A bus arrival time prediction method based on quantile convolutional network

Abstract

The invention discloses a bus arrival time prediction method based on the quantile convolution network, which performs two prediction modes of point prediction and quantile prediction for the bus arrival time, and extracts richer feature information from historical data , to better capture future uncertainty. Simultaneously, the present invention can overcome the problem that the historical data of some bus lines is sparse or sporadically unavailable, and utilizes a small amount of bus GPS data in the history and known changing characteristics (such as month, week, hour, whether to open bus-only Road, etc.), you can learn the complex mode of bus operation, and get the multi-step forecast results for a period of time in the future. In the future, the present invention can be applied to some specific bus routes where the interval between bus departures is too long and the GPS signal is unstable.

Description

technical field [0001] The invention relates to the technical field of bus travel time prediction, in particular to a bus arrival time prediction method based on a quantile convolution network. Background technique [0002] Conventional public transportation is the oldest urban public transportation mode in my country, and it is also the mode that undertakes the largest passenger traffic. Compared with rail transportation such as subways, it has a dense service line network and can be customized flexibility. [0003] However, in recent years, with the rapid development of urban rail transit, the rise of online car-hailing and slow-moving traffic, in most cities across the country, the public transport passenger volume and the proportion of passenger transport undertaken by conventional buses have shown a significant downward trend in recent years. [0004] Strong competition from other modes of transportation is the main external cause of the shrinking passenger volume of co...

AI Technical Summary

Problems solved by technology

[0004] Strong competition from other modes of transportation is the main external cause of the shrinkage of conventional bus passenger traffic. From the perspective of internal causes, conventional buses also have problems of insufficient attractiveness: slow travel speed, low punctuality rate of line services, and unpredictable travel time

This algorithm has a good performance in prediction accuracy, but the public transport system is essentially a dynamic random system: the road traffic volume changes with time, and the time distribution of traffic volume is random; residents' demand for rides fluctuates , the arrival of passengers at the bus station is random; the arrival time of the bus at the intersection is random, according to the queuing and arrival and departure characteristics of the bus at the intersection, the delay time of the bus intersection is affected by random factors

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