CN115426354B - Method and system for judging serious accident of long-distance logistics vehicle - Google Patents
Method and system for judging serious accident of long-distance logistics vehicle Download PDFInfo
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- CN115426354B CN115426354B CN202211045126.1A CN202211045126A CN115426354B CN 115426354 B CN115426354 B CN 115426354B CN 202211045126 A CN202211045126 A CN 202211045126A CN 115426354 B CN115426354 B CN 115426354B
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- 238000007405 data analysis Methods 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 21
- 230000002159 abnormal effect Effects 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 6
- 238000012544 monitoring process Methods 0.000 claims description 3
- 230000001960 triggered effect Effects 0.000 claims description 3
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention belongs to the technical field of traffic safety, and particularly relates to a method and a system for judging serious accidents of long-distance logistics vehicles, wherein the method comprises the following steps: the method comprises the steps that a vehicle-mounted terminal device is installed on a vehicle, the vehicle angular acceleration, the vehicle linear acceleration and a video image of the front end of the vehicle are collected through the vehicle-mounted terminal device, the state of the vehicle is monitored in real time, and collected vehicle state information and alarm information are uploaded to a cloud platform; uploading data to a cloud platform, and synchronously acquiring the vehicle position, the current road network information and the vehicle waybill data by the cloud platform; the cloud platform establishes a data analysis model to comprehensively analyze the vehicle information, determine the running state of the vehicle and comprehensively judge whether the vehicle has an accident or not. The vehicle-mounted terminal device and the cloud platform are matched to judge whether a serious accident occurs to a long-distance logistics vehicle or not, so that an alarm is timely helped, and drivers and passengers are timely rescued.
Description
Technical Field
The invention belongs to the technical field of traffic safety, and particularly relates to a method and a system for judging serious accidents of long-distance logistics vehicles.
Background
Long-distance logistics vehicles are the main mode of land transportation of goods at present, and along with the development of society and economy, the long-distance logistics vehicles are more and more; when serious accidents occur in the transportation process of the conventional long-distance logistics vehicles, drivers and passengers cannot give an alarm at the first time, and the drivers and passengers cannot be timely rescued, so that life and property are further lost.
Disclosure of Invention
The invention aims to provide a method and a system for judging serious accidents of long-distance logistics vehicles, which overcome the defects of the prior art, and judge whether the serious accidents occur to the long-distance logistics vehicles through the cooperation of vehicle-mounted terminal equipment and a cloud platform, so that the warning is timely assisted, and drivers and passengers are timely rescued.
In order to solve the problems, the technical scheme adopted by the invention is as follows:
a method for judging serious accidents of long-distance logistics vehicles comprises the following steps:
firstly, mounting vehicle-mounted terminal equipment on a vehicle, acquiring angular acceleration and linear acceleration of the vehicle and video images of the front end of the vehicle through the vehicle-mounted terminal equipment, monitoring the state of the vehicle in real time, and sending out collision alarm, rollover alarm and vehicle distance approaching alarm, wherein the vehicle-mounted terminal equipment uploads the acquired vehicle state information and alarm information to a cloud platform;
step two, uploading data to a cloud platform, and synchronously acquiring the vehicle position, the current road network information and the vehicle waybill data by the cloud platform;
thirdly, a cloud platform establishes a data analysis model to comprehensively analyze vehicle information, determine the running state of the vehicle and comprehensively judge whether the vehicle has an accident or not; if no accident occurs, the detection is stopped, the data uploaded by the vehicle-mounted terminal equipment is continuously received, and if the accident occurs, the accident alarm is triggered.
Further, in the first step, the vehicle-mounted terminal device includes a vehicle-mounted camera for acquiring front video image information, an inertial measurement device for acquiring angular velocity and linear acceleration of the vehicle, a vehicle-mounted positioning device for acquiring a vehicle position, and a wireless communication device for connecting with a cloud platform.
Further, in the second step, the road network information includes road condition, position and road periphery information;
road conditions include clear road sections and congested road sections;
the positions comprise a high-speed road section, a national road traffic large road section, a national road traffic small road section, a ramp road section, a road section in a service area and a road section in a park;
the road surrounding information includes parking lots, service areas, gas stations.
Further, in the third step, the vehicle information is comprehensively analyzed to determine the running state of the vehicle, and whether the vehicle has an accident or not is comprehensively judged, which comprises the following specific steps:
s1, judging whether the speed of the current position point of the vehicle is greater than 5km/h, if so, continuously receiving the vehicle data information, and if not, entering a detection mode;
s2, acquiring data of a previous position point of the vehicle, judging whether the speed value exceeds 60km/h, if yes, entering S3, if not, exiting a detection mode, and continuously receiving vehicle data information;
s3, calculating the acceleration value and the absolute value of the acceleration between the previous position point and the current position point of the vehicle, if the acceleration value and the absolute value of the acceleration are less than 1.4m/S 2 If yes, the detection mode is exited, the vehicle data information is continuously received, and if not, the S4 is entered;
s4, checking the state of the vehicle-mounted terminal equipment and an alarm signal, entering S5 if the state of the vehicle-mounted terminal equipment is abnormal or the alarm signal exists, exiting a detection mode if the state of the vehicle-mounted terminal equipment is abnormal or the alarm signal exists, and continuously receiving vehicle data information;
s5, acquiring the position of the vehicle, acquiring the road and road condition information of the vehicle from national road network and real-time road condition data, if the road of the vehicle is jammed or parked in a parking lot, a service area and a gas station, exiting a detection mode, continuously receiving the vehicle data information, and otherwise entering S6;
s6, judging whether the vehicle is in a logistics network point or not according to the running time and the travel path matching waybill data, if so, exiting the detection mode, continuously receiving the vehicle data information, otherwise, entering S7;
and S7, judging whether the parking duration exceeds 10 minutes, if so, triggering the cloud platform to alarm, and if not, circulating to S1.
Further, in S3, the current position point velocity v1 and time t1, the previous position point velocity v2 and time t2, the acceleration value a1= (v 1-v 2)/(t 1-t 2) between the two points.
The invention also protects a system for judging serious accidents of long-distance logistics vehicles, which comprises
The vehicle-mounted terminal equipment comprises a vehicle-mounted camera, an inertia measuring device, a vehicle-mounted positioning device and a wireless communication device;
the cloud platform is used for acquiring data information uploaded by the vehicle-mounted terminal equipment, acquiring vehicle positions, current road network information and vehicle waybill data, comprehensively analyzing the vehicle information through the data analysis model, determining the running state of the vehicle, and comprehensively judging whether the vehicle has an accident or not.
Compared with the prior art, the invention has the following beneficial effects:
the invention relates to a method and a system for judging serious accidents of long-distance logistics vehicles, which are characterized in that the vehicle accident alarming is generated by combining terminal host uploading data, national road network, real-time road condition data and vehicle waybill data and comprehensively calculating; the problems of false alarm, missing alarm, untimely alarm and the like of the vehicle accident are solved, enterprises find vehicles with serious accidents in time and intervene and rescue in time, and personnel and property losses are reduced.
Drawings
Fig. 1 is a flow chart of a method for judging serious accident of long-distance logistics vehicles.
Fig. 2 is a schematic block diagram of a serious accident judging system for a long-distance logistics vehicle.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in FIG. 1, the method for judging the serious accident of the long-distance logistics vehicle comprises the following steps:
firstly, mounting vehicle-mounted terminal equipment on a vehicle, acquiring angular acceleration and linear acceleration of the vehicle and video images of the front end of the vehicle through the vehicle-mounted terminal equipment, monitoring the state of the vehicle in real time, and sending out collision alarm, rollover alarm and vehicle distance approaching alarm, wherein the vehicle-mounted terminal equipment uploads the acquired vehicle state information and alarm information to a cloud platform;
the vehicle-mounted terminal device comprises a vehicle-mounted camera for acquiring the front video image information, an inertial measurement device for acquiring the angular speed and the linear acceleration of the vehicle, a vehicle-mounted positioning device for acquiring the position of the vehicle and a wireless communication device for connecting a cloud platform.
Step two, uploading data to a cloud platform, and synchronously acquiring the vehicle position, the current road network information and the vehicle waybill data by the cloud platform;
the vehicle waybill data includes departure position, destination position, departure time, and route.
The road network information comprises road conditions, positions and road periphery information;
road conditions include clear road sections and congested road sections;
the positions comprise a high-speed road section, a national road traffic large road section, a national road traffic small road section, a ramp road section, a road section in a service area and a road section in a park;
the road surrounding information includes parking lots, service areas, gas stations.
Thirdly, a cloud platform establishes a data analysis model to comprehensively analyze vehicle information, determine the running state of the vehicle and comprehensively judge whether the vehicle has an accident or not; if no accident occurs, the detection is stopped, the data uploaded by the vehicle-mounted terminal equipment is continuously received, and if the accident occurs, the accident alarm is triggered;
the specific judging method comprises the following steps:
s1, judging whether the speed of the current position point of the vehicle is greater than 5km/h, if so, continuously receiving vehicle data information if the vehicle is still in the continuous running process, and if not, entering a detection mode;
s2, acquiring data of a previous position point of the vehicle, judging whether the speed value exceeds 60km/h, if so, entering S3, if not, the vehicle is not subjected to emergency braking and has no serious accident, exiting the detection mode, and continuing to receive the vehicle data information;
s3, calculating an acceleration value and an acceleration absolute value between a previous position point and a current position point of the vehicle, wherein the current position point speed v1 and the time t1, the previous position point speed v2 and the time t2, and then the acceleration value a1= (v 1-v 2)/(t 1-t 2) between the two points; if the acceleration value and the absolute value of the acceleration are less than 1.4m/s 2 If yes, the vehicle is stopped in a non-emergency mode, the detection mode is exited, the vehicle data information is continuously received, and if not, the S4 is entered;
s4, checking the state of the vehicle-mounted terminal equipment and an alarm signal, entering S5 if the state of the vehicle-mounted terminal equipment is abnormal or the alarm signal exists, exiting a detection mode if the state is not the abnormal state of the vehicle, and continuously receiving vehicle data information;
s5, acquiring the position of the vehicle, acquiring the road and road condition information of the vehicle from national road network and real-time road condition data, if the road of the vehicle is jammed or parked in a parking lot, a service area and a gas station, indicating that the vehicle is normally parked, exiting a detection mode, continuously receiving the vehicle data information, and otherwise entering S6;
s6, judging whether the vehicle is in a logistics network point according to the running time and the travel path matching waybill data, if so, exiting the detection mode, continuously receiving the vehicle data information, otherwise, entering S7;
and S7, judging whether the parking duration exceeds 10 minutes, if so, triggering the cloud platform to alarm, and if not, circulating to S1.
As shown in FIG. 2, the invention also protects a system for judging serious accidents of long-distance logistics vehicles, which comprises
The vehicle-mounted terminal equipment comprises a vehicle-mounted camera, an inertia measuring device, a vehicle-mounted positioning device and a wireless communication device;
the cloud platform is used for acquiring data information uploaded by the vehicle-mounted terminal equipment, acquiring vehicle positions, current road network information and vehicle waybill data, comprehensively analyzing the vehicle information through the data analysis model, determining the running state of the vehicle, and comprehensively judging whether the vehicle has an accident or not.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (4)
1. A method for judging serious accidents of long-distance logistics vehicles is characterized by comprising the following steps of: the method comprises the following steps:
firstly, mounting vehicle-mounted terminal equipment on a vehicle, acquiring angular acceleration and linear acceleration of the vehicle and video images of the front end of the vehicle through the vehicle-mounted terminal equipment, monitoring the state of the vehicle in real time, and sending out collision alarm, rollover alarm and vehicle distance approaching alarm, wherein the vehicle-mounted terminal equipment uploads the acquired vehicle state information and alarm information to a cloud platform;
step two, uploading data to a cloud platform, and synchronously acquiring the vehicle position, the current road network information and the vehicle waybill data by the cloud platform;
thirdly, a cloud platform establishes a data analysis model to comprehensively analyze vehicle information, determine the running state of the vehicle and comprehensively judge whether the vehicle has an accident or not; if no accident occurs, the detection is stopped, the data uploaded by the vehicle-mounted terminal equipment is continuously received, and if the accident occurs, the accident alarm is triggered;
in the third step, the vehicle information is comprehensively analyzed to determine the running state of the vehicle, and whether the vehicle has an accident or not is comprehensively judged, and the specific steps include:
s1, judging whether the speed of the current position point of the vehicle is greater than 5km/h, if so, continuously receiving the vehicle data information, and if not, entering a detection mode;
s2, acquiring data of a previous position point of the vehicle, judging whether the speed value exceeds 60km/h, if yes, entering S3, if not, exiting a detection mode, and continuously receiving vehicle data information;
s3, calculating the acceleration value and the absolute value of the acceleration between the previous position point and the current position point of the vehicle, if the acceleration value and the absolute value of the acceleration are less than 1.4m/S 2 If yes, the detection mode is exited, the vehicle data information is continuously received, and if not, the S4 is entered;
in S3, the current position point speed v1 and time t1, and the previous position point speed v2 and time t2, the acceleration value a1= (v 1-v 2)/(t 1-t 2) between the two points;
s4, checking the state of the vehicle-mounted terminal equipment and an alarm signal, entering S5 if the state of the vehicle-mounted terminal equipment is abnormal or the alarm signal exists, exiting a detection mode if the state of the vehicle-mounted terminal equipment is abnormal or the alarm signal exists, and continuously receiving vehicle data information;
s5, acquiring the position of the vehicle, acquiring the road and road condition information of the vehicle from national road network and real-time road condition data, if the road of the vehicle is jammed or parked in a parking lot, a service area and a gas station, exiting a detection mode, continuously receiving the vehicle data information, and otherwise entering S6;
s6, judging whether the vehicle is in a logistics network point or not according to the running time and the travel path matching waybill data, if so, exiting the detection mode, continuously receiving the vehicle data information, otherwise, entering S7;
and S7, judging whether the parking duration exceeds 10 minutes, if so, triggering the cloud platform to alarm, and if not, circulating to S1.
2. The method for determining serious accident of long-distance logistics vehicles according to claim 1, wherein: the vehicle-mounted terminal device comprises a vehicle-mounted camera for acquiring front video image information, an inertia measuring device for acquiring angular velocity and linear acceleration of the vehicle, a vehicle-mounted positioning device for acquiring the position of the vehicle and a wireless communication device for connecting a cloud platform.
3. The method for determining serious accident of long-distance logistics vehicles according to claim 1, wherein: step two, the road network information comprises road condition, position and road periphery information;
road conditions include channel sections and congested sections;
the positions comprise a high-speed road section, a national road traffic large road section, a national road traffic small road section, a ramp road section, a road section in a service area and a road section in a park;
the road surrounding information includes parking lots, service areas, gas stations.
4. A system based on the method for judging serious accident of long-distance logistics vehicles according to claim 1, characterized in that: comprising
The vehicle-mounted terminal equipment comprises a vehicle-mounted camera, an inertia measuring device, a vehicle-mounted positioning device and a wireless communication device;
the cloud platform is used for acquiring data information uploaded by the vehicle-mounted terminal equipment, acquiring vehicle positions, current road network information and vehicle waybill data, comprehensively analyzing the vehicle information through the data analysis model, determining the running state of the vehicle, and comprehensively judging whether the vehicle has an accident or not.
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| CN103985223A (en) * | 2014-05-12 | 2014-08-13 | 苗林 | Motor-vehicle accident warning device, system and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103640533B (en) * | 2013-12-07 | 2016-03-23 | 成都亿盟恒信科技有限公司 | A kind of device and method based on vehicle collision rollover detection, automatic calling for help |
| KR101738414B1 (en) * | 2015-06-24 | 2017-05-22 | 주식회사 엔알피시스템 | Apparatus for detecting vehicle accident and emergency call system using the same |
| US10824145B1 (en) * | 2016-01-22 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle component maintenance and repair |
| CN107507445A (en) * | 2017-08-17 | 2017-12-22 | 千寻位置网络有限公司 | The method for reporting traffic accident and congestion track automatically based on high accuracy positioning |
| CN109410567B (en) * | 2018-09-03 | 2021-10-12 | 江苏大学 | Intelligent analysis system and method for accident-prone road based on Internet of vehicles |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103985223A (en) * | 2014-05-12 | 2014-08-13 | 苗林 | Motor-vehicle accident warning device, system and method |
| CN110503802A (en) * | 2019-09-26 | 2019-11-26 | 京东方科技集团股份有限公司 | Driving accident judgment method and system based on automobile data recorder |
| CN111667692A (en) * | 2020-06-15 | 2020-09-15 | 惠州市博实结科技有限公司 | Vehicle accident automatic processing method, vehicle-mounted terminal and vehicle |
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