Bicycle lane service level evaluation method based on hybrid Gaussian model

A hybrid Gaussian model and non-motorized lane technology, which is applied in complex mathematical operations, instruments, data processing applications, etc., can solve problems that have a large impact, do not take into account riders' feelings, fluctuations, etc.

Inactive Publication Date: 2018-11-09
ZHEJIANG UNIV
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  • Abstract
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Problems solved by technology

Since non-motorized vehicles do not have a shell to isolate the rider from the external environment, the cycling environment has a greater impact on non-motorized vehicle riders
At present, there are few studies on the service level of non

Method used

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  • Bicycle lane service level evaluation method based on hybrid Gaussian model
  • Bicycle lane service level evaluation method based on hybrid Gaussian model
  • Bicycle lane service level evaluation method based on hybrid Gaussian model

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Embodiment Construction

[0071] Below in conjunction with accompanying drawing, the present invention is described in detail, as figure 1 Shown, concrete steps of the present invention are as follows:

[0072] Step (1) Collect non-motor vehicle traffic flow parameters of the road section including

[0073] c11. Investigate the basic information of non-motorized lanes to obtain the width and isolation form of non-motorized lanes;

[0074] c12. Statistical section traffic flow information

[0075] Among them, because there is no fixed lane for non-motor vehicles, the traffic flow is a statistical value under the unit width. Statize the traffic flow and the speed of each non-motorized vehicle within a certain period of time, obtain the flow q per unit width and the average speed data v of non-motorized vehicles within this period of time, and obtain the density information k through the relationship q=kv of the three parameters of traffic flow; The overtaking rate is calculated by the following formul...

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Abstract

The invention discloses a bicycle lane service level evaluation method based on hybrid Gaussian model. The method is suitable for the bicycle lane with physical isolation and belongs to the technicalfield of the transportation planning. The bicycle lane service level is the index for measuring the riding service provided for the rider by the bicycle lane. Compared with the motorcycle, the bicyclerider can directly feel the external environment, so that the feeling of the rider is the important basis for the service level ranking. Since the feeling of the people has large fluctuation, the soft classification method is more fit with the actual condition. The basic thought of the method is to judge the probability of service level corresponding to one traffic stream operation state by establishing the hybrid Gaussian model, thereby establishing the service level evaluation system. By adopting the soft classification feature of the hybrid Gaussian model, the evaluation result is closer to the feeling of the rider, and the theoretic support is provided for the planning, construction and management of the bicycle lane with physical isolation.

Description

technical field [0001] The invention is an evaluation method for the service level of non-motorized vehicles with physical isolation, adopts a mixed Gaussian model, considers the fluctuation of cyclists' feelings, and establishes a soft classification model. This evaluation method can serve the current situation evaluation, planning, design and management of non-motor vehicle lanes, and belongs to the field of traffic planning. Background technique [0002] With the continuous development of social economy, the living standard of residents has been greatly improved, and the number of car ownership has increased rapidly. As a result, traffic congestion and environmental pollution in the city have also been exacerbated. Currently, non-motor vehicle traffic is developing rapidly in some domestic cities. From public bicycles, electric bicycles to shared bicycles, the development forms of non-motorized vehicles have been continuously innovated, and they are also occupying an in...

Claims

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Application Information

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IPC IPC(8): G06F17/18G06Q10/06
CPCG06F17/18G06Q10/06393
Inventor 金盛徐亮周禹佳常伟王殿海
Owner ZHEJIANG UNIV
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