Method and system for automatically generating conveying map route of muck truck

Abstract

The invention discloses an automatic generation method and system for a transport map route of a slag car, and belongs to the technical field of route planning. The system comprises a data acquisition module, a route planning module, a scheduling management module and a visualization module. The data acquisition module is used for acquiring a historical log, a transportation route map and a transportation application submitted by a construction unit, and acquiring the real-time road condition of each road section in the transportation route map in real time through a sensor; the route planning module obtains motorcade information and historical logs so as to calculate a predicted speed, marks road sections in a transportation route map according to a transportation application, calculates a congestion coefficient, and plans a to-be-selected route through the congestion coefficient; the scheduling management module is used for calculating the congestion index of each route to be selected and selecting a planned route, and a motorcade carries out transportation according to the planned route, analyzes the road conditions of other road sections in real time and dynamically adjusts the planned route; and the visualization module displays the transportation information of the motorcade in real time through a large visualization screen, generates a driving record after the transportation is completed, and uploads the driving record to a historical log.

Description

Technical Field

[0001] The present invention relates to the technical field of route planning, and in particular to a method and system for automatically generating a transportation map route for a muck truck. Background Art

[0002] With the development of new technologies, such as geographic information system GIS, global positioning system GPS, big data analysis and other technical tools, the research on route planning of muck truck transportation can be more accurate and scientific, providing data support for transportation management.

[0003] At present, for the route planning of the muck truck transportation map, the designated route is usually used for planning, which has certain problems. On the one hand, there are usually several intersecting forks between the designated routes or they are connected by multiple other routes. The connecting sections between these designated routes may have different road conditions, and the existing technology cannot quickly select the best intersection point between the designated routes to achieve the overall optimal route planning. On the other hand, due to the particularity of the transportation task, the muck truck fleet often works in groups and travels at a relatively slow speed, which often puts a certain pressure on the traffic capacity of conventional roads. The existing technology cannot solve the problem of minimizing the impact on the traffic capacity of the planned route while ensuring the maximization of the transportation efficiency. Therefore, at this stage, a technical solution for the automatic generation of muck truck transportation map routes is needed to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for automatically generating a transportation map route of a muck truck, so as to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides a method for automatically generating a route for a muck truck transportation map, comprising the following steps:

[0006] S100, collecting historical logs, transportation route maps and transportation applications submitted by construction units, and collecting real-time road conditions of each section in the transportation route map through sensors.

[0007] S200, obtaining fleet information and historical logs and calculating the expected speed, marking the sections in the delivery route map according to the delivery application and calculating the congestion coefficient, and planning the proposed route according to the congestion coefficient.

[0008] S300, calculating the congestion index of each proposed route and selecting a planned route, the fleet transports according to the planned route, analyzing the road conditions of other sections in real time and dynamically adjusting the planned route.

[0009] S400, displays the fleet's delivery information in real time through a large visual screen, generates driving records after delivery and uploads them to the historical log.

[0010] In S100, the historical log refers to the driving record of the vehicle, and each driving record includes the license plate number, load weight and average driving speed. The transportation route map refers to an electronic map used to display the driving route of the vehicle during transportation, including several road sections and the intersections between the sections. The construction unit refers to the construction party of the construction site. The transportation application includes the departure place, destination, and fleet information. The fleet information includes the load weight and license plate number of all vehicles. Road conditions refer to the parameter information and traffic flow information of each road section in the transportation route map. The parameter information includes the flatness index, road width and road length. The traffic flow information includes the average entry speed and the average exit speed, as well as the speed of each vehicle traveling on the road section, which is collected in real time by speedometers installed on both sides of the road.

[0011] The vehicle refers to the dump truck used to transport construction materials such as sand and gravel on the construction site. When the dump truck is driving on the road, it often has a great impact on the road's traffic speed due to the fact that the vehicles are traveling in a convoy, the large body of the vehicle, and the sand and gravel it carries.

[0012] The average entry speed and average exit speed are collected by speedometers installed at both ends of the road section. The average entry speed or average exit speed is obtained by collecting the speed of each vehicle entering or leaving the road section and calculating the average value. The speed data of each vehicle on the road section comes from the speed collected for the first time when entering the road section.

[0013] In S200, the specific steps are as follows:

[0014] S201. Mark all license plate numbers in the fleet information in the transport application and count the number j. Retrieve the driving records corresponding to the marked license plates in the historical logs. Group these driving records by license plate number and establish a training set for each group. Analyze the number of driving records U contained in each group. Use the load weight in the driving record as the independent variable and the average driving speed as the dependent variable. Package the independent variables and dependent variables under each driving record into samples, and put these U samples into the training set corresponding to the group to which they belong. Establish a linear regression model, substitute each training set into the training set to obtain j expressions; substitute the load weight of each vehicle in the fleet information into the corresponding expression to calculate the expected speed pv i .

[0015] The specific training process of the linear regression model is: take the independent variable in each sample as the input value, calculate the difference between the output result and the dependent variable of the corresponding sample, set the error threshold, and when the difference is less than the error threshold, mark the corresponding sample and calculate the next sample. In other cases, adjust the parameters of the regression coefficient and recalculate until all samples in the training set are marked. Among them, the expression of the linear regression model Q is:

[0016] Q=w0+w e r e

[0017] In the formula, w e is the e-th regression coefficient, r e is the e-th independent variable.

[0018] S202: Analyze the departure and destination in the transportation application, search for all routes between the departure and destination in the transportation route map, and mark all road sections included in these routes. Obtain the flatness index IRI, road width LK, road length LC, and average entry speed VR of each marked road section. ave and the average exit speed VC ave , as well as the number of vehicles m traveling on the road section and the speed sv of each vehicle n , and substitute it into the formula to calculate the congestion coefficient of each marked road section:

[0019]

[0020] Where YX is the congestion coefficient and α is a constant.

[0021] The congestion coefficient indicates the degree of congestion on the road section. The greater the difference between the average entry speed and the average exit speed, the greater the flatness index, the more vehicles are traveling on the road section and the lower the speed, the greater the congestion coefficient.

[0022] The International Roughness Index (IRI) is an index used to evaluate the roughness of a road surface. It is obtained by measuring the longitudinal roughness of the road surface within a certain length, usually expressed in meters / kilometers or millimeters / meters. IRI is widely used in highway engineering, maintenance and management in countries around the world. IRI provides a quantitative roughness value that can directly reflect the condition of the road surface. The smaller the value, the smoother the road surface; the larger the value, the more uneven the road surface.

[0023] S203, obtain the congestion coefficient of each marked road section and set the coefficient threshold YX pre , filter out the congestion coefficient less than or equal to YX pre The marked sections are used as the proposed sections. The starting point and the end point are marked on the transportation route map according to the departure place and the destination in the transportation application, and the route consisting of all the proposed sections between the starting point and the end point is retrieved and planned as the proposed route.

[0024] In S300, the specific steps are as follows:

[0025] S301, counting the number g of the proposed road sections contained in each proposed route, as well as the road length and congestion coefficient of each proposed road section, and bringing them into the formula to calculate the congestion index of each proposed route respectively, the formula is as follows:

[0026]

[0027] Where YZ is the congestion index, LC k is the length of the kth proposed road section, YX k is the congestion coefficient of the kth proposed road section.

[0028] The route consists of multiple sections. Each section has only one entrance and one exit and is one-way. Vehicles can only enter through the entrance and exit through the exit. The route is the same as the section.

[0029] S302: Select the proposed route with the lowest congestion index as the planned route, add the planned route to the transportation application and send it back to the construction unit, and the transportation team of the construction unit will drive according to the planned route. During the driving process, the current position of the team is used as the starting point, and the congestion coefficient and congestion index are calculated based on the real-time traffic analysis of other sections, and the planned route is dynamically adjusted.

[0030] In S400, the position of the fleet in the delivery route map and the current planned route are displayed in real time through a large visual screen. After the delivery is completed, the average driving speed of each vehicle is calculated, and the driving record is generated together with the load weight and license plate number and uploaded to the historical log.

[0031] A system for automatically generating a route map for a muck truck transportation includes a data collection module, a route planning module, a scheduling management module and a visualization module.

[0032] The data acquisition module is used to collect historical logs, transportation route maps and transportation applications submitted by construction units, and collects real-time traffic conditions of each section of the transportation route map through sensors. The route planning module obtains fleet information and historical logs to calculate the expected speed, marks the sections in the transportation route map according to the transportation application and calculates the congestion coefficient, and plans the proposed route based on the congestion coefficient. The scheduling management module is used to calculate the congestion index of each proposed route and select the planned route. The fleet transports according to the planned route, analyzes the road conditions of other sections in real time, and dynamically adjusts the planned route. The visualization module displays the fleet's transportation information in real time through a large visualization screen. After the delivery is completed, a driving record is generated and uploaded to the historical log.

[0033] The data collection module includes a history log collection unit, a transportation information collection unit and a road condition information collection unit.

[0034] The historical log collection unit is used to collect the driving records of the vehicle, each driving record includes the license plate number, loading weight and average driving speed.

[0035] The transport information collection unit is used to collect the departure, destination and fleet information. The fleet information includes the loading weight and license plate number of all vehicles.

[0036] The road condition information collection unit is used to collect parameter information and traffic flow information of each road section in the transportation route map. The transportation route map refers to an electronic map used to display the route of the vehicle during transportation. The parameter information includes the flatness index, road width and road length. The traffic flow information includes the average entry speed and average exit speed, as well as the speed of each vehicle traveling on the road section.

[0037] The route planning module includes a transportation analysis unit and a congestion analysis unit.

[0038] The transport analysis unit is used to calculate the estimated speed.

[0039] First, mark all the license plate numbers in the fleet information and count the number j. Retrieve the driving records corresponding to the marked license plates in the historical logs, group these driving records according to the license plate numbers and create a training set for each group. Secondly, analyze the number of driving records U contained in each group, use the loading weight in the driving record as the independent variable and the average driving speed as the dependent variable, package the independent variables and dependent variables under each driving record into samples, and put these U samples into the training set corresponding to the group to which they belong. Finally, establish a linear regression model, substitute each training set into the training set to obtain j expressions; substitute the loading weight of each vehicle in the fleet information into the corresponding expression to calculate the expected speed pv i .

[0040] The congestion analysis unit is used to calculate the congestion coefficient.

[0041] First, retrieve all routes between the departure point and the destination in the transport route map and mark all the road sections included in these routes. Obtain the flatness index IRI, road width LK, road length LC, and average entry speed VR of each marked road section. ave and the average exit speed VC ave , as well as the number of vehicles m traveling on the road section and the speed sv of each vehicle n .

[0042] Secondly, through the formula Calculate the congestion coefficient of each marked road section separately. Get the congestion coefficient of each marked road section and set the coefficient threshold YX pre , filter out the congestion coefficient less than or equal to YX pre The marked road section is taken as the proposed road section; where α is a constant.

[0043] Finally, the starting point and the end point are marked on the transportation route map according to the departure place and the destination in the transportation application, and the route between the starting point and the end point consisting entirely of the proposed road sections is retrieved and planned as the proposed route.

[0044] The scheduling management module includes a route selection unit and a dynamic debugging unit.

[0045] The route selection unit is used to select the planned route. First, count the number of proposed sections g contained in each proposed route, as well as the length and congestion coefficient of each proposed section. Then substitute into the formula In , the congestion index of each proposed route is calculated respectively, and the proposed route with the lowest congestion index is selected as the planned route. k is the length of the kth proposed road section, YX k is the congestion coefficient of the kth proposed road section.

[0046] The dynamic debugging unit is used to add the planned route to the transportation application and transmit it back to the construction unit. The construction unit's transportation fleet drives according to the planned route. During the driving process, the current location of the fleet is used as the starting point, and the congestion coefficient and congestion index are calculated based on the real-time traffic analysis of other sections, and the planned route is dynamically adjusted.

[0047] The visualization module uses a large visualization screen to display the fleet's position in the delivery route map and the current planned route in real time. After the delivery is completed, a driving record is generated for each vehicle and uploaded to the historical log.

[0048] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0049] This application calculates the expected speed by analyzing the historical driving records of each vehicle, and calculates the congestion coefficient based on the real-time traffic conditions of each road section. The proposed sections are selected based on the congestion coefficients of different sections, which is more intelligent than the shortest path selection method in the prior art. The congestion index is obtained by calculating the length of the proposed section in each proposed route and the congestion coefficient to determine the planned route, which is more efficient than the prior art.

[0050] In summary, compared with traditional technologies, the present invention has the advantages of intelligent road section screening and efficient route selection, and can improve transportation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0052] Figure 1 It is a flow chart of a method for automatically generating a transportation map route of a muck truck according to the present invention;

[0053] Figure 2 The present invention is a structural schematic diagram of a system for automatically generating a transportation map route of a muck truck. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] See also Figure 1 The present invention provides a method for automatically generating a route for a muck truck transportation map, comprising the following steps:

[0056] S100, collecting historical logs, transportation route maps and transportation applications submitted by construction units, and collecting real-time road conditions of each section in the transportation route map through sensors.

[0057] S200, obtaining fleet information and historical logs and calculating the expected speed, marking the sections in the delivery route map according to the delivery application and calculating the congestion coefficient, and planning the proposed route according to the congestion coefficient.

[0058] S300, calculating the congestion index of each proposed route and selecting a planned route, the fleet transports according to the planned route, analyzing the road conditions of other sections in real time and dynamically adjusting the planned route.

[0059] S400, displays the fleet's delivery information in real time through a large visual screen, generates driving records after delivery and uploads them to the historical log.

[0060] In S100, the historical log refers to the driving record of the vehicle, and each driving record includes the license plate number, load weight and average driving speed. The transportation route map refers to an electronic map used to display the driving route of the vehicle during transportation, including several road sections and the intersections between the sections. The construction unit refers to the construction party of the construction site. The transportation application includes the departure place, destination, and fleet information. The fleet information includes the load weight and license plate number of all vehicles. Road conditions refer to the parameter information and traffic flow information of each road section in the transportation route map. The parameter information includes the flatness index, road width and road length. The traffic flow information includes the average entry speed and the average exit speed, as well as the speed of each vehicle traveling on the road section, which is collected in real time by speedometers installed on both sides of the road.

[0061] The vehicle refers to the dump truck used to transport construction materials such as sand and gravel on the construction site. When the dump truck is driving on the road, it often has a great impact on the road's traffic speed due to the fact that the vehicles are traveling in a convoy, the large body of the vehicle, and the sand and gravel it carries.

[0062] The average entry speed and average exit speed are collected by speedometers installed at both ends of the road section. The average entry speed or average exit speed is obtained by collecting the speed of each vehicle entering or leaving the road section and calculating the average value. The speed data of each vehicle on the road section comes from the speed collected for the first time when entering the road section.

[0063] In S200, the specific steps are as follows:

[0064] S201. Mark all license plate numbers in the fleet information in the transport application and count the number j. Retrieve the driving records corresponding to the marked license plates in the historical logs. Group these driving records by license plate number and establish a training set for each group. Analyze the number of driving records U contained in each group. Use the load weight in the driving record as the independent variable and the average driving speed as the dependent variable. Package the independent variables and dependent variables under each driving record into samples, and put these U samples into the training set corresponding to the group to which they belong. Establish a linear regression model, substitute each training set into the training set to obtain j expressions; substitute the load weight of each vehicle in the fleet information into the corresponding expression to calculate the expected speed pv i .

[0065] The specific training process of the linear regression model is: take the independent variable in each sample as the input value, calculate the difference between the output result and the dependent variable of the corresponding sample, set the error threshold, and when the difference is less than the error threshold, mark the corresponding sample and calculate the next sample. In other cases, adjust the parameters of the regression coefficient and recalculate until all samples in the training set are marked. Among them, the expression of the linear regression model Q is:

[0066] Q=w0+w e r e

[0067] In the formula, w e is the e-th regression coefficient, r e is the e-th independent variable.

[0068] S202: Analyze the departure and destination in the transportation application, search for all routes between the departure and destination in the transportation route map, and mark all road sections included in these routes. Obtain the flatness index IRI, road width LK, road length LC, and average entry speed VR of each marked road section. ave and the average exit speed VC ave , as well as the number of vehicles m traveling on the road section and the speed sv of each vehicle n , and substitute it into the formula to calculate the congestion coefficient of each marked road section:

[0069]

[0070] Where YX is the congestion coefficient and α is a constant.

[0071] The congestion coefficient indicates the degree of congestion on the road section. The greater the difference between the average entry speed and the average exit speed, the greater the flatness index, the more vehicles are traveling on the road section and the lower the speed, the greater the congestion coefficient.

[0072] The International Roughness Index (IRI) is an index used to evaluate the roughness of a road surface. It is obtained by measuring the longitudinal roughness of the road surface within a certain length, usually expressed in meters / kilometers or millimeters / meters. IRI is widely used in highway engineering, maintenance and management in countries around the world. IRI provides a quantitative roughness value that can directly reflect the condition of the road surface. The smaller the value, the smoother the road surface; the larger the value, the more uneven the road surface.

[0073] S203, obtain the congestion coefficient of each marked road section and set the coefficient threshold YX pre , filter out the congestion coefficient less than or equal to YX pre The marked sections are used as the proposed sections. The starting point and the end point are marked on the transportation route map according to the departure place and the destination in the transportation application, and the route consisting of all the proposed sections between the starting point and the end point is retrieved and planned as the proposed route.

[0074] In S300, the specific steps are as follows:

[0075] S301, counting the number g of the proposed road sections contained in each proposed route, as well as the road length and congestion coefficient of each proposed road section, and bringing them into the formula to calculate the congestion index of each proposed route respectively, the formula is as follows:

[0076]

[0077] Where YZ is the congestion index, LC k is the length of the kth proposed road section, YX k is the congestion coefficient of the kth proposed road section.

[0078] The route consists of multiple sections. Each section has only one entrance and one exit and is one-way. Vehicles can only enter through the entrance and exit through the exit. The route is the same as the section.

[0079] S302: Select the proposed route with the lowest congestion index as the planned route, add the planned route to the transportation application and send it back to the construction unit, and the transportation team of the construction unit will drive according to the planned route. During the driving process, the current position of the team is used as the starting point, and the congestion coefficient and congestion index are calculated based on the real-time traffic analysis of other sections, and the planned route is dynamically adjusted.

[0080] In S400, the position of the fleet in the delivery route map and the current planned route are displayed in real time through a large visual screen. After the delivery is completed, the average driving speed of each vehicle is calculated, and the driving record is generated together with the load weight and license plate number and uploaded to the historical log.

[0081] See also Figure 2 The present invention provides a system for automatically generating a transportation map route of a muck truck, including a data acquisition module, a route planning module, a scheduling management module and a visualization module.

[0082] The data acquisition module is used to collect historical logs, transportation route maps and transportation applications submitted by construction units, and collects real-time traffic conditions of each section of the transportation route map through sensors. The route planning module obtains fleet information and historical logs to calculate the expected speed, marks the sections in the transportation route map according to the transportation application and calculates the congestion coefficient, and plans the proposed route based on the congestion coefficient. The scheduling management module is used to calculate the congestion index of each proposed route and select the planned route. The fleet transports according to the planned route, analyzes the road conditions of other sections in real time, and dynamically adjusts the planned route. The visualization module displays the fleet's transportation information in real time through a large visualization screen. After the delivery is completed, a driving record is generated and uploaded to the historical log.

[0083] The data collection module includes a history log collection unit, a transportation information collection unit and a road condition information collection unit.

[0084] The historical log collection unit is used to collect the driving records of the vehicle, each driving record includes the license plate number, loading weight and average driving speed.

[0085] The transport information collection unit is used to collect the departure, destination and fleet information. The fleet information includes the loading weight and license plate number of all vehicles.

[0086] The road condition information collection unit is used to collect parameter information and traffic flow information of each road section in the transportation route map. The transportation route map refers to an electronic map used to display the route of the vehicle during transportation. The parameter information includes the flatness index, road width and road length. The traffic flow information includes the average entry speed and average exit speed, as well as the speed of each vehicle traveling on the road section.

[0087] The route planning module includes a transportation analysis unit and a congestion analysis unit.

[0088] The transport analysis unit is used to calculate the estimated speed.

[0089] First, mark all the license plate numbers in the fleet information and count the number j. Retrieve the driving records corresponding to the marked license plates in the historical logs, group these driving records according to the license plate numbers and create a training set for each group. Secondly, analyze the number of driving records U contained in each group, use the loading weight in the driving record as the independent variable and the average driving speed as the dependent variable, package the independent variables and dependent variables under each driving record into samples, and put these U samples into the training set corresponding to the group to which they belong. Finally, establish a linear regression model, substitute each training set into the training set to obtain j expressions; substitute the loading weight of each vehicle in the fleet information into the corresponding expression to calculate the expected speed pv i .

[0090] The congestion analysis unit is used to calculate the congestion coefficient.

[0091] First, retrieve all routes between the departure point and the destination in the transport route map and mark all the road sections included in these routes. Obtain the flatness index IRI, road width LK, road length LC, and average entry speed VR of each marked road section. ave and the average exit speed VC ave , as well as the number of vehicles m traveling on the road section and the speed sv of each vehicle n .

[0092] Secondly, through the formula Calculate the congestion coefficient of each marked road section separately. Get the congestion coefficient of each marked road section and set the coefficient threshold YX pre , filter out the congestion coefficient less than or equal to YX pre The marked road section is taken as the proposed road section; where α is a constant.

[0093] Finally, the starting point and the end point are marked on the transportation route map according to the departure place and the destination in the transportation application, and the route between the starting point and the end point consisting entirely of the proposed road sections is retrieved and planned as the proposed route.

[0094] The scheduling management module includes a route selection unit and a dynamic debugging unit.

[0095] The route selection unit is used to select the planned route. First, count the number of proposed sections g contained in each proposed route, as well as the length and congestion coefficient of each proposed section. Then substitute the formula ∑ g k＝1 LC k ×YX k In , the congestion index of each proposed route is calculated respectively, and the proposed route with the lowest congestion index is selected as the planned route. k is the length of the kth proposed road section, YX k is the congestion coefficient of the kth proposed road section.

[0096] The dynamic debugging unit is used to add the planned route to the transportation application and transmit it back to the construction unit. The construction unit's transportation fleet drives according to the planned route. During the driving process, the current location of the fleet is used as the starting point, and the congestion coefficient and congestion index are calculated based on the real-time traffic analysis of other sections, and the planned route is dynamically adjusted.

[0097] The visualization module uses a large visualization screen to display the fleet's position in the delivery route map and the current planned route in real time. After the delivery is completed, a driving record is generated for each vehicle and uploaded to the historical log.

[0098] Embodiment 1:

[0099] Assume that the proposed route includes three proposed sections, A1, A2 and A3, and their road lengths and congestion coefficients are:

[0100] A1: Road length 60m; congestion coefficient 1.2;

[0101] A2: Road length 100m; congestion coefficient 1.5;

[0102] A3: Road length 80m; congestion coefficient 0.8;

[0103] Substitute the formula to calculate the congestion index of the proposed route: 60×1.2+100×1.5+80×0.8=286.

[0104] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0105] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for automatically generating a route map for a muck truck, characterized in that: The method comprises the following steps: S100, collecting historical logs, transportation route maps and transportation applications submitted by construction units, and collecting real-time road conditions of each section in the transportation route map through sensors; S200, obtaining fleet information and historical logs and calculating the expected speed, marking the road sections in the delivery route map according to the delivery application and calculating the congestion coefficient, and planning the proposed route according to the congestion coefficient; S300, calculating the congestion index of each proposed route and selecting a planned route, the fleet transports according to the planned route, analyzing the road conditions of other sections in real time and dynamically adjusting the planned route; S400, displays the fleet's delivery information in real time through a large visual screen, generates driving records after delivery and uploads them to the historical log.

2. The method for automatically generating a route map for a muck truck transportation according to claim 1, characterized in that: In S100, the historical log refers to the driving record of the vehicle, each driving record includes the license plate number, load weight and average driving speed; the transportation route map refers to the electronic map used to display the driving route of the vehicle during transportation, including several road sections and the intersections between the road sections; the construction unit refers to the construction party of the construction site, and the transportation application includes the departure place, destination, and fleet information. The fleet information includes the load weight and license plate number of all vehicles; the road condition refers to the parameter information and traffic flow information of each road section in the transportation route map; the parameter information includes the flatness index, road width and road length; the traffic flow information includes the average entry speed and the average exit speed, as well as the speed of each vehicle traveling on the road section, which is collected in real time by speed meters installed on both sides of the road.

3. The method for automatically generating a route map for a muck truck transportation according to claim 2, characterized in that: In S200, the specific steps are as follows: S201. Mark all the license plate numbers in the fleet information in the transport application and count the number j. Retrieve the driving records corresponding to the marked license plates in the historical logs. Group these driving records according to the license plate numbers and establish a training set for each group. Analyze the number of driving records U contained in each group. Take the load weight in the driving record as the independent variable and the average driving speed as the dependent variable. Pack the independent variables and dependent variables under each driving record into samples, and put these U samples into the training set corresponding to the group to which they belong. Establish a linear regression model, substitute each training set into the training set to obtain j expressions. Substitute the load weight of each vehicle in the fleet information into the corresponding expression to calculate the expected speed pv i ; S202, analyzing the departure and destination in the transportation application, searching for all routes between the departure and destination in the transportation route map, marking all road sections included in these routes; obtaining the flatness index IRI, road width LK, road length LC, and average entry speed VR of each marked road section ave and the average exit speed VC ave , as well as the number of vehicles m traveling on the road section and the speed sv of each vehicle n , and substitute it into the formula to calculate the congestion coefficient of each marked road section: In the formula, YX is the congestion coefficient, and α is a constant; S203, obtain the congestion coefficient of each marked road section and set the coefficient threshold YX pre , filter out the congestion coefficient less than or equal to YX pre The marked road section is used as the proposed road section; The starting point and the end point are marked on the transportation route map according to the departure place and the destination in the transportation application, and the route between the starting point and the end point consisting entirely of the proposed road sections is retrieved and planned as the proposed route.

4. The method for automatically generating a route map for a muck truck transportation according to claim 3, characterized in that: In S300, the specific steps are as follows: S301, counting the number g of the proposed road sections contained in each proposed route, as well as the road length and congestion coefficient of each proposed road section, and bringing them into the formula to calculate the congestion index of each proposed route respectively, the formula is as follows: Where YZ is the congestion index, LC k is the length of the kth proposed road section, YX k is the congestion coefficient of the kth proposed road section; S302, selecting the proposed route with the lowest congestion index as the planned route, adding the planned route to the transportation application and transmitting it back to the construction unit, and the transportation fleet of the construction unit travels according to the planned route; During driving, taking the current position of the fleet as the starting point, the congestion coefficient and congestion index are calculated based on the real-time traffic conditions of other sections and the planned route is adjusted dynamically.

5. The method for automatically generating a route map for a muck truck transportation according to claim 4, characterized in that: In S400, the position of the fleet in the delivery route map and the current planned route are displayed in real time through a large visual screen. After the delivery is completed, the average driving speed of each vehicle is calculated, and the driving record is generated together with the load weight and license plate number and uploaded to the historical log.

6. A system for automatically generating a route map for a muck truck, characterized in that: The system includes a data acquisition module, a route planning module, a scheduling management module and a visualization module; The data collection module is used to collect historical logs, transportation route maps and transportation applications submitted by construction units, and collect the real-time road conditions of each section in the transportation route map through sensors; the route planning module obtains fleet information and historical logs to calculate the expected speed, marks the sections in the transportation route map according to the transportation application and calculates the congestion coefficient, and plans the proposed route based on the congestion coefficient; The scheduling management module is used to calculate the congestion index of each proposed route and select the planned route. The fleet transports according to the planned route, analyzes the road conditions of other sections in real time and dynamically adjusts the planned route; the visualization module displays the fleet's transportation information in real time through a large visualization screen, generates a driving record after the delivery is completed, and uploads it to the historical log.

7. The system for automatically generating a route map for a muck truck according to claim 6, characterized in that: The data collection module includes a history log collection unit, a transportation information collection unit and a road condition information collection unit; The historical log collection unit is used to collect the driving records of the vehicle, each driving record includes the license plate number, loading weight and average driving speed; The transport information collection unit is used to collect the departure, destination, and fleet information. The fleet information includes the loading weight and license plate numbers of all vehicles; The road condition information collection unit is used to collect parameter information and traffic flow information of each road section in the transportation route map; the transportation route map refers to an electronic map used to display the route of the vehicle during transportation; the parameter information includes the flatness index, road width and road length; the traffic flow information includes the average entry speed and the average exit speed, as well as the speed of each vehicle traveling on the road section.

8. The system for automatically generating a route map for a muck truck according to claim 7, characterized in that: The route planning module includes a transportation analysis unit and a congestion analysis unit; The transport analysis unit is used to calculate the estimated speed; First, mark all the license plate numbers in the fleet information and count the number j. Then retrieve the driving records corresponding to the marked license plates in the historical logs, group these driving records according to the license plate numbers and create a training set for each group. Secondly, the number of driving records in each group is analyzed, and the loading weight in the driving record is used as the independent variable and the average driving speed is used as the dependent variable. The independent variables and dependent variables under each driving record are packaged as samples, and these U samples are put into the training set corresponding to the group to which they belong; finally, a linear regression model is established, and j expressions are obtained after substituting each training set into the training set; the loading weight of each vehicle in the fleet information is substituted into the corresponding expression to calculate the expected speed pv i ; The congestion analysis unit is used to calculate the congestion coefficient; First, retrieve all routes between the departure point and the destination in the transportation route map, mark all the road sections included in these routes; obtain the flatness index IRI, road width LK, road length LC, and average entry speed VR of each marked road section ave and the average exit speed VC ave , as well as the number of vehicles m traveling on the road section and the speed sv of each vehicle n ; Secondly, through the formula Calculate the congestion coefficient of each marked road section separately; obtain the congestion coefficient of each marked road section and set the coefficient threshold YX pre , filter out the congestion coefficient less than or equal to YX pre The marked road section is taken as the proposed road section; where α is a constant; Finally, the starting point and the end point are marked on the transportation route map according to the departure place and the destination in the transportation application, and the route between the starting point and the end point consisting entirely of the proposed road sections is retrieved and planned as the proposed route.

9. The system for automatically generating a route map for a muck truck according to claim 8, characterized in that: The dispatch management module includes a route selection unit and a dynamic debugging unit; The route selection unit is used to select the planned route. First, the number of proposed sections g contained in each proposed route, as well as the length and congestion coefficient of each proposed section are counted. Then, the formula is used to In the above example, the congestion index of each proposed route is calculated respectively, and the proposed route with the lowest congestion index is selected as the planned route; among them, LC k is the length of the kth proposed road section, YX k is the congestion coefficient of the kth proposed road section; The dynamic debugging unit is used to add the planned route to the transportation application and transmit it back to the construction unit. The transportation fleet of the construction unit travels according to the planned route; During driving, taking the current position of the fleet as the starting point, the congestion coefficient and congestion index are calculated based on the real-time traffic conditions of other sections and the planned route is adjusted dynamically.

10. The system for automatically generating a route map for a muck truck according to claim 9, characterized in that: The visualization module uses a large visualization screen to display the fleet's position in the delivery route map and the current planned route in real time. After the delivery is completed, a driving record is generated for each vehicle and uploaded to the historical log.

Images