| As urbanization process of the city grows steadily,meanwhile,the global car ownership is also rising rapidly,which also caused a series of social problems,such as traffic jams,environmental pollution and noise pollution,etc.Intelligent transportation system(ITS)came into being,and ITS,which can provide comprehensive,real-time,accurate and efficient service information is a comprehensive research subject incorporating information,communication,control and network technology into an organic whole.ITS is a great potential research,what is more,it will become a hotspot of relevant research fields.Dynamic route guidance system(DRGS)is an important branch of ITS,which provides real-time traffic information and optimal path for travelers by using the modern technology such as computers,communication networks.As the core technology in DRGS,the model can determine the optimal target of DRGS and the optimization algorithm can improve the efficiency of route guidance system to meet the real-time traffic environment.Therefore,this paper has made researches on modeling and optimization algorithm of DRGS respectively.1.Route-Choice Model.In real-time environment,the factors that affect the path selection of the walkers are diversified including cost,time,distance,pollution and so on.But most of the current route-choice models are based on single objective.In view of this,a route choice model based on multi-objective is constructed which is respectively considered from the angle of cost and time in this paper.In real-time environment,it analyzes of the generation of link impedance under the circumstances of smooth and congestion roads so as to build the shortest time objective function.On the basis of the above,the route-choice mode based on the lowest cost is constructed.The weighted sum method is used to aggregate the multi-target data objects to get the composite weight value while the weight coefficient can be set on the basis of travelers' needs or preferences.In order to more precisely response feedback results,in this paper,the multi-objective function values are preprocessed with similar magnitudes which can be balanced by the decision variables in the aggregate objective function of the dominant power.To verify the practical value of the model,the experimental environment is simulated by C++ and data is based on the VISSIM simulation combined with practice to reasonable setting.In the simulation environment,the model is compared with the route choice model based on the shortest distance of geometry.Experimental results show that the path of multi-objective optimal route choice mode has more practical value based on real time environment.2.Path Optimization AlgorithmIn the dynamic route guidance system,the traffic information is real-time and dynamic.Therefore,this paper proposes a hybrid dynamic path optimization algorithm in real-time environment which based on generalized adaptive A* algorithm and combined with pruning algorithm.Meanwhile,this thesis puts forward the optimized strategy of introducing PSO local optimal and global optimal intelligent storage and fuzzy time window into the hybrid dynamic path optimization algorithm.Pruning threshold based on the local optimum so as to effectively control the size of the threshold to avoid the threshold is too large or too small results.The fuzzy time window is applied to algorithm optimization time constraints and the control of simulation time so that the algorithm can better adapt to the real-time system.In order to verify the algorithm,the experimental environment is simulated by C++ and data is based on the New York map data.During simulation,the algorithm is verified the effectiveness of the optimization strategies,at the same time,the algorithm is compared with A* algorithm.The comparative experiment and analysis demonstrate that the optimization strategies have certain adaptability in the dynamic path optimization algorithm,moreover,it is proved that the algorithm can be applied to DRGS. |
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