CN110379161B - Urban road network traffic flow distribution method - Google Patents

Urban road network traffic flow distribution method Download PDF

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CN110379161B
CN110379161B CN201910651997.XA CN201910651997A CN110379161B CN 110379161 B CN110379161 B CN 110379161B CN 201910651997 A CN201910651997 A CN 201910651997A CN 110379161 B CN110379161 B CN 110379161B
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traffic
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travelers
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黄合来
韩春阳
徐光明
蒋梦溪
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Central South University
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Abstract

The invention discloses a method for distributing traffic flow of an urban road network, which comprises the following steps: carrying out survey on the routing behavior of the resident on trip safety consideration to obtain a survey result of the routing behavior of the traveler on trip safety consideration; the method comprises the steps of surveying the safety performance of the urban road network, and acquiring the safety performance data of each road section of the urban road network; calculating parameters of the safe routing model to obtain parameter values in the model; and distributing the road network flow by adopting a safe routing model to obtain the traffic flow of each road section in a balanced state. The invention starts from the safe routing behavior of travelers, constructs a traffic distribution model, can more accurately distribute the traffic flow of a road network when the travelers consider the safety factor and the efficiency factor at the same time, and makes up the defect of the traditional traffic distribution method in considering the safe routing behavior of the travelers.

Description

Urban road network traffic flow distribution method
Technical Field
The invention relates to the technical field of traffic planning, in particular to a method for distributing traffic flow of an urban road network.
Background
The rapid development and wide popularization of the intelligent traffic system provide a new way for improving the traffic safety problem. The traffic running safety state information is released through the travel information system, a safer travel path is provided for travelers, and the travel safety can be effectively improved. However, the distribution of the road network safety information will affect the path selection behavior of the travelers, so that the whole urban road network forms a new traffic balance state. Therefore, it is an urgent technical problem to provide a method for accurately allocating urban road network traffic flow based on urban resident travel data and urban traffic network basic data, which can simultaneously and reasonably quantify the consideration behavior of a traveler on the safety of a route based on the known route selection behavior of the traveler based on the consideration of efficiency.
The distribution of traffic flow is an important component of urban traffic planning, and is also a precondition and a core technology for traffic management. The traffic flow distribution means: according to the route selection principle (route selection behavior) of travelers, the traffic volume is distributed into the traffic network, so that the road section flow and the related traffic indexes are obtained. However, the existing road network traffic distribution model is based on a time impedance function, and models the path selection behavior of travelers (time-traffic function) based on a User Equalization (UE) or System Optimization (SO) theory, and a BPR function developed by the U.S. highway administration is widely used, and is called as an efficiency-based road network distribution method. Some studies have also been conducted to integrate the consideration of vehicle emission, comfort, etc. of travelers into a traveller routing model for traffic flow distribution. The few methods consider routing behavior factors of travelers based on safety considerations when setting routing principles.
Disclosure of Invention
Limited by the traditional route selection (routing principle) model based on travel efficiency, the existing traffic flow distribution method cannot accurately distribute traffic flow when a traveler considers the safety of the route. The invention constructs a traveler safety routing model based on a road traffic safety evaluation technology, and provides a whole set of city road network flow distribution method for considering routing behaviors in consideration of traveler safety and efficiency based on the model. The invention makes up the deficiency of the traditional traffic distribution method in considering the routing behavior of travelers, firstly proposes to construct a traffic distribution model from the safety routing behavior of travelers, can more accurately distribute the traffic flow of a road network when the travelers consider the safety factor and the efficiency factor at the same time, and achieves the advanced level of the world.
The technical scheme adopted by the invention is an urban road network traffic flow distribution method, which comprises the following steps:
step 101: carrying out survey on the routing behavior of the resident on trip safety consideration to obtain a survey result of the routing behavior of the traveler on trip safety consideration;
step 102: the method comprises the steps of surveying the safety performance of the urban road network, and acquiring the safety performance data of each road section of the urban road network;
step 103: calculating parameters of the safe routing model to obtain parameter values in the model;
step 104: and distributing the road network flow by adopting a safe routing model to obtain the traffic flow of each road section in a balanced state.
Preferably, the resident travel safety consideration routing behavior survey of step 101 further includes the following steps:
s1: sampling a survey object, wherein the sampling adopts a hierarchical sampling method;
s2: adopting an RP investigation method to carry out resident trip safety consideration routing behavior investigation, obtaining traveler safety consideration routing behavior investigation results, and counting the investigation results;
preferably, in step S2, the survey, specifically the home visit survey, is obtained in the same place; the survey content includes: and (3) supposing that m classes of travelers with different safety concerns and n classes of travelers with different weighing standards exist in the region, investigating the safety concerns of the travelers, classifying, investigating the weighing behaviors of the travelers on the traveling safety and the traveling efficiency, and classifying.
Preferably, the safety performance data of each road segment of the urban road network in step 102 specifically includes accident information data reflecting the average safety performance of the road and traffic conflict related data reflecting the safety and reliability performance of the road.
Preferably, the accident information data in step 102 specifically includes accident position information and severity thereof, property loss and other information within at least one year, and the intersection accidents need to be categorized according to the turning positions where the main responsible parties happen or the turning behaviors in progress.
Preferably, the traffic conflict related data described in step 102 specifically includes information such as the type and severity of the conflict, and the intersection conflict needs to be recorded for different turning directions of each entrance.
Preferably, the calculation of the parameters of the secure routing model in step 103 further includes the following steps:
step 301: summarizing the safety attention degree and the safety-efficiency measurement index of the travelers according to the survey result of the routing behavior considered by the travelers in the step 101, calculating the ratio of the travelers under each safety attention degree (or under the measurement index), and summarizing the ratio into structured data;
step 302: calculating the average safety performance E (r) of each inlet steering of each road section and intersection according to the accident information data obtained in the step 102 by dividing the total cost generated by the traffic accidents occurring at the road section or the intersection by the data time span rangea) And E (r)a→b) The unit is: yuan/min, the calculation formula is:
Figure BDA0002135549160000021
or
Figure BDA0002135549160000022
Wherein the content of the first and second substances,
Figure BDA0002135549160000023
for segment a, a ═ occurrence of accident Z, (1,2, …, a), loss of property for Z ═ occurrence of (1,2, …, Z), N is the length of time the accident data was collected;
step 303: according to the traffic conflict data in the step 102, calculating the discrete situations of the traffic conflicts in the entrance turning periods of the road sections and the intersections, and judging the safety and reliability of the entrance turning of the road sections and the intersections. The method is characterized in that the variance value of the number of times of traffic conflicts in each period is calculated, the variance of the number of conflicts of each road section and each intersection with the incoming turn is divided into three types of low, medium and high, and different safe reliability values are matched for each type of road section and each intersection with each incoming turn
Figure BDA0002135549160000031
And
Figure BDA0002135549160000032
the unit is: yuan/min.
Step 304: the method for counting the attribute parameter values of the inlet turning of each road section and each intersection comprises the following steps: obtaining the traffic capacity C of each road section and intersection according to historical dataaZero flow time impedance
Figure BDA0002135549160000033
And the existing road condition data such as the retardation coefficients alpha and beta, and the road average safety performance and safety and reliability performance data obtained in the steps 302 and 303 are arranged into a structured data format.
Preferably, the road network flow calculation and distribution in step 104 further includes the following steps:
step 401: firstly, drawing a road network topological structure diagram including intersection turning according to urban road network structure information in historical data, generating an access relation matrix according to an inter-cell access relation displayed by the structure diagram, and generating a travel demand matrix according to resident travel OD (origin-destination) data among all traffic cells;
step 402: according to the result of step 301, traveler's safety preference parameters in the model are input, including: traveler occupation ratio lambda of different safety concernsmM ═ 1,2, …, M is the number of panelists, and the ratio θ of panelists to different safety-to-efficiency metricsnN is (1,2, …, N) is the number of panelists; inputting initial data of the model according to the statistical data in the step 304 and the step 401, including information of each road section (1. retardation coefficient alpha, beta, 2. zero flow time)
Figure BDA0002135549160000034
3. Traffic capacity c a4, average security, 5, safe reliability) and the travel demand of user class m between OD pairs. And meanwhile, setting a model calculation error limit value epsilon (self-setting according to the precision requirement).
Step 403: calculating the path flow by adopting a traveler routing rule model;
step 404: according to the path flow obtained in the step 403, reversely deducing the flow of the path passing through all road sections and intersection inlet steering through the access relation matrix in the step 401, and updating the flow of the road sections and intersection inlet steering;
step 405: and judging whether the balance is achieved. According to step 404, if the difference between the calculated road section and intersection approach steering flow of this time and the flow result calculated last time is less than the calculation error limit value epsilon set in step 402, the calculation is stopped, and the final distributed traffic volume of the road section a can be obtained at this time, otherwise, the step 403 is returned.
Preferably, the calculating the path flow by using the traveler routing rule model in step 403 further includes the following steps:
step 4031: calculating the passing time of each road section according to the flow of each road section; specifically, the traffic capacity c of each road section obtained through the step 304 by adopting the BPR functionaAnd zero stream time
Figure BDA0002135549160000046
Calculating the traffic volume q of each road sectionaThe following transit time is calculated by the formula:
Figure BDA0002135549160000041
wherein alpha and beta are retardation coefficients obtained in step 304, the traffic flow is zero and the transit time is zero flow time under the initial condition
Figure BDA0002135549160000047
Step 4032: calculating generalized travel expenses of the imported steering of each road section and each intersection; the calculation formula is as follows:
Figure BDA0002135549160000042
Ca→b＝E(ra→b)
multiplying the transit time obtained in the step 4031 by the safety-efficiency trade-off index theta of various travelersnAnd the safety of each road section obtained in step 302Adding the performances to obtain the generalized travel cost C of the n types of users on the road sectionaThe generalized travel cost of the intersection import steering is E (r)a→b)；
Step 4033: computing a minimum cost path set
Figure BDA0002135549160000048
Specifically, based on the generalized travel costs of the road section and the intersection inlet turning calculated in step 4032, the generalized travel costs of all the routes passing through the road section are added, and the generalized travel costs of all the routes between each OD pair are calculated:
Figure BDA0002135549160000043
wherein the content of the first and second substances,
Figure BDA0002135549160000049
and
Figure BDA00021355491600000410
if the road section and the intersection are in the path p, the value is 1, otherwise the value is 0; for the convenience of subsequent calculation, the first 10 paths with the minimum cost are selected between each OD pair to form a minimum cost path set;
step 4034: according to the safety reliability obtained in steps 303 and 304, in combination with the attention of the traveler in step 301 to the safety reliability of the route, on the basis of the generalized travel cost obtained in step 4033, the safety reliability cost of the route of different travelers is added, and the formula is as follows:
Figure BDA0002135549160000044
and outputting the minimum cost path of each class of travelers in the new minimum cost path set, thereby obtaining the minimum cost path of m classes of travelers in the minimum cost path set
Figure BDA0002135549160000045
Step 4035: and distributing traffic flow according to the travel demand in the step 401. Distributing the demand of m classes of travelers between the ODs obtained in the step 401 to the shortest paths of the m classes of travelers by adopting an all-existence and all-nothing distribution method to obtain the additional traffic volume of each path
Figure BDA0002135549160000051
Step 4036: calculating the current traffic volume of each current (g-th distribution) path by using a weighted average method
Figure BDA0002135549160000052
The formula is as follows:
Figure BDA0002135549160000053
the invention relates to a method for distributing traffic flow aiming at an urban road network by considering behaviors of quantifying the path safety and efficiency of travelers at the same time. The method mainly comprises the steps of resident travel safety consideration and routing behavior investigation, urban road network safety performance investigation and safe routing model parameter calculation; and calculating and distributing the road network flow. The invention starts from the safe routing behavior of travelers, constructs a traffic distribution model, can more accurately distribute the traffic flow of a road network when the travelers consider the safety factor and the efficiency factor at the same time, and makes up the defect of the traditional traffic distribution method in considering the safe routing behavior of the travelers.
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The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. In the drawings, like reference numerals designate corresponding parts throughout the different views.
Fig. 1 is a schematic diagram of a topological structure of an urban road network according to a second embodiment of the present invention;
FIG. 2 is a diagram of a traffic relationship matrix between traffic cells according to a second embodiment of the present invention;
fig. 3 is a diagram of a travel demand matrix among cells according to the second embodiment of the present invention;
fig. 4 is a road section information diagram (sequentially showing traffic capacity, zero-flow time, average safety, safe reliability, and retardation coefficient) according to the second embodiment of the present invention;
FIG. 5 is a graph of average safety of approach turns at the intersection as shown in example two of the present invention;
FIG. 6 is a safety reliability diagram for intersection approach turns according to a second embodiment of the present invention;
fig. 7 is a diagram of generalized travel costs of each path after the initial iteration according to the second embodiment of the present invention;
FIG. 8 is a generalized cost graph of paths for a class of population after the initial iteration as shown in embodiment two of the present invention;
FIG. 9 is a generalized cost graph of paths for the second population after the first iteration according to the second embodiment of the present invention;
FIG. 10 is a graph of additional traffic for each path of a class of travelers after the initial iteration according to a second embodiment of the present invention;
FIG. 11 is a graph of additional traffic for each path of the two classes of travelers after the initial iteration according to the second embodiment of the present invention;
FIG. 12 is a traffic flow chart of each road segment after the initial iteration according to the second embodiment of the present invention;
fig. 13 is a graph of traffic flow values of each link in a balanced state calculated by MATLAB as shown in the second embodiment of the present invention.
FIG. 14 is a flow chart of a method for distributing traffic flow in urban road network according to the present invention
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Various equivalent modifications of the invention, which fall within the scope of the appended claims of this application, will occur to persons skilled in the art upon reading this disclosure.
The invention is further described with reference to the following figures and examples.
Example one
The technical scheme adopted by the invention is an urban road network traffic flow distribution method, which comprises the following steps:
step 101: carrying out survey on the routing behavior of the resident on trip safety consideration to obtain a survey result of the routing behavior of the traveler on trip safety consideration;
step 102: the method comprises the steps of surveying the safety performance of the urban road network, and acquiring the safety performance data of each road section of the urban road network;
step 103: calculating parameters of the safe routing model to obtain parameter values in the model;
step 104: and distributing the road network flow by adopting a safe routing model to obtain the traffic flow of each road section in a balanced state.
Preferably, the resident travel safety consideration routing behavior survey of step 101 further includes the following steps:
s1: sampling a survey object, wherein the sampling adopts a hierarchical sampling method;
s2: adopting an RP investigation method to carry out resident trip safety consideration routing behavior investigation, obtaining traveler safety consideration routing behavior investigation results, and counting the investigation results;
preferably, in step S2, the survey, specifically the home visit survey, is obtained in the same place; the survey content includes: and (3) supposing that m classes of travelers with different safety concerns and n classes of travelers with different weighing standards exist in the region, investigating the safety concerns of the travelers, classifying, investigating the weighing behaviors of the travelers on the traveling safety and the traveling efficiency, and classifying.
Preferably, the safety performance data of each road segment of the urban road network in step 102 specifically includes accident information data reflecting the average safety performance of the road and traffic conflict related data reflecting the safety and reliability performance of the road.
Preferably, the accident information data in step 102 specifically includes accident position information and severity thereof, property loss and other information within at least one year, and the intersection accidents need to be categorized according to the turning positions where the main responsible parties happen or the turning behaviors in progress.
Preferably, the traffic conflict related data described in step 102 specifically includes information such as the type and severity of the conflict, and the intersection conflict needs to be recorded for different turning directions of each entrance.
Preferably, the calculation of the parameters of the secure routing model in step 103 further includes the following steps:
step 301: summarizing the safety attention degree and the safety-efficiency measurement index of the travelers according to the survey result of the routing behavior considered by the travelers in the step 101, calculating the ratio of the travelers under each safety attention degree (or under the measurement index), and summarizing the ratio into structured data;
step 302: calculating the average safety performance E (r) of each inlet steering of each road section and intersection according to the accident information data obtained in the step 102 by dividing the total cost generated by the traffic accidents occurring at the road section or the intersection by the data time span rangea) And E (r)a→b) The unit is: yuan/min, the calculation formula is:
Figure BDA0002135549160000071
or
Figure BDA0002135549160000072
Wherein the content of the first and second substances,
Figure BDA0002135549160000073
for segment a, a ═ occurrence of accident Z, (1,2, …, a), loss of property for Z ═ occurrence of (1,2, …, Z), N is the length of time the accident data was collected;
step 303: calculating the discrete situation of the traffic conflict in each road section and each inlet turning period of the intersection according to the traffic conflict data in the step 102, judging the safety and reliability of each inlet turning of the road section and the intersection, considering that the stability of the occurrence frequency of the traffic conflict in each period can indirectly represent the safety and reliability of each inlet turning of the road section and the intersection, and the higher the stability is, the higher the safety can beThe better the reliability. The method is characterized in that the variance value of the number of times of traffic conflicts in each period is calculated, the variance of the number of conflicts of each road section and each intersection with the incoming turn is divided into three types of low, medium and high, and different safe reliability values are matched for each type of road section and each intersection with each incoming turn
Figure BDA0002135549160000074
And
Figure BDA0002135549160000075
the unit is: yuan/min.
Step 304: the method for counting the attribute parameter values of the inlet turning of each road section and each intersection comprises the following steps: obtaining the traffic capacity C of each road section and intersection according to historical dataaZero flow time impedance
Figure BDA0002135549160000076
And the existing road condition data such as the retardation coefficients alpha and beta, and the road average safety performance and safety and reliability performance data obtained in the steps 302 and 303 are arranged into a structured data format.
Preferably, the road network flow calculation and distribution in step 104 further includes the following steps:
step 401: firstly, drawing a road network topological structure diagram including intersection turning according to urban road network structure information in historical data, generating an access relation matrix according to an inter-cell access relation displayed by the structure diagram, and generating a travel demand matrix according to resident travel OD (origin-destination) data among all traffic cells;
step 402: according to the result of step 301, traveler's safety preference parameters in the model are input, including: traveler occupation ratio lambda of different safety concernsmM ═ 1,2, …, M is the number of panelists, and the ratio θ of panelists to different safety-to-efficiency metricsnN is (1,2, …, N) is the number of panelists; inputting initial data of the model according to the statistical data in the step 304 and the step 401, including information of each road section (1. retardation coefficient alpha, beta, 2. zero flow time)
Figure BDA0002135549160000083
3. Traffic capacity c a4, average security, 5, safe reliability) and the travel demand of user class m between OD pairs. And meanwhile, setting a model calculation error limit value epsilon (self-setting according to the precision requirement).
Step 403: calculating the path flow by adopting a traveler routing rule model;
step 404: according to the path flow obtained in the step 403, reversely deducing the flow of the path passing through all road sections and intersection inlet steering through the access relation matrix in the step 401, and updating the flow of the road sections and intersection inlet steering;
step 405: and judging whether the balance is achieved. According to step 404, if the difference between the calculated road section and intersection approach steering flow of this time and the flow result calculated last time is less than the calculation error limit value epsilon set in step 402, the calculation is stopped, and the final distributed traffic volume of the road section a can be obtained at this time, otherwise, the step 403 is returned.
Preferably, the calculating the path flow by using the traveler routing rule model in step 403 further includes the following steps:
step 4031: calculating the passing time of each road section according to the flow of each road section; specifically, the traffic capacity c of each road section obtained through the step 304 by adopting the BPR functionaAnd zero stream time
Figure BDA0002135549160000084
Calculating the traffic volume q of each road sectionaThe following transit time is calculated by the formula:
Figure BDA0002135549160000081
wherein alpha and beta are retardation coefficients obtained in step 304, the traffic flow is zero and the transit time is zero flow time under the initial condition
Figure BDA0002135549160000085
Step 4032: calculating generalized travel expenses of the imported steering of each road section and each intersection; the calculation formula is as follows:
Figure BDA0002135549160000082
Ca→b＝E(ra→b)
multiplying the transit time obtained in the step 4031 by the safety-efficiency trade-off index theta of various travelersnAnd adding the safety performance of each road section obtained in the step 302 to obtain the generalized travel cost C of the n types of users on the road sectionaThe generalized travel cost of the intersection import steering is E (r)a→b)；
Step 4033: computing a minimum cost path set
Figure BDA0002135549160000091
Specifically, based on the generalized travel costs of the road section and the intersection inlet turning calculated in step 4032, the generalized travel costs of all the routes passing through the road section are added, and the generalized travel costs of all the routes between each OD pair are calculated:
Figure BDA0002135549160000092
wherein the content of the first and second substances,
Figure BDA0002135549160000093
and
Figure BDA0002135549160000094
if the road section and the intersection are in the path p, the value is 1, otherwise the value is 0; for the convenience of subsequent calculation, the first 10 paths with the minimum cost are selected between each OD pair to form a minimum cost path set;
step 4034: according to the safety reliability obtained in steps 303 and 304, in combination with the attention of the traveler in step 301 to the safety reliability of the route, on the basis of the generalized travel cost obtained in step 4033, the safety reliability cost of the route of different travelers is added, and the formula is as follows:
Figure BDA0002135549160000095
and outputting the minimum cost path of each class of travelers in the new minimum cost path set, thereby obtaining the minimum cost path of m classes of travelers in the minimum cost path set
Figure BDA0002135549160000096
Step 4035: and distributing traffic flow according to the travel demand in the step 401. Distributing the demand of m classes of travelers between the ODs obtained in the step 401 to the shortest paths of the m classes of travelers by adopting an all-existence and all-nothing distribution method to obtain the additional traffic volume of each path
Figure BDA0002135549160000097
Step 4036: calculating the current traffic volume of each current (g-th distribution) path by using a weighted average method
Figure BDA0002135549160000098
The formula is as follows:
Figure BDA0002135549160000099
example two
Step 101: survey of route selection behavior for resident travel safety consideration
(1) And (5) investigating methods. In this embodiment, a family visit survey method is adopted to sample family visits of residents in a surveyed urban area. Wherein the sampling rate can be obtained by referring to table 1 according to the population number of cities in the investigation region. The sampling survey adopts a layered sampling method, and comprises the following implementation steps:
dividing the traffic districts into a plurality of types (layers) according to the existing urban traffic district dividing data and taking the land property of the traffic districts as the characteristic;
for traffic districts with the same properties, determining the sample size of each layer by the district population multiplied by the sampling rate;
and performing random sampling home visit, and enabling the investigators to know the travel safety-efficiency consideration behaviors of all members of the investigated residents on the spot.
TABLE 1, Home visit survey sampling Rate lookup Table
Figure BDA0002135549160000101
(2) The investigation content mainly comprises:
designing different travel scenes comprising different travel purposes, travel time, travel partners and other scenes;
according to different scenes, investigating the attention degree of a traveler to safety under various travel scenes;
according to different scenes, the balance behaviors of travelers on the travel safety and the travel efficiency under various travel scenes are investigated.
The questionnaire can be designed by the RP survey method according to the above-mentioned problems. Different scenes are set, and the safety attention of a traveler and the safety and efficiency balance index are measured in a scoring mode.
(3) Data pre-processing
The score of each respondent was recorded and the questionnaire results were arranged into the structured data form shown in table 2.
Table 2, summary table of survey results of routing behavior of traveler's safety considerations
Figure BDA0002135549160000102
Step 102: urban road network safety performance data survey
The embodiment needs to acquire safety performance data of each road segment of the urban road network. The traffic conflict information data comprises accident information data reflecting the average safety performance of the road and traffic conflict related data reflecting the safety and reliability performance of the road. The traffic accident information data can be acquired by traffic related departments and comprises accident position information within at least one year, severity of the accident position information, property loss and other information. It should be noted that intersection accidents need to be classified according to the turning position or the ongoing turning behavior of the main responsible party at the time of the incident. The traffic conflict data needs to adopt a traffic conflict investigation technology to acquire information including the type and severity of the conflict through field investigation. And investigating traffic conflict information in a signal period aiming at the signalized intersection, and investigating conflict information in a fixed time interval aiming at the non-signalized intersection. Likewise, intersection conflicts require recording of different turns for each entrance. Based on the collected historical accident data and traffic conflict data, structured data as shown in tables 3 and 4 are drawn according to information of each road segment in the urban road network.
TABLE 3 summary of road accident information
Figure BDA0002135549160000111
Note: PDO is simply a loss of property
TABLE 4 summary of road conflict information
Figure BDA0002135549160000112
Figure BDA0002135549160000121
Step 103: secure routing model parameter calculation
(1) Calculation of traveler safety concern and safety-efficiency measurement index
In this embodiment, the safety attention and the safety-efficiency measurement index of travelers in different travel scenes are calculated through the score data in table 2, and the larger the score is, the larger the attention to safety is. The safety preference of residents in the area can be known through the scoring condition of the travelers on the safety attention degree in different scenes, so that the ratio of the travelers with different safety attention degrees in various scenes is obtained. Similarly, the traveler proportion of different trade-off indexes under each scene can be obtained. Firstly, calculating the proportion of scores in different ranges under each scene, such as: respondents scored in the range of 0-2 accounted for 5% of the total respondents, i.e., low-interest travelers accounted for 5% of the total travelers. The segmentation standard and the classification number of the scores can be set according to the requirements of the model. Then, the safety-efficiency measure index is calculated in the same manner. Finally, the results of the calculations are summarized in the form of structured data as shown in table 5.
TABLE 5 summary of traveler's safety psychological parameters
Figure BDA0002135549160000122
(2) Road safety performance calculation
The present embodiment quantifies the average safety performance of each road section or intersection by converting an accident into a corresponding economic loss according to the accident record occurring at each road section or intersection. Calculating the average safety performance E (r) of each inlet turn of each road section and intersection by dividing the total cost generated by the traffic accidents occurring at the road section or intersection by the data time span range according to the historical accident information counted in the table 3a) And E (r)a→b) The unit is: yuan/min, the calculation formula is:
Figure BDA0002135549160000131
or
Figure BDA0002135549160000132
Wherein the content of the first and second substances,
Figure BDA0002135549160000135
for segment a, the property loss of the accident Z occurs (1,2, …, a), Z (1,2, …, Z), and N is the length of time (years) that the accident data was collected.
Then, the embodiment determines each road section and intersection by calculating the discrete situation of the traffic conflict in each inlet steering cycle of each road section and intersectionThe safety and reliability of the inlet steering of the intersection can be indirectly represented by the stability (variance) of the number of times of traffic conflicts in each period, and the higher the stability is, the better the safety and reliability is. According to the traffic conflict information counted in table 4, firstly, the variance value of the number of times of occurrence of traffic conflicts in each period is calculated; then, dividing the variance values of the turning of each road section and each inlet of the intersection into three types of low, medium and high; finally, matching different safe reliability values for each type of road section and each inlet steering of the intersection
Figure BDA0002135549160000136
And
Figure BDA0002135549160000137
the unit is: yuan/min, match values refer to Table 6.
TABLE 6 road fail safe matching reference values
Figure BDA0002135549160000133
Finally, the attribute parameter values of the inlet turning of each road section and each intersection are counted, wherein the attribute parameter values comprise the traffic capacity CaZero flow time impedance
Figure BDA0002135549160000138
And the data of the existing road conditions such as the retardation coefficients alpha and beta, and the data of the average safety performance and the safety and reliability performance collected in the embodiment are arranged into a structured data format as shown in table 7.
TABLE 7 summary of asset parameter values
Figure BDA0002135549160000134
Figure BDA0002135549160000141
And calculating the relevant psychological parameters of the urban resident safety and the road safety performance parameters.
Step 104: road network flow distribution
In the embodiment, a traffic flow distribution algorithm based on a safe routing model is designed, and the algorithm is realized through Matlab software. Firstly, according to the urban road network structure information which is investigated in the past, a road network topological structure diagram (shown in figure 1) containing intersection turning is drawn, and according to the inter-cell access relation displayed by the structure diagram, an access relation matrix shown in figure 2 is generated, wherein each row represents each route from a starting point to an end point, and all road segment numbers passed by the route are listed. Then, a travel demand matrix (as shown in table 9) is generated according to the resident travel OD data between the traffic cells, wherein the first column of the matrix represents the origin cell, the second column represents the arrival cell, and the third column represents the travel demand between the cells.
The traffic flow distribution is carried out at present, and the specific steps are as follows:
the first step is as follows: initializing model parameters
Setting model parameters according to the calculation result in the step two, wherein the setting comprises the following steps: safety concern λ for travelersmM is (1,2, …, M) the number of categories of attention; safety-efficiency scale index thetanN is (1,2, …, N) is the number of the classification meshes of the measuring index, and five types of indexes are selected in the invention (table 5); safety-efficiency scale index thetanN is (1,2, …, N) is the number of the classification meshes of the measuring index, and five types of indexes are selected in the invention (table 5); calculating an error limit value epsilon (set by a user according to the precision requirement), and calculating the total travel requirement of the user class m between the OD pairs (figure 3); the information of each road section comprises 1. retardation coefficient alpha, beta, 2. zero flow time
Figure BDA0002135549160000143
Figure BDA0002135549160000143
3. Traffic capacity c a4, average safety and 5, safety and reliability. Fig. 4, 5, 6 show data setting formats in MATLAB environments, where matrix elements in fig. 5 and 6 represent the turn between row representative road segments to column representative road segments.
The second step is that: calculating path flow
(1) Calculating the passing time of each road section according to the flow of each road section; passing capacity c of each road section by adopting BPR functionaAnd zero stream time
Figure BDA0002135549160000144
Calculating the traffic volume q of each road sectionaThe following transit time is calculated by the formula:
Figure BDA0002135549160000142
wherein alpha and beta are retardation coefficients, and the traffic flow is zero (q) under the initial conditiona0), the transit time is the zero stream time
Figure BDA0002135549160000154
(2) Calculating generalized travel expenses of the imported steering of each road section and each intersection; the calculation formula is as follows:
Figure BDA0002135549160000151
Ca→b＝E(ra→b)
multiplying transit time by the safety-efficiency trade-off index theta for various travelersnAnd adding the safety performance of each road section to obtain generalized travel cost C of n types of user road sections of the road sectionaThe generalized travel cost of the intersection import steering is E (r)a→b)；
(3) Computing a minimum cost path set
Figure BDA0002135549160000155
Based on the generalized travel cost of the road sections and the intersection for the approach steering, the generalized travel cost of each path passing through the road sections is added, and the generalized travel cost of all paths between each OD pair is calculated:
Figure BDA0002135549160000152
wherein the content of the first and second substances,
Figure BDA0002135549160000156
and
Figure BDA0002135549160000157
to select the coefficients, if the road segment and intersection approach turns on path p, which has a value of 1,
otherwise, the value is 0; for the convenience of subsequent calculation, the first 10 paths with the minimum cost are selected between each OD pair to form a minimum cost path set. The present invention case sets only the average safety-efficiency index θ of all residents in the surveyed area to 4, and does not perform classification processing. Fig. 7 shows the path generalized cost between ODs at the first iteration.
(4) And calculating generalized travel expenses of different travelers (different safety preferences) on each path in the minimum expense set of the last step, and outputting the minimum expense path of each type of travelers in a 10-minimum expense path set. According to the attention of the traveler to the safety and reliability of the path, adding the attention of the traveler to the safety and reliability on the basis of the generalized cost of the last step, wherein the formula is as follows:
Figure BDA0002135549160000153
thereby obtaining the minimum cost path of m classes of travelers in 10-minimum cost path set
Figure BDA0002135549160000158
The scheme divides travelers into two categories according to the safety concern, namely lambda1＝1，λ2Fig. 8 shows the path generalized cost for one population between ODs at the first iteration, and fig. 9 shows the path generalized cost for two populations.
(5) And distributing the traffic flow according to the requirement. Distributing the demand of m classes of travelers between ODs to the shortest path of m classes of travelers by adopting an all-existence-all-nothing distribution method to obtain the additional traffic volume of each path
Figure BDA0002135549160000159
In this case, it is assumed that various travelers are uniformly distributed in equal proportion among urban residents, and fig. 11 shows the distributed traffic volume after the first iteration of the two types of travelers.
(6) Calculating the current traffic volume of each current (g-th distribution) path by using a weighted average method
Figure BDA0002135549160000161
The formula is as follows:
Figure BDA0002135549160000162
and thirdly, updating the flow of the road section (or the intersection entrance steering). According to the road section flow and the access relation matrix, reversely deducing the flow x of the inlet steering of the path passing through all the road sections and the intersectionsaOr xa→b. Fig. 12 shows the traffic flow assigned to each road segment by reverse estimation after the first iteration.
And fourthly, judging whether the balance is achieved. If the difference between the flow of the g-th calculated road section (intersection approach steering) and the flow of the last (g-1) calculated road section is smaller than the calculation error limit value epsilon (in the case of the embodiment, epsilon is 10 ═ c)-4) And stopping the calculation, obtaining the final distributed traffic volume of the road section a at the moment, and returning to the second step if not. Fig. 13 shows the traffic flows allocated to the respective road sections after the equilibrium state is reached, and table 8 shows specific values of the traffic flows of the respective road sections when the equilibrium state is reached.
TABLE 8 summary of traffic flow values for each road segment under balanced conditions
Figure BDA0002135549160000163
Figure BDA0002135549160000171
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Although the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the invention. It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention. The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.

Claims (6)

1. A method for distributing traffic flow of an urban road network is characterized by comprising the following steps:
step 101: carrying out survey on the routing behavior of the resident on trip safety consideration to obtain a survey result of the routing behavior of the traveler on trip safety consideration;
step 102: the method comprises the steps of surveying the safety performance of the urban road network, and acquiring the safety performance data of each road section of the urban road network;
step 103: calculating parameters of the safe routing model to obtain parameter values in the model;
step 104: distributing the road network flow by adopting a safe routing model to obtain the traffic flow of each road section in a balanced state;
the secure routing model parameter calculation in step 103 further includes the following steps:
step 301: summarizing the safety attention degree and the safety-efficiency measurement index of the travelers according to the survey result of the routing behavior considered by the travelers in the step 101, calculating the ratio of the travelers under each safety attention degree (or under the measurement index), and summarizing the ratio into structured data;
step 302: calculating the average safety performance E (r) of each inlet steering of each road section and each intersection according to the accident information data obtained in the step 102 by dividing the total cost generated by the traffic accidents occurring at each road section or each intersection by the data time span rangea) And E (r)a→b) The unit is: yuan/min, the calculation formula is:
Figure FDA0002816409190000011
or
Figure FDA0002816409190000012
Wherein the content of the first and second substances,
Figure FDA0002816409190000013
property loss is caused by the road section a, the accident Z occurs when a is equal to (1,2, …, A), and the accident Z is equal to (1,2, …, Z),
Figure FDA0002816409190000014
accident for intersection turning a → b
Figure FDA0002816409190000015
Figure FDA0002816409190000016
N is the length of time of the collected accident data;
step 303: calculating the discrete situation of the traffic conflict in each road section and each imported steering period of the intersection according to the traffic conflict data in the step 102, judging the safety and reliability performance of each imported steering of each road section and the intersection, considering that the stability of the number of times of the traffic conflict in each period can indirectly represent the safety and reliability of each imported steering of each road section and the intersection, the higher the stability is, the better the safety and reliability is, specifically, calculating the variance value of the number of times of the traffic conflict in each period, dividing the variance of the number of conflicts of each imported steering of each road section and the intersection into three types of low, medium and high, and matching different safety and reliability values with each type of road section and each imported steering of the intersection
Figure FDA0002816409190000017
And
Figure FDA0002816409190000018
the unit is: yuan/min;
step 304: the method for counting the attribute parameter values of the inlet turning of each road section and each intersection comprises the following steps: obtaining the traffic capacity C of each road section and intersection according to historical dataaZero flow time impedance
Figure FDA0002816409190000019
The retardation coefficient alpha, beta existing road condition data, and the road average safety performance and safety and reliability performance data obtained in the steps 302 and 303 are arranged into a structured data format;
the road network flow calculation and distribution in step 104 further includes the following steps:
step 401: firstly, drawing a road network topological structure diagram including intersection turning according to urban road network structure information in historical data, generating an access relation matrix according to an inter-cell access relation displayed by the structure diagram, and generating a travel demand matrix according to resident travel OD (origin-destination) data among all traffic cells;
step 402: according to the result of step 301, traveler's safety preference parameters in the model are input, including: traveler occupation ratio lambda of different safety concernsmM ═ 1,2, …, M is the number of panelists, and the ratio θ of panelists to different safety-to-efficiency metricsnN is (1,2, …, N) is the number of panelists; inputting initial data of the model according to the statistical data in the step 304 and the step 401, including information of each road section (1. retardation coefficient alpha, beta, 2. zero flow time)
Figure FDA0002816409190000021
3. Traffic capacity caAverage safety, 5 safety reliability) and the travel requirement of the user class m between OD pairs, and simultaneously setting a model calculation error limit value epsilon (self-setting according to the precision requirement);
step 403: calculating the path flow by adopting a traveler routing rule model;
step 404: according to the path flow obtained in the step 403, reversely deducing the flow of the path passing through all road sections and intersection inlet steering through the access relation matrix in the step 401, and updating the flow of the road sections and intersection inlet steering;
step 405: judging whether the balance is achieved or not, according to the step 404, if the difference value between the current calculated road section and intersection inlet steering flow and the last calculated flow result is less than the calculation error limit value epsilon set in the step 402, stopping calculation, and at the moment, obtaining the final distributed traffic volume of the road section a, otherwise, returning to the step 403;
the step 403 of calculating the path flow by using the traveler routing rule model further includes the following steps:
step 4031: calculating the passing time of each road section according to the flow of each road section; specifically, the traffic capacity c of each road section obtained through the step 304 by adopting the BPR functionaAnd zero stream time
Figure FDA0002816409190000022
Calculating the traffic volume q of each road sectionaThe following transit time is calculated by the formula:
Figure FDA0002816409190000023
wherein alpha and beta are retardation coefficients obtained in step 304, the traffic flow is zero and the transit time is zero flow time under the initial condition
Figure FDA0002816409190000024
Step 4032: calculating generalized travel expenses of the imported steering of each road section and each intersection; the calculation formula is as follows:
Figure FDA0002816409190000025
Ca→b＝E(ra→b)
multiplying the transit time obtained in the step 4031 by the safety-efficiency trade-off index theta of various travelersnAnd adding the safety performance of each road section obtained in the step 302 to obtain the generalized travel cost C of the n classes of users on the road sectionaThe generalized travel cost of the intersection import steering is E (r)a→b)；
Step 4033: computing a minimum cost path set
Figure FDA0002816409190000031
Specifically, based on the generalized travel costs of the road section and the intersection inlet turning calculated in step 4032, the generalized travel costs of all the routes passing through the road section are added, and the generalized travel costs of all the routes between each OD pair are calculated:
Figure FDA0002816409190000032
wherein the content of the first and second substances,
Figure FDA0002816409190000033
and
Figure FDA0002816409190000034
if the road section and the intersection are in the path p, the value is 1, otherwise the value is 0; for the convenience of subsequent calculation, the first 10 paths with the minimum cost are selected between each OD pair to form a minimum cost path set;
step 4034: according to the safety reliability obtained in steps 303 and 304, in combination with the attention of the traveler in step 301 to the safety reliability of the route, on the basis of the generalized travel cost obtained in step 4033, the safety reliability cost of the route of different travelers is added, and the formula is as follows:
Figure FDA0002816409190000035
and outputting the minimum cost path of each class of travelers in the new minimum cost path set, thereby obtaining the minimum cost path of m classes of travelers in the minimum cost path set
Figure FDA0002816409190000036
Figure FDA0002816409190000037
Step 4035: distributing traffic flow according to travel demand in step 401, distributing the demand of m types of travelers between the ODs obtained in step 401 to the shortest path of m types of travelers by adopting an all-or-nothing distribution method, and obtaining the additional traffic volume of each path
Figure FDA0002816409190000038
Step 4036: calculating the current traffic volume of each current (g-th distribution) path by using a weighted average method
Figure FDA0002816409190000039
The formula is as follows:
Figure FDA00028164091900000310
2. the method according to claim 1, wherein the step 101 of investigating the route selection behavior of the resident for travel safety consideration further comprises the steps of:
s1: sampling a survey object, wherein the sampling adopts a hierarchical sampling method;
s2: and (3) carrying out resident trip safety consideration routing behavior survey by adopting an RP survey method, obtaining a traveler safety consideration routing behavior survey result, and counting the survey result.
3. The method for distributing traffic flow of urban road network according to claim 2, wherein in step S2, said survey, specifically a family visit survey, is performed while obtaining survey data; the survey content includes: and (3) supposing that m classes of travelers with different safety concerns and n classes of travelers with different weighing standards exist in the region, investigating the safety concerns of the travelers, classifying, investigating the weighing behaviors of the travelers on the traveling safety and the traveling efficiency, and classifying.
4. The method according to claim 1, wherein the safety performance data of each road segment of the urban road network in step 102 specifically includes accident information data reflecting average safety performance of roads and traffic conflict related data reflecting safety and reliability performance of roads.
5. The method according to claim 4, wherein the accident information data of step 102 specifically includes accident location information and severity thereof, property loss information for at least one year, and intersection accidents need to be classified according to the turning location or ongoing turning behavior of the main responsible party at the time of the incident.
6. The method according to claim 5, wherein the data related to traffic conflicts in step 102 specifically includes conflict type and severity information, and the intersection conflict needs to be recorded for different turning directions of each entrance.
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