CN115830872B - Method for judging elastic influence of accident occurrence on bicycle use - Google Patents

Method for judging elastic influence of accident occurrence on bicycle use Download PDF

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CN115830872B
CN115830872B CN202211663826.7A CN202211663826A CN115830872B CN 115830872 B CN115830872 B CN 115830872B CN 202211663826 A CN202211663826 A CN 202211663826A CN 115830872 B CN115830872 B CN 115830872B
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bicycle
accident
influence
buffer area
usage
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CN115830872A (en
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郭延永
丁红亮
刘攀
刘佩
岳全胜
陈晓薇
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Southeast University
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Abstract

The invention discloses a method for judging the elastic influence of accident on bicycle use, which comprises the steps of collecting accident sample information, dividing time units according to accident time, dividing reasonable buffer areas according to accident places, collecting bicycle station information in the buffer areas, counting the bicycle use amount of each bicycle station in each time unit, and further counting the bicycle use amount of the buffer areas; according to the influence factors of the buffer area, combining the bicycle usage amount of the buffer area, and constructing a bicycle usage amount elastic model; and (3) applying a bicycle usage elastic model, and judging the influence of the variable quantity on the bicycle usage according to the influence coefficient. The accident occurrence is analyzed by calculating the change of the bicycle usage amount in the buffer area in unit time based on the influence of each influence factor on the bicycle usage elasticity. The method can better guide the traffic management department how to efficiently schedule the bicycles when traffic accidents occur.

Description

Method for judging elastic influence of accident occurrence on bicycle use
Technical Field
The invention relates to the technical field of traffic safety and public bicycles, in particular to a method for judging the elastic influence of accidents on the use of bicycles.
Background
In order to relieve urban traffic jam and improve urban traffic operation efficiency, governments in various places are actively pushing public bicycles to be used. In order to promote the use of bicycle, all increase or reduce the bicycle and throw in according to the condition of bicycle website use amount. The related patent, such as CN101038685a city bicycle common management system, only researches the unified management of the common bicycles. However, there is little research on the impact of bicycle usage at surrounding bicycle stations on the occurrence of uncertain events, such as traffic accidents, and there are many objective factors associated with the prior art that do not take into account the bicycle usage at the location of an uncertain event. At present, aiming at the occurrence of uncertain events, relevant factors can be comprehensively considered, the influence of the use elasticity of the bicycle can be judged, and the problem that the most reasonable use rate of the bicycle scheduling is needed to be solved is realized.
Disclosure of Invention
The invention aims at: the method for judging the elastic influence of the accident occurrence on the use of the bicycle is provided, and the elastic influence of the accident occurrence on the use of the bicycle is accurately estimated by dividing an influence buffer zone and setting unit time to consider influence factors.
In order to achieve the above purpose, a method for judging the elastic influence of accident occurrence on bicycle use comprises the following steps:
s1, acquiring sample information about occurrence time and place of each accident in a target area;
s2, presetting an accident occurrence time period based on accident occurrence time in sample information, and dividing time units for the accident occurrence time period; the method comprises the following steps: based on the time of accident, dividing the time unit of G hours before and after the accident in units of t minutes, wherein the time unit is as follows:
G i ={t 1 …t n },
wherein i is the number of the accident sample;
s3, presetting an accident occurrence buffer area according to the accident occurrence place in the sample information, and collecting bicycle station information in the buffer area; the preset accident occurrence buffer area specifically comprises the following components: an accident impact buffer area is established by taking the accident place as the center of a circle and the preset distance as the radius respectively, and the bicycle station information in the accident buffer area is correspondingly collected,
n i ={d 1 …d k }
wherein ni Preset distance buffer for accident i,d k Is a bicycle station within the buffer, where k > 1;
s4, counting the bicycle usage amount of each driving station in each time unit according to the time unit in the step S2 and the bicycle station information obtained in the step S3, and further counting the bicycle usage amount of the buffer zone; the bicycle usage amount of the statistical buffer zone is as follows:
wherein ,Q(dk ) The bicycle usage amount for each driving station in each time unit;
s5, collecting impact factors of the buffer area, and constructing a bicycle usage elastic model by combining the bicycle usage of the buffer area; the method specifically comprises the following steps of collecting influencing factors: road network density K ti Economical GDP ti Population P ti Number of bus stops D ti Bicycle usage M combined with buffer zone ti The elastic model of the bicycle usage is constructed as follows:
wherein ,is an influencing factor; epsilon is a model error term, alpha i Regression coefficient, beta, for each influencing factor 0 Constant terms for the model;
wherein C is the variance and covariance matrix of the random parameters, j is the number of random parameters,refers to other random and uncorrelated variables;
s6, applying a bicycle usage elastic model, judging the influence of each influence factor on bicycle usage according to the influence coefficient, and applying the bicycle usage elastic model to obtain an influence coefficient alpha, wherein if alpha is a positive number, the influence factor corresponding to the alpha has a positive influence on the bicycle usage, otherwise, the influence factor has a negative influence.
Further, in the method for judging the elastic influence of the accident on the use of the bicycle, the accident buffer zone is preset by taking the accident place as the circle center and taking 400 meters as the radius.
Compared with the prior art, the invention has the following beneficial effects: different unit time is set by determining traffic accident occurrence time, an influence buffer area is built by taking a reasonable preset distance as a radius accident place as a core, and the influence of accident occurrence on the use elasticity of the bicycle is analyzed by calculating the change of the use amount of the bicycle in the buffer area in unit time. The method can better guide the traffic management department how to efficiently schedule the bicycles when traffic accidents occur.
Drawings
FIG. 1 is a method flow diagram of one embodiment of the present invention.
Detailed Description
For a better understanding of the technical content of the present invention, specific examples are set forth below, along with the accompanying drawings.
Aspects of the invention are described herein with reference to the drawings, in which there are shown many illustrative embodiments. The embodiments of the present invention are not limited to the embodiments described in the drawings. It is to be understood that this invention is capable of being carried out by any of the various concepts and embodiments described above and as such described in detail below, since the disclosed concepts and embodiments are not limited to any implementation. Additionally, some aspects of the disclosure may be used alone or in any suitable combination with other aspects of the disclosure.
As shown in fig. 1, a method for judging the elastic influence of accident occurrence on the use of a bicycle comprises the following steps:
s1, acquiring sample information about occurrence time and place of each accident in a target area;
step S2, presetting an accident occurrence time period based on accident occurrence time in sample information, and dividing time units of the accident occurrence time period, wherein the time units are specifically as follows: based on the time of accident, dividing the time unit of G hours before and after the accident in units of t minutes, wherein the time unit is as follows:
G i ={t 1 …t n },
where i is the number of the accident sample.
S3, presetting an accident occurrence buffer area according to the accident occurrence place in the sample information, and collecting bicycle station information in the buffer area; the preset accident occurrence buffer area specifically comprises the following components: the accident impact buffer areas are respectively established by taking the accident place as the center of a circle and 400 meters as the radius, and the bicycle station information in the accident buffer areas is correspondingly collected,
n i ={d 1 …d k }
wherein ni A preset distance buffer zone d for accident i k Is a bicycle station within the buffer, where k > 1.
The bicycle station information is shown in table 1:
TABLE 1
And S4, counting the bicycle usage amount of each driving station in each time unit according to the time unit in the step S2 and the bicycle station information obtained in the step S3, and further counting the bicycle usage amount of the buffer zone. The bicycle usage of the statistical buffer is as follows:
wherein ,Q(dk ) The bicycle usage amount for each driving station in each time unit.
Step S5, collecting influencing factors: road network density K ti Economical GDP ti Population P ti Number of bus stops D ti Bicycle usage M combined with buffer zone ti The elastic model of the bicycle usage is constructed as follows:
wherein ,xi Is an influencing factor;
wherein C is the variance and covariance matrix of the random parameters, j is the number of random parameters,refers to other random and uncorrelated variables.
The influence factor statistics are shown in table 2:
TABLE 2
Site(s) AADT P GDP K D
F 1 AADT 1 P 1 GDP 1 K 1 D 1
F 2 AADT 2 P 2 GDP 2 K 2 D 2
F i AADT i P i GDP i K i D i
And S6, applying the elastic model of the bicycle usage amount, and judging the influence of the influence factors on the bicycle usage in the unit time after the accident occurs, wherein if the influence coefficient alpha is regular, the influence of the factors on the bicycle usage is positive, otherwise, the influence of the factors on the bicycle usage is negative. Targeted performance strategies may be employed to reduce the impact of incidents on the stability of the bicycle system based on the impact of factors.
While the invention has been described in terms of preferred embodiments, it is not intended to be limiting. Those skilled in the art will appreciate that various modifications and adaptations can be made without departing from the spirit and scope of the present invention. Accordingly, the scope of the invention is defined by the appended claims.

Claims (2)

1. A method of determining the elastic impact of an accident on the use of a bicycle, comprising the steps of:
s1, acquiring sample information about occurrence time and place of each accident in a target area;
s2, presetting an accident occurrence time period based on accident occurrence time in sample information, and dividing time units for the accident occurrence time period; the method comprises the following steps: based on the time of accident, dividing the time unit of G hours before and after the accident in units of t minutes, wherein the time unit is as follows:
G i ={t 1 …t n },
wherein i is the number of the accident sample;
s3, presetting an accident occurrence buffer area according to the accident occurrence place in the sample information, and collecting bicycle station information in the buffer area; the preset accident occurrence buffer area specifically comprises the following components: an accident impact buffer area is established by taking the accident place as the center of a circle and the preset distance as the radius respectively, and the bicycle station information in the accident buffer area is correspondingly collected,
n i ={d 1 …d k }
wherein ni A preset distance buffer zone d for accident i k Is a bicycle station in a buffer zone, where k>1;
S4, counting the bicycle usage amount of each driving station in each time unit according to the time unit in the step S2 and the bicycle station information obtained in the step S3, and further counting the bicycle usage amount of the buffer zone; the bicycle usage amount of the statistical buffer zone is as follows:
wherein ,Q(dk ) The bicycle usage amount for each driving station in each time unit;
s5, collecting impact factors of the buffer area, and constructing a bicycle usage elastic model by combining the bicycle usage of the buffer area; the method specifically comprises the following steps of collecting influencing factors: road network density K ti Economical GDP ti Population P ti Number of bus stops D ti Bicycle usage M combined with buffer zone ti The elastic model of the bicycle usage is constructed as follows:
wherein ,is an influencing factor; epsilon is a model error term, alpha i Regression coefficient, beta, for each influencing factor 0 Constant terms for the model;
wherein C is the variance and covariance matrix of the random parameters, j is the number of random parameters,refers to other random and uncorrelated variables;
s6, applying a bicycle usage elastic model, judging the influence of each influence factor on bicycle usage according to the influence coefficient, and applying the bicycle usage elastic model to obtain an influence coefficient alpha, wherein if alpha is a positive number, the influence factor corresponding to the alpha has a positive influence on the bicycle usage, otherwise, the influence factor has a negative influence.
2. The method of claim 1, wherein the predetermined accident buffer zone is established with a radius of 400 meters around the accident site.
CN202211663826.7A 2022-12-23 2022-12-23 Method for judging elastic influence of accident occurrence on bicycle use Active CN115830872B (en)

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IL186237A0 (en) * 2007-09-24 2008-01-20 Schaffer Alon Flexible bicycle derailleur hanger
CN107679668A (en) * 2017-10-16 2018-02-09 东南大学 The electric bicycle travel time prediction method of duration model based on risk
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CN108550218A (en) * 2018-06-01 2018-09-18 厦门市市政工程设计院有限公司 A kind of bicycle capacity integrated control system and its management-control method
CN109559504A (en) * 2018-09-02 2019-04-02 吉林大学 Signalized intersections electric bicycle opens the determination method of bright time in advance
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CN111507617A (en) * 2020-04-15 2020-08-07 桂林电子科技大学 Analysis system based on electric bicycle risk driving behavior scale
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