Research On A Real Time Navigation Algorithm Avoid Traffic Jam Based On Simplified Road Network Model

In recent years, with the rapid development of economy and society in our country,urban transport has been facing with tremendous pressure. Under this condition, thepath navigation plays an important role on easing the urban traffic congestion, whichhas been intensively reported in domestic and foreign researches. Among these studies,road network models considering many transport elements, for example, intersectiondelay, could often give a solution for path navigation close to the real time traffic.However, single optimal path would readily induce the traffic fall into the "secondarycongestion”, while the recommendations of the multi-path are also difficult to avoidsuch problems in the unsaturated status of the transport network. That’s because mostof the multi-path algorithms fail to recommend an ideal path with high degreediscrimination. Based on the above problem, this thesis proposes a real-time networkmodel for path navigation much closer to the actual traffic conditions and studies onhow to prevent the traffic congestion.Main research topics of this thesis are as follows:①According to the fast changing urban traffic conditions, this thesis presents asimplified real-time network model, and based on this model designs a real-timenavigation algorithm—RTNA. The model is apt to collect real-time traffic data andalso considers the effect of various traffic factors, for instance, intersection delay, onvehicle running time. As a result, the algorithm RTNA can bring about dynamicalnavigation according to the latest release of real-time data and give the optimal path inthe present traffic conditions.②Study on the “second congestion” caused by the overuse of navigation systemin the same traffic direction. Firstly, in light of the problem that the present multi-pathmethods can’t put forward paths with higher difference degree, this thesis advancesMI-Genetic algorithm based on simplified real time road network model. Thisalgorithm takes the difference function as constraint, and would give k paths withhigher difference degree. Secondly, on the basis of MI-Genetic algorithm we alsopropose a navigation algorithm-ATRN. It may guide vehicles in the same way to shuntinto multi-level running directions, thereby precluding “second congestion” caused byoveruse of navigation system.③Test and verify the correctness and effectiveness of the proposed algorithms.1) Compared with the TDNA (Time Division Navigation Algorithm), algorithm RTNAcan adjust the guidance dynamically according to the traffic information, and showsobvious real-time effect.2) Algorithm ATRN can recommend real time multi-pathnavigations with higher difference degree and realize multi-stage shunt.The navigation algorithms disclosed in this dissertation may fulfill the real-timedemands of path navigation in urban traffic, help to relieve traffic congestion, and haveimportant reference value for related academic and applied research.