Dangerous chemical substance logistics transportation scheduling method based on multiple data sources

Abstract

The invention discloses a hazardous chemical substance logistics transportation scheduling method based on multiple data sources, and relates to the technical field of hazardous chemical substance logistics transportation, and the method comprises the following steps: collecting static basic data and dynamic real-time data through a multi-source data collection device; cleaning and filtering the collected multi-source data, and judging and processing abnormal values; a preliminary transportation path is generated by analyzing the collected data, an optimal transportation path is analyzed by using the road transportation cost, and a standby path storage module and a path risk real-time monitoring mechanism are set to monitor the selected transportation path; analyzing the risk change of the road condition by using the collected real-time data, and adjusting a risk monitoring threshold value in real time according to the change of the risk condition; the enhanced monitoring mode is set to analyze and judge the transportation risk change condition, and the delayed monitoring mode is set, so that the data acquisition time interval is shortened in the enhanced monitoring mode, the risk judgment time can be shortened, and the accuracy of the risk judgment result is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of dangerous chemical product logistics transportation, and particularly relates to a dangerous chemical product logistics transportation scheduling method based on multiple data sources. BACKGROUND

[0002] The logistics transportation of dangerous chemicals has high risk, and the path selection and risk control in the transportation process are directly related to people's life and property safety and ecological environment. The traditional dangerous chemical transportation scheduling mode often relies on fixed route planning and manual experience judgment, and is difficult to cope with complex and changeable real-time road conditions, weather conditions and different characteristics of different dangerous chemicals.

[0003] At present, although some technologies attempt to introduce data collection and analysis means to assist transportation scheduling, there are many deficiencies. For example, the data source is relatively single, and is mostly concentrated in road condition information, lacking fusion analysis of multi-dimensional data such as the properties of dangerous chemicals, road conditions and environmental parameters. The path generation lacks dynamic adaptability and cannot be adjusted in time according to real-time data changes. The risk judgment does not fully consider the differences in the types of goods carried, uses a unified safety threshold, and when individual road transportation risk influencing factors change without affecting the overall risk change to reach the threshold, it cannot identify and warn the impact of individual potential factors, leading to inaccurate and untimely risk assessment, making it difficult to achieve targeted safety control. SUMMARY

[0004] The purpose of the present application is to provide a dangerous chemical product logistics transportation scheduling method based on multiple data sources to solve the problems in the prior art.

[0005] To achieve the above purpose, the present application provides the following technical scheme: a dangerous chemical product logistics transportation scheduling method based on multiple data sources, the method comprising the following steps:

[0006] Step S1: collecting static basic data and dynamic real-time data through multiple source data collection devices;

[0007] Step S2: cleaning and filtering the collected multiple source data and judging and processing abnormal values;

[0008] Step S3: generating a preliminary transportation path by analyzing the collected data, selecting the best transportation path by analyzing the road transportation cost, and setting a backup path storage module and a path risk real-time monitoring mechanism to monitor the selected transportation path;

[0009] Step S4: analyzing the change of transportation risk using the collected dynamic real-time data, and dynamically adjusting the risk monitoring threshold according to the change of transportation risk.

[0010] Further, in step S1: static basic data and dynamic real-time data are collected by multi-source data collection equipment; static basic data is obtained through database import and manual input, including hazardous chemical properties and fixed road network information; dynamic real-time data is collected in real time through API interface, sensors and vehicle terminal, including real-time road condition information, environmental monitoring data, vehicle real-time state and surrounding sensitive area distribution, and the collected data is stored in a distributed database.

[0011] Further, in step S2: the collected data is cleaned, filtered and processed for abnormal values; for continuous dynamic data, 3σ rule is used in combination with a sliding window for abnormal detection, when the data value exceeds the range of [μ-3σ, μ+3σ], it is determined as an abnormal value, and the mean value of the adjacent 3 valid values in the window is used to replace it, where μ represents the mean value in the window, and σ represents the standard deviation in the window; for discrete data, an abnormal judgment threshold is set to determine whether there is an abnormal value in the collected data, and the previous valid value is used to replace the abnormal value.

[0012] Further, step S3 includes the following steps:

[0013] S3-1, based on the coordinates of the transportation starting point and the ending point, an electronic map API is called to obtain a short-distance path as a basic path, and then the road information stored in the database is used to filter out the impassable road sections in the basic path; after filtering out the road sections that cannot be passed, an initial candidate path set is formed;

[0014] S3-2, before transportation starts, the road transportation cost formula is used to calculate the transportation cost of the paths in the initial candidate path set, and after transportation starts, the road transportation cost is updated in real time according to the real-time data collected during transportation;

[0015] S3-3, a threshold is set to select a candidate transportation path set that meets the requirements, and according to the calculated transportation cost, the best transportation path is selected from the candidate transportation path set; at the same time, a standby path storage module is designed, the paths in the candidate transportation path set that are not selected are recorded as standby paths, and stored in the standby path storage module;

[0016] S3-4, a road transportation cost real-time monitoring mechanism is set, the road transportation cost of the transportation path is monitored in real time during transportation, and whether the transportation road needs to be adjusted is judged according to the monitoring result, and an adjustment instruction is generated when it is judged that the transportation road needs to be adjusted.

[0017] Further, in step S3-2: a transportation road is divided into m nodes; in each road section divided by nodes in a path, the parameters affecting the road transportation cost include time cost Q 1i , risk cost Q2i and energy cost Q 3i ; the time cost of the transport path is calculated according to the following formula: where Y represents the length of the road section, v0 represents the basic speed, such as 80 km / h for expressway, 60 km / h for national highway, and 50 km / h for provincial highway; p represents the speed reduction coefficient varying with the congestion degree of the road section; the congestion degree of the road section is divided into four levels, namely, smooth, first-level congestion, second-level congestion, and third-level congestion, and the congestion degrees of the four levels are from low to high; the speed reduction coefficients of the four levels of congestion degree are set respectively, p1 is the speed reduction coefficient corresponding to smooth, p2 is the speed reduction coefficient corresponding to first-level congestion, p3 is the speed reduction coefficient corresponding to second-level congestion, and p4 is the speed reduction coefficient corresponding to third-level congestion; the speed reduction coefficients are set according to the analyzed road congestion degree, for example, when the road is smooth, the speed of the vehicle will not decrease due to congestion, so the speed reduction coefficient p1 is usually set to 1; when it is judged to be third-level congestion, it means that the congestion is very serious, the speed of the vehicle will decrease seriously during the driving, and even there is a parking situation, so the speed reduction coefficient p4 is set to 0.4 or a lower value;

[0018] The risk cost of the road section is calculated according to the following formula: where r1 represents the environmental risk coefficient; r2 represents the sensitive area risk coefficient; r3 represents the road safety risk coefficient; the environmental risk coefficient varies dynamically with the change of the environmental temperature and the wind level: where T represents the real-time monitored environmental temperature, T0 represents the set environmental temperature safety threshold; D represents the real-time monitored wind level, D0 represents the set wind level safety threshold; f1 and f2 represent the influence weights of the environmental temperature and the wind level on the environmental risk respectively, f1+f2=1, the values of f1 and f2 are adjusted according to the different types of dangerous and hazardous chemicals, for the dangerous and hazardous chemicals which are highly affected by temperature, f1 is adjusted to be high, and for the dangerous and hazardous chemicals which are highly affected by wind, f2 is adjusted to be high; the value of r2 decreases with the increase of the distance between the transport road section and the sensitive area; the road safety risk is set for special road sections, the road safety risk coefficient is set to 2 when a construction road section is encountered, the road safety risk coefficient is set to 1.5 when a tunnel and a bridge road section are encountered, and the road safety risk coefficient is set to 1 when an ordinary road section is encountered;

[0019] The energy cost is calculated according to the following formula: where w represents the road slope influence coefficient, the value of w is less than 1 when a downhill is detected, and decreases with the increase of the slope; the value of w is 1 when a flat road is detected; the value of w is greater than 1 when an uphill is detected, and increases with the increase of the slope; G represents the actual load weight, and G0 represents the basic load weight set by the system.

[0020] Further, the road transportation cost of a transportation path is calculated according to the following formula:

[0021]

[0022] wherein S represents the road transportation cost of a transportation path; i represents the node label, i = 1, 2, …, m;

[0023] Before the transportation starts, the road transportation cost of each path in the initial candidate path set is calculated by using the road condition information and environmental information input through the API port and the road transportation cost formula, and the predicted road transportation cost of each path in the initial candidate path set is obtained; after the transportation starts, the real-time road transportation cost is calculated by using the real-time dynamic data collected in real time, so as to update the road transportation cost in real time; for example, when the vehicle travels to an intermediate node k of the transportation path, the actual transportation cost value from the starting point to the node k is updated to the road transportation cost, and by using the road condition change and environmental change data collected in the transportation, the road transportation cost of the path from the node k to the terminal node m which has not been traveled to is analyzed and predicted again, so as to obtain the road transportation cost which is updated in real time according to the transportation road condition and the transportation environment.

[0024] Further, in step S3-3: a road transportation cost basic threshold S1 is set, the predicted road transportation cost of each transportation path in the initial candidate path set is compared with the basic threshold S1, the paths with the road transportation cost less than S1 are extracted as candidate transportation paths, and the predicted road transportation cost of each candidate transportation path is compared to select the path with the lowest road transportation cost as the best transportation path; by analyzing and calculating the road transportation cost, the effect that the best transportation path can be selected before the transportation starts is achieved, and the selected best transportation path can take into account the advantages of the shortest transportation time, the smallest transportation risk and the smallest transportation energy consumption; a backup path storage module is designed, and the remaining candidate transportation paths are stored in the backup path storage module as backup paths, which are recorded as {B1, B2, …, B h};and after the start of transportation, the real-time dynamic data collected and the road transportation cost analysis method are used to update the road transportation cost of the standby path in the standby path storage module in real time; the actual cost after the transportation vehicle travels is combined with the predicted transportation cost without traveling to update the real-time road transportation cost of the transportation path in real time, solving the problem of information update not in time caused by analyzing the road transportation cost for a single time, and being able to timely find the situation of transportation cost increase caused by sudden situations to the road transportation, and setting the standby path storage module, storing the standby paths meeting the transportation cost requirements, facilitating timely replacement of the transportation path when encountering sudden situations.

[0025] Further, in step S3-4: a path road transportation cost real-time monitoring mechanism is set, the road transportation cost basic threshold S1 is used as a low cost basic monitoring threshold, and a high cost monitoring threshold S2 is set, and after the start of transportation, the real-time change value S of the road transportation cost is monitored in real time; S is compared with the set threshold polarity, and the analysis result is as follows:

[0026] If S < S1, it indicates that the road transportation cost is normal, and no road adjustment instruction is generated;

[0027] If S1≤S≤S2, it indicates that the road transportation cost is increasing, and a first-level warning and a transportation path fine-tuning instruction c1 are issued;

[0028] If S > S2, it indicates that the road transportation cost is abnormally high, and a second-level warning and a transportation path adjustment instruction c2 are issued;

[0029] After receiving the first-level warning and the instruction c1, the parameters affecting the road transportation path in the current transportation path are analyzed, the abnormal parameters and the road sections where the abnormal parameters appear are analyzed, and the road sections where the abnormal parameters appear are replaced using the alternative paths in the road network information;

[0030] After receiving the second-level warning and the instruction c2, the parameters affecting the road transportation path in the current transportation path are analyzed, and the standby paths in the standby path storage module are extracted, the road transportation cost of the standby paths is updated and evaluated, and the path with the lowest road transportation cost in the standby paths is selected to replace the current path.

[0031] Further, in step S4: according to the collected dangerous chemical properties, the dangerous chemicals are divided into three categories: explosives, toxic gases and corrosive substances; when performing transportation risk analysis, only the three types of dangerous chemicals are analyzed respectively, and the analysis results are as follows:

[0032] For explosives, the risk factors affecting the transportation risk of explosives include vibration frequency, environmental temperature and static voltage;

[0033] For toxic gas, the risk factors affecting the transportation risk of toxic gas include leakage concentration, wind diffusion speed, and distance between transportation section and sensitive area;

[0034] For corrosive substance, the risk factors affecting the transportation risk of corrosive substance include tank corrosion rate, environmental humidity, and road bumping degree;

[0035] The basic safety threshold M0 is set for each type of dangerous chemical according to the risk factors combined with industry standards, and the risk factor data is collected every interval Δt for comparison and analysis with the set basic safety threshold. If the real-time collected risk factor data are all lower than the set basic safety threshold, it indicates that the transportation risk is low. If one of the real-time collected risk factor data is higher than the set basic threshold value, it is predicted that the transportation risk will increase, and the intensive monitoring mode is started.

[0036] Further, the intensive monitoring duration ΔJ is set after starting the intensive monitoring mode, and the interval of collecting monitoring data is shortened to Δt / 2 in the intensive monitoring mode;

[0037] If the risk factor data originally exceeding the basic threshold returns to below the basic threshold within the intensive monitoring duration, z ΔJ intensive monitoring durations are added for delay monitoring after the first intensive monitoring duration ends. If no risk factor data higher than the set basic threshold is monitored during the delay monitoring, the intensive monitoring mode is released;

[0038] If the risk factor data again appears higher than the set basic threshold during the delay monitoring, it is judged that the transportation risk has a fluctuating increasing trend. After the fluctuating increasing trend of the transportation risk appears, the strictness of monitoring the risk factors affecting the transportation risk is improved, the basic threshold is adjusted, and the adjusted basic threshold is calculated according to the following formula: M = (1-c x a)M0; wherein, M represents the adjusted basic threshold, c represents the number of risk factor data with fluctuating increasing trend, a represents the basic threshold adjustment coefficient set by the system; at the same time, the risk cost in the transportation cost is adjusted, and the adjusted risk cost is calculated according to the following formula: Q 2i ′ = (1+θ)Q 2i ; wherein, θ represents the risk cost adjustment coefficient set by the system, Q 2i ′ represents the risk cost with meteorite risk fluctuation addition;

[0039] After adjusting the basic safety threshold, the strengthened monitoring is continued for a time length of ΔJ, if the risk factor data higher than the basic threshold is not monitored in the strengthened monitoring time length, the delay monitoring is continued, if the risk factor data higher than the basic threshold is not monitored in the delay monitoring, the strengthened monitoring state is released, and the warning threshold is restored to the state before adjustment, if the risk factor higher than the basic prediction is monitored, the transportation risk increase warning is directly sent out, if the risk factor data higher than the basic threshold is monitored after adjusting the basic threshold, the transportation risk increase warning is directly sent out;

[0040] If the risk factor data affecting the transportation risk detected in the strengthened monitoring time length is continuously higher than the set basic threshold, the transportation risk increase warning is generated, at the same time of sending out the transportation risk increase warning, the risk cost in the transportation cost is adjusted: Q 2i =(1+3θ)Q 2i ; wherein, Q 2i " indicates the risk cost with transportation risk increase addition; the data collection time interval is shortened in the strengthened monitoring mode, the risk judgment time can be shortened, and the accuracy of the risk judgment result is improved; and the delay monitoring is set, the accuracy of the monitoring result is improved.

[0041] Compared with the prior art, the beneficial effects of the present application are:

[0042] The application provides a technical scheme for analyzing the transportation cost of dangerous chemicals by risk time cost, risk cost and energy consumption cost, which is used for planning the transportation road of dangerous chemicals. Through the analysis and calculation of the road transportation cost, the effect that the best transportation path can be selected before the transportation is started is achieved. The selected best transportation path can take into account the advantages of the shortest transportation time, the smallest transportation risk and the smallest transportation energy consumption. Moreover, the analysis of the road transportation cost of the application is still updated according to the real-time data in the transportation process after the transportation is started. The actual cost after the transportation vehicle drives is combined with the predicted transportation cost without driving to update the real-time road transportation cost of the transportation path in real time, so as to solve the problem of untimely information update caused by single road transportation cost analysis, to be able to timely find the situation that the transportation cost of road transportation is increased due to the sudden situation, and to set a standby path storage module to store the standby path meeting the transportation cost requirement, so as to facilitate the timely replacement of the transportation path when the sudden situation occurs. Meanwhile, a transportation risk monitoring mechanism is set. In the transportation of dangerous chemicals, the factors affecting the transportation risk of dangerous chemicals are monitored in real time. Moreover, a strengthened monitoring mode is set. After it is monitored that the risk factor data exceeds the set basic threshold value, the strengthened monitoring mode is started to analyze and judge the change of the transportation risk. The data collection time interval is shortened in the strengthened monitoring mode, so as to shorten the risk judgment time and improve the accuracy of the risk judgment result. Moreover, a delay monitoring is set, so as to improve the accuracy of the monitoring result. After the risk factor data is monitored to have an increasing trend and the transportation risk is judged to be increased, the risk cost in the road transportation cost is adjusted by transportation risk fluctuation addition and transportation risk increase addition, so as to improve the safety of the transportation of dangerous chemicals. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 FIG. 1 is a flowchart of a dangerous chemical logistics transportation scheduling method based on multiple data sources. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0045] As shown in FIG. 1, the application provides a technical scheme, a dangerous chemical logistics transportation scheduling method based on multiple data sources, which comprises the following steps: Figure 1

[0046] Step S1: collecting static basic data and dynamic real-time data by multiple source data acquisition devices respectively; ​

[0047] Step S2: cleaning and filtering the collected multi-source data, and judging and processing abnormal values;

[0048] Step S3: generating a preliminary transportation path by analyzing the collected data, selecting the best transportation path by analyzing the road transportation cost, and setting a backup path storage module and a path risk real-time monitoring mechanism to monitor the selected transportation path;

[0049] Step S4: analyzing the changes of transportation risks by using the collected dynamic real-time data, and dynamically adjusting the risk monitoring threshold according to the changes of transportation risks.

[0050] In step S1: static basic data and dynamic real-time data are collected by multi-source data collection equipment; static basic data is obtained by database import and manual input, and static basic data includes hazardous chemical properties and fixed road network information; dynamic real-time data is collected in real time by API interface, sensor and vehicle terminal, and dynamic real-time data includes real-time road condition information, environmental monitoring data, vehicle real-time state and surrounding sensitive area distribution, and the collected data is stored in a distributed database.

[0051] In step S2: the collected data is cleaned, filtered and abnormal value processed; for continuous dynamic data, 3σ rule is adopted to detect abnormal values in combination with sliding window, when the data value is out of the range of [μ-3σ, μ+3σ], it is determined as an abnormal value, and the mean value of the adjacent 3 valid values in the window is used to replace it, wherein μ represents the mean value in the window, and σ represents the standard deviation in the window; for discrete data, whether there is an abnormal value in the collected data is judged by setting an abnormal judgment threshold, and the previous valid value is used to replace the abnormal value.

[0052] Step S3 includes the following steps:

[0053] S3-1, based on the coordinates of the transportation starting point and the ending point, calling an electronic map API to obtain a short distance path as a basic path, and then filtering out the impassable road sections in the basic path through the road information stored in the database; after filtering out the road sections that cannot be passed, an initial candidate path set is formed;

[0054] S3-2, before transportation starts, the road transportation cost formula is used to calculate the transportation cost of the paths in the initial candidate path set, and after transportation starts, the road transportation cost is updated in real time according to the real-time data collected during transportation;

[0055] S3-3, set threshold value to select candidate transportation path set meeting requirements, and select the best transportation path in the candidate transportation path set according to the calculated transportation cost; meanwhile, design a backup path storage module, record the paths in the candidate transportation path set that are not selected as backup paths, and store them in the backup path storage module;

[0056] S3-4, set a road transportation cost real-time monitoring mechanism to monitor the road transportation cost of the transportation path in real time during transportation, and judge whether the transportation road needs to be adjusted according to the monitoring result, and generate an adjustment instruction when it is judged that the transportation road needs to be adjusted.

[0057] In step S3-2: divide a transportation road into m nodes; in each road section divided by nodes in a path, the parameters affecting the road transportation cost include time cost Q 1i , risk cost Q 2i and energy consumption cost Q 3i ; the time cost of the transportation path is calculated according to the following formula: Where Y represents the length of the road section, v0 represents the basic speed, and p represents the speed reduction coefficient varying with the congestion degree of the road section; the congestion degree of the road section is divided into four levels, namely, smooth, first-level congestion, second-level congestion and third-level congestion, and the congestion degrees of the four levels are from low to high; the speed reduction coefficients of the four levels of congestion degree are set respectively, p1 is the speed reduction coefficient corresponding to smooth, p2 is the speed reduction coefficient corresponding to first-level congestion, p3 is the speed reduction coefficient corresponding to second-level congestion, and p4 is the speed reduction coefficient corresponding to third-level congestion;

[0058] The risk cost of the road section is calculated according to the following formula: Where r1 represents the environmental risk coefficient; r2 represents the sensitive area risk coefficient; r3 represents the road safety risk coefficient; wherein the environmental risk coefficient varies dynamically in real time with the change of the environmental temperature and the wind level: Where T represents the real-time monitored environmental temperature, T0 represents the set environmental temperature safety threshold, D represents the real-time monitored wind level, D0 represents the set wind level safety threshold, f1 and f2 represent the influence weights of the environmental temperature and the wind level on the environmental risk respectively, f1+f2=1, the values of f1 and f2 are adjusted according to the types of the dangerous and hazardous chemicals, for the dangerous and hazardous chemicals that are highly affected by temperature, f1 is adjusted to be high, and for the dangerous and hazardous chemicals that are highly affected by wind, f2 is adjusted to be high; the value of r2 decreases with the increase of the distance between the transportation road section and the sensitive area; the road safety risk is set for special road sections, the road safety risk coefficient is set to 2 when a construction road section is encountered, the road safety risk coefficient is set to 1.5 when a tunnel and a bridge road section are encountered, and the road safety risk coefficient is set to 1 when an ordinary road section is encountered;

[0059] The energy consumption cost is calculated according to the following formula: Wherein, w represents the road slope influence coefficient, the value of w is less than 1 when a downhill is detected, and decreases with the increase of the slope; the value of w is 1 when a flat road is detected; the value of w is greater than 1 when an uphill is detected, and increases with the increase of the slope; G represents the actual load weight, and G0 represents the basic load weight set by the system.

[0060] The road transportation cost of a transportation path is calculated according to the following formula:

[0061]

[0062] Wherein, S represents the road transportation cost of a transportation path; i represents the node label, i = 1, 2, …, m;

[0063] Before the transportation starts, the road transportation cost of each path in the initial candidate path set is calculated by using the road condition information and environmental information input through the API port and the road transportation cost formula, and the predicted road transportation cost of each path in the initial candidate path set is obtained; after the transportation starts, the real-time road transportation cost is calculated by using the real-time dynamic data collected in real time, so as to update the road transportation cost in real time.

[0064] In step S3-3: set the road transportation cost basic threshold S1, compare the predicted road transportation cost of each transportation path in the initial candidate path set with the basic threshold S1, extract the paths with the road transportation cost less than S1 as the candidate transportation paths, compare the predicted road transportation cost of each candidate transportation path, and select the path with the lowest road transportation cost as the best transportation path; design a backup path storage module, store the remaining candidate transportation paths as backup paths in the backup path storage module, and mark them as {B1, B2, …, B h}; and after the transportation starts, the real-time dynamic data collected and the road transportation cost analysis method are used to update the road transportation cost of the backup paths in the backup path storage module in real time.

[0065] In step S3-4: set the path road transportation cost real-time monitoring mechanism, use the road transportation cost basic threshold S1 as the low cost basic monitoring threshold, set the high cost monitoring threshold S2, and monitor the real-time change value S of the road transportation cost after the transportation starts; compare S with the set threshold polarity, and the analysis result is as follows:

[0066] If S < S1, it indicates that the road transportation cost is normal, and no road adjustment instruction is generated;

[0067] If S1≤S≤S2, it means that the road transportation cost is increasing, and a first-level warning and transportation path fine-tuning instruction c1 is issued;

[0068] If S>S2, it means that the road transportation cost is abnormally high, and a second-level warning and transportation path adjustment instruction c2 is issued;

[0069] After receiving the first-level warning and instruction c1, the parameters affecting the road transportation path in the current transportation path are analyzed, the abnormal parameters and the road sections where the abnormal parameters appear are analyzed, and the road sections where the parameters are abnormally high are replaced using the alternative paths in the road network information;

[0070] After receiving the second-level warning and instruction c2, the parameters affecting the road transportation path in the current transportation path are analyzed, and the standby paths in the standby path storage module are extracted, the road transportation cost of the standby paths is updated and evaluated, and the path with the lowest road transportation cost in the standby path is selected to replace the current path.

[0071] In step S4: According to the collected dangerous chemical properties, the dangerous chemicals are divided into three categories: explosives, toxic gases and corrosive substances; When performing transportation risk analysis, only the three types of dangerous chemicals are analyzed respectively, and the analysis results are as follows:

[0072] For explosives, the risk factors affecting the transportation risk of explosives include vibration frequency, environmental temperature and static voltage;

[0073] For toxic gases, the risk factors affecting the transportation risk of toxic gases include leakage concentration, wind diffusion speed and distance between transportation section and sensitive area;

[0074] For corrosive substances, the risk factors affecting the transportation risk of corrosive substances include tank corrosion rate, environmental humidity and road surface bumping degree;

[0075] Set a basic safety threshold M0 for each type of dangerous chemical according to the industry standard, collect risk factor data every interval Δt for comparison and analysis with the set basic safety threshold, if the real-time collected risk factor data are all lower than the set basic safety threshold, it means that the transportation risk is low; If one of the real-time collected risk factor data is higher than the set basic threshold value, it is predicted that the transportation risk will increase, and the intensive monitoring mode is started.

[0076] After starting the intensive monitoring mode, set the intensive monitoring time ΔJ, and in the intensive monitoring mode, shorten the interval time for collecting monitoring data to Δt / 2;

[0077] If the risk factor data that originally exceeds the basic threshold value is restored to below the basic threshold value during the intensive monitoring duration, after the first intensive monitoring duration ends, the intensive monitoring duration is increased by z ΔJ intensive monitoring durations for extended monitoring, and if no risk factor data higher than the set basic threshold value is monitored during the extended monitoring, the intensive monitoring mode is removed;

[0078] If the risk factor data again appears higher than the set basic threshold value during the extended monitoring, it is determined that the transportation risk has a fluctuation increasing trend, and after the fluctuation increasing trend of the transportation risk appears, the strictness of monitoring the risk factors affecting the transportation risk is increased, the basic threshold value is adjusted, and the adjusted basic threshold value is calculated according to the following formula: M = (1 - c x a) M0; wherein M represents the adjusted basic threshold value, c represents the number of risk factor data with fluctuation increase, and a represents the basic threshold value adjustment coefficient set by the system; at the same time, the risk cost in the transportation cost is adjusted, and the adjusted risk cost is calculated according to the following formula: Q 2i ′ = (1 + θ) Q 2i ; wherein θ represents the risk cost adjustment coefficient set by the system, and Q 2i ′ represents the risk cost with meteorite risk fluctuation addition.

[0079] After adjusting the basic safety threshold value, intensive monitoring with a duration of ΔJ is continued, if no risk factor data higher than the basic threshold value is monitored during the intensive monitoring duration, extended monitoring is continued, and if no risk factor data higher than the basic threshold value is monitored during the extended monitoring, the intensive monitoring state is removed, and the threshold value is restored to the state before adjustment; if the risk factor is higher than the basic threshold value, a transportation risk increase warning is directly issued; if the risk factor data is monitored to be higher than the basic threshold value after adjusting the basic threshold value, a transportation risk increase warning is directly issued;

[0080] If the risk factor data affecting the transportation risk detected during the intensive monitoring duration is continuously higher than the set basic threshold value, a transportation risk increase warning is generated, and at the same time, the risk cost in the transportation cost is adjusted: Q 2i ″ = (1 + 3θ) Q 2i ; wherein Q 2i ″ represents the risk cost with transportation risk increase addition.

[0081] Embodiment 1:

[0082] In step S3-2: a transportation road is divided into m = 200 nodes; in each road section divided by nodes in a path, the parameters affecting the road transportation cost include time cost Q 1i , risk cost Q2i and energy cost Q 3i ; the time cost of the transport path is calculated according to the following formula: where Y represents the length of the road section, v0=80km / h represents the basic speed; p represents the speed reduction coefficient varying with the congestion degree of the road section; the congestion degree of the road section is divided into four levels, namely, smooth, first-level congestion, second-level congestion and third-level congestion, and the congestion degrees of the four levels are from low to high; the speed reduction coefficients are set for the four levels of congestion degrees, p1=1 is the speed reduction coefficient corresponding to smooth, p2=0.9 is the speed reduction coefficient corresponding to first-level congestion, p3=0.7 is the speed reduction coefficient corresponding to second-level congestion, and p4=0.4 is the speed reduction coefficient corresponding to third-level congestion;

[0083] The risk cost of the road section is calculated according to the following formula: where r1 represents the environmental risk coefficient; r2 represents the sensitive area risk coefficient; r3 represents the road safety risk coefficient; the environmental risk coefficient varies dynamically in real time with the changes of the environmental temperature and the wind level: where T represents the real-time monitored environmental temperature, T0=30℃ represents the set environmental temperature safety threshold; D represents the real-time monitored wind level, D0=5 levels represents the set wind level safety threshold; f1 and f2 represent the influence weights of the environmental temperature and the wind level on the environmental risk respectively, f1+f2=1, the values of f1 and f2 are adjusted according to the types of the transported dangerous chemicals, for the dangerous chemicals which are highly affected by the temperature, f1 is adjusted to be high, and for the dangerous chemicals which are highly affected by the wind, f2 is adjusted to be high; the value of r2 decreases with the increase of the distance between the transport road section and the sensitive area; the road safety risk is set for special road sections, the road safety risk coefficient is set to 2 when a construction road section is encountered, the road safety risk coefficient is set to 1.5 when a tunnel and a bridge road section are encountered, and the road safety risk coefficient is set to 1 when an ordinary road section is encountered;

[0084] The energy cost is calculated according to the following formula: where w represents the road slope influence coefficient, the value of w is less than 1 when a downhill is detected, and decreases with the increase of the slope; the value of w is 1 when a flat road is detected; the value of w is greater than 1 when an uphill is detected, and increases with the increase of the slope; G represents the actual load weight, G0=10t represents the basic load weight set by the system.

[0085] The road transport cost of a transport path is calculated according to the following formula:

[0086]

[0087] where S represents the road transport cost of a transport path; i represents the node label; m=200;

[0088] Before the transportation starts, the road transportation cost of each path in the initial candidate path set is calculated by using the road condition information and environmental information input through the API port and the road transportation cost formula, and the predicted road transportation cost of each path in the initial candidate path set is obtained; after the transportation starts, the real-time road transportation cost is calculated by using the real-time dynamic data collected in real time, so as to update the road transportation cost in real time.

[0089] In step S3-3: set a road transportation cost basic threshold S1, compare the predicted road transportation cost of each transportation path in the initial candidate path set with the basic threshold S1, extract the paths with the road transportation cost less than S1 as candidate transportation paths, compare the predicted road transportation cost of each candidate transportation path, select the path with the lowest road transportation cost as the best transportation path, design a backup path storage module, store the remaining candidate transportation paths in the backup path storage module as backup paths, and mark them as {B1, B2, …, B h}; and after the transportation starts, the road transportation cost of the backup paths in the backup path storage module is updated in real time by using the real-time dynamic data collected and the road transportation cost analysis method.

[0090] It is apparent to those skilled in the art that the present application is not limited to the details of the foregoing exemplary embodiments, and the present application can be realized in other concrete forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all respects as illustrative and not restrictive, and the scope of the present application should be defined by the appended claims rather than the above description, and it is intended to embrace all changes falling within the meaning and scope of the equivalent elements of the claims. Any reference signs in the claims should not be considered as limiting the claims involved.

Claims

1. A method for scheduling dangerous chemical logistics transportation based on multiple data sources, characterized in that: The method comprises the following steps: Step S1: Collecting static basic data and dynamic real-time data through multi-source data acquisition equipment respectively; Step S2: Cleaning and filtering the collected multi-source data, and judging and processing abnormal values; Step S3: Generating a preliminary transportation path by analyzing the collected data, selecting the best transportation path by analyzing the road transportation cost, and setting a backup path storage module and a path risk real-time monitoring mechanism to monitor the selected transportation path; Step S4: Analyzing the changes of transportation risk by using the collected dynamic real-time data, and dynamically adjusting the risk monitoring threshold according to the changes of transportation risk. 2.The method of claim 1, wherein: In step S1: Collecting static basic data and dynamic real-time data through multi-source data acquisition equipment; Static basic data is obtained through database import and manual input, and static basic data includes hazardous chemical properties and fixed road network information; Dynamic real-time data is collected in real time through API interface, sensor and vehicle terminal, and dynamic real-time data includes real-time road condition information, environmental monitoring data, vehicle real-time state and surrounding sensitive area distribution, and the collected data is stored in a distributed database. 3.The method of claim 1, wherein: In step S2: Cleaning and filtering the collected data and processing abnormal values; For continuous dynamic data, 3σ rule is used in combination with sliding window for abnormal detection, when the data value exceeds the range of [μ-3σ, μ+3σ], it is determined as an abnormal value, and the mean value of the adjacent three valid values in the window is used to replace it, wherein μ represents the mean value in the window, and σ represents the standard deviation in the window; For discrete data, whether there is an abnormal value in the collected data is judged by setting an abnormal judgment threshold, and the previous valid value is used to replace the abnormal value. 4.The method of claim 1, wherein: Step S3 comprises the following steps: S3-1, based on the coordinates of the transportation starting point and the ending point, calling the electronic map API to obtain the short distance path as the basic path, and then screening out the impassable road sections in the basic path through the road information stored in the database; After screening out the impassable road sections, an initial candidate path set is formed; S3-2, before transportation starts, the transportation cost of the paths in the initial candidate path set is calculated by using the road transportation cost formula, and after transportation starts, the road transportation cost is updated in real time according to the real-time data collected during transportation; S3-3, setting a threshold to select a candidate transportation path set meeting the requirements, and selecting the best transportation path in the candidate transportation path set according to the calculated transportation cost; At the same time, a backup path storage module is designed, the paths in the candidate transportation path set that are not selected are recorded as backup paths, and stored in the backup path storage module; S3-4, setting a road transportation cost real-time monitoring mechanism to monitor the road transportation cost of the transportation path in real time during transportation, and judging whether the transportation road needs to be adjusted according to the monitoring result, and generating an adjustment instruction when it is judged that the transportation road needs to be adjusted.

5. The method of claim 4, wherein: In step S3-2: divide a transportation road into m nodes; the parameters affecting the road transportation cost in each road section divided by nodes in a path include time cost Q 1i , risk cost Q 2i , and energy consumption cost Q 3i ; The time cost of the transportation path is calculated according to the following formula: Wherein Y represents the length of the road section, v0 represents the basic speed, and p represents the speed reduction coefficient varying with the congestion degree of the road section; the congestion degree of the road section is divided into four levels, namely, smooth, first-level congestion, second-level congestion and third-level congestion, and the congestion degrees of the four levels are from low to high; the speed reduction coefficients are set for the congestion degrees of the four levels, p1 is the speed reduction coefficient corresponding to the smooth, p2 is the speed reduction coefficient corresponding to the first-level congestion, p3 is the speed reduction coefficient corresponding to the second-level congestion, and p4 is the speed reduction coefficient corresponding to the third-level congestion. The risk cost of the road section is calculated according to the following formula: Wherein, r1 represents the environmental risk coefficient; r2 represents the sensitive area risk coefficient; r3 represents the road safety risk coefficient; wherein the environmental risk coefficient changes dynamically in real time with the change of the environmental temperature and the wind force level: Wherein T represents the real-time monitored environmental temperature, T0 represents the set environmental temperature safety threshold; D represents the real-time monitored wind force level, D0 represents the set wind force level safety threshold; f1 and f2 respectively represent the influence weight of the environmental temperature and the wind force level on the environmental risk, f1+f2=1, the values of f1 and f2 are adjusted according to the different types of dangerous chemicals transported, for the dangerous chemicals which are highly affected by the temperature, f1 is adjusted to be high, for the dangerous chemicals which are highly affected by the wind force, f2 value is adjusted to be high; the value of r2 decreases with the increase of the distance between the transportation road section and the sensitive area; the road safety risk is set for special road sections, when encountering construction road sections, the road safety risk coefficient is set to 2, when encountering tunnel and bridge road sections, the road safety risk coefficient is set to 1.5, and when encountering ordinary road sections, it is set to 1; The energy consumption cost is calculated according to the following formula: Wherein, w represents the road slope influence coefficient, the value of w is less than 1 when the downhill is detected, and decreases with the increase of the slope; the value of w is 1 when the flat road is detected; the value of w is greater than 1 when the uphill is detected, and increases with the increase of the slope; G represents the actual load weight, and G0 represents the basic load weight set by the system.

6. The method of claim 5, wherein: The road transportation cost of a transportation path is calculated according to the following formula: Wherein, S represents the road transportation cost of a transportation path; i represents the node label, i=1, 2, …, m; Before the transportation starts, the road transportation cost of each path in the initial candidate path set is calculated by using the road condition information and environmental information input through the API port and the road transportation cost formula, to obtain the predicted road transportation cost of each path in the initial candidate path set; after the transportation starts, the real-time road transportation cost is calculated by using the real-time dynamic data collected in real time, so as to update the road transportation cost in real time.

7. The method of claim 4, wherein: In step S3-3: set a road transport cost basic threshold S1, compare the predicted road transport cost of each transport path in the initial candidate path set with the basic threshold S1, extract the paths with road transport cost less than S1 as candidate transport paths, and compare the predicted road transport cost of each candidate transport path to select the path with the lowest road transport cost as the optimal transport path; design a backup path storage module, store the remaining candidate transport paths as backup paths in the backup path storage module, denoted as {B1, B2, …, B h}; and after the start of transport, the real-time dynamic data collected and the road transport cost analysis method are used to update the road transport cost of the backup paths in the backup path storage module in real time. 8.The method of claim 6, wherein: In step S3-4: a path road transportation cost real-time monitoring mechanism is set, the road transportation cost basic threshold S1 is used as a low cost basic monitoring threshold, and a high cost monitoring threshold S2 is set, the real-time change value S of the road transportation cost is monitored in real time after the transportation starts; S is compared with the set threshold polarity, and the analysis result is as follows: If S < S1, it indicates that the road transportation cost is normal, and no road adjustment instruction is generated; If S1≤S≤S2, it indicates that the road transportation cost is increasing, a first-level warning and a transportation path fine-tuning instruction c1 are issued; If S > S2, it indicates that the road transportation cost is abnormally high, a second-level warning and a transportation path adjustment instruction c2 are issued; After receiving the first-level warning and the instruction c1, the parameters affecting the road transportation path in the current transportation path are analyzed, the abnormal parameters and the road sections where the abnormal parameters appear are analyzed, and the road sections where the abnormal parameters appear are replaced by using the alternative paths in the road network information; After receiving the second-level warning and the instruction c2, the parameters affecting the road transportation path in the current transportation path are analyzed, and the standby paths in the standby path storage module are extracted, the road transportation cost of the standby paths is updated and evaluated, and the path with the lowest road transportation cost in the standby paths is selected to replace the current path. 9.The method of claim 1, wherein: In step S4: the dangerous chemicals are divided into three categories of explosive, toxic gas and corrosive substance according to the collected dangerous chemical attributes; when the transportation risk is analyzed, only the three categories of dangerous chemicals are analyzed respectively, and the analysis result is as follows: For the explosive, the risk factors affecting the transportation risk of the explosive include vibration frequency, environmental temperature and electrostatic voltage; For the toxic gas, the risk factors affecting the transportation risk of the toxic gas include leakage concentration, wind diffusion speed and distance between the transportation section and the sensitive area; For the corrosive substance, the risk factors affecting the transportation risk of the corrosive substance include tank corrosion rate, environmental humidity and road bumping degree; The basic safety threshold M0 is set for each category of dangerous chemicals according to the risk factors of each category of dangerous chemicals, and the risk factor data is collected every interval Δt for comparison and analysis with the set basic safety threshold, if the real-time collected risk factor data is lower than the set basic safety threshold, it indicates that the transportation risk is low; if one risk factor in the real-time collected risk factor data is higher than the set basic threshold, it is predicted that the transportation risk will increase, and the intensive monitoring mode is started.

10. The method of claim 9, wherein: After the intensive monitoring mode is started, the intensive monitoring time ΔJ is set, and the interval time for collecting the monitoring data is shortened to Δt / 2 in the intensive monitoring mode; If the risk factor data that originally exceeds the basic threshold value is restored to below the basic threshold value during the intensive monitoring duration, after the first intensive monitoring duration ends, the intensive monitoring duration is increased by z ΔJ intensive monitoring durations for extended monitoring. If no risk factor data higher than the set basic prediction is monitored during the extended monitoring, the intensive monitoring mode is removed. If the risk factor data again appears higher than the set basic threshold value during the extended monitoring, it is determined that the transportation risk has a fluctuating upward trend. After the fluctuation increase trend of the transport risk appears, the strictness of monitoring the risk factors affecting the transport risk is increased, the basic threshold set is adjusted, and the adjusted basic threshold is calculated according to the following formula: M = (1 - c x a)M0; wherein M represents the adjusted basic threshold, c represents the number of risk factor data with fluctuation increase, and a represents the basic threshold adjustment coefficient set by the system; meanwhile, the risk cost in the transport cost is adjusted, and the adjusted risk cost is calculated according to the following formula: Q 2i ′ = (1 + theta)Q 2i ; wherein theta represents the risk cost adjustment coefficient set by the system, and Q 2i ′ represents the risk cost with meteorite risk fluctuation addition. After adjusting the basic safety threshold, intensive monitoring with a duration of ΔJ is continued. If no risk factor data higher than the basic threshold value is monitored during the intensive monitoring duration, extended monitoring is continued. If no risk factor data higher than the basic threshold value is monitored during the extended monitoring, the intensive monitoring state is removed, and the threshold value is restored to the state before adjustment. If the risk factor is higher than the basic prediction, a transportation risk increase warning is directly issued. If the risk factor data appears higher than the basic threshold value after adjusting the basic threshold, a transportation risk increase warning is directly issued. If the risk factor data affecting the transportation risk detected in the strengthened monitoring duration continues to be higher than the set basic threshold value, a transportation risk increase warning is generated; at the same time of issuing the transportation risk increase warning, the risk cost in the transportation cost is adjusted: Q 2i "=(1+3θ)Q 2i ; wherein, Q 2i " represents the risk cost with the transportation risk increase addition.

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