Research On Methods Of Traffic Travel Service Composition Based On AI Planning

With the development of informationization in the transportation industry,the use of network resources to provide travelers with real-time and effective travel services has become an important application of urban intelligent transportation systems.However,the existing traffic travel service functions are relatively single,and it is particularly important to combine new services with specific values that provide functional value-added services and meet the needs of travelers.As the quality of service information is increasingly constrained by the traveler,the combined method under the design service quality affected is the current research focus.However,the existing service composition method is difficult to provide a suitable combination scheme according to the individual needs of the traveler.Therefore,this article has conducted in-depth research on the selection process of intelligent combination technology and service quality perception.Among them,the focus of work and innovation can be summarized by the following three points:1.Analyze Web service description language and the characteristics of traffic environment,point out the key issues of semantic description of traffic travel services,and build a model of traffic travel service description based on the classification of traffic areas and functional factors.The model enhances the semantic expressiveness of the unique attributes of the traffic environment while defining the traffic service specification.2.Aiming at the randomness of the existing hierarchical task network planning method in selecting the decomposition method,a hierarchical task network planning method based on the control strategy is designed to meet the functional requirements of the traveler.This method expands the scope of the search combination scheme by decomposing the full expansion method,and can accurately search for the optimal abstract service sequence.At the same time,in order to reduce the cost of planning calculations brought about by the full expansion method,short-term return factors and control factors are introduced,which effectively control the search space and play a regulatory role.3.The ant colony algorithm is applied to the service quality perception-based traffic travel service composition method to solve the optimized configuration of the traffic travel service so as to meet the non-functional requirements of the traveler.For the traditional antcolony algorithm,the early search is slow,and it is easy to fall into the local optimal solution in the later period.Combining the domain characteristics of traffic travel services,a strategy for path innovation,a strategy to reduce poor path interference,and a strategy for service evaluation on the distribution of initial pheromone are proposed.An improved ant colony algorithm for traffic travel service composition was designed.Finally,a traffic travel scenario is designed to verify the availability and effectiveness of the proposed algorithm.The results show that the hierarchical task network planning method based on control strategy can reduce the calculation cost;the improved ant colony algorithm for traffic travel service composition can quickly search for non-inferior solutions,and then provide a feasible solution for matching the traffic travel service composition that meets the needs of the traveler.