Cigarette distribution traffic safety digital management platform

Abstract

The invention provides a cigarette distribution traffic safety digital management platform. The platform comprises a personnel portrait management module, a vehicle portrait management module, a line portrait management module and a retail customer portrait management module. Traffic safety digital display is carried out by acquiring data of a personnel portrait management module, a vehicle portrait management module, a line portrait management module and a retail customer portrait management module; personnel, vehicles, routes and retail clients are managed, management and control of the routes, personnel, vehicles and distribution links are achieved, and therefore the safety of cigarette distribution traffic is improved.

Description

Technical Field

[0001] The invention relates to the technical field of cigarette distribution, in particular to a digital management platform for cigarette distribution traffic safety. Background Art

[0002] This year, the logistics industry at home and abroad has gradually transformed digitally, making a new generation of "revolution" in the logistics supply chain. At the same time, the logistics industry is also an important part of my country's tertiary industry. The high-quality development of the national economy and the new thinking of the digital economy are driving the rapid transformation of the logistics industry. Improving the digital capabilities of logistics companies has become a necessary path for digital transformation.

[0003] Cigarette logistics delivery vehicles are the carriers of cigarette distribution business. They have a wide daily driving range, long routes, heavy loads, and terrain factors such as remote mountainous areas and depressions. They face great safety risks and are difficult to manage. The existing transportation problems are as follows:

[0004] (1) There are blind spots in the supervision of drivers’ daily driving behavior, making management difficult.

[0005] After the existing ADAS driving assistance system was officially put into use, statistics from that month found that drivers had committed thousands of violations, including smoking, making phone calls, distracted driving, and fatigued driving. Therefore, there are major problems in drivers' daily driving.

[0006] (2) The basic vehicle inventory has not been computerized and management is not sophisticated enough.

[0007] The existing Putian Logistics Vehicle Management Account has established a complete set of "Vehicle Use and Maintenance Management Regulations". Relevant systems have been formed for vehicle maintenance standards, maintenance requirements, assessment management, etc., and standardized maintenance accounts and approval processes have also been established. However, the relevant accounts are currently only in the paper version collection stage, and the basic vehicle accounts have not been informatized. The daily management of vehicles is not detailed enough, and it is difficult to accurately control the vehicle condition.

[0008] (3) The road environment failed to be displayed in a layered and classified manner, and the early warning failed to achieve dynamic control.

[0009] Delivery vehicles cover a wide distribution area. Especially when delivery personnel rotate delivery routes, they are unfamiliar with the new delivery routes, and the personalized areas between roads and routes are not known in advance. Prior warnings are not given on accident-prone sections, flood-prone areas, holiday effects and other sections. During driving, drivers fail to have a good understanding of road conditions such as traffic volume, road damage, and real-time changes in environmental conditions on the delivery routes. There is no layered and classified display of the road environment, and the early warning function fails to achieve dynamic control.

[0010] (IV) Customer classification is not accurate enough and there are certain blind spots in delivery regulations.

[0011] At present, the regulatory supervision in the field of logistics and distribution mainly adopts methods such as investigating vehicle driving tracks, secretly tracking delivery vehicles, randomly stopping vehicles for inspection, and questioning retail customers. The focus is on checking whether the cigarettes are delivered to the business address on the license, whether the actual number of cigarette specifications delivered is consistent with the delivery and receipt photos, and whether there are behaviors such as centralized delivery to large households, interception of scarce cigarettes, or illegal purchase of cigarettes. The content displayed on the photo receipt page is relatively simple, especially when contactless delivery is adopted under the normalization of the epidemic. The background recognition of some retail customers' stores is not high, and the store characteristics cannot be specifically reflected in the cigarette receipt photos. When the monopoly internal management department conducts special inspections on delivery specifications, it usually questions the delivery specifications on the grounds that the receipt photos are not taken in a standardized manner and the store characteristics are not obvious. Summary of the invention

[0012] In order to overcome the above problems, the purpose of the present invention is to provide a digital management platform for cigarette delivery traffic safety, which can improve the safety of cigarette delivery traffic through a digital-led intelligent delivery model.

[0013] The present invention is implemented by the following scheme: a digital management platform for cigarette distribution traffic safety, the platform comprising a personnel portrait management module, a vehicle portrait management module, a route portrait management module, and a retail customer portrait management module;

[0014] The personnel portrait management module installs an ADAS driving assistance system on the delivery vehicle to conduct full-process portrait supervision of the driver's driving behavior;

[0015] The vehicle image management module performs full-process image supervision on vehicle departure safety inspection, vehicle on-the-way operation status, and vehicle in-stock management;

[0016] The route profile management module uses the vehicle GPS and ADAS driving assistance system to collect the traffic flow, road damage, and real-time environmental condition change information of the delivery route;

[0017] The retail customer portrait management module performs classification operations on retail customers. The customer portrait information includes basic customer information, customer tags, and historical delivery information;

[0018] Traffic safety is digitally displayed by acquiring data from the personnel portrait management module, vehicle portrait management module, route portrait management module, and retail customer portrait management module; personnel, vehicles, routes, and retail customers are managed to achieve control over routes, personnel, vehicles, and distribution, thereby improving the safety of cigarette distribution traffic.

[0019] Furthermore, the personnel portrait management module records the driver's bad driving habits or unsafe driving behaviors such as smoking, making or receiving phone calls, distracted driving, and fatigued driving, and formulates detailed rules for evaluating the driver's driving performance by digitally displaying the recorded data; combined with the driver's daily performance in vehicle maintenance, vehicle safety inspection, and safety education and training, the driver's safety risk awareness is portrayed from five dimensions: safety awareness, safe driving, safety inspection, safety training, and vehicle maintenance, and the drivers are then grouped and analyzed to ultimately form a driver portrait.

[0020] Furthermore, the vehicle portrait management module realizes the informatization of vehicle ledger management by entering and updating basic data such as vehicle mileage, maintenance costs, fuel consumption per 100 kilometers, repairs and maintenance, and vehicle accidents; analyzes the safety risk points of vehicles in the full life cycle management, and conducts a comprehensive analysis of vehicle maintenance conditions. Through analysis and classification, it can be viewed that vehicle parts that are replaced more frequently.

[0021] Furthermore, the route portrait management module adopts "four levels and four dimensions" to form a vehicle thermal display map and cover the city's delivery routes. The first level is red, and the reference dimension is: the route where the vehicle has had a traffic accident; the second level is orange, and the reference dimension is: the vehicle route is a prone to accident route; the third level is yellow, and the reference dimension is: the vehicle route is a prone to congestion and complex traffic conditions; the fourth level is blue, and the vehicle route is a low-lying, flood-prone, and holiday effect route; big data is used to analyze the route conditions, mark accident-prone points, road design defects, and safety risk points of routes in periodic dense areas, and achieve accurate portraits of the city's delivery routes.

[0022] Furthermore, the retail customer portrait management module realizes the labeling of user information, which is convenient for logistics companies to pay attention to special customers such as poor households and lonely elderly people, and realize the precise delivery model. The management methods of the retail customer portrait management module include: Method 1, home delivery and abnormal store operation marking: home delivery without opening the door to pick up the goods by phone, other people picking up the goods at the door, and the store operation scale not matching the actual sales volume;

[0023] Method 2: Labeling for customers in special geographical locations: Retail customers who cannot have their homes delivered are labeled during the delivery process, and the information is summarized and fed back to the Monopoly Department for filing;

[0024] Method 3: Labeling of store business formats: Based on the classification of business formats in the monopoly department, re-classify the store business formats, with a focus on non-main grocery stores, which include massage shops, mobile phone shops, car wash shops, restaurants, tea shops, and chess and card rooms;

[0025] Method 4: Service labeling, which labels the information of poor households and lonely elderly people.

[0026] The beneficial effects of the present invention are as follows: the present invention focuses on the three major subjects in traffic safety - "people, vehicles, and roads", and develops a digital management platform for cigarette distribution traffic safety. It uses the system as a "pen" and data as a "painting" to make a "precise portrait" of "people, vehicles, and roads", and then uses it to manage risks, treat hidden dangers, and reduce dangers, so as to achieve forward movement of checkpoints, source control, and in-depth prevention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a system principle block diagram of the present invention.

[0028] Figure 2 It is a three-color image of the driver portrait in the embodiment of the present invention.

[0029] Figure 3 is a four-dimensional scoring diagram of the driver's driving behavior in an embodiment of the present invention

[0030] Figure 4 It is a schematic diagram of accurate vehicle portrait in an embodiment of the present invention.

[0031] Figure 5 It is a heat map of accident-frequently occurring locations in an embodiment of the present invention.

[0032] Figure 6 It is a schematic diagram of the retail customer portrait structure in an embodiment of the present invention.

[0033] Figure 7 Schematic diagram of the ant colony algorithm in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described below in conjunction with the accompanying drawings.

[0035] See also Figure 1 As shown, the present invention provides a digital management platform for cigarette distribution traffic safety, the platform includes a personnel portrait management module, a vehicle portrait management module, a route portrait management module, and a retail customer portrait management module;

[0036] The personnel portrait management module installs an ADAS driving assistance system on the delivery vehicle to conduct full-process portrait supervision of the driver's driving behavior;

[0037] The vehicle image management module performs full-process image supervision on vehicle departure safety inspection, vehicle on-the-way operation status, and vehicle in-stock management;

[0038] The route profile management module uses the vehicle GPS and ADAS driving assistance system to collect the traffic flow, road damage, and real-time environmental condition change information of the delivery route;

[0039] The retail customer portrait management module performs classification operations on retail customers. The customer portrait information includes basic customer information, customer tags, and historical delivery information;

[0040] Traffic safety is digitally displayed by acquiring data from the personnel portrait management module, vehicle portrait management module, route portrait management module, and retail customer portrait management module; personnel, vehicles, routes, and retail customers are managed to achieve control over routes, personnel, vehicles, and distribution, thereby improving the safety of cigarette distribution traffic.

[0041] The personnel portrait management module records the driver's bad driving habits or unsafe driving behaviors such as smoking, making or receiving phone calls, distracted driving, and fatigued driving, and formulates detailed rules for driver performance evaluation by digitally displaying the recorded data; combined with the driver's daily performance in vehicle maintenance, vehicle safety inspection, and safety education and training, the driver's safety risk awareness is portrayed from five dimensions: safety awareness, safe driving, safety inspection, safety training, and vehicle maintenance, and the drivers are then grouped and analyzed to ultimately form a driver portrait.

[0042] The vehicle portrait management module realizes the informatization of vehicle ledger management by entering and updating basic data such as vehicle mileage, maintenance costs, fuel consumption per 100 kilometers, repairs and maintenance, and vehicle accidents; analyzes the safety risk points in the vehicle's full life cycle management, and conducts a comprehensive analysis of the vehicle's maintenance status. Through analysis and classification, it can view vehicle parts that are replaced more frequently.

[0043] The route portrait management module adopts "four levels and four dimensions" to form a vehicle thermal display map and cover the city's delivery routes. The first level is red, and the reference dimension is: the route where the vehicle has had a traffic accident; the second level is orange, and the reference dimension is: the vehicle's route is prone to accidents; the third level is yellow, and the reference dimension is: the vehicle's route is prone to congestion and has complex traffic conditions; the fourth level is blue, and the vehicle's route is low-lying and prone to flooding, and has holiday effects; use big data to analyze route conditions, mark accident-prone points, road design defects, and safety risk points in periodic dense areas, and achieve accurate portraits of the city's delivery routes.

[0044] The retail customer portrait management module realizes the labeling of user information, which is convenient for logistics companies to pay attention to special customers such as poor households and lonely elderly people, and realize the precise delivery model. The management methods of the retail customer portrait management module include: Method 1, home delivery and abnormal store operation marking: home delivery without opening the door to pick up the goods by phone, other people picking up the goods at the door, and the store operation scale not matching the actual sales volume;

[0045] Method 2: Labeling for customers in special geographical locations: Retail customers who cannot have their homes delivered are labeled during the delivery process, and the information is summarized and fed back to the Monopoly Department for filing;

[0046] Method 3: Labeling of store business formats: Based on the classification of business formats in the monopoly department, re-classify the store business formats, with a focus on non-main grocery stores, which include massage shops, mobile phone shops, car wash shops, restaurants, tea shops, and chess and card rooms;

[0047] Method 4: Service labeling, which labels the information of poor households and lonely elderly people.

[0048] The present invention will be further described below in conjunction with a specific embodiment:

[0049] A digital management platform for cigarette distribution traffic safety, the platform comprising a personnel portrait management module, a vehicle portrait management module, a route portrait management module, and a retail customer portrait management module;

[0050] 1.1 Personnel portrait management module

[0051] Integrate relevant business systems, platforms, and terminals, eliminate data barriers, achieve the goal of unified data collection, create a "multi-platform one application" supervision model, and simplify terminal system management and use by integrating the Changce Intelligent Delivery Assistant APP, and initially realize data interoperability and information sharing. Drivers are managed using the "three-color map" classification, and information technology is used to collect drivers' driving violations. The detailed rules for drivers' driving performance evaluation are re-formulated. Combined with the drivers' daily performance in vehicle maintenance, vehicle safety inspections, safety education and training, the five dimensions of safety awareness, safe driving, safety inspections, safety training, and vehicle maintenance, and 29 detailed indicators are used to characterize the drivers' safety risk awareness based on their recent behavior performance, and then the drivers are grouped and analyzed to form a driver portrait. Points below or equal to 80 are red, 80-95 points are blue, and 95 points and above are green. Accurate personnel management is achieved through the "three-color map" (see Figure 2 As shown in the figure, targeted education will be provided to drivers with lower scores. Finally, through data aggregation, the system will directly apply the results and eventually form a performance evaluation system.

[0052] At the same time, the data is connected to the vehicle ADAS driving assistance system to obtain real-time driver-related data information in the system, focusing on four indicators: fatigue driving, smoking, making phone calls, and speeding. Figure 3 As shown in the figure, drivers are comprehensively scored and a “three-color chart” is formed for classification management. The data can be summarized and analyzed to highlight the driver’s personalized indicator issues.

[0053] 1.2 Vehicle Image Management Module

[0054] By collecting vehicle maintenance amounts, maintenance parts details and other indicators, setting vehicle-related benchmarking indicators such as repair costs per 100 kilometers, fuel consumption per 100 kilometers, etc., setting indicator achievement lines, drivers are encouraged to actively participate, find gaps and make up for shortcomings, and vehicle management personnel include vehicles with abnormal vehicle indicators as key supervision targets. Vehicle management personnel regularly review system data, use a combination of qualitative and quantitative analysis methods to conduct a comprehensive analysis of vehicle conditions, and propose the accuracy, completeness and richness of "one vehicle, one file" information to achieve an accurate portrait of each vehicle.

[0055] Combined with the precise image of the vehicle (see Figure 4 As shown in the figure, analyze the safety risk points in the whole life cycle management of the vehicle and take corresponding preventive measures. At the same time, the terminal system is used to conduct a comprehensive analysis of the vehicle maintenance situation, and deeply mine the vehicle maintenance-related data. Through analysis and classification, it is possible to view the vehicle parts that are frequently replaced, and the amount of the same type of parts can be calculated through the system to achieve zero error in the settlement of vehicle parts. Using data portraits, it is also possible to calculate the common and individual problems in vehicle maintenance, and provide data support for vehicle replacement procurement and improving the driving habits of drivers.

[0056] 1.3 Line Profile Management Module

[0057] Relying on the Changce intelligent distribution system, we explore the level of comprehensive route portraits and strive to create a "four-level four-dimensional" route portrait intelligent management model, using "four-level four-dimensional" to form a vehicle thermal display map (such as Figure 5 The first level is red, with the reference dimension being: the road section (route) where the vehicle has had a traffic accident (incident); the second level is orange, with the reference dimension being: the road section (route) where the vehicle passes is prone to accidents; the third level is yellow, with the reference dimension being: the road section (route) where the vehicle passes is prone to congestion and has complex traffic conditions; the fourth level is blue, with the road section (route) where the vehicle passes is low-lying, prone to flooding, or has holiday effects. By adopting the "four-level, four-dimensional" vehicle portrait intelligent management model, vehicle management is becoming more refined, portrait content is becoming more data-based, and system terminals are becoming more intelligent, and ultimately a complete line road warning function is formed to prevent road accidents and improve the driving safety of delivery vehicles.

[0058] 1.4 Retail Customer Profile Management Module

[0059] The concept of customer portrait was first proposed by Alan Cooper, the "Father of VB" and "Father of Interaction Design": "Personasare a concrete representation of target users." He believes that "customer portrait is a virtual representation of real customers and a target user model based on a series of real data." Through the understanding of various aspects of customer information, a variety of information is combined to form a unique characteristic and temperament of a certain type, thus forming a unique "portrait" of the user. In a word, customer portrait is the labeling of user information.

[0060] See also Figure 6 As shown, the present invention incorporates the "customer classification" section, which contains basic customer information, customer tags (customer type, geographic location, business conditions, business classification), historical delivery conditions and other related information. Accurate portraits of retail customers facilitate the focus on special customers such as poor households and lonely elderly people, achieve accurate services, and improve customer satisfaction. At the same time, it provides relevant information on market maintenance to the monopoly department, facilitates its market supervision, assists the marketing department to better understand the customer's business capabilities, and improves the accuracy of cigarette brand marketing and non-tobacco sales.

[0061] 2. “Line Reorganization” Promotes Digitalization of Dynamic Services

[0062] 2.1 Line Optimization Digitalization

[0063] Based on the original hybrid simulated annealing algorithm, this optimization focuses on the clustering of routes, diluting the customer department balance to the county and district regional balance, and recalculating the transportation capacity. Under high saturation conditions, only 26 routes are needed to complete the delivery operation under the new mode. Group operation means that all delivery routes are divided into various areas, and each area is covered by delivery vehicles every day. The area is divided into 5 small areas according to working days, and group delivery is carried out in the corresponding small areas. There is no delivery vehicle coverage in other small areas. For those that exceed the full load of a single vehicle, a secondary delivery will be arranged after adjustment within the group. Group operation in the same delivery area ensures that the first delivery is basically fully loaded, and the second delivery is arranged according to the remaining delivery volume to ensure the vehicle loading rate.

[0064] That is, the present invention combines the original hybrid simulated annealing algorithm with the ant colony algorithm (see Figure 7As shown in the figure, the original delivery routes are re-arranged. The essential characteristics of the Ant Colony Optimization can be summarized as follows: a. Path probability selection mechanism - the higher the pheromone concentration, the greater the probability of the path being selected; b. Pheromone update mechanism - the shorter the path, the faster the pheromone concentration on the path increases; c. Collaborative work mechanism - ant individuals (delivery trucks) communicate information through pheromones. These characteristics are exactly consistent with the characteristics of the meta-heuristic algorithm. In the Ant Colony Optimization Algorithm, the foraging ants are replaced by artificial ants, and the pheromones released by the ants are replaced by artificial pheromones. The crawling of ants and the evaporation of pheromones are no longer continuous, but are carried out in discrete time and space.

[0065] The ant colony algorithm further includes: Step 1: variable initialization:

[0066] n=size(D,1); for i=1:nD(i,i)=eps; end

[0067] Eta = 1. / D; %Eta is the heuristic factor, which is set as the reciprocal of the distance here.

[0068] Tau=ones(n,n); %Tau is the pheromone matrix

[0069] Tabu=zeros(m,n); %Store and record the generation of the path

[0070] NC=1; % Iteration counter

[0071] R_best=zeros(NC_max,n); % Best route for each generation

[0072] L_best=inf.*ones(NC_max,1); %The length of the best route in each generation

[0073] L_ave=zeros(NC_max,1);% Average length of each generation route

[0074] while NC<=NC_max% One of the stop conditions: reaching the maximum number of iterations

[0075] Step 2: Place m delivery trucks (m ants) in n cities for delivery;

[0076] Randpos=[]; for i=1:(ceil(m / n))Randpos=[Randpos, randperm(n)];

[0077] end;Tabu(:,1)=(Randpos(1,1:m))';

[0078] Step 3: m delivery trucks select the next city according to the probability function and complete their respective tours

[0079] for j=2:n, for i=1:m, visited=Tabu(i,1:(j-1));% cities visited=zeros(1,(n-j+1));% cities to be visited

[0080] P=J;%Probability distribution of the cities to be visited

[0081] Jc=1; for k=1:n, if length(find(visited==k))==0

[0082] J(Jc)=k; Jc=Jc+1; end

[0083] Next, we calculate the probability distribution of the selected cities.

[0084] for k=1:length(J)

[0085] P(k)=(Tau(visited(end),J(k))^Alpha)*(Eta(visited(end),J(k))^Beta); %(pheromone^pheromone coefficient)*(inspiration factor^inspiration factor coefficient)endP=P / (sum(P));

[0086] % Select the next city according to the probability principle Pcum=cumsum(P);

[0087] Select=find(Pcum>=rand); to_visit=J(Select(1));

[0088] Tabu(i,j)=to_visit;end

[0089] end if NC>=2

[0090] Tabu(1,:)=R_best(NC-1,:); end

[0091] Step 4: Record the best route for this iteration;

[0092] L=zeros(m,1); for i=1:m R=Tabu(i,:);

[0093] for j=1:(n-1)L(i)=L(i)+D(R(j),R(j+1));end

[0094] L(i)=L(i)+D(R(1),R(n));end

[0095] L_best(NC)=min(L); pos=find(L==L_best(NC));

[0096] R_best(NC,:)=Tabu(pos(1),:); L_ave(NC)=mean(L);

[0097] NC=NC+1

[0098] Step 5: Update pheromones;

[0099] Delta_Tau=zeros(n,n); for i=1:m, for j=1:(n-1)

[0100] Delta_Tau(Tabu(i,j),Tabu(i,j+1))=Delta_Tau(Tabu(i,j),Tabu(i,j+1))+Q / L(i)e nd

[0101] Delta_Tau(Tabu(i,n),Tabu(i,1))=Delta_Tau(Tabu(i,n),Tabu(i,1))+Q / L(i);end

[0102] Tau=(1-Rho).*Tau+Delta_Tau;

[0103] Step 6: Clear the taboo table;

[0104] Tabu=zeros(m,n);end

[0105] Step 7: Output the results;

[0106] Pos=find(L_best==min(L_best));Shortest_Route=R_best(Pos(1),:)Shortest_Len gth=L_best(Pos(1))

[0107] Through the system's comprehensive analysis of data such as the number of individual orders and customer locations, some peripheral C lines with excess capacity will be cut, and some medium-distance B lines with insufficient capacity will be expanded.

[0108] 2.2 Switch to digitalization during off-season and peak-season

[0109] In early January 2022, cigarette sales surged, and the digital and intelligent "double random" collaborative delivery model was actively applied. The "double random" collaborative delivery model effectively solved the problem of sorting delays caused by the surge in sales. The delivery department adopted the strategy of "vehicle axle rotation, watching people instead of cars" according to the sorting progress, that is, the personnel and vehicles are not fixed, and they are loaded as soon as they arrive. Each vehicle only needs to retain one delivery person who is familiar with the route, and a new delivery combination is formed in real time according to the current standby personnel. Based on the integrated platform and GPS positioning system, the department's internal staff can make a rough prediction of the return time according to the delivery progress and road conditions of the delivery vehicle, and can make real-time plans for the return vehicles and personnel, and dispatch delivery personnel in agile and efficient manner to ensure the smooth operation of the overall delivery link. The new model can not only maintain the familiarity of each vehicle with the route and ensure the delivery efficiency, but also speed up the operation of the delivery vehicles and ensure the maximum utilization of vehicles and personnel.

[0110] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. Cigarette delivery traffic safety digital management platform, characterized by: The platform includes a personnel portrait management module, a vehicle portrait management module, a route portrait management module, and a retail customer portrait management module; The personnel portrait management module installs an ADAS driving assistance system on the delivery vehicle to conduct full-process portrait supervision of the driver's driving behavior; The vehicle image management module performs full-process image supervision on vehicle departure safety inspection, vehicle on-the-way operation status, and vehicle in-stock management; The route profile management module uses the vehicle GPS and ADAS driving assistance system to collect the traffic flow, road damage, and real-time environmental condition change information of the delivery route; The retail customer portrait management module performs classification operations on retail customers. The customer portrait information includes basic customer information, customer tags, and historical delivery information; Traffic safety is digitally displayed by acquiring data from the personnel portrait management module, vehicle portrait management module, route portrait management module, and retail customer portrait management module; personnel, vehicles, routes, and retail customers are managed to achieve control over routes, personnel, vehicles, and distribution, thereby improving the safety of cigarette distribution traffic.

2. The cigarette distribution traffic safety digital management platform according to claim 1 is characterized by: The personnel portrait management module records the driver's bad driving habits or unsafe driving behaviors such as smoking, making or receiving phone calls, distracted driving, and fatigued driving, and formulates detailed rules for driver performance evaluation by digitally displaying the recorded data; combined with the driver's daily performance in vehicle maintenance, vehicle safety inspection, and safety education and training, the driver's safety risk awareness is portrayed from five dimensions: safety awareness, safe driving, safety inspection, safety training, and vehicle maintenance, and the drivers are then grouped and analyzed to ultimately form a driver portrait.

3. The cigarette distribution traffic safety digital management platform according to claim 1 is characterized by: The vehicle portrait management module realizes the informatization of vehicle ledger management by entering and updating basic data such as vehicle mileage, maintenance costs, fuel consumption per 100 kilometers, repairs and maintenance, and vehicle accidents; analyzes the safety risk points in the vehicle's full life cycle management, and conducts a comprehensive analysis of the vehicle's maintenance status. Through analysis and classification, it can view vehicle parts that are replaced more frequently.

4. The cigarette distribution traffic safety digital management platform according to claim 1 is characterized by: The route portrait management module adopts "four levels and four dimensions" to form a vehicle thermal display map and cover the city's delivery routes. The first level is red, and the reference dimension is: the route where the vehicle has had a traffic accident. The second level is orange, and the reference dimension is: the vehicle route is a route prone to accidents. The third level is yellow, and the reference dimension is: the vehicle route is a route prone to congestion and complex traffic conditions. The fourth level is blue, and the vehicle route is a low-lying, flood-prone, holiday effect route; Use big data to analyze route conditions, mark accident-prone areas, road design defects, and safety risk points in periodically densely populated areas, and achieve an accurate portrait of the city's delivery routes.

5. The cigarette distribution traffic safety digital management platform according to claim 4 is characterized by: The retail customer portrait management module realizes the labeling of user information, which is convenient for logistics companies to pay attention to special customers such as poor households and lonely elderly people, and realize the precise delivery model. The management methods of the retail customer portrait management module include: Method 1, home delivery and abnormal store operation marking: home delivery without opening the door to pick up the goods by phone, other people picking up the goods at the door, and the store operation scale not matching the actual sales volume; Method 2: Labeling for customers in special geographical locations: Retail customers who cannot have their homes delivered are labeled during the delivery process, and the information is summarized and fed back to the Monopoly Department for filing; Method 3: Labeling of store business formats: Based on the classification of business formats in the monopoly department, re-classify the store business formats, with a focus on non-main grocery stores, which include massage shops, mobile phone shops, car wash shops, restaurants, tea shops, and chess and card rooms; Method 4: Service labeling, which labels the information of poor households and lonely elderly people.

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