CN-122022630-A - Fatigue reminding and road condition analysis method and system in logistics transportation

CN122022630ACN 122022630 ACN122022630 ACN 122022630ACN-122022630-A

Abstract

The invention provides a fatigue reminding and road condition analysis method and system in logistics transportation, which relate to the technical field of logistics transportation, and the method comprises the steps of obtaining various data; the method comprises the steps of preparing benefit indexes, preparing a transportation path according to historical traffic data, dividing the transportation path into a plurality of road sections according to road traffic data, calculating risk grades of each road section according to a Dirichlet process mixed model, obtaining heart consumption data of a driver according to road sections with different risk grades, analyzing fatigue degree of the driver according to characteristic behavior data to obtain real-time fatigue data, and preparing a rest reminding strategy according to the real-time fatigue data and the transportation path. According to the invention, the rest reminding strategy is formulated according to the real-time fatigue degree of the driver and in combination with the transportation path, so that the accuracy and reliability of fatigue monitoring of the driver are improved, the fatigue state of the driver can be found in time, corresponding measures are taken, traffic accidents caused by fatigue driving are reduced, and road traffic safety is ensured.

Inventors

WANG SENHUA
XIAO SHAN
BAI LIJUN
LI HUINIAN

Assignees

智运通(北京)科技有限责任公司

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. The method for reminding fatigue and analyzing road conditions in logistics transportation is characterized by comprising the following steps: acquiring historical traffic data and personal sign data of a driver, and acquiring road traffic data and characteristic behavior data of the driver in real time; Setting benefit indexes for transported objects, setting transport paths according to the historical traffic data, dividing the transport paths into a plurality of road sections according to the road traffic data, and calculating the risk grade of each road section according to a dirichlet process mixed model; acquiring heart consumption data of a driver according to road sections with different risk grades, and analyzing the fatigue degree of the driver by combining the characteristic behavior data to obtain real-time fatigue data; and according to the real-time fatigue data and in combination with the transportation path, setting a rest reminding strategy.
2. The method for reminding fatigue and analyzing road conditions in logistics transportation according to claim 1, wherein the step of collecting the characteristic behavior data of the driver in real time comprises the steps of: Monitoring the facial expression, blink and eyeball movement of a driver to obtain facial features, and monitoring the heart rate and brain waves to obtain physiological features; Analyzing steering wheel rotation angle, throttle and brake pedal travel and lane offset according to driving habit of a driver to obtain driving behavior data; Establishing a unified space-time reference through hardware clock synchronization and space coordinate mapping, and carrying out normalization processing on the facial features, the physiological features and the driving behavior data to obtain a parallel feature set; extracting key influence features related to fatigue degree from the parallel feature set, and calculating Kendell rank correlation coefficients among the key influence features to obtain a correlation value And selecting key influence characteristics corresponding to the relevance value larger than a preset threshold value as characteristic behaviors, and integrating all the characteristic behaviors to obtain the characteristic behavior data.
3. The method for reminding fatigue and analyzing road conditions in logistics transportation according to claim 1, wherein the step of formulating the benefit index comprises: Calculating the transportation cost rate according to the transportation total cost and the cargo value aiming at different transported cargoes, and obtaining cost indexes by combining unit mileage cost; calculating the order number delivered on time and the total order number according to different transported goods to obtain on-time delivery rate, and combining average transportation timeliness to obtain timeliness indexes; calculating the damage rate of the goods according to the number of the broken goods and the total number of the transported goods aiming at different transported goods, and obtaining a safe and environment-friendly index by considering the carbon emission intensity; And setting weights for the cost index, the time-effect index and the safety environment-friendly index according to the characteristics of transported goods, and calculating comprehensive benefits to obtain the benefit index.
4. The method for reminding fatigue and analyzing road conditions in logistics transportation according to claim 1, wherein the step of making the transportation path comprises: Extracting historical congestion records, average speed and road section traffic rate caused by different weather from the historical traffic data as route influencing factors; Acquiring longitude and latitude coordinates of a departure point and a destination point, generating a plurality of conventional routes, and expanding the conventional routes by combining the route influencing factors to obtain a plurality of candidate routes; and calculating the benefit index of each candidate route to obtain a corresponding benefit score, and selecting the candidate route with the highest benefit score as the transportation route.
5. The method for reminding fatigue and analyzing road conditions in logistics transportation according to claim 1, wherein the step of dividing the transportation path into a plurality of road segments comprises: Extracting basic geographic data and dynamic traffic data from the road traffic data, removing abnormal coordinate points, and supplementing the missing track through linear interpolation; determining geographic features according to road grades and physical attributes, determining traffic flow features according to congestion mode differences and vehicle speed fluctuation thresholds, and determining management demand features according to administrative areas and service area intervals; Dividing the transportation path from the geographic features, the traffic flow features and the management demand features to obtain a plurality of primary road sections; sampling route track points of each primary branching section, extracting characteristics of each route track point, defining the radius of the field and the minimum point number, dividing each route track point into a plurality of continuous areas, and each area corresponds to one primary branching section; And merging the primary branching sections corresponding to the continuous areas meeting the preset conditions, and forming a plurality of road sections with other primary branching sections.
6. The method for reminding fatigue and analyzing road conditions in logistics transportation according to claim 1, wherein the step of calculating the risk level of each road segment comprises: Obtaining observation data and covariate data of each road section according to the historical traffic data; performing extremely poor normalization on the observed data and the covariate data, constructing a similarity matrix, and calculating risk similarity between road sections; The approximate posterior distribution is minimized through KL divergence, and the posterior probability of different risks is calculated for each road section by combining the risk similarity; And carrying out risk classification on each road section according to different posterior probabilities.
7. The method for fatigue warning and traffic analysis in physical transportation according to claim 1, wherein the step of acquiring the heart consumption data of the driver comprises: Acquiring physiological characteristic data of drivers on road sections with different risk levels, acquiring triggering events when the vehicle carries out road sections with different risk levels, and sampling the triggering events by taking preset time as a window to obtain a plurality of window data; setting corresponding sampling frequencies according to different risk levels, and extracting each window data to obtain road section driving data; carrying out standardized processing on the road section driving data and the physiological characteristic data in a one-to-one correspondence manner, constructing a judgment matrix, and calculating the importance of different physiological characteristics on heart consumption to obtain heart consumption indexes; And carrying out association analysis on the heart consumption index and the risk level, and taking the psychological influence of different events into consideration to obtain the heart consumption data.
8. The method for reminding fatigue and analyzing road conditions in logistics transportation according to claim 1, wherein the step of analyzing the real-time fatigue data comprises the steps of: synchronizing the heart consumption data and the characteristic behavior data according to time stamps, removing noise and interference components in the heart consumption data, extracting heart key characteristics from the heart consumption data, and determining a fatigue state label; Extracting time domain features from the heart key features; Inputting the time domain features and the fatigue state labels into a random forest model for training, and adjusting weights of different features to obtain a fatigue evaluation model; inputting the heart key features and the key influence features into the fatigue evaluation model, outputting to obtain a current fatigue degree evaluation result, and analyzing the fatigue state change trend of the driver to obtain the real-time fatigue data.
9. The method for fatigue reminding and road condition analysis in logistics transportation according to claim 1, wherein the step of formulating the rest reminding strategy comprises: Setting reminding triggering conditions by combining the real-time fatigue data and the transportation path, integrating rest points along the transportation path, calculating the safe driving time of the driver according to the remaining distance of the transportation path and the fatigue degree of the driver, and calculating the optimal rest time and position by combining the rest points; and according to the actual condition and driving habit of the vehicle, a personalized reminding mode is formulated, and when the reminding triggering condition is met, the optimal rest opportunity and position are sent to a driver according to the personalized reminding mode to obtain the rest reminding strategy.
10. A system for analyzing fatigue and road conditions in logistics transportation, which adopts the method for analyzing fatigue and road conditions in logistics transportation according to any one of claims 1 to 9, wherein the analysis system comprises: The real-time data acquisition module is used for acquiring historical traffic data and personal sign data of a driver and acquiring road traffic data and characteristic behavior data of the driver in real time; the benefit path risk module is used for making benefit indexes for the transported objects, making a transport path according to the historical traffic data, dividing the transport path into a plurality of road sections according to the road traffic data, and calculating the risk grade of each road section according to a dirichlet process mixed model; The heart fatigue analysis module is used for acquiring heart consumption data of the driver according to road sections with different risk grades, and analyzing the fatigue degree of the driver by combining the characteristic behavior data to obtain real-time fatigue data; and the personalized customization module is used for formulating a rest reminding strategy according to the real-time fatigue data and in combination with the transportation path.

Description

Fatigue reminding and road condition analysis method and system in logistics transportation Technical Field The invention relates to the technical field of logistics transportation, in particular to a method and a system for fatigue reminding and road condition analysis in logistics transportation. Background With the rapid development of the global logistics industry, the daily average driving range and the duration of long-distance freight vehicles continuously climb. According to statistics, the annual average driving mileage of the heavy goods vehicle in China exceeds 20 ten thousand kilometers, and the daily average driving time of a driver exceeds 10 hours. In this context, fatigue driving has become one of the biggest hazards of logistical transportation safety, with about 60% of freight accidents being directly related to driver fatigue status. The traditional fatigue monitoring system mostly depends on a single physiological signal (such as steering wheel rotation angle or blink frequency), and lacks dynamic association analysis on complex road conditions and transportation path risks, so that early warning hysteresis and false alarm rate are high. In the aspect of transportation path planning, the current system usually only focuses on conventional factors such as distance, time and the like, and influences of risk levels of different road sections in the path on fatigue and transportation benefits of drivers are ignored. For example, some road segments may have a high risk due to large traffic flow, complex road conditions or multiple accidents, but the existing methods do not evaluate and consider this effectively. This may not only lead to the driver consuming more energy and time on the high risk road section and increasing the fatigue level, but also may reduce the transportation efficiency due to frequent encounters of traffic jams, road construction, etc., increase the transportation cost, and affect the on-time delivery of goods and the overall transportation benefits. In addition, the existing rest reminding strategy lacks individuation and real-time performance. Most reminding strategies are based on fixed driving duration or preset time intervals, and cannot accurately remind according to the actual fatigue state of a driver and the specific condition of a transportation path. Such an unreasonable rest arrangement may result in the driver continuing to drive in a tired state or resting prematurely if not necessary, thereby affecting the continuity and efficiency of the transportation task. In order to solve the problems, the method provides a fatigue reminding and road condition analysis method in logistics transportation. Disclosure of Invention The invention provides a fatigue reminding and road condition analysis method and system in logistics transportation, which are used for solving the defects that the influence of risk grades of different road sections in a path on fatigue and transportation benefits of a driver is ignored and accurate reminding cannot be carried out according to the actual fatigue state of the driver and the specific condition of a transportation path in the prior art. On the one hand, the invention provides a fatigue reminding and road condition analysis method in logistics transportation, which comprises the following steps: Historical traffic data and driver personal sign data are acquired, and road traffic data and driver characteristic behavior data are acquired in real time. And (3) formulating benefit indexes for the transported objects, formulating a transportation path according to the historical traffic data, dividing the transportation path into a plurality of road sections according to the road traffic data, and calculating the risk level of each road section according to the Dirichlet process mixed model. And acquiring heart consumption data of the driver according to road sections with different risk grades, and analyzing the fatigue degree of the driver by combining the characteristic behavior data to obtain real-time fatigue data. And (5) setting a rest reminding strategy according to the real-time fatigue data and combining with the transportation path. According to the fatigue reminding and road condition analysis method in logistics transportation provided by the invention, the step of collecting the characteristic behavior data of the driver in real time comprises the following steps: Facial expression, blink and eye movement of the driver are monitored to obtain facial features, and heart rate and brain waves are monitored to obtain physiological features. And analyzing the steering wheel rotation angle, the travel of the accelerator and brake pedal and the lane offset according to the driving habit of the driver to obtain driving behavior data. And establishing a unified space-time reference through hardware clock synchronization and space coordinate mapping, and carrying out normalization processing on facial features, physiological featu