A snow-clearing vehicle operation path planning method based on key impact road section identification

Abstract

The present invention is applicable to the field of emergency management technology, and provides a method for planning the operation path of snow-clearing vehicles based on the identification of key affected sections, including: first, by analyzing the strength of the section, the number of edges, the influence of points of interest, and the influence of snow accumulation on the total travel time of vehicles on the section, the key affected sections of the city under snowfall conditions are identified. Then, a snow-clearing vehicle path planning model is established, and the initial set of key affected sections is input into the model to generate the initial operation path of the snow-clearing vehicle. During the snow-clearing process, the traffic status information of the road network is updated in a timely manner, including the snow accumulation on the road and the traffic flow changes. The set of key affected sections is re-evaluated and updated according to the updated road network information. The newly determined set of key affected sections is input into the snow-clearing vehicle path planning model to obtain an updated snow-clearing vehicle operation path. The present invention improves the emergency response capability of the city to snow disasters, ensures that traffic quickly returns to normal, and protects the safety of public travel.

Description

Technical Field

[0001] The present invention belongs to the technical field of emergency management, and in particular relates to a snow-clearing vehicle operation path planning method based on the identification of key impacted road sections. Background Art

[0002] In snowy weather, snow on the road will seriously affect the normal operation of the urban road traffic system. In order to ensure the safety and efficiency of traffic, it is crucial to formulate scientific, reasonable and efficient snow removal strategies. These strategies are designed to reduce the impact of snowfall on the urban road network and ensure that the traffic system can quickly resume normal operation.

[0003] Road snow removal is the key to dealing with winter snowfall. Many scholars have studied the problem of snow removal on winter road networks. For example, Lin Sixiang defined the criticality of a road section based on the increase in the travel cost of the entire road network after the failure of the road section, and used this to divide the priority service level of the road section, and established a snow removal vehicle path planning model with the shortest snow removal completion time as the goal. Yu Yang et al. considered the service level, fleet size and other constraints in winter road maintenance, and established an integer programming model for the optimal scheduling of snow removal vehicles under real-time information. Quirion-Blais et al. proposed that in an emergency, the problem of large-scale snow removal vehicle path optimization should be solved with the goal of minimizing the weighted operation time of each priority section. With the goal of improving the resilience of the road network, Wang Jing established a mathematical model for the road network recovery problem under ice and snow weather, and solved the problem of emergency material layout for snow removal in urban road networks under uncertain information in extreme ice and snow weather and the problem of optimizing snow removal operations.

[0004] However, there are still some limitations in the existing research on snow removal vehicle path planning. First, when selecting snow removal sections, existing studies often do not fully consider the impact of adjacent facilities, which affects the snow removal efficiency and the overall operation of the road network. Secondly, since snowfall is a dynamic loading process, the state of the road network will change dynamically. Therefore, the path planning of snow removal vehicles needs to be able to adapt to such changes, reduce invalid operations, and speed up the recovery of the road network. For this reason, a snow removal vehicle operation path planning method based on the identification of key affected sections is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a snow-clearing vehicle operation path planning method based on the identification of key affected road sections, aiming to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A snow-clearing vehicle operation path planning method based on key impact road section identification includes the following steps:

[0008] Step S1, Identification of road sections that are affected by snowfall: Identify road sections that are affected by snowfall based on the road network structure, function and adjacent facility features. Specifically, calculate the road section strength. U ij , edge betweenness D ij , Interest point influence P ij The impact of snow accumulation on the total travel time of vehicles on the road section B ij To identify the key impact sections in the city and form a key impact section set;

[0009] Step S2, plan the operation path of the snow-clearing vehicle according to the dynamic update of the key affected sections of the city: establish a snow-clearing vehicle operation path planning model, input the initial key affected section set into the snow-clearing vehicle operation path planning model, and generate the initial operation path of the snow-clearing vehicle; during the snow-clearing process, dynamically update the key affected section set according to the snowfall information and the traffic conditions of each section, and bring it into the snow-clearing vehicle operation path planning model to obtain the path planning scheme of the snow-clearing vehicle in the snow removal operation area; the input of the snow-clearing vehicle operation path planning model is the key affected section set, and the output is the driving path of the snow-clearing vehicle during the entire snow-clearing process and the timing arrangement of the working sections.

[0010] Furthermore, by measuring the strength of the road section U ij , edge betweenness D ij , Interest point influence P ij The importance of the road section is obtained after deviation standardization I ij :

[0011] Formula 12: ;

[0012] Where: Indicates the importance of the road segment; Indicates that the data is subjected to deviation standardization; Respectively D ij、 U ij and P ij The weight of B ij represents the impact of snow accumulation on the total travel time of vehicles on the road section; h represents the road section r ij Depth of snow on

[0013] Importance to road section I ij To normalize the deviation:

[0014] Formula 13: ;

[0015] When the result is When the result is When the snow depth is 0, it is determined as a minor road section; when the snow depth is 0, it is determined as a non-key affected road section.

[0016] Update the traffic status of each road section according to the snowfall information and calculate the importance of each road section I ij Then, according to formula 13, we determine whether the road section is a key impact road section, and get the key impact road section set A m ={ E m} ,in A m represents the set of key affected road sections obtained when the traffic status of the road section is updated for the mth time, E m Represents a collection of directed road segments.

[0017] Further, the strength of the road section is calculated U ij The formula is as follows:

[0018] Formula 1: ;

[0019] Formula 2: ;

[0020] Formula 3: ;

[0021] Formula 4: ;

[0022] Formula 5: ;

[0023] Formula 6: ;

[0024] Formula 7: ;

[0025] Formula 8: ;

[0026] Where: C i Representation Node i The overall strength of S i Indicates the target node i strength; represents the influence coefficient; Representation Node iThe set of neighbor nodes; Q j Indicates the target node j The strength of adjacent nodes; Q i Indicates the target node i The strength of adjacent nodes; λ Indicates the degree value influence coefficient; Indicates the target node i The penetration strength value; Indicates the target node i Output strength value; θ ji Indicates a directed segment r ji Weight; θ ij Indicates a directed segment r ij The weight of q ij Indicates road segment r ij Number of vehicles on board; G Represents a set of directed road segments in a road network. Any arc ( i , j ) indicates the direction is from the node i To adjacent nodes j directional segments; j Represents the neighbor nodes of target node i.

[0027] Further, the edge betweenness is calculated D ij The formula is as follows:

[0028] Formula 9: ;

[0029] Where: n G Representing road network G The total number of shortest paths between any nodes in ; n ij Indicates the road segment passed in the shortest path r ij The number of paths.

[0030] Further, the influence of the interest point is calculated P ij The formula is as follows:

[0031] Formula 10: ;

[0032] Where: P ij Indicates the influence of the point of interest; n The number of categories representing points of interest; Indicates road segment r ij The number of interest points of category ω within the buffer; IP ω Represents the importance value of the interest point of category ω.

[0033] Further, the influence of the snow accumulation on the total travel time of vehicles on the road section is calculated. B ij The formula is as follows:

[0034] Formula 11: ;

[0035] Where: l ij Indicates road segment r ij length; Indicates road segment r ij When the snow depth on the road is h, r ij The average speed of vehicles on the road; v ij Indicates road segment r ij When the snow depth is 0, the road section r ij The average speed of vehicles on the road.

[0036] Furthermore, the snow removal vehicle operation path planning model is shown in Formula 14-22;

[0037] Formula 14: ;

[0038] Formula 15: ;

[0039] Formula 16: ;

[0040] Formula 17: ;

[0041] Formula 18: ;

[0042] Formula 19: ;

[0043] Formula 20: ;

[0044] Formula 21: ;

[0045] Formula 22: ;

[0046] Formula 14 is the objective function, which means that the snowplow takes the shortest time to clear all the key affected sections; Formula 15 means that the snowplow can only perform snow removal operations on the sections in its driving path; Formula 16 means that the vehicle p Path continuity; Formula 17 represents the flow balance constraint of snow-clearing vehicles at each node; Formula 18 represents the flow balance constraint of snow-clearing vehicles entering and leaving the entire road network; Formula 19 represents the time when snow-clearing vehicles start and finish snow removal in each time period; Formula 20 represents the time when snow-clearing vehicles start and finish snow removal in each time period; p In the m When the snow-clearing task is concentrated on the key affected road sections, r ij Driving; Formula 21 represents snow clearing vehicle p In the m Whether to clear the road sections when the snow-clearing task is concentrated on the key affected road sections r ij ; Formula 22 represents snow clearing vehicle p In the m The number of unattended visits to key impacted sections when snow clearing is being carried out;

[0047] Where: T Indicates the time it takes for all snow-clearing vehicles to complete snow-clearing operations on all road sections; Snow removal vehicle p Total non-working driving time; Snow removal vehicle p Total working driving time; M Indicates the number of times the key impact section set is updated; m Indicates m Update the set of key impacted road sections; A m Indicates m A collection of key impacted road sections; P Indicates the assembly of snow-clearing vehicles; p Indicates p snow-clearing vehicles; l ij Indicates road segment r ij length; Indicated in m When the key impact segment set is updated, the segment r ij The average speed of vehicles on the road; v 0 means the rated operating speed of the snow-clearing vehicle; Indicates m When the snow-clearing task is concentrated on the key affected road sections, the snow-clearing vehicles p Is it on the road? r ji Travel on; Indicates mWhen the snow-clearing task is concentrated on the key affected road sections, the snow-clearing vehicles p Is it on the road? r ij Travel on; Snow clearing vehicle p Whether to affect the key road section set A m Work on the road section in the o Virtual nodes representing all snow-clearing vehicles entering the road network; d A virtual node representing all snow-clearing vehicles exiting the road network; Snow removal vehicle p The service start time; Snow removal vehicle p exist A m The time to complete snow clearing work; Snow removal vehicle p exist A m-1 The time to complete snow clearing work; Snow removal vehicle p On the road r ij The number of air traffic visits; i Represents a node; j Indicates adjacent nodes; G represents the road network; x ijp Snow clearing vehicle p Is it on the road? r ij Travel on; x jip Snow clearing vehicle p Is it on the road? r ji Travel on; y ijp Snow clearing vehicle p Is it for road section r ij Carry out homework; y jip Snow clearing vehicle p Is it for road section r ji Carry out homework; x ojp Snow clearing vehicle p Whether to travel from the virtual starting point o to node j; x jdp Snow clearing vehicle p Is it in the node j To the virtual destination d Drive on.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention provides a snow-clearing vehicle operation path planning method based on the identification of key affected road sections, aiming to enhance the emergency response capability of urban traffic when snow disasters occur. Through this method, the operation path of snow-clearing vehicles can be reasonably planned to ensure that the snow on the road is cleared in a timely and effective manner, and to avoid repeated operations or missing key areas. This method helps to quickly restore the normal operation of urban traffic and ensure that social and economic activities can proceed smoothly, thereby improving the city's emergency response efficiency and ensuring public travel safety in the event of snow disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 Flow chart of the method of the present invention.

[0051] Figure 2 This is a schematic diagram of the topological structure of the road traffic network in some areas of Changchun City in the present invention.

[0052] Figure 3 This is a snow-clearing operation path planning diagram for the first snow-clearing vehicle in the present invention.

[0053] Figure 4 This is a snow-clearing operation path planning diagram for the second snow-clearing vehicle in the present invention.

[0054] Figure 5 This is a snow-clearing operation path planning diagram for the third snow-clearing vehicle in the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0056] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0057] like Figure 1 As shown, an embodiment of the present invention provides a snow-clearing vehicle operation path planning method based on key impact road section identification, comprising the following steps:

[0058] Step S1, Identification of road sections that are affected by snowfall: Identify road sections that are affected by snowfall based on the road network structure, function and adjacent facility features. Specifically, calculate the road section strength. U ij , edge betweenness D ij , Interest point influence P ij The impact of snow accumulation on the total travel time of vehicles on the road sectionB ij To identify the key impact sections of the city and form a key impact section set; the content is as follows:

[0059] (1) Calculation of road section strength ;

[0060] Road section strength is the comprehensive strength of the nodes at both ends of the edge The product of the node comprehensive strength is determined by the target node strength and adjacent node strength Composition, target node strength By entry strength And output strength Add, enter strength is the weight of the directed path pointing to this node The sum of the output strength is the weight of the directed edge starting from this node The sum of the weights of the directed segments is the number of vehicles on the directional road segment Ratio to the total number of vehicles on the road network, influence strength of adjacent nodes It is the node strength value of the adjacent nodes of the target node;

[0061] Formula 1: ;

[0062] Formula 2: ;

[0063] Formula 3: ;

[0064] Formula 4: ;

[0065] Formula 5: ;

[0066] Formula 6: ;

[0067] Formula 7: ;

[0068] Formula 8: ;

[0069] Where: U ij Indicates the strength of the road section; C i Representation Node i The overall strength of S i Indicates the target node i strength; represents the influence coefficient; Representation Nodei The set of neighbor nodes; Q j Indicates the target node j The strength of adjacent nodes; Q i Indicates the target node i The strength of adjacent nodes; λ Indicates the degree value influence coefficient; Indicates the target node i The penetration strength value; Indicates the target node i Output strength value; θ ji Indicates a directed segment r ji Weight; θ ij Indicates a directed segment r ij The weight of q ij Indicates road segment r ij The number of vehicles on the vehicle; Unit: vehicle; G Represents a set of directed road segments in a road network. Any arc ( i , j ) indicates the direction is from the node i To adjacent nodes j directional segments; j Represents the neighbor nodes of target node i.

[0070] (2) Calculating edge betweenness D ij ;

[0071] Edge betweenness D ij For all the shortest paths in the network r ij The ratio of the number of paths to the number of shortest paths:

[0072] Formula 9: ;

[0073] Where: D ij represents the edge betweenness; n G Representing road network G The total number of shortest paths between any nodes in ; n ij Indicates the road segment passed in the shortest path r ij The number of paths.

[0074] (3) Calculate the influence of interest points Pij ;

[0075] Point of interest influence P ij It is equal to the number of facilities multiplied by the importance of that type of facility:

[0076] Formula 10: ;

[0077] Where: P ij Indicates the influence of the point of interest; n The number of categories representing points of interest; Indicates road segment r ij The number of interest points of category ω within the buffer; IP ω Represents the importance value of the interest point of category ω.

[0078] (4) Calculate the impact of the snow accumulation on the total travel time of vehicles on the road section B ij ;

[0079] The impact of snow accumulation on the total travel time of vehicles on a road section B ij Equal to the increase in travel time for all vehicles on the road segment:

[0080] Formula 11: ;

[0081] Where: B ij Indicates the impact of snow accumulation on the total travel time of vehicles on the road section, unit: hour; l ij Indicates road segment r ij Length, unit: kilometers; Indicates road segment r ij When the snow depth on the road is h, r ij The average speed of the vehicles on the road, in kilometers per hour; v ij Indicates road segment r ij When the snow depth is 0, the road section r ij The average speed of vehicles on the road, in kilometers per hour.

[0082] (5) Calculating the importance of road sections I ij ;

[0083] Road section importance Iij is to convert the road section strength U ij , edge betweenness D ij , Interest point influence P ij After deviation standardization, it is obtained, as shown in formula 12:

[0084] Formula 12: ;

[0085] Where: Indicates the importance of the road segment; Indicates that the data is subjected to deviation standardization; Respectively D ij、 U ij and P ij The weight of B ij represents the impact of snow accumulation on the total travel time of vehicles on the road section; h represents the road section r ij Depth of snow on

[0086] (6) Identify the road sections with the greatest impact;

[0087] Importance to road section I ij Perform deviation standardization, as shown in formula 13:

[0088] Formula 13: ;

[0089] When the result is When the result is When the snow depth on the road is 0, it is determined to be a non-key affected section.

[0090] Update the traffic status of each road section according to the snowfall information and calculate the importance of each road section I ij Then, according to formula 13, we determine whether the road section is a key impact road section, and get the key impact road section set A m ={ E m} ,in A m represents the set of key affected road sections obtained when the traffic status of the road section is updated for the mth time, E m Represents a collection of directed road segments.

[0091] Step S2, plan the operation path of the snow-clearing vehicle according to the dynamic update of the key affected sections of the city: establish a snow-clearing vehicle operation path planning model, input the initial key affected section set into the snow-clearing vehicle operation path planning model, and generate the initial operation path of the snow-clearing vehicle; during the snow-clearing process, dynamically update the key affected section set according to the snowfall information and the traffic conditions of each section, and bring it into the snow-clearing vehicle operation path planning model to obtain the path planning scheme of the snow-clearing vehicle in the snow removal operation area; the input of the snow-clearing vehicle operation path planning model is the key affected section set, and the output is the driving path of the snow-clearing vehicle during the entire snow-clearing process and the timing arrangement of the working sections.

[0092] The snow removal vehicle operation path planning model is shown in equation 14-22;

[0093] Formula 14: ;

[0094] Formula 15: ;

[0095] Formula 16: ;

[0096] Formula 17: ;

[0097] Formula 18: ;

[0098] Formula 19: ;

[0099] Formula 20: ;

[0100] Formula 21: ;

[0101] Formula 22: ;

[0102] Formula 14 is the objective function, which means that the snowplow takes the shortest time to clear all the key affected sections; Formula 15 means that the snowplow can only perform snow removal operations on the sections in its driving path; Formula 16 means that the vehicle p Path continuity; Formula 17 represents the flow balance constraint of snow-clearing vehicles at each node; Formula 18 represents the flow balance constraint of snow-clearing vehicles entering and leaving the entire road network; Formula 19 represents the time when snow-clearing vehicles start and finish snow removal in each time period; Formula 20 represents the time when snow-clearing vehicles start and finish snow removal in each time period; p In the m When the snow-clearing task is concentrated on the key affected road sections, r ij Driving; Formula 21 represents snow clearing vehicle p In the m Whether to clear the road sections when the snow-clearing task is concentrated on the key affected road sections rij ; Formula 22 represents snow clearing vehicle p In the m The number of unattended visits to key impacted sections when snow clearing is being carried out;

[0103] Where: T It indicates the time it takes for all snow-clearing vehicles to complete snow-clearing operations on all road sections, in hours; Snow removal vehicle p Total non-working driving time, unit: hours; Snow removal vehicle p Total working driving time, unit: hours; M Indicates the number of times the key impact section set is updated; m Indicates m Update the set of key impacted road sections; A m Indicates m A collection of key impacted road sections; P Indicates the assembly of snow-clearing vehicles; p Indicates p snow-clearing vehicles; l ij Indicates road segment r ij Length, unit: kilometers; Indicated in m When the key impact segment set is updated, the segment r ij The average speed of the vehicles on the road, in kilometers per hour; v 0 means the rated operating speed of the snow-clearing vehicle, unit: km / h; Indicates m When the snow-clearing task is concentrated on the key affected road sections, the snow-clearing vehicles p Is it on the road? r ji Travel on; Indicates m When the snow-clearing task is concentrated on the key affected road sections, the snow-clearing vehicles p Is it on the road? r ij Travel on; Snow clearing vehicle p Whether to affect the key road section set A m Work on the road section in the o Virtual nodes representing all snow-clearing vehicles entering the road network; d A virtual node representing all snow-clearing vehicles exiting the road network; Snow removal vehicle p The service start time; Snow removal vehiclep exist A m The time to complete snow clearing work; Snow removal vehicle p exist A m-1 The time to complete snow clearing work; Snow removal vehicle p On the road r ij The number of air traffic visits; i Represents a node; j Indicates adjacent nodes; G Represents a road network; x ijp Snow clearing vehicle p Is it on the road? r ij Travel on; x jip Snow clearing vehicle p Is it on the road? r ji Travel on; y ijp Snow clearing vehicle p Is it for road section r ij Carry out homework; y jip Snow clearing vehicle p Is it for road section r ji Carry out homework; x ojp Snow clearing vehicle p Whether to travel from the virtual starting point o to node j; x jdp Snow clearing vehicle p Is it in the node j To the virtual destination d Drive on.

[0104] Example 1: The above method is applied to some areas of Changchun City, Jilin Province. Considering the characteristics of snow removal vehicles, the intersections are abstracted as nodes and the road sections are abstracted as edges, with a total of 13 nodes and 36 directed edges. The selected area is converted into a directed graph. G =( I， E ),in I= { i | i =1, 2, ..., 13} represents the set of nodes corresponding to the intersections or endpoints of urban roads, E= { e | e =1, 2, ..., 36} represents the set of directed segments connecting two adjacent nodes, such as Figure 2 As shown in FIG. 1 , the road sections and nodes are numbered.

[0105] The relevant parameters of the study area were collected, and the basic situation of the study area is shown in Table 1;

[0106] Table 1 Basic information of the study area

[0107] Road Section Road length (km) Traffic volume (pcu / 5min) Initial average speed (km / h) 1 0.54 211 20.7 2 0.54 263 20.7 3 0.84 148 24.4 4 0.84 217 36.6 5 0.12 183 30 6 0.12 115 10 ... ... ...

[0108] The operation routes of snow-clearing vehicles were planned based on the key affected road sections in the city: the snowfall was set at 1 hour, the snowfall was 0.3 mm, the driving speed of the snow-clearing vehicles was stipulated to be 10 km / h during snow-clearing work, and a total of 3 snow-clearing vehicles were dispatched for the operation.

[0109] First, the initial key directional segment set is calculated according to formulas 1 to 13 A 1 Among them, when calculating the strength of the road section, the degree value influence coefficient Take 0.5; when calculating the influence of interest points, 10 types of interest points are selected. The importance values ​​of various interest points are shown in Table 2, and the interest points within the 30m buffer zone of the road are regarded as effective facilities that affect the importance of the road; when calculating the importance of the road section, the road section strength U ij , edge betweenness D ij , Interest point influence P ij The weight values ​​of the three indicators are 0.297, 0.164, and 0.539 respectively. Then the initial key directional road segment set A 1 The snow-clearing vehicle operation path planning model is introduced, as shown in equations 14 to 22, and the initial snow-clearing vehicle operation path is obtained by using the heuristic algorithm. During the snowfall period, the traffic status of the road network is updated every 30 minutes, and then the key directed road segment set is updated according to equations 1 to 13. Based on the current position of the snow-clearing vehicle, the model such as equations 14 to 22 is used to solve the operation path of the snow-clearing vehicle in the next stage until the snowfall stops and the update process ends.

[0110] Table 2 Importance values ​​of points of interest

[0111] First level classification Secondary classification Weight Residential land Residential building land 0.171 Public Administration Government agencies, administrative offices 0.063 Education and scientific research land Land for colleges and universities, and land for secondary vocational schools 0.051 Primary and secondary school land 0.120 Medical and health land General Hospital 0.183 Community Health Service Center 0.049 Commercial facility land Retail commercial land, hotel land 0.039 Farmers Market Land 0.039 Hotel land 0.032 Business facilities land Comprehensive office space for finance, insurance, securities, news publishing, etc. 0.040 Land for public utility business outlets Gas station land 0.092 Land for transportation facilities Bus ground stations and terminal stations 0.121

[0112] Table 3 shows the path information of the snow-clearing vehicles to complete the snow-clearing operation of the entire road network, including: the service path of the snow-clearing vehicles, the time for each vehicle to complete the snow-clearing operation and the idle time on the path. The path plan of each snow-clearing vehicle is as follows: Figure 3 , Figure 4 and Figure 5As shown in the figure, the solid line represents the working section and the dotted line represents the non-working driving section. The service path results in Table 3 only reflect the order of the working sections, that is, the order in which the solid lines occur, not the actual driving path.

[0113] Table 3 Path planning results

[0114] Snow removal vehicle number Service route (section number) Service completion time (h) Idle time (h) 1 18-1-3-4-18-31-33-34-32-19-16-15-20-17 1.78 0.25 2 10-8-7-10-8-25-27-36-35-28-26-29 1.93 0.16 3 29-12-30-12-6-1-3-13-23-24-22-21-14-5 1.59 0.25

[0115] According to Table 3, it took 1.93 hours from the start of the first snow-clearing vehicle to the completion of the last snow-clearing vehicle. Some sections of the road experienced multiple cleanings. This was due to the continuous loading of snow on the road and the continuous updating of the traffic status of the road network, which resulted in these sections being considered as priority affected sections again. In addition, all sections in the study area were eventually cleaned, thanks to the design of the key affected section determination method, which ensured that all sections could be identified and determined as key affected sections after the snowfall ended, and thus received corresponding cleaning services. Most current path planning studies use static models for optimization design, that is, the snow-clearing route is preset before the snow-clearing begins, which ignores the dynamics and uncertainty of actual snowfall. This method integrates real-time data, such as changes in snowfall conditions and road conditions, to improve the flexibility and timeliness of snow-clearing scheduling.

[0116] The above are only preferred embodiments of the present invention. It should be pointed out that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention. These should also be regarded as the protection scope of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A snow-clearing vehicle operation path planning method based on key impact road section identification, characterized in that: The following steps are involved: Step S1, Identification of road sections that are affected by snowfall: Identify road sections that are affected by snowfall based on the road network structure, function and adjacent facility features. Specifically, calculate the road section strength. U ij , edge betweenness D ij , Interest point influence P ij The impact of snow accumulation on the total travel time of vehicles on the road section B ij To identify the key impact sections in the city and form a key impact section set; Step S2, planning the snow-clearing vehicle operation path according to the dynamic update of the key impacted road sections in the city: establishing a snow-clearing vehicle operation path planning model, inputting the initial key impacted road section set into the snow-clearing vehicle operation path planning model, and generating the initial operation path of the snow-clearing vehicle; During the snow removal process, the key impact road section set is dynamically updated according to the snowfall information and the traffic status of each road section, and is brought into the snow removal vehicle operation path planning model to obtain the path planning scheme of the snow removal vehicle in the snow removal operation area; the input of the snow removal vehicle operation path planning model is the key impact road section set, and the output is the driving path of the snow removal vehicle during the entire snow removal process and the timing arrangement of the working road section; By U ij , edge betweenness D ij , Interest point influence P ij The importance of the road section is obtained after deviation standardization I ij : Formula 12: ; Where: Indicates the importance of the road segment; Indicates that the data is subjected to deviation standardization; Respectively D ij、 U ij and P ij The weight of B ij represents the impact of snow accumulation on the total travel time of vehicles on the road section; h represents the road section r ij Depth of snow on Importance to road section I ij To normalize the deviation: Formula 13: ; When the result is When the result is When the snow depth is 0, it is determined as a minor road section; when the snow depth is 0, it is determined as a non-key affected road section; Update the traffic status of each road section according to the snowfall information and calculate the importance of each road section I ij Then, according to formula 13, we determine whether the road section is a key impact road section, and get the key impact road section set A m ={ E m } ,in A m represents the set of key affected road sections obtained when the traffic status of the road section is updated for the mth time, E m Represents a set of directed road segments; Calculate the strength of the road segment U ij The formula is as follows: Formula 1: ; Formula 2: ; Formula 3: ; Formula 4: ; Formula 5: ; Formula 6: ; Formula 7: ; Formula 8: ; Where: C i Representation Node i The overall strength of S i Indicates the target node i strength; represents the influence coefficient; Representation Node i The set of neighbor nodes; Q j Indicates the target node j The strength of adjacent nodes; Q i Indicates the target node i The strength of adjacent nodes; λ Indicates the degree value influence coefficient; Indicates the target node i The penetration strength value; Indicates the target node i Output strength value; θ ji Indicates a directed segment r ji Weight; θ ij Indicates a directed segment r ij The weight of q ij Indicates road segment r ij Number of vehicles on the G Represents a set of directed road segments in a road network. Any arc ( i , j ) indicates the direction is from the node i To adjacent nodes j directional segments; j Represents the neighbor node of target node i; Calculate the edge betweenness D ij The formula is as follows: Formula 9: ; Where: n G Representing road network G The total number of shortest paths between any nodes in ; n ij Indicates the road segment passed in the shortest path r ij The number of paths; Calculate the influence of the interest point P ij The formula is as follows: Formula 10: ; Where: P ij Indicates the influence of the point of interest; n The number of categories representing points of interest; Indicates road segment r ij The number of interest points of category ω within the buffer; IP ω Represents the importance value of the interest point of category ω; Calculate the impact of the snow accumulation on the total travel time of vehicles on the road section B ij The formula is as follows: Formula 11: ; Where: l ij Indicates road segment r ij length; Indicates road segment r ij When the snow depth on the road is h, r ij The average speed of vehicles on the road; v ij Indicates road segment r ij When the snow depth is 0, the road section r ij The average speed of vehicles on the road.

2. The snow-clearing vehicle operation path planning method based on key impact road section identification according to claim 1 is characterized in that: The snow removal vehicle operation path planning model is shown in equation 14-22; Formula 14: ; Formula 15: ; Formula 16: ; Formula 17: ; Formula 18: ; Formula 19: ; Formula 20: ; Formula 21: ; Formula 22: ; Formula 14 is the objective function, which means that the snow removal vehicle takes the shortest time to clear all the key affected sections; Formula 15 indicates that the snow removal vehicle can only perform snow removal operations on the road sections along its driving path; Formula 16 indicates that the vehicle p Path continuity; Equation 17 represents the flow balance constraint of snow-clearing vehicles at each node; Equation 18 represents the flow balance constraint of snow-clearing vehicles entering and exiting the entire road network; Equation 19 represents the time when snow-clearing vehicles start and finish snow removal in each time period; Formula 20 represents a snow clearing vehicle p In the m When the snow-clearing task is concentrated on the key affected road sections, r ij Driving; Formula 21 represents a snow clearing vehicle p In the m Whether to clear the road sections when the snow-clearing task is concentrated on the key affected road sections r ij ; Formula 22 represents snow clearing vehicle p In the m The number of unattended visits to key impacted sections when snow clearing is being carried out; Where: T Indicates the time it takes for all snow-clearing vehicles to complete snow-clearing operations on all road sections; Snow removal vehicle p Total non-working driving time; Snow removal vehicle p Total working driving time; M Indicates the number of times the key impact section set is updated; m Indicates m Update the set of key impacted road sections; A m Indicates m A collection of key impacted road sections; P Indicates the assembly of snow-clearing vehicles; p Indicates p snow-clearing vehicles; l ij Indicates road segment r ij length; Indicated in m When the key affected segment set is updated, the segment r ij The average speed of vehicles on the road; v 0 means the rated operating speed of the snow-clearing vehicle; Indicates m When the snow-clearing task is concentrated on the key affected road sections, the snow-clearing vehicles p Is it on the road? r ji Travel on; Indicates m When the snow-clearing task is concentrated on the key affected road sections, the snow-clearing vehicles p Is it on the road? r ij Travel on; Snow clearing vehicle p Whether to affect the key road section set A m Work on the road sections; o Virtual nodes representing all snow-clearing vehicles entering the road network; d A virtual node representing all snow-clearing vehicles exiting the road network; Snow removal vehicle p The service start time; Snow removal vehicle p exist A m The time to complete snow clearing work; Snow removal vehicle p exist A m-1 The time to complete snow clearing work; Snow removal vehicle p On the road r ij The number of visits made by the air traffic controller; i Represents a node; j Indicates adjacent nodes; G Represents a road network; x ijp Snow clearing vehicle p Is it on the road? r ij Travel on; x jip Snow clearing vehicle p Is it on the road? r ji Travel on; y ijp Snow clearing vehicle p Is it for road section r ij Carry out homework; y jip Snow clearing vehicle p Is it for road section r ji Carry out homework; x ojp Snow clearing vehicle p Whether to travel from the virtual starting point o to node j; x jdp Snow clearing vehicle p Is it in the node j To the virtual destination d Drive on.

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