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Flow prediction method for urban shared travel

A flow forecasting and urban technology, applied in traffic flow detection, traffic control system of road vehicles, instruments, etc., can solve problems such as traffic congestion that cannot be cured

Active Publication Date: 2021-11-30
SOUTHEAST UNIV
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  • Abstract
  • Description
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Problems solved by technology

However, the practical experience of various countries in relieving traffic congestion shows that blindly building more roads cannot solve the problem of traffic congestion, and may even encourage more people to drive on the road invisibly

Method used

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  • Flow prediction method for urban shared travel
  • Flow prediction method for urban shared travel
  • Flow prediction method for urban shared travel

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Embodiment Construction

[0049] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0050] The present invention designs a flow prediction method for urban shared travel, such as figure 1 As shown, the specific implementation process is as follows.

[0051] 1) Obtain the topology of the complex network according to the urban traffic network.

[0052] According to the geographical location and traffic elements of urban traffic, each area of ​​the city is divided into multiple traffic districts. Each traffic district can be the source of traffic trips, called the starting point or O point of traffic trips; it can also be the attraction source of traffic trips, called the destination point or D point of traffic trips. A pair of origins and destinations consisting of an origin and an destination is called an OD pair, denoted by w. The set of all OD pairs in the transportation network is denoted by W. The traffic flow betwe...

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Abstract

The invention discloses a flow prediction method for urban shared travel. The method comprises the steps of obtaining a topological structure of an urban traffic network, obtaining a travel mode and related data in the urban traffic network, and obtaining an OD traffic demand in the urban traffic network; constructing an urban multi-mode random P2P ride-sharing user balanced traffic network, and establishing a traffic demand constraint and a ride-sharing matching constraint of the network; calculating the generalized travel cost of the traveler from multi-angle comprehensive consideration of travel time perceived by the traveler, in-vehicle comfort loss and a hitchhiking online operation mechanism; and carrying out flow distribution on the network based on the logit travel selection behavior and the random P2P ride-sharing user balance principle to obtain the path traffic flow of the urban multi-mode complex network. According to the invention, the traffic flow of the modern urban traffic network can be effectively predicted, so that a reliable basis is provided for related departments to formulate management measures and industrial standards.

Description

technical field [0001] The invention belongs to the field of urban traffic engineering, and in particular relates to a flow prediction method for urban shared travel. Background technique [0002] With the increase of private car ownership year after year, traffic congestion has become one of the most important problems faced by city managers. However, the practical experience of various countries in alleviating traffic congestion shows that blindly building more roads cannot cure the problem of traffic congestion, and may even encourage more people to drive on the road invisibly. Riding rides (also known as shared rides, ridesharing) gather travelers whose travel trajectories partially or completely overlap into one vehicle, and reduce the number of motor vehicles on the road and ease traffic by improving the utilization of space in the vehicle. The problem of congestion has already been practiced in major cities in my country. These changes require that urban traffic flow...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G08G1/065
CPCG08G1/0129G08G1/065
Inventor 马捷王牵莲陈景旭
Owner SOUTHEAST UNIV
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