Key Technology Research On Urban Dynamic Route Guidance

As one of the effective ways to ease the urban traffic pressure, urban dynamic traffic guidance, by releasing guiding information to affect people on their way or to go out, can balance the traffic flow to maximize the traffic capacity of the traffic network at macro level, and help people save time and money for going out to maximize the effectiveness of road network traffic facilities at micro level. The focus of traffic guidance is to select the shortest path. The preference for path varies with each individual, and most people emphasize the travel time. The travel time of road section is an important parameter indicating the state of urban traffic network, which can visually reflect the road conditions. Based on the above analysis, this paper, focusing on the travel time of road section, is written to go into the three main technologies of dynamic shortest path guidance-traffic network model abstraction, short-term travel time prediction and dynamic shortest path searching algorithm.The paper mainly covers:1. The paper studies how the traffic network model is simplified by reducing considerations as far as possible without influence on the path planning effect, so as to respond to the navigation demand of travelers better. In the study, a simplified traffic network series model specific to urban traffic is put forward, which requires a little road information, while can indirectly reflect the effect of the real-time state (complicated factors such as delay due to different steering at intersection, traffic speed of road section, traffic light state, zebra crossing, etc.) of urban traffic on the travel time, simple and useful.2. Based on the above-mentioned simplified traffic series model, study is made on the method of real-time collection of travel time specific to the simplified traffic series model, and in-depth research on the key technology thereof-license plate recognition algorithm is carried out, of guiding and referential significance to the overall application of dynamic urban traffic guidance system subsequently. In order to obtain the travel time required for follow-up study to be made herein, and make up for the deficiency of the current backward urban intelligent traffic system, research on the method of travel time collection based on VISSIM microscopic simulation is made, and models are built based on the real road traffic information.3. A SVMR-based short-term travel time prediction model is put forward based on the data characteristics of travel time under simplified traffic network conditions, and the effectiveness and accuracy of the predication model are verified via VISSIM simulation data.4. Formulas for calculating the dynamic weight of road section are established, and the existing static shortest path search algorithm is improved. Besides, a dynamic shortest path search algorithm is put forward, which takes the effect of dynamic traffic information changes on travel time into account. The guidance plan based thereon can satisfy the actual needs better. The feasibility and effectiveness of the algorithm are verified via Visual Studio complier development tools.The key technologies of urban dynamic route guidance put forward herein are of certain referential value academically and practically to addressing the actual need to solve dynamic path guidance, relieving the urban traffic pressure, and raising the travel efficiency.