A Study on the Application of Baysian Approach to the Route Guidance System Planning

本研究的目的在于明确驾驶员路径选择意愿对路径诱导中网络流的影响。将路径选择行为模型由路段行程时间估计模型、路径变更模型和路径选择模型组成。路段行程时间估计模型采用贝叶斯方法对行程时间的概率分布进行修正。路径变更模型提供了重新考虑路径的机会，路径选择模型决定从当前计划路径变更为新路径，利用开发的路径选择行为模型，对科比市的城市场所进行了路径诱导系统的仿真。在不实施路径诱导的情况下进行仿真，确定一个参数，并将路段交通量与观测值进行比较。结果表明，尽管对高峰时段进行了处理，但路段交通量仍符合观测值。在实施路径诱导时的仿真结果表明，所设想的路径诱导系统所提供的交通信息的可靠性较低。然而，如果将该交通信息添加到路径选择行为的判断数据中，感应车不会变得不利。这是当感应轿厢增加时取消问题的可能性的结果。

The purpose of this study is to make the influence which route choice behaivior by driver gives the network flow in route guidance clear. We made route choice behavior model to compose from the link travel time estimate model, the route change model and the route choice model. The link travel time estimate model corrects probability distribution about the travel time using Baysian approach. The route change model gives the opportunity of the route reconsideration and the route choice model decides a change into the new route from the present plan route.Using developed route choice behavior model, it executed the simulation of route guidance system for the city place in Kobe City. It did the simulation when not implementing route guidance to fix a parameter and it compared link traffic volume with the observation value. As a result, in spite of the dealing with the peak time, the link traffic volumes suited observation values. The simulation result when implementing route guidance showed a thing with the low reliability of the traffic information by the assumed route guidance system. However, if making add this traffic information to the data of the judgment for route choice behavior, the induction car never became disadvantageous. This is the result by which the possibility to cancel the problem when an induction car is increased is suggestive.