One-button target search optimization method for intelligent vehicle-mounted information service terminal

Abstract

The invention provides a one-button target search optimization method for an intelligent vehicle-mounted information service terminal. The method comprises the following steps: S1, acquiring latitude and longitude coordinates of a point A1 where a vehicle lies and acquiring information of a surrounding target site Ck; S2, acquiring latitude and longitude coordinates of a point A2 where the vehicle lies after the vehicle runs for a time of delta t; S3, working out the distances between the point A1 and the point A2 and between the target site Ck and the point A1 as well as the point A2; S4, judging that whether the site Ck is a point in the forward path of the vehicle or not; S5, working out the shortest path of the points in the forward path of the vehicle and finding out the target in the minimum distance; and S6, invoking the latitude and longitude of the target site in the minimum distance and tagging in a map for navigation. The method not only can ensure that a user can obtain the optimal path to the best destination that is most suitable for the current travelling state and satisfy special requirements of the user, but also can allow the user not to select search results manually, so as to ensure safety driving of a driver and saving time for the user.

Description

technical field [0001] The invention relates to the technical field of computer software decision-making, in particular to a one-button target search optimization method for an intelligent vehicle-mounted information service terminal. Background technique [0002] In recent years, the speed of national urban construction and the development of the automobile industry have accelerated, the number of private cars has begun to increase sharply, and the urban road network and expressway network are also expanding, making the transportation network more and more complicated. Although the driver has more room to choose travel routes when traveling, the complexity of travel also increases at the same time. When an emergency occurs during driving and the car owner needs to find a nearby gas station or auto repair station, the existing on-board information terminal needs to locate first and then search for information on the surrounding gas stations or auto repair stations. The searc...

AI Technical Summary

Problems solved by technology

Dijkstra's shortest path algorithm itself is an NP problem, and the calculation is more complicated. If it is based on the consideration of predicting the end of the path, reverse elimination of the path, and optimizing the end of the path, the complexity will be greater, the calculation will be slower, and it will not be able to meet the growing demand. Therefore, a new target optimization method is needed to automatically screen and select

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