Vehicle transportation management system based on vehicle-mounted dynamic weighing

Abstract

The invention discloses a vehicle transportation management system based on vehicle-mounted dynamic weighing, and relates to the technical field of vehicle transportation management.An information collection module is arranged to collect task execution data of a vehicle, and a transportation analysis module is used for analyzing the task execution data according to a pre-driving path in the task execution data; dividing each pre-driving path into a plurality of path combinations, and determining a plurality of trend combinations and road trend indexes in the pre-driving paths according to changes of real-time cargo weight, driving speed and instantaneous fuel consumption of the vehicle in each path combination, the transportation management platform splits each generated driving path into a plurality of path combinations on the basis of a path planning algorithm, matches the path combinations with trend combinations in the transportation analysis module, selects a pre-driving path for the vehicle, adds analysis of the road surface flatness condition in the process of selecting the pre-driving path, and improves the road surface flatness accuracy. And the finally selected pre-driving path is more accurate.

Description

Technical Field

[0001] The invention relates to the technical field of vehicle transportation management, and in particular to a vehicle transportation management system based on vehicle-mounted dynamic weighing. Background Art

[0002] A vehicle-mounted load cell is a device used to measure the weight of a vehicle. It calculates the weight of the cargo by detecting the physical changes (such as deformation, pressure, etc.) produced when the vehicle is loaded with cargo. These sensors are usually installed on the spring steel plate or other load-bearing structure of the vehicle, and can provide real-time load information in different operating environments;

[0003] However, in the prior art, the display of the vehicle load on the transport vehicle is just a simple value, and the monitoring is more for the convenience of the driver to understand the vehicle load situation and ensure that the vehicle is not overloaded. The route planning for the transport vehicle is more based on the distance and time of the transport route, and the driver is given the optimal driving route based on the shortest transportation time. However, the optimal driving route in this way does not take into account the unevenness of the road section. The transport vehicle driving on such a road section may cause the vehicle load to change. One result of the change in vehicle load is excessive fuel consumption and increased transportation costs. The optimal route recommendation obtained without considering the change in vehicle load is undoubtedly inaccurate.

[0004] In order to solve the above problems, the present invention proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a vehicle transportation management system based on on-board dynamic weighing, in order to solve the problem that the prior art does not take into account the unevenness of the road section when providing the driver with the optimal driving route based on the shortest transportation time. When a transport vehicle travels on such a road section, the vehicle load may change, and one result of the change in vehicle load is excessive fuel consumption, which increases transportation costs. The optimal route recommendation obtained without considering the change in vehicle load is undoubtedly inaccurate.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] Vehicle transportation management system based on on-board dynamic weighing, including:

[0008] The information collection module collects the task execution data of the vehicle after it completes the transportation task. The task execution data includes the pre-driving route, basic cargo weight data, the real-time driving speed of the vehicle during the transportation task, cargo weight and instantaneous fuel consumption;

[0009] The transportation management platform is used to store the task execution data of vehicles that have completed the transportation task;

[0010] The transportation analysis module is used to analyze all task execution data stored in the transportation management platform according to preset analysis steps to obtain analysis result data of several pre-driving routes;

[0011] When a vehicle is preparing to perform a transportation task, the transportation management platform obtains the location information of the starting point and the end point of the vehicle's pre-execution of the transportation task, and generates a pre-driving path for the vehicle's pre-execution of the transportation task according to the preset path planning rules. The transportation management platform transmits the pre-driving path of the vehicle to the driver of the vehicle, and guides the driver of the vehicle to perform the transportation task according to the pre-driving path.

[0012] Furthermore, the pre-travel route includes the location information of the starting point, the location information of the end point, and the location information of several waypoints along the way for the vehicle to perform the transportation task.

[0013] Furthermore, the basic cargo weight data refers to the total weight of the cargo measured by the on-board weighing sensor mounted on the vehicle after the cargo is loaded but before the vehicle starts driving.

[0014] Beneficial effects of the present invention:

[0015] The present invention collects task execution data of a vehicle after the vehicle completes the transportation task by setting an information collection module. The transportation analysis module divides each pre-driving path into several route combinations according to the pre-driving paths contained in the several task execution data, and determines several trend combinations and road surface trend indicators in the pre-driving path according to the changes of the real-time cargo weight, driving speed and instantaneous fuel consumption of the vehicle in each route combination. The transportation management platform divides each generated driving path into several route combinations based on the path planning algorithm, and matches the route combination with the trend combination in the transportation analysis module. The pre-driving path is selected for the vehicle according to the number of trend combinations in each driving path and the road surface trend indicator corresponding to the trend combination. In this way, the analysis of the road surface flatness is added in the process of selecting the pre-driving path, which makes the final selected pre-driving path more accurate on the one hand, and on the other hand, the vehicle driving on a relatively flat road can also avoid excessive vibration of the vehicle causing the cargo on the vehicle to shift, thereby improving the accuracy of weighing the vehicle cargo, and the balance of cargo weight also avoids unnecessary fuel consumption and increases in transportation costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below in conjunction with the accompanying drawings.

[0017] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0018] 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.

[0019] like Figure 1 As shown, the vehicle transportation management system based on on-board dynamic weighing includes an information collection module, a transportation management platform and a transportation analysis module;

[0020] The information collection module is used to collect the task execution data of the vehicle after the vehicle completes the transportation task, and the information collection module includes a first collection unit and a second collection unit;

[0021] The first collection unit collects basic data of the vehicle to perform the transport task, the basic data including the pre-driving route and basic cargo weight data, wherein the pre-driving route includes the location information of the starting point, the location information of the end point and the location information of several passing points in the middle of the pre-transport task of the vehicle, and the basic cargo weight data refers to the total weight of the cargo measured by the on-board weighing sensor carried by the vehicle after the cargo is loaded and before the vehicle starts to travel;

[0022] The second collection unit collects real-time transportation data of the vehicle performing the transportation task, the real-time transportation data includes the real-time driving speed, real-time cargo weight and real-time instantaneous fuel consumption of the vehicle performing the transportation task, and the real-time cargo weight is measured in real time based on the on-board weighing sensor carried by the transportation vehicle;

[0023] The vehicle performs the transport task, which means that the vehicle follows the pre-travel route and transports the goods on the vehicle from the starting point of the pre-travel route to the end point after passing through several waypoints in the specified sequence of the waypoints in the pre-travel route;

[0024] The information collection module generates the task execution data of the vehicle based on the basic data collected based on the transportation task and the real-time transportation data after the vehicle completes the transportation task, and transmits it to the transportation management platform;

[0025] A transport management platform is used to manage transport vehicles, and the transport management platform stores the task execution data of the vehicle after receiving the data;

[0026] When a vehicle is about to perform a transportation task, the transportation management platform obtains the location information of the starting point and the ending point of the vehicle's pre-execution transportation task, and generates the pre-driving path of the vehicle's pre-execution transportation task according to the preset path planning rules. The preset path planning rules are as follows:

[0027] S21: by obtaining the location information of the starting point and the ending point of the vehicle for the current transport task to be performed, a path planning algorithm is used to obtain a plurality of driving paths that can be driven from the starting point to the ending point and the corresponding estimated driving time, wherein each of the obtained driving paths includes the location information of a plurality of waypoints in addition to the location information of the starting point and the ending point;

[0028] The waypoints have an order in the driving path, and the order is used to specify the order in which the vehicle arrives at each waypoint. In this embodiment, the path planning algorithm can be one of the A* algorithm, the genetic algorithm or the Dijkstra algorithm;

[0029] S22: according to the order of the estimated travel time corresponding to each travel path from small to large, all corresponding travel paths are marked as N1, N2, ..., Nn, where n≥1;

[0030] S23: Mark the starting point of the pre-execution transportation task obtained this time as Q1, and the end point as Qq;

[0031] S24: Calculate and obtain the special road surface assessment value V1 of the path to be assessed according to the preset calculation rules, as follows:

[0032] S241: Selecting the driving path N1 as the path to be evaluated, marking the several waypoints included in the path to be evaluated as Q2, Q3, ..., Qq-1 in order from the earliest to the latest according to the order in which the designated vehicle arrives at the waypoints;

[0033] S242: in the order of Q1, Q2, ..., Qq, Q1 and Q2, Q2 and Q3, ..., Qq-1 and Qq are sequentially regarded as a route combination, and are marked as R1, R2, ..., Rr, where r = 1, 2, ..., q-1;

[0034] S243: traverse the analysis result data of all pre-travel routes stored in the transportation management platform, match the trend combination consistent with the route combination R1, if there is no trend combination consistent with the route combination R1, no processing is performed, otherwise, the road surface trend index of the consistent trend combination is obtained. It should be noted here that the trend combination consistent with the route combination R1 has the same group start point and group end point as the group start point and group end point of the route combination R1;

[0035] S244: According to S243, the analysis result data of all the pre-travel routes stored in the transportation management platform are matched with the trend combinations consistent with the route combinations R1, R2, ..., Rr in sequence, and the road surface trend indicators corresponding to the consistent trend combinations are obtained, and the road surface trend indicators of all the matched trend combinations are marked as U1, U2, ..., Uu in sequence, 1≤u≤r;

[0036] S245: Utilize formula Calculate and obtain the special road surface assessment value V1 of the path to be assessed, β1 and β2 are respectively the preset first and second proportion adjustment factors, and Umax and Umin are respectively the maximum and minimum values ​​of the road surface lack of direction indicators U1, U2, ..., Uu;

[0037] S25: According to S24, the driving paths N1, N2, ..., Nn are selected in sequence as the paths to be evaluated, and the special road surface evaluation values ​​V1, V2, ..., Vn of the driving paths N1, N2, ..., Nn are calculated and obtained, and the driving path corresponding to Vmin is selected as the pre-driving path of the vehicle, where Vmin is the minimum value among the special road surface evaluation values ​​V1, V2, ..., Vn;

[0038] The transportation management platform transmits the vehicle's pre-travel route to the vehicle's driver, and guides the vehicle's driver to perform the transportation task according to the pre-travel route;

[0039] The transportation analysis module is used to regularly analyze the task execution data of all vehicles stored in the data storage unit. The specific analysis steps are as follows:

[0040] S11: firstly, a pre-travel route is selected as the route to be analyzed, the starting point of the route to be analyzed is marked as A1, the end point is marked as Aa, a≥1, and the several waypoints are marked as A2, A3, ..., Aa-1 in sequence according to the order in which the vehicle arrives at the several waypoints in the route to be analyzed;

[0041] S12: Mark all the task execution data containing the path to be analyzed in the data storage unit as B1, B2, ..., Bb in sequence, where b≥1;

[0042] S13: In the order of A1, A2, ..., Aa, successively take A1 and A2, A2 and A3, ..., Aa - 1 and Aa as a route combination, and correspondingly label them as C1, C2, ..., Cc, where c = 1, 2, ..., a - 1; among them, A1 and A2 are respectively the intra - group starting point and intra - group ending point of route combination C1, A2 and A3 are respectively the intra - group starting point and intra - group ending point of route combination C2, and so on, Aa - 1 and Aa are respectively the intra - group starting point and intra - group ending point of route combination Cc;

[0043] S14: Calculate and obtain the cargo load deviation value L1 of route combination C1 in task execution data B1 according to the pre - designed calculation rules. The calculation rules are as follows:

[0044] S141: Obtain the real - time cargo weight, real - time driving speed, and real - time instantaneous fuel consumption during the process of the vehicle driving from the intra - group starting point of route combination C1 to the intra - group ending point of route combination C1 from task execution data B1. According to the order of the distance from each cargo weight collection moment to the current moment, mark all the collected cargo weights as D1, D2, ..., Dd in descending order, where d ≥ 1;

[0045] According to the order of the distance from each driving speed collection moment to the current moment, mark all the collected driving speeds as E1, E2, ..., Ed in descending order;

[0046] According to the order of the distance from each instantaneous fuel consumption collection moment to the current moment, mark all the collected instantaneous fuel consumptions as F1, F2, ..., Fd in descending order;

[0047] S142: Use the formula G1 = Dmax - D1 to calculate and obtain the maximum cargo load deviation capacity G1 of the vehicle in route combination C1, where Dmax is the average value of cargo weights D1, D2, ..., Dd;

[0048] S143: Use the formula 1 ≤ h ≤ d to calculate and obtain the residuals H1 of driving speeds E1, E2, ..., Ed. Compare the magnitudes of H1 and H. At this time, E is the average value of Eh, and H is the residual threshold of the preset route combination H1;

[0049] If H1 ≥ H, then in the order of |Eh - E| from large to small, successively delete the corresponding Eh and calculate the residual H1 of the remaining Eh. Compare the magnitudes of H1 and H again until H1 < H. Re - calibrate the average value of all the remaining driving speeds participating in the residual calculation at this time as the driving average speed of route combination C1, and label it as I1;

[0050] S144: Create a start-stop variable J1. First, compare the instantaneous fuel consumption F1 with P1 and P2. If the instantaneous fuel consumption F1 > P1 or the instantaneous fuel consumption F1 < P2, increment the value of the start-stop variable J1 by 1. Otherwise, do nothing. P1 and P2 are the instantaneous fuel consumption thresholds for accelerating and braking respectively under the route combination C1.

[0051] S145: According to S144, compare the instantaneous fuel consumptions F1, F2,..., Fd with P1 and P2 respectively. After all the comparisons are completed, obtain the final value of the start variable and label it as K1.

[0052] S146: Use the formula to calculate and obtain the tendency value L1 of the change in the weight of the goods on the road surface of the route combination C1 in the task execution data B1. Here, α1 is a preset start-stop compensation value used to compensate for the deviation capacity of the goods weight caused by traffic reasons under the driving average speed I1. The tendency value L1 is defined artificially to characterize the influence characteristics of the change in the weight of the goods on the road surface when the vehicle is driving on the road condition of the route combination C1 in the task execution data B1.

[0053] S15: According to S14, calculate and obtain the tendency values L1, L2,..., Lb of the route combination C1 in the task execution data B1, B2,..., Bb in sequence, and use the sum and average formula to calculate and obtain their average value, and label the average value as the road surface tendency index of the route combination C1, marked as M1.

[0054] S16: Compare the road surface tendency index M1 with M. If M1 ≥ M, determine that the route combination C1 is a tendency combination. Otherwise, do nothing. M is a preset tendency combination determination threshold.

[0055] S17: According to S14 to S16, determine whether the route combinations C1, C2,..., Cc are tendency combinations in sequence. After all the determinations are completed, obtain all the tendency combinations and their corresponding road surface tendency indexes.

[0056] The transportation analysis module generates the analysis result data of the path to be analyzed based on the route combinations C1, C2,..., Cc and all the road surface tendency indexes determined as tendency combinations therein, and transmits it to the transportation management platform for update and storage.

[0057] S18: According to S11 to S17, sequentially select all the pre-travel paths included in the task execution data of all vehicles stored in the data storage unit as the paths to be analyzed, calculate and obtain the analysis result data of all the pre-travel paths in sequence, and transmit it to the transportation management platform for update and storage.

[0058] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0059] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0060] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A vehicle transportation management system based on vehicle-mounted dynamic weighing, characterized in that: include: The information collection module collects the task execution data of the vehicle after it completes the transportation task. The task execution data includes the pre-driving route, basic cargo weight data, the real-time driving speed of the vehicle during the transportation task, cargo weight and instantaneous fuel consumption; The transportation management platform is used to store the task execution data of vehicles that have completed the transportation task; The transportation analysis module is used to analyze all task execution data stored in the transportation management platform according to preset analysis steps to obtain analysis result data of several pre-driving routes; When a vehicle is preparing to perform a transportation task, the transportation management platform obtains the location information of the starting point and the end point of the vehicle's pre-execution of the transportation task, and generates a pre-driving path for the vehicle's pre-execution of the transportation task according to the preset path planning rules. The transportation management platform transmits the pre-driving path of the vehicle to the driver of the vehicle, and guides the driver of the vehicle to perform the transportation task according to the pre-driving path.

2. The vehicle transportation management system based on vehicle-mounted dynamic weighing according to claim 1 is characterized in that: The pre-travel route includes the location information of the starting point, the end point and several waypoints along the way for the vehicle to perform the transportation task.

3. The vehicle transportation management system based on vehicle-mounted dynamic weighing according to claim 1 is characterized in that: The basic cargo weight data refers to the total weight of the cargo measured by the on-board weighing sensor mounted on the vehicle after the cargo is loaded but before the vehicle starts driving.

4. The vehicle transportation management system based on vehicle-mounted dynamic weighing according to claim 2 is characterized in that: The specific analysis steps for analyzing all the task execution data stored in the transportation management platform and obtaining the analysis result data of several pre-driving routes are as follows: S11: firstly, a pre-travel route is selected as the route to be analyzed, the starting point of the route to be analyzed is marked as A1, the end point is marked as Aa, a≥1, and the several waypoints are marked as A2, A3, ..., Aa-1 in sequence according to the order in which the vehicle arrives at the several waypoints in the route to be analyzed; S12: Mark all the task execution data containing the path to be analyzed in the data storage unit as B1, B2, ..., Bb in sequence, where b≥1; S13: In the order of A1, A2, ..., Aa, A1 and A2, A2 and A3, ..., Aa-1 and Aa are taken as a route combination, and marked as C1, C2, ..., Cc, where c=1, 2, ..., a-1; wherein A1 and A2 are respectively the starting point and the end point of the route combination C1, A2 and A3 are respectively the starting point and the end point of the route combination C2, and so on, Aa-1 and Aa are respectively the starting point and the end point of the route combination Cc. S14: Calculate and obtain the cargo load deviation value L1 of the route combination C1 in the task execution data B1 according to a preset calculation rule; S15: According to S14, the trend values ​​L1, L2, ..., Lb of the route combination C1 in the task execution data B1, B2, ..., Bb are calculated in sequence, and their averages are calculated using the addition and averaging formula, and the averages are calibrated as the road surface trend index of the route combination C1, which is marked as M1; S16: Compare the road surface tendency index M1 with M. If M1 ≥ M, determine that the route combination C1 is a tendency combination; otherwise, do nothing. M is a preset determination threshold for the tendency combination. S17: Sequentially determine whether the route combinations C1, C2, ..., Cc are tendency combinations according to S14 to S16. After all determinations are completed, obtain all the tendency combinations and their corresponding road surface tendency indexes. The transportation analysis module generates analysis result data for the to-be-analyzed path based on the route combinations C1, C2, ..., Cc and all the road surface tendency indexes determined to be tendency combinations therein. S18: Sequentially select all the pre-travel paths included in the task execution data of all vehicles stored in the data storage unit as the to-be-analyzed paths according to S11 to S17, and sequentially calculate and obtain the analysis result data for all the pre-travel paths.

5. The vehicle transportation management system based on vehicle-mounted dynamic weighing according to claim 4 is characterized in that: For the above S14, the calculation rule for obtaining the cargo load deviation value L1 of the route combination C1 in the task execution data B1 is as follows: S141: Obtain the real-time cargo weight, real-time driving speed, and real-time instantaneous fuel consumption during the process of the vehicle driving from the start point within the route combination C1 to the end point within the route combination C1 from the task execution data B1. According to the order of the distance from each cargo weight collection moment to the current moment, mark all the collected cargo weights as D1, D2, ..., Dd in descending order, where d ≥ 1. According to the order of the distance from each driving speed collection moment to the current moment, mark all the collected driving speeds as E1, E2, ..., Ed in descending order, and according to the order of the distance from each instantaneous fuel consumption collection moment to the current moment, mark all the collected instantaneous fuel consumptions as F1, F2, ..., Fd in descending order. S142: Calculate and obtain the maximum cargo load deviation capacity G1 of the vehicle in the route combination C1 using the formula G1 = Dmax - D1, where Dmax is the average value of the cargo weights D1, D2, ..., Dd. S143: Using formula 1≤h≤d calculates the residual H1 of the driving speeds E1, E2, ..., Ed, and compares H1 with H. At this time, E is the average value of Eh, and H is the residual threshold of the preset route combination H1; If H1 ≥ H, then delete the corresponding Eh in descending order of |Eh - E|, calculate the residual H1 of the remaining Eh, and compare H1 with H again until H1 < H. Then, re-calibrate the average value of all the remaining driving speeds participating in the residual calculation as the driving average speed of the route combination C1, marked as I1. S144: Create a start-stop variable J1. First, compare the instantaneous fuel consumption F1 with P1 and P2. If the instantaneous fuel consumption F1 > P1 or the instantaneous fuel consumption F1 < P2, increment the value of the start-stop variable J1 by 1; otherwise, do nothing. P1 and P2 are the instantaneous fuel consumption thresholds for stepping on the accelerator and stepping on the brake under the route combination C1, respectively. S145: According to S144, compare the instantaneous fuel consumptions F1, F2, ..., Fd with P1 and P2 respectively. After all the comparisons are completed, obtain the final value of the start variable and calibrate it as K1. S146: Using formula The trend value L1 of the route combination C1 road surface in the task execution data B1 for the change in cargo weight is calculated and obtained, wherein α1 is the preset start-stop compensation value.

6. The vehicle transportation management system based on vehicle-mounted dynamic weighing according to claim 1 is characterized in that: The specific steps for generating the pre-travel path of the vehicle for the current pre-executed transportation task are as follows: S21: by obtaining the location information of the starting point and the ending point of the vehicle for the current transport task to be performed, a path planning algorithm is used to obtain a plurality of driving paths that can be driven from the starting point to the ending point and the corresponding estimated driving time, wherein each driving path obtained includes the location information of a plurality of waypoints in addition to the location information of the starting point and the ending point; the waypoints have an order in the driving path; S22: according to the order of the estimated travel time corresponding to each travel path from small to large, all corresponding travel paths are marked as N1, N2, ..., Nn, where n≥1; S23: Mark the starting point of the pre-execution transportation task obtained this time as Q1, and the end point as Qq; S24: Calculate and obtain the special road surface assessment value V1 of the path to be assessed according to a preset calculation rule; S25: According to S24, driving paths N1, N2, ..., Nn are selected in turn as paths to be evaluated, and the special road surface evaluation values ​​V1, V2, ..., Vn of the driving paths N1, N2, ..., Nn are calculated and obtained, and the driving path corresponding to Vmin is selected as the pre-driving path of the vehicle, and Vmin is the minimum value among the special road surface evaluation values ​​V1, V2, ..., Vn.

7. The vehicle transportation management system based on vehicle-mounted dynamic weighing according to claim 6 is characterized in that: The calculation rule of S24, calculating and obtaining the special road surface evaluation value V1 of the path to be evaluated, is as follows: S241: Selecting the driving path N1 as the path to be evaluated, marking the several waypoints included in the path to be evaluated as Q2, Q3, ..., Qq-1 in order from the earliest to the latest according to the order in which the designated vehicle arrives at the waypoints; S242: in the order of Q1, Q2, ..., Qq, Q1 and Q2, Q2 and Q3, ..., Qq-1 and Qq are sequentially regarded as a route combination, and are marked as R1, R2, ..., Rr, where r = 1, 2, ..., q-1; S243: traverse the analysis result data of all pre-travel routes stored in the transportation management platform, match the trend combination consistent with the route combination R1, if there is no trend combination consistent with the route combination R1, no processing is performed, otherwise, the road surface trend index of the consistent trend combination is obtained. It should be noted here that the trend combination consistent with the route combination R1 has the same group start point and group end point as the group start point and group end point of the route combination R1; S244: According to S243, the analysis result data of all the pre-travel routes stored in the transportation management platform are matched with the trend combinations consistent with the route combinations R1, R2, ..., Rr in sequence, and the road surface trend indicators corresponding to the consistent trend combinations are obtained, and the road surface trend indicators of all the matched trend combinations are marked as U1, U2, ..., Uu in sequence, 1≤u≤r; S245: Utilize formula The special road surface assessment value V1 of the path to be assessed is calculated, β1 and β2 are the preset first and second proportion adjustment factors, and Umax and Umin are the maximum and minimum values ​​of the road surface lack of direction indicators U1, U2, ..., Uu.

Images