Payment intention-based flexible bus stop grading and transforming method

Abstract

The invention discloses a method for classifying and transforming flexible bus stops based on willingness to pay, comprising steps: 1) selecting the scope of a flexible bus service mode to be provided, obtaining passenger demand information, and collecting basic data of passenger demand points; 2) ) Screen the effective information of passenger demand points, input corresponding evaluation indicators, evaluate the demand points, and output the scores of each demand point; Initial probability of demand response; 4) Combined with passengers' willingness to pay, convert the grades of some demand points, adjust their demand response probability, and obtain the final demand response probability of each demand point, which provides a basis for subsequent scheduling work. The method can enable passengers to know the situation of the station and adjust the demand response probability of the station according to the willingness to pay, and carry out reasonable scheduling under the premise of effectively ensuring the transportation efficiency, which has practical promotion value.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to the field of flexible public transportation in the smart city traffic system, in particular to a method for classifying and transforming flexible public transportation stations based on willingness to pay. Background technique [0002] Demand-responsive public transportation can fully reflect the high-quality characteristics of the transportation process in terms of vehicle facilities, stops, service hours, comfort and safety, freedom and privacy. In smart cities where the mobile Internet is popularized, people who have long travel distances and do not have the ability to travel by car or bicycle, such as the elderly, weak, sick, disabled, pregnant and most low-income groups, they prefer to travel according to their wishes. Travel by bus, book a bus and express your willingness to pay, save the time and distance of arrival and departure (choose the nearest pick-up and drop-...

AI Technical Summary

Problems solved by technology

Different from the bus service of fixed routes, fixed points, fixed classes, and fixed models in traditional urban buses, demand-responsive buses provide humanized flexible schedules and ride-sharing services based on flexible routes according to passenger needs. There will be a large number of detours and stops on the line, which will affect the riding experience of passengers, and it is difficult to make up for the service gap between the one-to-one service online car-hailing and the intensive fixed bus; The "preparation" model based on passengers' choice of rides cannot fully express passengers' willingness to pay, and does not well link passengers' needs with their willingness to pay

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