然而随着车辆越来越多，道路的拥挤程度越来越严重，现有的路径规划系统仅仅

然而随着车辆越来越多，道路的拥挤程度越来越严重，现有的路径规划系统仅仅规划出最短路线渐渐不能满足人们的需求，人们希望有一个能够考虑当前各种约束信息的规划路径系统，在路径规划系统中考虑当前交通状况，而只不是静态路径。本文对传统Dijkstra算法进行了数据的预处理和权值的优化，得到了改进的交通路径规划模型，仿真实验结果表明，该模型具有较快的运算速度和较高的准确度，并且鲁棒性较好

結果 (英文) 1:

However, as more and more vehicles, traffic congestion is getting worse, existing path-planning systems just work out the shortest route can't meet the needs of people, people wanted to be able to consider the planned route of current constraint information systems in path planning system considering current traffic conditions, but is not a static path. Data preprocessing for traditional Dijkstra algorithm and optimization of weight, traffic route planning model has been improved, and simulation results indicate that the model has faster operating speed and high accuracy and robustness

結果 (英文) 2:

However, with more and more vehicles, more serious road congestion level, the existing path planning system is only planning the shortest route gradually can not meet people's needs, people want to be able to consider a variety of constraint programming current path information system, regardless of the current traffic conditions in the path planning system, rather than a static route only. In this paper, the traditional Dijkstra algorithm is optimized pretreatment and weight data to obtain an improved traffic path planning model, the simulation results show that this model has a faster operation speed and high accuracy and robustness good

結果 (英文) 3:

However, as more and more vehicles, road congestion is becoming more serious, the path planning system of the existing just planning out the shortest route gradually can not meet people's needs, people hope there is an account of the path planning of the system current constraint information, the path planning to consider the current traffic system, but rather a static route. The optimization of data pretreatment and the weight of tradition Dijkstra algorithm in this paper, the traffic path planning model has been improved, simulation and experimental results show that, the model has fast calculation speed and high accuracy, and better robustness.