CN109523787B - Fatigue driving analysis method based on vehicle passing track - Google Patents
Fatigue driving analysis method based on vehicle passing track Download PDFInfo
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Abstract
A fatigue driving analysis method based on a vehicle passing track is characterized in that data are obtained without depending on vehicle-mounted equipment installed on a vehicle, objectivity of the data can be guaranteed, the data can be collected in real time, an alarm is sent out actively, and law enforcement personnel are assisted in performing law enforcement actions. It includes: s1: acquiring the bayonets of all analyzed vehicle paths before calculation by taking the head bayonet Ks as a starting point; s2: calculating the passing time difference and the navigation distance between the adjacent bayonets taking the head bayonet Ks as a starting point; s3: selecting a detection road section, and marking the last bayonet of the detection road section as a tail bayonet Ke; s4: calculating the average passing speed between adjacent bayonets from the head bayonet Ks to the tail bayonet Ke; s5: according to the road type and the speed threshold value, judging a suspected vehicle with fatigue driving suspicion; s6: extracting pictures of suspected vehicles shot by all the checkpoints; s7: confirming driver information; s8: and if the phenomenon of replacing the driver does not exist, judging that the vehicle is fatigue-driven.
Description
Technical Field
The invention relates to the technical field of intelligent traffic control, in particular to a fatigue driving analysis method based on a vehicle passing track.
Background
With the rapid development of the current economic society, the logistics industry is developed and strong, the competition of the passenger and freight transportation market is intensified day by day, and some car owners and drivers continuously drive for a long time in order to obtain economic benefits, so that the fatigue driving phenomenon occurs, and serious road traffic accidents are frequently caused. In the prior art, a fatigue driving analysis method is mainly performed based on data collected by various vehicle-mounted devices, the integrity and the validity of the data are difficult to guarantee by the analysis method, the data are incomplete and the data are tampered, and the method has the premise that the relevant vehicle-mounted devices need to be installed in advance, and once the vehicle is not installed or damaged, law enforcement personnel cannot obtain the relevant data.
Disclosure of Invention
In order to solve the problems that data are in safety risk due to the fact that fatigue driving depends on vehicle-mounted equipment, and evidence cannot be obtained due to the fact that the vehicle-mounted equipment is damaged in the prior art, the fatigue driving analysis method based on the vehicle passing track is provided, the obtained data do not depend on the vehicle-mounted equipment installed on a vehicle, objectivity of the data can be guaranteed, the data can be collected in real time, an alarm is sent out actively, and law enforcement personnel are assisted to conduct law enforcement.
The technical scheme of the invention is as follows: a fatigue driving analysis method based on a vehicle passing track is characterized by comprising the following steps:
s1: the first bayonet needing to be analyzed is marked as a head bayonet Ks, and all bayonets of the analyzed vehicle path before calculation is started are obtained by taking the head bayonet Ks as a starting point;
s2: extracting the vehicle running track, and calculating the passing time difference t between each pair of adjacent bayonets with the head bayonet Ks as a starting pointiNavigation distance si；
S3: selecting a detection road section, and recording a last passing bayonet of the detection road section as a tail bayonet Ke;
s4: by the navigation distance siAnd said passing time difference tiCalculating the average passing speed v between each pair of adjacent bayonets from the head bayonets Ks to the tail bayonets Kei
vi = si/ti；
S5: according to the road type of the road section between each pair of adjacent bayonets, a speed threshold value omega is preset respectivelyiPassing through said average transit speed v between each pair of adjacent bayonetsiAnd the speed threshold value omega corresponding theretoiCalculating to judge whether the analyzed vehicle has a parking rest behavior between the bayonet pairs, if the analyzed vehicle has no parking rest on the road section between each pair of adjacent bayonet pairs, judging that the analyzed vehicle has a fatigue driving suspicion, and recording that the vehicle is a suspect vehicle;
s6: for each suspected vehicle, extracting pictures of the suspected vehicles shot by all the checkpoints from the Ks to the Ke;
s7: carrying out image recognition on the picture of the suspected vehicle through a face recognition technology, and confirming driver information;
s8: and if the phenomenon of driver replacement does not exist, judging the vehicle as a fatigue driving vehicle, pushing information of the fatigue driving vehicle to road law enforcement personnel through the traffic control platform, carrying out subsequent manual judgment by the road law enforcement personnel, and finishing the analysis.
It is further characterized in that:
the selection method for selecting the detected road section in the step S3 includes the following steps:
s3-1: accumulating said passing time difference t starting from the first said passing time differenceiObtaining the accumulated running time T;
s3-2: when the accumulated running time T is larger than the preset fatigue driving threshold time, setting the passing road section as the detection road section;
passing through the average passing speed v in step S5iAnd the speed threshold value omega corresponding theretoiThe calculation method for calculating and further judging whether the detected vehicle has parking behavior comprises the following steps:
s5-1: passing through said average transit speed viAnd the speed threshold value omega corresponding theretoiCalculating the possible value p of the continuous running of the vehicle between each pair of adjacent gatesi；
S5-2: by all said possible values piCalculating the vehicle continuation possibility P
P = 
；
S5-3: in reality, the speed threshold set according to the road type can be influenced by the difference between a driver and the road condition, so that a continuous driving possibility threshold delta is set, the continuous possibility P of the vehicle is compared with the continuous driving possibility threshold delta, and when P is larger than delta, the vehicle is recorded as a suspected vehicle;
after step S5-3, the following steps need to be performed:
s5-4: when P < delta, recording the vehicle as a tracking detection vehicle;
s5-5: finding the tracking detected vehicle is calculated in step S5-1The first of said possible values p to be given is smaller than 1iSetting the tail bayonet of the pair of adjacent bayonets corresponding to the possible value pi as the head bayonet Ks;
s5-6: repeating the steps S1 to S5 until the qualified data of the detected road section cannot be obtained from the gate device, and finishing the analysis;
the value range of the continuous travel possibility threshold value δ is [0.8,0.9 ].
The invention provides a fatigue driving analysis method based on a vehicle passing track, which is separated from vehicle-mounted equipment installed on a vehicle, analyzes whether the vehicle has a parking behavior or not by comparing and calculating the average running speed of the vehicle on a road section of each bayonet pair with a speed threshold value based on the existing public resources, confirms whether a driver replacing behavior exists or not by a face recognition technology, and further judges whether the vehicle is continuously driven on the detected road section or not; the data is automatically acquired through the public traffic control equipment, and cannot be tampered by a private person, the data cannot be lost due to the damage of personal equipment, and the objectivity and the safety of the data are ensured; after the real-time data are calculated, the suspected vehicle is notified to law enforcement personnel, so that the law enforcement personnel can timely handle the suspected vehicle, and the probability of traffic safety accidents is reduced.
Drawings
FIG. 1 is a schematic view of the flow structure of the method.
Detailed Description
As shown in fig. 1, the fatigue driving analysis method based on the vehicle passing trajectory of the present invention is characterized in that it comprises the following steps:
s1: the first bayonet needing to be analyzed is marked as a head bayonet Ks, and all bayonets of the analyzed vehicle path before calculation is started are obtained by taking the head bayonet Ks as a starting point;
s2: extracting the vehicle running track, and calculating the passing time difference t between each pair of adjacent bayonets with the head bayonet Ks as a starting pointiAnd a navigation distance s between adjacent gates obtained by using an electronic map servicei；
S3: selecting a detection road section, and recording a last passing bayonet of the detection road section as a tail bayonet Ke;
s4: by navigating a distance siAnd a passing time difference tiCalculating the average passing speed v between each pair of adjacent bayonets from the head bayonets Ks to the tail bayonets Kei
vi = si/ti；
S5: according to the road type of the road section between each pair of adjacent bayonets, a speed threshold value omega is preset respectivelyiBy the average transit speed v between each pair of adjacent gatesiAnd a speed threshold value omega corresponding theretoiCalculating to judge whether the analyzed vehicle has a parking rest behavior between the adjacent bayonet pairs, if the analyzed vehicle has no parking rest on the road section between each pair of adjacent bayonet pairs, judging that the analyzed vehicle has a fatigue driving suspicion, and recording that the vehicle is a suspected vehicle; by setting different speed thresholds omega for different types of roadsi，Let each average traffic speed viThe comparison is carried out according to the actual road condition, so as to ensure the authenticity and the accuracy of the calculation result;
s6: for each suspected vehicle, pictures of the suspected vehicles shot by all the checkpoints are extracted from the head gate Ks to the tail gate Ke respectively;
s7: carrying out image recognition on the picture of the suspected vehicle through a face recognition technology, and confirming driver information;
s8: and if the phenomenon of driver replacement does not exist, judging the vehicle as fatigue driving, pushing information of the fatigue driving vehicle to road law enforcement personnel through the traffic control platform, carrying out subsequent manual judgment by the road law enforcement personnel, and finishing the analysis.
The selection method for selecting the detected road section in the step S3 includes the following steps:
s3-1: accumulating the passing time difference t from the first passing time differenceiObtaining the accumulated running time T;
s3-2: when the accumulated driving time T is larger than the preset fatigue driving threshold time, setting a passing road section as a detection road section;
according to sixty-two seventh provisions of ' regulations on implementation of road traffic safety laws of the people's republic of China ' that ' continuously driving a motor vehicle for more than four hours and having no rest or having rest time less than twenty minutes after parking ' is fatigue driving, the threshold time of the fatigue driving is set to be 4 hours;
the detected section is defined by accumulating the travel time, and if there is a rest time in the detected section, the travel time of the detected vehicle in the detected section is necessarily less than 4 hours, and the travel distance thereof is necessarily less than the travel distance of the continuous travel.
Passing average passing speed v in step S5iAnd a speed threshold value omega corresponding theretoiThe calculation method for calculating and further judging whether the detected vehicle has parking behavior comprises the following steps:
s5-1: by average passing speed viAnd a speed threshold value omega corresponding theretoiCalculating the possible value p of the continuous running of the vehicle between each pair of adjacent gatesi；
S5-2: by all possible values piCalculating the vehicle continuation possibility P
P = 
(ii) a In actual work, the speed threshold set according to the road type is found to be influenced by the difference between a driver and the road condition, so that a continuous driving possibility threshold delta is set to correct the possible error of the speed threshold, the conclusion is closer to the real situation, and the accuracy of the scheme result is ensured;
s5-3: according to the different road types of the road sections through which the analyzed vehicle passes, respectively setting a continuous driving possibility threshold value delta for different detection road sections, comparing the continuous possibility P of the vehicle with the continuous driving possibility threshold value delta, and recording the vehicle as a suspected vehicle when P is larger than delta; the value range of the continuous driving possibility threshold value delta is [0.8,0.9], technicians can select specific numerical values corresponding to the continuous driving possibility threshold value delta for each type of detected road sections according to specific road types and installation conditions of bayonet equipment in roads, and calculation results can reflect actual conditions better;
s5-4: when P < delta, recording the vehicle as a tracking detection vehicle;
s5-5: finding the first possible value p smaller than 1 calculated in step S5-1 for the tracking-detected vehicleiSetting the tail bayonet of the pair of adjacent bayonet pairs corresponding to the possible value pi as a head bayonet Ks;
s5-6: and repeating the steps S1 to S5 until the qualified data of the detected road section cannot be obtained from the gate device, the vehicle stops running, and the analysis is finished.
The following illustrates a specific embodiment of the present invention:
table 1 is a table in which information on a specific detected road section, such as a gate, a road type, and time, extracted from a public transportation monitoring device is recorded, and the details are as follows:
table 1 detailed information of detected section
As can be seen from table 1, the target vehicle travels from 11:00 to 15:23, the accumulated travel time T = 4.38, and passes through 5 checkpoints between Ks and Ke in sequence, and the number of route segments is 4, i.e., i = 4.
According to the longitude and latitude information of the 5 bayonets, a navigation service is utilized to obtain a specific passing line between the adjacent bayonets to obtain navigation distances, which are respectively as follows:
s1= 110 road, s2= 85 km, s3= 20 km, s4= 114 km;
then respectively obtaining the vehicle uniform speed between the adjacent bayonets as follows:
v1= 82.5 km/h v2= 68 gongLi/hr, v3= 44.4 km/h v4= 96.3 km/h;
before calculating the suspicion degree of fatigue driving of the vehicle, firstly setting a vehicle passing speed mean value threshold according to the road type:
high-speed uniform speed is omega1 = 80 km/h, lane-saving uniform speed omega2 = 60 km/h, city road omega3 = 40 km/h, highway omega4 = 80 km/h;
by average passing speed viAnd a speed threshold value omega corresponding theretoiCalculating the possible value p of continuous vehicle running between each pair of gatesi：
p1 = 1、p2 = 1、p3 = 1、p4 = 1，
Comparing the values between the uniform speed and the threshold respectively shows that the ratio of the uniform speed of the vehicle running from the gate A to the gate B to the high-speed uniform speed is larger than 1, so that the vehicle is considered to run continuously from the gate A to the gate B. Similarly, the vehicle can be determined to continuously run from the bayonet B to the bayonet C, from the bayonet C to the bayonet D and from the bayonet D to the bayonet E, and no parking rest is generated;
the value of the vehicle continuation probability P is:
P = p1* p2* p3* p4 = 1；
the value range of the continuous driving possibility threshold value δ is [0.8,0.9], and no matter what value δ is, P must be larger than δ, that is to say:
the detected vehicle passes through the gate A to the gate E for more than 4 hours, so that the vehicle is considered to continuously run for more than 4 hours and has the suspicion of fatigue driving, and the vehicle is recorded as the suspicion vehicle;
for the suspected vehicle, pictures of the suspected vehicle shot by all the checkpoints are extracted from the head gate Ks to the tail gate Ke, the pictures of the suspected vehicle are subjected to image recognition through a face recognition technology, whether the driver is changed or not is confirmed, whether the driver of the vehicle is tired or not can be confirmed, and after the pictures are pushed to law enforcement personnel, the law enforcement personnel perform subsequent manual confirmation.
By using the technical scheme of the invention, the existing road monitoring equipment is used without depending on vehicle-mounted equipment installed on the vehicle, the algorithm idea is clear, the realization is convenient, and the method is used as the technical scheme of traffic management department for traffic safety control and has the characteristics of low cost, high efficiency and high accuracy; according to the method, the vehicle with fatigue driving behaviors is pushed to the road law enforcement officers, and then the law enforcement officers perform subsequent manual judgment, so that the workload of early manual screening is reduced, and the law enforcement efficiency is improved; and the suspected vehicle can be automatically identified, instead of handling the accident after the traffic accident happens, so that the traffic accident is effectively prevented.
Claims (2)
1. A fatigue driving analysis method based on a vehicle passing track is characterized by comprising the following steps:
s1: the first bayonet needing to be analyzed is marked as a head bayonet Ks, and bayonets through which all analyzed vehicles pass before calculation is started are obtained by taking the head bayonet Ks as a starting point;
s2: extracting the vehicle running track, and calculating the passing time difference t between each pair of adjacent bayonets with the head bayonet Ks as a starting pointiNavigation distance si；
S3: selecting a detection road section, and recording a last passing bayonet of the detection road section as a tail bayonet Ke;
the selection method for selecting the detection road section comprises the following steps:
s3-1: accumulating said passing time difference t starting from the first said passing time differenceiObtaining the accumulated running time T;
s3-2: when the accumulated running time T is larger than the preset fatigue driving threshold time, setting the passing road section as the detection road section;
s4: by the navigation distance siAnd said passing time difference tiCalculating the average passing speed v between each pair of adjacent bayonets from the head bayonets Ks to the tail bayonets Kei
vi = si/ti；
S5: according to the road type of the road section between each pair of adjacent bayonets, a speed threshold value omega is preset respectivelyiPassing through said average transit speed v between each pair of adjacent bayonetsiAnd the speed threshold value omega corresponding theretoiCalculating, can judge whether there is the action of parking rest by the vehicle of being analyzed between arbitrary adjacent bayonet socket pair, and then judge whether there is the driver fatigue suspicion by the vehicle of being analyzed to the record suspicion vehicle specifically includes following step:
s5-1: passing through said average transit speed viAnd the speed threshold value omega corresponding theretoiCalculating the possible value p of the continuous running of the vehicle between each pair of adjacent gatesi；
Wherein the possible values pi = 1 indicate that between the ith pair of adjacent gates, continuous driving has no stop and rest;
s5-2: by all said possible values piAnd calculating the continuous driving possibility P of the vehicle on the detected road section:
s5-3: in reality, the speed threshold set according to the road type can be influenced by the difference between a driver and the road condition, so that a continuous driving possibility threshold delta is set, the continuous driving possibility P of the vehicle is compared with the continuous driving possibility threshold delta, and when P is larger than delta, the vehicle is recorded as a suspect vehicle; step S6 is executed;
when P is less than or equal to delta, recording the vehicle as a tracking detection vehicle;
finding the first possible value p smaller than 1 calculated in step S5-1 by the tracking detected vehicleiThe pair of adjacent said possible values pi corresponds toThe tail bayonet in the bayonet is set as the head bayonet Ks;
repeating the steps S1 to S5 until the data of the detected road section cannot be obtained from the bayonet device, and finishing the analysis;
s6: for each suspected vehicle, extracting pictures of the suspected vehicles shot by all the checkpoints from the Ks to the Ke;
s7: carrying out image recognition on the picture of the suspected vehicle through a face recognition technology, and confirming driver information;
s8: and if the phenomenon of driver replacement does not exist, judging the vehicle as a fatigue driving vehicle, pushing information of the fatigue driving vehicle to road law enforcement personnel through the traffic control platform, carrying out subsequent manual judgment by the road law enforcement personnel, and finishing the analysis.
2. The fatigue driving analysis method based on the vehicle passing track as claimed in claim 1, wherein: the value range of the continuous travel possibility threshold value δ is [0.8,0.9 ].
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| CN111696349B (en) * | 2020-06-10 | 2022-02-11 | 长威信息科技发展股份有限公司 | Fatigue driving distinguishing method based on real-time traffic condition of road section |
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