination control, cellular phone probe car, dynamic OD estimation, traffic information fusion, travel time extraction, hierachical support vector machine, fuzzy control
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