Bus-network-based system and method for predicting passenger requirements

Abstract

The invention discloses a bus-network-based system and method for predicting passenger requirements. According to the method, the unevenness, the abruptness, the periodicity and other factors are compressively taken into consideration, and predicting of the passenger requirements in a bus network is finally obtained through predicting models such as a Poisson model changing along with time, a Poisson model weighing time changing and a moving average model synthesizing autoregression and an integrating frame based on a sliding window. The demand of passengers obtained through prediction of the system and method can provide a more convenient, faster and more comfortable bus trip environment for the passengers, and therefore the bus waiting time of the passengers is shortened, and overcrowding or over loosening of buses is avoided.

Description

technical field [0001] The invention relates to a passenger demand prediction system and method based on a public transport network. Background technique [0002] Along with the rapid economic development, the transportation industry has developed rapidly, but the traffic situation has been deteriorating, resulting in a series of traffic problems: traffic congestion and road blockages are becoming more and more serious, traffic accidents occur frequently, and the resulting energy Consumption and environmental pollution have also attracted more and more attention from the society. Public transport, especially bus services, can effectively alleviate these problems. Bus service can effectively utilize existing transportation facilities, reduce traffic load and environmental pollution, ensure traffic safety, improve transportation efficiency, and improve the convenience and comfort of road users. In addition, buses are widely distributed and cheap, so they are increasingly fav...

AI Technical Summary

Problems solved by technology

[0006] In conclusion, the main shortcomings of existing methods are: 1. None of the current research works consider the real-time demand of passengers for bus services, which is the main factor in traffic management; 2. Many current research works assume that all The driver's active cooperation is the premise, and these assumptions are not feasible in most practical applications; 3. The existing research work has not considered the non-uniformity, suddenness and periodicity of passenger demand, which are in the It must be considered in the analysis of passenger demand, otherwise it will affect the final predicted passenger demand results; 4. The existing research work based on taxis has incomplete data

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