Dynamic Traffic Assignment Modeling And Implementation Based On Traveler Behavior

In recent years, urban developmentprocess only cost a short span of30yearscompare with western developed countriesnearly a centurywith the rapid development ofurban construction in China. A strong traffic demand was released by a big strideforwardon the development of cites, which leads to prominent contradiction between supply anddemand increasingly. The traditional method to solve the traffic problem has been provedto be useless as to purely increase supply by the new roads. New roads tend to inducenew travel demand, and the balance always lay the demand rather than the supply. Hence,the single method of increasing new road is not reasonable. Eventually, it can alsoexacerbate the contradiction of land resources. Consequently, the effective measure toalleviate the prominent contradiction and improve the network running efficiency is byusing intelligent traffic management under the background of limited area of land.According to “National medium and long-term science and technology developmentplan (2006-2020)”, the topic of “intelligent traffic management system construction anddevelopment” is listed as a priority developing theme. Striving to develop the technologyof urban traffic guidance will be a hotspot in the future. This dissertation studied dynamictraffic assignment combined with travelers’ constraint based on "National Science andTechnology Support Plan" project and "National Natural Fund” Project, in order torealize the true intelligent traffic management and improve the road environment. Atfinal, these studies can be the foundation and support for improving the network runningefficiency.Based on the existing research on the basis of dynamic traffic assignment model,this dissertation analyzed the advantage and disadvantage of distributed dynamic trafficassignment and centralized dynamic traffic assignment respectively, aiming to proposea real-time and strategy update fast closed-loop centralized dynamic traffic assignmentmodel. The proposed strategy can effectively combine the advantage of the distributeddynamic traffic assignment strategy which is hereby form a new mechanism withinteractive feedback. Furthermore, it is to make up current open-loop of single inducedpatternand the dilemma of hard to solve. First of all, game mechanism of dynamic trafficassignment was introduced through the analysis of the network dynamic equilibriumbased on the research of existing theories. And then, the author designed a creative routechoice preference investigation method by selecting the significant factors which thetravelers feel the most obvious. These investigated data not only can be support for thedynamic traffic management but also can provide a brand new angle of the travel preference investigation. Afterwards, regional autonomy distributed dynamic trafficassignment model was proposed as well as in-vehicle route calculate solutions werediscussed. At the final, this dissertation constructed a centralized guidance framework tostudy the centralized dynamic traffic assignment confronted different user levelscombined the induce pattern with distributed and centralized by considering thedistribution of user groups. According to above studies, the results of proposed modelscan improve the intelligent traffic guidance efficiency meanwhile provide powerfultechnical method guarantee of developing network loading. The main research asfollows:（1）Network equilibrium modeling method based on the dynamic demandThis paper summarizes the existing modeling methods of traffic distribution first onthe basis of extensively reading network equilibrium theory researches. Then the paperanalyzes optimum traffic assignment model of dynamic system and user optimum trafficassignment model specially and proposes a method to study the process of dynamic gamebehavior using Stackelberg game behavior theory whose breakthrough point is thecontradiction between supply and demand of traffic as well as the necessity of theapplication of intelligent traffic guidance technology, combining with time-variantcharacteristics of dynamic traffic flow.（2）Route choice behavior modeling based on the expected benefitsConsidering the travelers’ subjective route choice preference and combining withreliability and uncertainty of travel time, this paper puts forward aroute choice behaviormodel based on the expected benefits which is on the basis of the applicability researchof expected utility theory and the expected utility theory in travel behavior. Besides, thispaper researches the behavior choice deeply under the condition of "risk" and "fuzzy"situation in the route choosing process of uncertainty condition, getting the functionrelationship between delay time probability and the probability of choice preference.Experimental results can well reflect choice behavior of road travelers in reality, whichhas a positive promoting role in making an accurate path preference estimates whentravelers are under the premise of no cognition on the path.（3）Continuous search method with multi-interest pointsThis paper proposes a continuous path search method which can meet travelers toaccess to more than one points of interest during a trip on the basis of detailed analysis ofvehicle shortest path algorithm and combination with the actual travel demand. Themethod is optimized in road network structure and data access mechanism and calculatesthe optimal travel paththrough the temporal and spatial relation reasoning of the adjacentarea of the interest points. The proposed path search method is verified byexperimentsand the results show that the new path search methodcan effectively improvethe computing performancecompared with the average nearest neighbor algorithm, to avoid unreasonable path of travel and meet the access requirements under different rulesof traveler.（4）The distributed dynamic traffic assignment model based on marginal traveltimeThis paper puts forward a distributed dynamic traffic assignment model based onmarginal travel time and gives the model solving algorithmin view ofthedifficultimplement of traditional traffic assignment methodin large-scale road networkand slow update of strategy, which is based on utility theory. The proposed distributedstructure providesa local real-time adaptive allocation strategy under limited information.This proposed method which is based on local control strategy can effectively responseto real-time network traffic flow changes, whose amount of calculation is less and updatespeed is fast. In addition, choosing model parameters and influence factors such asnetwork coverage (nodes) are verified numericallyrespectively.The proposed distributeddynamic traffic assignment method not only can effectively meet the needs of the systemrunning, but also provides a new train of thought and theory support for the constructionof guidance system in ITS.（5）Multiple users oriented center-basedguidance strategyThis paper analyzes the Stackelberg game behavior between distribution side andcenter from the perspective of game theory and combination with the distributed dynamictraffic assignment strategy advantage for central type induced traffic problems and putsforward a new interactive center type induction strategy and builds a multi-user inductionmodel based on Stackelberg model whose solution algorithm is given, geared to theneeds of different level users. The simulation results show that the proposed center typeinduction strategy can improve the system efficiency and effectively guarantee thestability of the system, perfectthe existing dynamic traffic assignment methodandprovides a theoretical support for the realization of the urban intelligent trafficmanagement technology.