Multi-mode trip chain optimization method and system facing to integration trip

Abstract

The invention discloses multi-mode trip chain optimization method and system facing to integration trip. Selectable trip routes, containing multiple trip modes and combinations thereof, are divided until non-dividable units; and with consideration of real-time data, short-time prediction, user preference and the like, the utilization coefficient of each non-dividable unit is calculated; and then on the basis of different targets including convenience, reliability, economy, comfort and the like, generalized costs of the available trip routes are calculated so as to form a whole trip chain alternative route sequence, which satisfies user demands, and a recommended trip route is pushed to the user. The method and the system can integrate information of multiple trip modes and can recommend trip schemes, at trip chain level, including parking, bicycles and the like comprehensive trip modes; and meanwhile, trip modes and user intention are combined, so that a specific trip mode is supplied for the user; the trip route is individually pushed and recommendation of differentiation trip modes is supplied, so that individual trip server level is greatly improved.

Description

technical field [0001] The invention relates to the field of travel plan recommendation, in particular to a multi-mode travel chain optimization method and system for integrated travel. Background technique [0002] Among existing network services, such as AutoNavi and Baidu API, they can provide travel solutions with multiple paths between any origin and destination. Taking Baidu Maps as an example, Baidu Maps pushes a variety of travel plans based on the location of the origin and destination. The travel plans include public transportation, self-driving, walking and other travel methods, including the shortest time and shortest routes. However, the commonly used travel plans such as those pushed by Baidu Maps only provide basic plans such as the shortest route, the shortest time, and the smallest cost, which have little correlation with the personal attributes of the traveler, and also need to choose the travel mode manually. If you need to choose self-driving Or the bus....

AI Technical Summary

Problems solved by technology

However, the commonly used travel plans such as those pushed by Baidu Maps only provide basic plans such as the shortest route, the shortest time, and the smallest cost, which have little correlation with the personal attributes of the traveler, and also need to choose the travel mode manually. If you need to choose self-driving or bus

In addition, with the gradual promotion of public bicycles, public bicycle travel will fill more of the vacancies of bus terminal travel, but the method and route selection scheme recommended by Baidu Maps does not appear that public bicycle travel can achieve the ratio between multiple routes. selection and recommendation

Therefore, the travel plan pushed by Baidu Maps does not take into account the personal attributes of public bicycles and travelers, as well as environmental attributes such as departure time, and the final recommended travel plan is single and not rich enough.

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