Traffic bearing capacity calculation method considering road network reserve capacity

Abstract

The invention discloses a traffic bearing capacity calculation method considering road network reserve capacity, and belongs to the field of urban traffic. The method solves the problems that an existing traffic bearing capacity calculation method is high in complexity and low in timeliness. According to the method, the reserve capacity of the road network is considered, the traffic volume is loaded into the traffic network in a step-by-step loading mode, the maximum traffic bearing capacity of the road network under the condition that the capacity constraint of the road sections in the road network is met can be obtained, and the calculation method is suitable for the road networks of any scale and any morphological structure and has high practicability. The problems that according to an existing traffic bearing capacity calculation method, road network scales and road network morphological structure planning need to be considered, and different models need to be adopted for calculation for different road network scales and road network morphologies are solved, the traffic bearing capacity calculation method is put forward on the basis of a traffic distribution calculation method, operation calculation is easy, and the calculation efficiency is improved. Complexity of calculation is reduced, and timeliness of calculation is improved. The method can be applied to traffic bearing capacity calculation.

Description

Technical Field

[0001] The invention belongs to the field of urban transportation, and in particular relates to a method for calculating the traffic carrying capacity taking into account the reserve capacity of a road network. Background Art

[0002] Urban transportation network resilience is a property that measures whether the urban transportation network can guarantee the demand for the transportation system in the process of post-disaster rescue and evacuation in the city and quickly restore its transportation function when facing various disasters. Traffic carrying capacity is a key parameter of urban transportation network resilience. Real-time and accurate measurement of the traffic carrying capacity of the urban road network is of great significance for improving the post-disaster evacuation capacity of the urban road network and formulating the post-disaster evacuation strategy of the city. The urban transportation network is planned and laid out based on meeting the daily transportation needs of the city. The passenger flow is stable during the daily operation of the city, and the traffic carrying capacity can meet the daily transportation needs. However, when the city faces various disasters, abnormal passenger flow will occur in the transportation network, which will have a severe impact on the entire transportation network. In order to restore the normal operation of the urban transportation network as soon as possible, it is necessary to reasonably measure the traffic carrying capacity of the urban transportation network to meet the needs of post-disaster rescue and post-disaster recovery.

[0003] However, the existing methods need to rely on survey data to calculate traffic carrying capacity, so there are problems of high computational complexity and low timeliness, which cannot meet the timeliness requirements of traffic carrying capacity calculation for post-disaster evacuation. Summary of the invention

[0004] The purpose of the present invention is to solve the problems of high complexity and low time efficiency of existing traffic carrying capacity calculation methods, and to propose a traffic carrying capacity calculation method that takes into account the reserve capacity of the road network.

[0005] The technical solution adopted by the present invention to solve the above technical problems is: a method for calculating traffic carrying capacity taking into account the reserve capacity of the road network, the method specifically comprising the following steps:

[0006] Step 1: Obtain the structural parameters of the urban transportation network and establish a graph network structure model based on the structural parameters;

[0007] Step 2: Establish the impedance function of each road section in the graph network structure model;

[0008] Step 3, respectively setting the maximum traffic load level threshold of the road section in the graph network structure model and the maximum traffic load level range of the urban traffic network;

[0009] Step 4: Obtain the origin and destination matrix of traffic trips under normal traffic conditions of the urban traffic network, that is, obtain the OD traffic volume matrix;

[0010] Step 5: Initialize the number of iterations i = 1, and initialize the OD traffic volume matrix obtained in step 4 to Q 0 ;

[0011] Step 6: According to the impedance function established in step 2, the OD traffic matrix Q i-1 The traffic volume in the city is distributed to each section of the urban transportation network;

[0012] Step 7: After the traffic volume is distributed, the total number of road sections that have not reached their own maximum traffic volume load level threshold is counted, and then it is determined whether the total number of road sections obtained by counting is within the maximum traffic volume load level range of the urban traffic network;

[0013] If the total number of road sections obtained by statistics is within the maximum traffic load level range of the urban traffic network, then the current OD traffic matrix is ​​the maximum traffic carrying capacity of the current urban traffic network;

[0014] Otherwise, execute step eight;

[0015] Step 8: Multiply the current OD traffic volume matrix by the adjustment coefficient to obtain the adjusted OD traffic volume matrix, and set i=i+1, and use the adjusted OD traffic volume matrix to return to step 6.

[0016] The beneficial effects of the present invention are:

[0017] The present invention takes into account the reserve capacity of the road network, and loads the traffic volume into the traffic network in a step-by-step loading manner, so as to obtain the maximum traffic carrying capacity of the road network under the condition of satisfying the capacity constraints of the road sections in the road network. Moreover, the calculation method of the present invention is applicable to road networks of any scale and any morphological structure, and solves the problem that the existing traffic carrying capacity calculation method needs to consider the road network scale and the road network morphological structure planning, and different road network scales and road network morphologies need to adopt different models for calculation. Moreover, the traffic carrying capacity calculation method proposed by the present invention is proposed on the basis of the traffic distribution calculation method, is easy to operate and calculate, reduces the complexity of the calculation, and improves the timeliness of the calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the method of the present invention;

[0019] Figure 2 This is the road network structure diagram of city A;

[0020] Figure 3 This is a schematic diagram of the road network nodes and section numbering in City A. DETAILED DESCRIPTION

[0021] Specific implementation method 1: A method for calculating traffic carrying capacity considering road network reserve capacity described in this implementation method specifically includes the following steps:

[0022] Step 1: Obtain the structural parameters of the urban transportation network and establish a graph network structure model based on the structural parameters;

[0023] Step 2: Establish the impedance function of each road section in the graph network structure model;

[0024] Step 3, respectively setting the maximum traffic load level threshold of the road section in the graph network structure model and the maximum traffic load level range of the urban traffic network;

[0025] Step 4: Obtain the traffic origin and destination matrix (current OD matrix) under the normal traffic state of the urban traffic network (normal traffic state refers to the non-post-disaster state), that is, obtain the OD traffic volume matrix;

[0026] Step 5: Initialize the number of iterations i = 1, and initialize the OD traffic volume matrix obtained in step 4 to Q 0 ;

[0027] Step 6: Based on the impedance function established in step 2, the OD traffic matrix Q is transformed into i-1 The traffic volume in the city is distributed to each section of the urban transportation network;

[0028] Step 7: After the traffic volume is distributed, the total number of road sections that have not reached their own maximum traffic volume load level threshold is counted, and then it is determined whether the total number of road sections obtained by counting is within the maximum traffic volume load level range of the urban traffic network;

[0029] If the total number of road sections obtained by statistics is within the maximum traffic load level range of the urban traffic network, then the current OD traffic matrix is ​​the maximum traffic carrying capacity of the current urban traffic network;

[0030] Otherwise, execute step eight;

[0031] Step 8: Multiply the current OD traffic volume matrix by the adjustment coefficient to obtain the adjusted OD traffic volume matrix, and set i=i+1, and use the adjusted OD traffic volume matrix to return to step 6.

[0032] The road network reserve capacity in the present invention refers to the maximum OD traffic volume that can be actually accommodated in the road network when the actual OD traffic volume of the road network is Q and the traffic capacity and service level constraints of the road sections in the network are met, which is μQ. Then (μ-1)Q is the reserve capacity in the road network.

[0033] Specific implementation method 2: This implementation method is different from the specific implementation method 1 in that the urban traffic network structure parameters include urban traffic network vertices, road section locations and road section lengths.

[0034] The other steps and parameters are the same as those in the first embodiment.

[0035] For an urban transportation network, both ends of each road segment are vertices in the urban transportation network.

[0036] Specific implementation method three: This implementation method is different from specific implementation methods one or two in that the graph network structure model is established based on the structure parameters, specifically:

[0037] After numbering the vertices and road sections in the urban transportation network, an urban transportation network adjacency matrix is ​​established, that is, a graph network structure model including vertices, road sections and adjacency matrix is ​​obtained.

[0038] The other steps and parameters are the same as those in the first or second embodiment.

[0039] Specific implementation method 4: This implementation method is different from the specific implementation methods 1 to 3 in that the specific process of step 2 is as follows:

[0040] For any road segment in the graph network structure model, the impedance function of the road segment is:

[0041]

[0042] Where Q is the traffic volume in the road section; C is the designed traffic capacity of the road section; t 0 is the travel time of the road section under free flow state; α and β are the parameters of the impedance function; t is the travel time of the road section when the traffic volume on the road section is Q.

[0043] The other steps and parameters are the same as those in Specific Embodiments 1 to 3.

[0044] Specific implementation method five: This implementation method is different from any one of specific implementation methods one to four in that the maximum traffic load level threshold of the road section is set to the design traffic volume of the road section.

[0045] The other steps and parameters are the same as those in Specific Embodiments 1 to 4.

[0046] The maximum traffic load level threshold of a road section in an urban traffic network is determined according to the traffic network congestion level, which can be divided into three levels: the first level congestion level corresponds to a traffic volume that is more than 2 times the design traffic volume of the road section, the second level congestion level corresponds to a traffic volume that is more than 1.5 times the design traffic volume of the road section, and the third level congestion level corresponds to a traffic volume that is more than 1 times the design traffic volume of the road section. In this implementation, the threshold of the third level congestion level is selected as the maximum traffic load level threshold of the road section.

[0047] Specific implementation method six: This implementation method is different from any one of specific implementation methods one to five in that the maximum traffic load level range of the urban transportation network is [94%A, 96%A], where A is the total number of road sections in the urban transportation network.

[0048] The other steps and parameters are the same as those in Specific Implementation Methods 1 to 5.

[0049] Specific implementation method 7: This implementation method is different from any one of specific implementation methods 1 to 6 in that the traffic volume in the OD traffic volume matrix obtained in step 4 is distributed to each road section of the urban traffic network, and the distribution objective function is:

[0050]

[0051] Where v is the traffic volume allocated to road section a, It is the road section travel time when the traffic volume assigned to road section a is v, A is the road section set of the urban transportation network, and T is the travel time of all passengers in the urban transportation network.

[0052] The other steps and parameters are the same as those in Specific Embodiments 1 to 6.

[0053] Specific implementation eight: This implementation differs from any one of specific implementations one to seven in that, in step eight, the current OD traffic matrix is ​​multiplied by the adjustment coefficient to obtain the adjusted OD traffic matrix, specifically:

[0054] If the total number of road sections obtained by statistics is greater than 96% A, the traffic volume data in the current OD traffic volume matrix is ​​enlarged, that is,

[0055] Q i =(1+δ i )Q i-1

[0056] Among them, Q i-1 is the current OD traffic matrix, δ i is the step size coefficient, Q i is the adjusted OD traffic volume matrix;

[0057] If the total number of road sections obtained by statistics is less than 94% A, the traffic volume data in the current OD traffic volume matrix is ​​reduced, that is,

[0058] Q i =(1-δ i )Q i-1

[0059] The other steps and parameters are the same as those in Specific Embodiments 1 to 7.

[0060] This implementation method directly uses the current traffic demand information and the road network reserve capacity to amplify the current OD matrix until the maximum limit of the road network capacity is reached. The traffic volume in the current state is the maximum traffic carrying capacity of the road network.

[0061] Specific implementation method 9: This implementation method is different from any one of the specific implementation methods 1 to 8 in that the step length coefficient δ i The value is taken as 2%.

[0062] The other steps and parameters are the same as those in Specific Embodiments 1 to 8.

[0063] Example

[0064] Combine the following Figure 1 , Figure 2 and Figure 3 This embodiment provides a method for calculating the traffic carrying capacity taking into account the road network reserve capacity. The calculation flow chart is as follows: Figure 1 As shown, it includes:

[0065] S1: Obtain the parameters of the urban traffic network structure and establish a graph network structure model. The established graph network structure is as follows: Figure 2 As shown, the vertices and edges in the graph network structure model are numbered, and the numbering results are as follows Figure 3 shown.

[0066] S2: According to the traffic capacity of the road sections in the traffic network, the impedance function of each road section in the traffic network is established. The impedance function of the road section in the traffic network is shown in Table 1, that is, α=0.15, β=4 in the impedance function, which can also be obtained by traffic flow fitting;

[0067] Table 1. Section impedance function

[0068] Section number Section capacity Link impedance function 1 25900 6*[1+0.15*(Q / 25900)**4 2 23403 4*[1+0.15*(Q / 23403)**4 3 25900 6*[1+0.15*(Q / 25900)**4 4 4958 5*[1+0.15*(Q / 4958)**4 5 23403 4*[1+0.15*(Q / 23403)**4 6 17110 4*[1+0.15*(Q / 17110)**4 7 23403 4*[1+0.15*(Q / 23403)**4 8 17110 4*[1+0.15*(Q / 17110)**4 9 17782 2*[1+0.15*(Q / 17782)**4 10 4908 6*[1+0.15*(Q / 4908)**4 … … … 74 5091 4*[1+0.15*(Q / 5091)**4 75 4885 3*[1+0.15*(Q / 4885)**4 76 5078 2*[1+0.15*(Q / 5078)**4

[0069] S3: Formulate the thresholds of the maximum traffic load levels of sections and networks in the urban road network. In this embodiment, the maximum traffic load level of the section is formulated using a three-level congestion level, that is, when the traffic volume of each section reaches the design traffic volume of the section, it is considered that the maximum traffic load level is reached. The maximum traffic volume of each section is shown in Table 2. The maximum traffic load level of the traffic network is set to ensure that 94% to 96% of the sections do not reach the maximum traffic load level of the section as the threshold of the maximum traffic load level of the network;

[0070] Table 2

[0071]

[0072]

[0073] S4: Obtain a traffic trip origin and destination matrix (current OD matrix) under normal traffic conditions of the urban traffic network. The OD matrix can be obtained through traffic surveys. The traffic network trip OD matrix in this embodiment is shown in Table 3.

[0074] Table 3. Transportation network travel OD matrix

[0075]

[0076]

[0077] S5: Allocate the current OD traffic volume to the current traffic network using the traffic allocation method. The allocation results are shown in Table 4.

[0078] Table 4 Allocation results

[0079]

[0080]

[0081] S6: Determine whether each road section in the road network has reached its maximum traffic load level threshold. The comparison between the traffic volume of the road section in the road network and the maximum traffic load level threshold of the road section is shown in Table 5;

[0082] Table 5

[0083]

[0084]

[0085] S7: judging whether the entire road network has reached its maximum traffic load level range according to the maximum traffic load level range of the road network. In this embodiment, only the traffic volume of the road section numbered 48 has reached its maximum traffic load level. Therefore, the entire network has not reached its maximum traffic load level range.

[0086] S8: according to whether the overall road network has reached its maximum traffic load level range, the current state OD matrix is ​​enlarged or reduced until the entire traffic network reaches its maximum traffic load level range after the obtained OD matrix is ​​allocated to the current traffic network using the traffic allocation method. In this embodiment, if the traffic network does not reach its maximum traffic load level range after the first traffic allocation, the OD matrix is ​​updated;

[0087] If the total number of road sections obtained by statistics is greater than 96% A, then the current state OD matrix Q i-1 According to a certain step coefficient δ i To zoom in,

[0088] Q i =(1+δ i )Q i-1

[0089] If the total number of road sections obtained by statistics is less than 94% A, the traffic volume data in the current OD traffic volume matrix is ​​reduced, that is,

[0090] Q i =(1-δi )Q i-1

[0091] Among them, the step coefficient δ i Take 2% and repeat the above steps. Finally, the OD matrix that reaches the maximum traffic load level after traffic distribution and the traffic volume of each section after distribution are obtained as shown in Table 6:

[0092] Table 6

[0093]

[0094]

[0095] When the road network is in the maximum traffic load level range, the comparison of the traffic volume of the road section in the road network and the threshold value of the maximum traffic load level of the road section is shown in Table 7;

[0096] Table 7

[0097]

[0098]

[0099] The corresponding road network OD matrix under the current state is the maximum traffic carrying capacity of the traffic network.

[0100] The above calculation examples of the present invention are only used to explain the calculation model and calculation process of the present invention in detail, and are not intended to limit the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for calculating traffic carrying capacity taking into account road network reserve capacity, characterized in that: The method specifically comprises the following steps: Step 1: Obtain the structural parameters of the urban transportation network and establish a graph network structure model based on the structural parameters; Step 2: Establish the impedance function of each road section in the graph network structure model; Step 3, respectively setting the maximum traffic load level threshold of the road section in the graph network structure model and the maximum traffic load level range of the urban traffic network; Step 4: Obtain the origin and destination matrix of traffic trips under normal traffic conditions of the urban traffic network, that is, obtain the OD traffic volume matrix; Step 5, initialize the number of iterations i = 1, and initialize the OD traffic volume matrix obtained in step 4 to Q0; Step 6: According to the impedance function established in step 2, the OD traffic matrix Q i-1 The traffic volume in the city is distributed to each section of the urban transportation network; Step 7: After the traffic volume is distributed, the total number of road sections that have not reached their own maximum traffic volume load level threshold is counted, and then it is determined whether the total number of road sections obtained by counting is within the maximum traffic volume load level range of the urban traffic network; If the total number of road sections obtained by statistics is within the maximum traffic load level range of the urban traffic network, then the current OD traffic matrix is ​​the maximum traffic carrying capacity of the current urban traffic network; Otherwise, execute step eight; Step 8: Multiply the current OD traffic volume matrix by the adjustment coefficient to obtain the adjusted OD traffic volume matrix, and set i=i+1, and use the adjusted OD traffic volume matrix to return to step 6.

2. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 1, characterized in that: The urban traffic network structure parameters include urban traffic network vertices, road section locations and road section lengths.

3. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 2, characterized in that: The graph network structure model is established based on the structural parameters, specifically: After numbering the vertices and road sections in the urban transportation network, an urban transportation network adjacency matrix is ​​established, that is, a graph network structure model including vertices, road sections and adjacency matrix is ​​obtained.

4. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 3, characterized in that: The specific process of step 2 is as follows: For any road segment in the graph network structure model, the impedance function of the road segment is: Among them, Q is the traffic volume in the section; C is the designed traffic capacity of the section; t0 is the travel time of the section under the free flow state; α and β are the parameters of the impedance function; t is the travel time of the section when the traffic volume on the section is Q.

5. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 4, characterized in that: The maximum traffic load level threshold of the road section is set to the design traffic volume of the road section.

6. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 5, characterized in that: The maximum traffic load level range of the urban traffic network is [94%A, 96%A], where A is the total number of road sections in the urban traffic network.

7. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 6, characterized in that: The traffic volume in the OD traffic volume matrix obtained in step 4 is distributed to each road section of the urban traffic network, and the objective function of the distribution is: Where v is the traffic volume allocated to road section a, It is the road section travel time when the traffic volume assigned to road section a is v, A is the road section set of the urban transportation network, and T is the travel time of all passengers in the urban transportation network.

8. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 7, characterized in that: In step eight, the current OD traffic matrix is ​​multiplied by the adjustment coefficient to obtain the adjusted OD traffic matrix, which is specifically: If the total number of road sections obtained by statistics is greater than 96% A, the traffic volume data in the current OD traffic volume matrix is ​​enlarged, that is, Q i =(1+δ i )Q i-1 Among them, Q i-1 is the current OD traffic matrix, δ i is the step size coefficient, Q i is the adjusted OD traffic volume matrix; If the total number of road sections obtained by statistics is less than 94% A, the traffic volume data in the current OD traffic volume matrix is ​​reduced, that is, Q i =(1-δ i )Q i-1 。 9. A method for calculating traffic carrying capacity taking into account road network reserve capacity according to claim 8, characterized in that: The step size coefficient δ i The value is taken as 2%.

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