Traffic flow database generation method based on time slice division

Abstract

The invention discloses a traffic flow database generation method based on time slice division. The method comprises the steps that the historical traffic flow information of a road i is acquried; according to the traffic flow information, the traffic flow curve of each period of every day of the road i is acquired; a first peak point X (im1) and a second peak point X (im2) on the traffic flow curve are used as cut-off points, curves fi (xi) and gi (xi) are fitted; fi (xi) and gi (xi) are respectively divided into N / 2 time slices, and a split point is seeked, so that the area enclosed by a step function and the fitted curves are the smallest; the traffic flow of each time slice of the road i is set; steps from 1 to 5 are repeated, and the traffic flow of each time slice of other roads are calculated to form a traffic flow database. According to the method, according to the historical traffic flow information of each period of the whole road network topology, the daily traffic flow curve of each road is divided into a number of time periods according to a peak division method; different traffic flow can be preset in different periods; and the database of the whole road network topology is generated.

Description

Technical field [0001] The invention relates to a method for generating a vehicle flow database based on time slice division. Background technique [0002] With the gradual modernization of the urbanization process, the increasing congestion of urban traffic has brought many problems to urban construction and life, especially the increase in personal car consumption in recent years, and the scarcity of land resources, resulting in a high-density living environment and high-flow traffic The contradiction between supply and demand, leading to traffic congestion is an important factor that seriously hinders the further development of the city. In the traffic road network, finding the optimal route between any two points is the basic function of travel navigation. The optimal path is generally the path with the shortest distance or the path with the shortest time. [0003] In the field of intelligent transportation, the core module: path planning, often determines the pros and cons o...

AI Technical Summary

Problems solved by technology

However, in the current intelligent transportation system, the path planning follows the preset road network topology, and the same road is always given between the same source and destination nodes, and the path planning is not carried out intelligently due to different time periods and different traffic volumes. To adapt to the change of traffic flow, the path given in this way is often not the global optimum in the whole time period, nor can it reach the local optimum, which will cause serious congestion on some road sections and enter a vicious circle, while some roads are abnormally smooth. It causes a great waste of resources, and it takes too long for users to travel, and the distance is too long, which reduces the time efficiency and energy utilization efficiency

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