A method for estimating accessibility of urban freight transportation based on multi-path capacity allocation

Abstract

The present invention discloses a method for estimating the accessibility of urban freight transportation based on multi-path capacity allocation, including: 1. collecting urban freight road transportation networks under different road structures; 2. determining the traffic load of each road section of urban freight transportation; 3. finding an effective transportation path from a freight loading point in the city to an exit point at the city boundary; 4. based on a multi-path capacity allocation model, using a multinomial logit model to determine the selection probability of different effective paths; 5. obtaining the UCTA of a freight loading point in the city according to the path selection probability; 6. determining the UCTA of all freight loading points in the city, and obtaining the mobility of urban freight transportation under the road structure. The present invention can select urban freight transportation paths based on multi-path capacity allocation and the anti-interference ability of paths under different urban road network structures, so as to improve the accuracy and reliability of urban freight transportation accessibility estimation, thereby better determining the mobility of goods.

Description

Technical Field

[0001] The present invention relates to the field of urban freight road transportation, and in particular to an urban freight transportation accessibility estimation method based on multi-path capacity allocation under different road network structures. Background Art

[0002] The rapid development of urban road network layout and logistics industry in recent decades has had a profound impact on the mobility of goods, which is reflected in the more complete transportation network and more frequent freight transportation. The complexity of the transportation network and the diversity of spatial changes make it difficult for transportation planners to accurately understand the problem and propose solutions, because they know little about the mechanism of building an urban freight mobility system. In this context, the urban road network structure has become an important part of the freight transportation system, strengthening the understanding and thinking of transportation planners on public policies, urban planning and land use. Previous scientific research only described different urban road network structures and analyzed their advantages and disadvantages, and rarely linked them to urban freight transportation. Summary of the invention

[0003] In order to solve the shortcomings of the above-mentioned prior art, the present invention proposes a method for estimating the accessibility of urban freight transportation based on multi-path capacity allocation, so as to select urban freight transportation paths based on multi-path capacity allocation and the anti-interference ability of paths under different urban road network structures, so as to improve the accuracy and reliability of urban freight transportation accessibility estimation, thereby better determining the mobility of goods.

[0004] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme:

[0005] The method for estimating accessibility of urban freight transportation based on multi-path capacity allocation of the present invention is characterized in that it comprises the following steps:

[0006] Step 1: Assume that the urban freight road network W contains I max Cargo shipping point and J max The export points on the city border are searched according to the electronic map of the urban freight road network W, and all paths from each cargo shipping point to each export point are searched, among which the i-th cargo shipping point is the export point. i To the jth exit point out j The set of all paths is denoted as R ij ;Remember the path set R ij Any y-th path in Path y The kth road segment between any two intersection points is recorded as

[0007] Step 2: Use formula (1) to get the path The kth road segment Traffic load And as a vehicle on the corresponding road section Shipping time:

[0008]

[0009] In formula (1), is the kth road segment Length, is the kth road segment of traffic volume, Corresponding road section The ability to travel freely, and are pending parameters, and have:

[0010]

[0011]

[0012]

[0013] In formula (2) to formula (4), is the kth road segment The vehicle speed, is the kth road segment The maximum traffic volume, The traffic volume is The best speed when

[0014] Using equations (5) and (6) to establish the unknown parameters and The maximum freight flow and optimal speed The relationship is:

[0015]

[0016]

[0017] Step 3: Find an effective transportation path from the cargo loading point to the export point in the urban cargo transportation road network W;

[0018] Step 3.1: Assume that the yth path The kth road segment in The starting point is u ij,k , the end point is t ij,k , using formula (7) to construct the kth road segment r ij,k Quantitative indicator Ep(out j ,u ij,k tij,k ):

[0019]

[0020] In formula (7), T min (u ij,k ,out j ) is the starting point u ij,k To the jth exit point out j The minimum traffic load, T min (t ij,k ,out j ) is from the end point t ij,k To the jth exit point out j Minimum traffic load;

[0021] Step 3.2: If Ep(out j ,u ij,k t ij,k )≤θ or T min (u ij,k ,out j )=T min (t ij,k ,out j ), then the starting point is u ij,k , the end point is t ij,k The kth road segment r ij,k is the effective section r′ ij,k ; Otherwise, discard the kth road segment r ij,k , where θ represents the set threshold;

[0022] Step 3.3: According to steps 3.1 and 3.2, judge each section in all paths to obtain the set r′ of all valid sections. ij ;

[0023] Step 3.4: Find the route from the i-th cargo shipping point to the transport point from all valid routes. i Arrive at the jth exit point out j The set of all valid paths R′ ij ;

[0024] Step 4: Use formula (1) to obtain the valid path set R′ ij The sth valid path in The transportation time of each valid section of the road is calculated, so as to obtain the sth valid path The sum of the transportation time of all valid sections in the sth valid path Transportation time

[0025] Step 5: Use equation (8) to calculate the sth effective path The effect

[0026]

[0027] In formula (9), m represents the valid path set R′ ij The number of valid paths in ;

[0028] Step 6: Use formula (9) to calculate the transport cost from the i-th cargo shipping point i To the jth exit point out j The sth valid path The probability of selection

[0029]

[0030] In formula (9), is a fixed parameter;

[0031] Step 7: Set the valid path set R′ ij The valid road segment set r′ in ij Abstract as nodes, intersection points of all valid road segments and I max Cargo shipping point and J max The exit points are abstracted as edges to construct a complex network G;

[0032] Step 8: Calculate the sth effective path R′ in the complex network G using formula (10): ij The eth section Network connectivity after a disturbance

[0033]

[0034] In formula (10), N ij is the total number of initial nodes in the complex network G, p is the different interference modes, The total number of nodes that are stabilized under the p interference mode;

[0035] Step 9: Use formula (11) to give the sth effective path R′ ij The e-th section r′ ij,e Reliability Factor

[0036]

[0037] In formula (11), δ p is the interference condition in section r′ ij,e Reliability coefficient.

[0038] Step 10: Use formula (12) to calculate the effective path of the sth path Reliability factor

[0039]

[0040] In formula (12), c is the effective path The number of road sections in ;

[0041] Step 11: Use formula (13) to determine the calculation of the transport cost from the i-th cargo shipping point i To the jth exit point out j The sth valid path Average shipping time

[0042]

[0043] Step 12: Repeat steps 2-11 to get the transport from the i-th cargo shipping point i To the city border max Average transportation time for all export stations;

[0044] Step 13: Use formula (14) to get the i-th cargo shipping point in the city trans i Transport accessibility i :

[0045]

[0046] In formula (14), G j is the set of all exit sites on the city boundary, and out j ∈G j ;

[0047] Step 14: Repeat steps 2 to 13 to obtain the city I max The transport accessibility of each cargo shipping point is used to determine the mobility of urban cargo transportation.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0049] 1. This invention proposes the impact of different urban road network structures on urban freight transportation. Urban road network structures include grid type, belt type and ring-shaped radial type, and they continue to develop on this basis, gradually forming a mixed urban road network structure. Different urban road network structures may have different impacts on it. The study of the accessibility of freight transportation under different road network structures can explore the characteristics of freight transportation under different urban road network structures, which is conducive to further analyzing the mobility of urban freight transportation.

[0050] 2. The present invention describes the urban freight transport accessibility UCTA reflected by the transportation time. The selection of different paths is based on multi-path capacity allocation. The shorter the time, the greater the probability of being selected. It is simpler to operate than previous methods for exploring accessibility.

[0051] 3. The present invention takes into account the stability of the urban freight road transport network, and obtains the anti-interference ability of the effective path by performing interference simulation on the road section. When selecting the path, more comprehensive factors are considered, so its rationality and accuracy can be guaranteed.

[0052] 4. The present invention improves the selection of effective paths in the existing multi-path capacity allocation model, adds a quantitative index Ep when selecting effective paths, and ensures the rationality of road transport path selection.

[0053] 5. The present invention uses the dual method to abstract the urban freight transportation road network into a complex network, which is conducive to simplifying computer simulation and analyzing the stability of the road section to the overall transportation network. At the same time, interfering with the road section can ensure the integrity of the road network to a certain extent, which is more in line with the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a flow chart of the method of the present invention;

[0055] Figure 2 A basic urban freight road transport network;

[0056] Figure 3 Improve the graph for efficient paths;

[0057] Figure 4 Constructing a complex road network for urban freight road transport for the dual method;

[0058] Figure 5 is the road section interference graph;

[0059] Figure 6 Constructing graphs for road network interference policy models. DETAILED DESCRIPTION

[0060] In this embodiment, a method for estimating the accessibility of urban freight transportation based on multi-path capacity allocation is applied to the accessibility of urban freight transportation under different urban road network structures, and combines the urban road network structure with the transit transportation of freight in the city, while considering the reliability of the urban freight road transportation network, including: 1. Collecting urban freight road transportation networks under different road structures; 2. Determining the traffic load of each road section for urban freight transportation, that is, the actual time required to pass through the section; 3. Finding an effective transportation path from the cargo shipping point in the city to the exit point at the city boundary; 4. Based on the multi-path capacity allocation model, using the multinomial logit model to determine the selection probability of different effective paths; 5. Analyzing the stability of each effective path to the overall urban freight transportation network, and deriving the UCTA of a cargo shipping point in the city based on the path selection probability; 6. Determining the UCTA of all cargo shipping points in the city, and deriving the liquidity of urban freight transportation under the road structure, specifically, Figure 1 As shown, it is done according to the following steps:

[0061] Step 1: Assume that the urban freight road network W contains I max Cargo shipping point and J max Exit points on the city border, such as Figure 2 As shown, according to the electronic map of the urban freight road network W, all paths from each cargo shipping point to each export point are searched, among which the i-th cargo shipping point is the i To the jth exit point out j The set of all paths is denoted as R ij ;Remember the path set R ij Any y-th path in Path y The kth road segment between any two intersection points is recorded as

[0062] Step 2: Use formula (1) to get the path The kth road segment Traffic load And as a vehicle on the corresponding road section Shipping time:

[0063]

[0064] In formula (1), is the kth road segment Length, is the kth road segment of traffic volume, For the corresponding road section The ability to travel freely, and are pending parameters, and have:

[0065]

[0066]

[0067]

[0068] In formula (2) to formula (4), is the kth road segment The vehicle speed, is the kth road segment The maximum traffic volume, The traffic volume is The best speed when

[0069] Using equations (5) and (6) to establish the unknown parameters and The maximum freight flow and optimal speed The relationship is:

[0070]

[0071]

[0072] The urban road impedance function can reflect the traffic characteristics of the road network and is the basis of traffic distribution and network analysis. The accuracy of the road impedance function is the key to whether the distribution can be carried out correctly. The research on the road resistance function is essentially to determine the relationship between travel time and road traffic flow and road driving conditions. In the application of traffic distribution, the most widely used BPR impedance function is still used in the present invention to calculate the traffic load.

[0073] Step 3: Find an effective transportation path from the cargo loading point to the export point in the urban cargo transportation road network W;

[0074] Step 3.1: Assume that the yth path The kth road segment in The starting point is u ij,k , the end point is t ij,k , using formula (7) to construct the kth road segment r ij,k Quantitative indicator Ep(out j ,u ij,k t ij,k ):

[0075]

[0076] In formula (7), T min (uij,k ,out j ) is the starting point u ij,k To the jth exit point out j The minimum traffic load, T min (t ij,k ,out j ) is from the end point t ij,k To the jth exit point out j Minimum traffic load;

[0077] The selection of different paths is based on multi-path capacity allocation. The less time it takes, the higher the utility, and the higher the probability of being selected. When using this model, the effective road section and effective travel route for each OD point pair (i, j) must be determined first. The present invention discusses a multi-path allocation model and redefines the effective path by introducing a quantitative index Ep. That is, among the alternative feasible paths, if the relative difference between the right of way of the selected path and the right of way of the shortest path is within a certain range θ (that is, the distance or time that the traveler can tolerate in the process of transporting goods compared to the shortest path), it is an effective path.

[0078] Step 3.2: If Ep(out j ,u ij,k t ij,k )≤θ or T min (u ij,k ,out j )=T min (t ij,k ,out j ), then the starting point is u ij,k , the end point is t ij,k The kth road segment r ij,k is the effective section r′ ij,k ; Otherwise, discard the kth road segment r ij,k , where θ represents the set threshold;

[0079] In the original multi-path capacity allocation model, when determining the effective path, the effective section is determined only by the road rights between the two points of the section and the end point. This method of determining the effective path has certain defects, such as T min (u ij,k ,out j )=99<T min (t ij,k ,out j )=100, on the road section (u ij,k ,j ij,k ), the starting point u of the road segment ij,k Than the end of the section ij,k Closer to the city border, the jth exit point out j, so in a certain OD point pair, after t ij,k The path of the point is not considered a valid path. But in reality, in the road segment (u ij,k ,j ij,k ), if the road segment T min (u ij,k ,j ij,k )=1, then u ij,k After t ij,k Arrive at the jth exit point out at the city boundary j The path length is And from u ij,k Point directly reaches the jth exit point out j The path length is At this time, it is obviously unreasonable to allocate all freight volumes to path 2, so based on the above ideas, the existing method for determining effective paths is improved. Figure 3 shown.

[0080] Step 3.3: According to steps 3.1 and 3.2, judge each section in all paths to obtain the set r′ of all valid sections. ij ;

[0081] Step 3.4: Find the route from the i-th cargo shipping point to the transport point from all valid routes. i Arrive at the jth exit point out j The set of all valid paths R′ ij ;

[0082] Step 4: Use formula (1) to obtain the valid path set R′ ij The sth valid path The transportation time of each valid section of the road is calculated, so as to obtain the sth valid path The sum of the transportation time of all valid sections in the sth valid path Transportation time

[0083] Step 5: Use formula (8) to calculate the sth effective path The effect

[0084]

[0085] In formula (9), m represents the valid path set R′ ij The number of valid paths in ;

[0086] Step 6: Use formula (9) to calculate the transport cost from the i-th cargo shipping point i To the jth exit point out j The sth valid path The probability of selection

[0087]

[0088] In formula (9), is a fixed parameter;

[0089] Step 7: Use the dual method to convert the effective path set R′ ij The valid road segment set r′ in ij Abstract as nodes, intersection points of all valid road segments and I max Cargo shipping point and J max The exit points are abstracted as edges. Figure 4 As shown, a complex network G is constructed;

[0090] Step 8: Determine the stability of the effective paths to the overall freight transportation network.

[0091] Step 8.1: Establish the adjacency matrix of the urban freight transportation road network G. Perform random attacks and selective attacks on the complex network based on simulation software.

[0092] In the complex road network of the traffic road system, the stability of the road system refers to the response law of the urban freight transportation road network to various interference conditions when facing various operation interferences. In the operation of freight transportation, it is necessary to fully consider the random volatility of the road network and select the freight transportation path based on the road reliability, so as to improve the effectiveness of the path selection scheme. The present invention mainly interferes with the road section, which can ensure the integrity of the road network to a certain extent, which is more in line with the actual situation. Figure 5 shown.

[0093] The present invention makes the following assumptions about all possible interference situations of the urban freight road transport network:

[0094] 1. Carry out random interference attacks on an abstract cargo transportation network, simulating occasional interference on a single road section, such as road traffic accidents, sudden road congestion, etc. The characteristics of this interference mode are that the impact range is relatively small, it has strong randomness, and it has universal applicability. In the road network, it manifests as single-node single-section damage, that is, a certain section is damaged.

[0095] 2. According to the geographical location characteristics of the road network, collect the road sections in the study area where geological disasters frequently occur. The road sections in the area may suffer from occasional interference such as landslides and roadbed collapse. Selective interference attacks can be carried out on areas where geological disasters frequently occur. The characteristics of this interference mode are that the impact range is relatively small and it has a certain selectivity. In the road network, it is manifested as the destruction of a single node and a single road section, that is, a certain road section is destroyed.

[0096] 3. Selectively interfere with important nodes of the abstract freight transportation network. In the urban freight road transportation network, the larger the degree value of a node, the more important the node is in the network. At the same time, the more intersections there are at the node, the more likely it is to cause congestion during road operation. The interference mode is characterized by single-point multi-section damage, that is, multiple sections in the same area are interfered with at the same time.

[0097] The interference simulation process of the present invention is as follows Figure 6 shown.

[0098] Step 8.2: Use formula (10) to calculate the sth effective path R′ in the complex network G ij The eth section Network connectivity after a disturbance

[0099]

[0100] In formula (10), N ij is the total number of initial nodes in the complex network G, p is the different interference modes, The total number of nodes that have stabilized under the p interference mode.

[0101] The maximum connected subgraph is the size of the node when the network cascade failure ends and reaches a stable state. The ratio of its size value to the total number of nodes in the original network can be used to characterize the anti-interference ability. It is an important indicator for measuring the traffic capacity of the urban freight transportation network. The higher the ratio, the stronger the connectivity of the transportation network and the better the stability of the road section.

[0102] Step 9: Use formula (11) to give the sth effective path R′ ij The e-th section r′ ij,e Reliability Factor

[0103]

[0104] In formula (11), δ p is the interference condition in section r′ ij,e Reliability coefficient.

[0105] Step 10: Use formula (12) to calculate the effective path of the sth path Reliability factor

[0106]

[0107] In formula (12), c is the effective path The number of road segments in .

[0108] Step 11: Use formula (13) to determine the calculation of the transport cost from the i-th cargo shipping point i To the jth exit point out j The sth valid path Average shipping time

[0109]

[0110] Step 12: Repeat steps 2-11 to get the transport from the i-th cargo shipping point i To the city boundary max The average transportation time for all export stations.

[0111] Step 13: Based on the above assumptions, the UCTA of a cargo shipping point in the city will be aggregated into A i :

[0112]

[0113] In formula (14), G j is the set of all exit sites on the city boundary, and out j ∈G j ; A i is a UCTA at a cargo shipping point j in the city, J max is the number of exit sites on the city boundary.

[0114] Step 14: Repeat steps 2 to 13 to get the city I max The UCTA of each cargo shipping point determines the mobility of urban cargo transportation, so as to build urban cargo logistics parks around the larger cargo shipping points of UCTA to improve the efficiency of urban cargo transportation.

Claims

1. A method for estimating the accessibility of urban freight transportation based on multi-path capacity allocation, It is characterized in that The following steps are involved: Step 1: Assume that the urban freight road network Included Cargo shipping points and exit points on the city border and based on the urban freight road network electronic map, searching for all the paths from each cargo loading point to each export point, where Cargo shipping points To Exit Points The set of all paths is denoted as ; Record path set Any y-th path in , the yth path The kth road segment between any two intersection points is recorded as ; Step 2: Use formula (1) to get the path The kth road segment Traffic load , and as a vehicle on the corresponding road section Shipping time: (1) In formula (1), is the kth road segment Length, is the kth road segment of traffic volume, Corresponding road section The ability to travel freely, and are pending parameters, and have: (2) (3) (4) In formula (2) to formula (4), is the kth road segment The vehicle speed, is the kth road segment The maximum traffic volume, The traffic volume is The best speed when Using equations (5) and (6) to establish the unknown parameters and The maximum freight flow and optimal speed The relationship is: (5) (6) Step 3: Cargo transportation in the city road network Find out the efficient transportation path from the cargo loading point to the export point; Step 3.1: Assume that the yth path The kth road segment in The starting point is , the end point is , using formula (7) to construct the kth road segment Quantitative indicators : (7) In formula (7), From the starting point To Exit Points The minimum traffic load, From the end point To Exit Points Minimum traffic load; Step 3.2: If or , then the starting point is , the end point is The kth road segment For effective sections ; Otherwise, discard the kth road segment ,in, Indicates the set threshold; Step 3.3: According to step 3.1 and step 3.2, judge each section in all paths to obtain all valid sections. ; Step 3.4: Find the path from the first Cargo shipping points Arrive at Exit Points The set of all valid paths ; Step 4: Use formula (1) to obtain the valid path set The sth valid path in The transportation time of each valid section of the road is calculated, so as to obtain the sth valid path The sum of the transportation time of all valid sections in the sth valid path Transportation time ; Step 5: Use formula (8) to calculate the sth effective path The effect : (8) In formula (9), Represents a set of valid paths The number of valid paths in ; Step 6: Use formula (9) to calculate Cargo shipping points To Exit Points No. Valid paths The probability of selection : (9) In formula (9), is a fixed parameter; Step 7: Collect the valid paths The set of valid road segments in Abstract as nodes, intersection points of all valid road segments and Cargo shipping points and The exit points are abstracted as edges to build a complex network ; Step 8: Calculate the complex network using formula (10) The sth valid path in The eth section Network connectivity after a disturbance : (10) In formula (10), For complex networks The total number of initial nodes in , For different interference modes, Received The total number of nodes after stabilization in interference mode; Step 9: Use formula (11) to give the sth effective path The eth section Reliability Factor : (11) In formula (11), For Interference on the road section Reliability coefficient; Step 10: Use formula (12) to calculate the Path Valid Path Reliability factor : (12) In formula (12), For effective path The number of road sections in ; Step 11: Use formula (13) to determine the calculation from the first Cargo shipping points To Exit Points No. Valid paths Average shipping time : (13) Step 12: Repeat steps 2 to 11 to obtain Cargo shipping points To the city border Average transportation time for all export stations; Step 13: Use formula (14) to get the Cargo shipping points Transport accessibility : (14) In formula (14), is the set of all exit sites on the city boundary, and ; Step 14: Repeat steps 2 to 13 to get the city The transport accessibility of each cargo shipping point is used to determine the mobility of urban cargo transportation.

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