Combination model of traffic distribution and traffic flow assignment considering traveler's destination preference

A technique for combining models and travel distribution matrices, applied in the field of traffic engineering

Inactive Publication Date: 2021-09-03
SOUTHEAST UNIV
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Problems solved by technology

However, both approaches employ a gravity model to capture destination choice behavior and use only limited explanatory variables
However, the characteristics of travelers, especially their preferences for different destinations, cannot be given by the gravity model

Method used

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  • Combination model of traffic distribution and traffic flow assignment considering traveler's destination preference
  • Combination model of traffic distribution and traffic flow assignment considering traveler's destination preference
  • Combination model of traffic distribution and traffic flow assignment considering traveler's destination preference

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Embodiment Construction

[0077] Below in conjunction with accompanying drawing of description, the present invention will be further described:

[0078] Step 1: Build a travel distribution model considering traveler preferences

[0079] The polynomial logit model is the simplest and most popular discrete choice model for destination selection. It is based on random utility theory, assuming that a representative traveler living in region r will obtain random utility U from alternative destinations s rs . The utility consists of:

[0080] u rs =V rs +ε rs

[0081] Among them, V rs Indicates the utility that can be observed, ε rs Indicates utility that cannot be observed. The traveler is faced with some attribute of the candidate, which is defined as Therefore, V rs Can be expressed as:

[0082] V rs = β s +β 1 x rs 1+β 2 x rs 2+…+β k x rsk

[0083] Among them, β s is a candidate-specific constant that represents the average utility of all factors not included in the model, also kn...

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Abstract

The invention establishes a combination model of traffic distribution and traffic flow allocation considering traveler's destination preference. The widely used four-stage travel demand forecasting model in traffic planning has inconsistency problems, and the gravity model used in existing solutions for traffic distribution has great limitations because it cannot fully reflect the decision-making behavior of travelers. Some key variables that play an important role in destination choice are not included, the most prominent of which is traveler destination preference. Therefore, the present invention establishes a combined model of traffic distribution and traffic flow allocation considering traveler's destination preference. The main steps include: (1) building a travel distribution model considering traveler preferences; (2) building a travel allocation model under user equilibrium; (3) building a simplified four-stage model with feedback; (4) using constant weight iterations The weighted method (MSA) is used to solve the model; (5) The specific implementation is described in combination with the Nguyen‑Dupuis network commonly used in traffic network analysis.

Description

Technical field: [0001] The invention establishes a combination model of traffic distribution and traffic flow allocation considering traveler's destination preference, and belongs to the technical field of traffic engineering. Background technique: [0002] The four-stage model is a commonly used model for forecasting travel demand, and is usually composed in the order of trip generation, trip distribution, traffic mode division, and trip allocation. That is, the output of the previous step is used as the input of the subsequent step. This method of forecasting is clear and understandable, and it is widely used in planning practice. However, the shortcoming of this method is also obvious, that is, the travel time (cost) in trip generation, trip distribution, and trip mode partitioning is not consistent with the travel time (cost) calculated in trip allocation. Therefore, complex feedback relationships must be resolved to obtain an equilibrium level of demand, even if the ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/30G06F17/18
CPCG06F17/18G06Q10/04G06Q10/06312G06Q50/30
Inventor 林宏志褚晨予
Owner SOUTHEAST UNIV
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