A travel route planning method and system combining a taxi and a subway

Abstract

The present invention provides a travel route planning method and system for a combination of taxi and subway. The method includes: receiving a route planning request sent by a user device. The route planning request includes: departure place and destination; and obtaining all the information according to the departure place and destination. A combined travel mode that can reach the destination. Each combined travel mode is a combination of taxi and subway. According to the starting point and end point of each mode of transportation in each combined travel mode, the travel mode is The route optimization model determines the optimal route among all combined travel modes; the optimal route is the shortest time route for the combined travel modes, or the optimal route is the least cost route for the combined travel modes; the optimal route is sent to the user device, and the user can conveniently The optimal travel route sent by the system of the present invention is obtained through smart devices such as mobile phones, thereby achieving the effects of optimizing travel routes, shortening travel time, and improving the predictability of travel time.

Description

Technical field [0001] The invention belongs to the field of computer technology, and in particular relates to a travel route planning method and system for a combination of taxi and subway. Background technique [0002] Urban rail transit has become the first choice for many citizens to travel because of its high speed, large capacity, and accurate time. However, as a skeleton transportation mode, urban rail transit has the characteristics of relatively low line network density and relatively sparse distribution of subway stations, which has caused the "last mile" problem. Therefore, it needs to be effectively connected with other modes of transportation to give full play to its transportation Advantage. However, the travel time from ground public transport to the subway station is less controllable, which may result in a longer overall travel time. Therefore, for people with high travel time requirements, shortening travel time and improving travel time predictability are urg...

AI Technical Summary

Problems solved by technology

[0003] The existing software is mainly based on the combined travel recommendation of bus + subway, which is not suitable for people who have high requirements for travel time (such as rushing to a meeting, rushing to the train station, going to the airport, etc.), the existing The route recommended by the software is a simple combination of several feasible schemes, lacking support for the overall optimization scheme with the goal of optimal time

In addition, the existing technology also provides a combination of travel modes based on taxi-hailing software, such as: taxis, special cars, express trains, ride-hailing and buses, etc., which are pure taxi-hailing optimization based on passenger orders, without combining public transportation such as subways. The tool has a single combination method and cannot meet the needs of various passengers

[0004] In the absence of big data analysis support, the traditional bus+subway and taxi+subway travel methods usually choose the nearest subway station as the subway connection point, but going to the nearest subway station is not necessarily the most economical travel plan For example, if there is congestion on the route to the nearest subway station, passengers will not be able to reach the subway station as soon as possible, or if the flow of people at the nearest subway station is too large, passengers will not be able to take the subway on time. Increased time for travel plans

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