CN114070848A - Searching method and searching system for adjacent key vehicles of traffic accidents - Google Patents
Searching method and searching system for adjacent key vehicles of traffic accidents Download PDFInfo
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Abstract
The invention relates to a searching method and a searching system for adjacent key vehicles of traffic accidents, which comprise a cloud server and a vehicle-mounted terminal; the cloud server comprises a communication module and a calculation module; the communication module is used for carrying out information interaction with the vehicle-mounted terminal, and the calculation module is used for generating a vehicle data table and a neighbor data table and calculating the position of a neighboring key vehicle; the vehicle-mounted terminal comprises a communication module, a positioning module, a calculation module and a sensor module, wherein the positioning module is used for generating longitude and latitude coordinate positions of the vehicle, the calculation module is used for calculating the time and the speed of the vehicle, the sensor module is used for calculating the acceleration value of the vehicle, and the communication module is used for carrying out information interaction with the cloud server; the invention can adapt to most traffic scenes, increases the diversity of the current traffic accident evidence taking, and has wide adaptive scenes; and the accident evidence obtaining difficulty can be reduced, the accident scene is restored, the counterfeit evidence is avoided, and the accuracy and the fairness of the traffic accident responsibility identification are improved.
Description
Technical Field
The invention relates to a method and a system for searching adjacent key vehicles of traffic accidents, belonging to the technical field of traffic equipment.
Background
The existing traffic accident evidence obtaining method mostly depends on the self-description of a vehicle-mounted automobile data recorder, a road camera facility and accident related personnel. In some traffic scenes, when some traffic accidents occur, it may be inconvenient for the accident scene to collect evidence due to factors such as dead angles shot by the driving recorder of the vehicle, lack of road camera facilities, etc., and it is hoped that important functions such as recovering the traffic accident scene and identifying responsibility are assisted by videos shot by the driving recorder of the adjacent vehicle. Retrieving related technologies, a patent document (application number CN201810344553.7 is a driving record information processing method based on a block chain) provides a solidified evidence technology for adding a video image into the block chain after an accident occurs, and characteristics such as evidence non-repudiation and non-tampering are guaranteed; the patent document (application number CN201810705479.7 accident data processing method based on block chain) proposes writing the accident data in the surrounding vehicles passing through the accident site and the roadbed equipment into the block chain for accident liability judgment; according to the patent document (application number CN201810446923.8, a block chain-based accurate accident handling method for networked automobiles), field data is collected and linked up by using an intelligent terminal of a vehicle accident field, accident handling is completed by participation of multiple parties, and the transparency of the accident handling process is improved; the patent document (application number CN201910298644.6, a structure and a working method for collecting traffic accident information based on a block chain) provides a three-layer structure of a cloud service layer, an edge computing layer and a sensing layer, and the three-layer structure comprises four steps of accident information inquiry, return, roadside unit consensus and storage, and an edge computing technology is adopted, so that the load of roadside units is effectively reduced, and the information collection efficiency is improved.
By summarizing the above technical solution, it is not possible to find out the adjacent related vehicles before and after the accident by using the searching technique after the accident occurs. Moreover, the automobile driving recorder of the accident vehicle shoots the video in front of the automobile, and the accident occurrence process intercepted and recorded by other adjacent related vehicle visual angles is lacked when the accident occurs; furthermore, even if the car recorder of the neighboring vehicle passes through the recording accident, it is not known where to provide the key recorded video for restoring or reconstructing the accident process, so that the key video is not available or how to obtain the key video is unknown.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for searching the adjacent key vehicles of the traffic accident, aiming at overcoming the defects of the existing method that the searching difficulty of the vehicles around the accident is higher, the screening of the adjacent key vehicles and the evidence obtaining are complicated and difficult, and the method can select workshop searching, centralized searching or mixed cooperative searching to find the adjacent key vehicles and ask for the key video according to different conditions after the accident occurs. The method not only can efficiently and accurately search the adjacent key vehicles, but also can automatically intercept the video clip shot by the vehicle-mounted automobile data recorder related to the accident, and the acquisition process has no human interference, and can immediately and automatically encrypt the uplink, thereby ensuring the authenticity of data.
The technical scheme of the invention is as follows:
a system for searching adjacent key vehicles of traffic accidents comprises a cloud server and a vehicle-mounted terminal;
the cloud server comprises a communication module and a calculation module; the communication module is used for carrying out information interaction with the vehicle-mounted terminal, and the calculation module is used for generating a vehicle data table and a neighbor data table and calculating the position of a neighboring key vehicle;
the vehicle-mounted terminal comprises a communication module, a positioning module, a calculation module and a sensor module, wherein the positioning module is used for generating longitude and latitude coordinate positions of the vehicle, the calculation module is used for calculating the time and the speed of the vehicle, the sensor module is used for calculating the acceleration value of the vehicle, and the communication module is used for carrying out information interaction with the cloud server;
the vehicle is connected with the internet through a wireless network or a mobile network to form communication networks between vehicles and between the vehicles and a server, as shown in figure 1, and identity authentication, message interaction and data updating are carried out;
the identity authentication is that the vehicle utilizes a communication network to connect a server and a Block Chain (Block Chain) to carry out public key exchange (Upload Hash (PKA)); the message interaction is that the vehicle sends characteristic messages of the vehicle to the cloud server and adjacent vehicles according to a certain period so as to maintain a vehicle data table or a neighbor data table, wherein the characteristic messages comprise longitude and latitude coordinate positions, time, speed, track and acceleration values; one of the data updating operations is that any vehicle receives the characteristic message sent by the adjacent vehicle and updates the neighbor data table of the vehicle in real time; the data update step two is a vehicle data table of each vehicle real-time position updated by the server by using the characteristic message sent by the vehicle.
Preferably, the communication module adopts a satellite-cloud interconnection intelligent drive test terminal T-Station or Hua Li Zhi xing MOCAR I-Classic RSE, the calculation module adopts Amazon EC2, the positioning module adopts a satellite-cloud interconnection intelligent vehicle-mounted terminal V-Box or Hua Li Zhi xing MOCAR V-Classic OBE, and the sensor module adopts Beijing science and technology AKE 392B.
Preferably, the period of the message interaction is every 1-10 seconds. Depending on the situation, for example every 1 second, every 5 seconds, every 10 seconds.
Preferably, the adjacent vehicles are vehicles with a mutual distance of 0 m-1000 m, and the vehicles can realize vehicle-to-vehicle direct connection communication without a transfer mode.
A method for searching adjacent key vehicles of traffic accidents comprises the following steps:
(1) the vehicle regularly sends the characteristic information of the vehicle to the adjacent vehicle and the cloud server by using a communication network so as to maintain a vehicle data table and update a neighbor data table in real time;
(2) when a traffic accident occurs, the accident vehicle uploads the characteristic information of the accident vehicle to a cloud server for storage and recording; meanwhile, a computing module of the cloud server acquires road characteristics and road section types by combining a high-precision electronic map according to longitude and latitude coordinate positions of accident vehicles, eliminates irrelevant vehicles, and preliminarily judges the search range of key vehicles adjacent to the accident; the road section types comprise double/single direction and isolation belts or not;
(3) narrowing the search range and screening out adjacent key vehicles;
(4) requesting the uploading of accident video from the neighboring key vehicles.
Preferably, in the step (2), uploading the characteristic message of the accident vehicle comprises automatically uploading the vehicle and manually uploading by a driver and a passenger; the automatic uploading of the vehicle is to trigger an automatic uploading instruction when the vehicle-mounted sensor module monitors abnormality; for example, a sensor signal (e.g., an accelerometer) is used to detect a variation of acceleration, and when the variation exceeds a threshold (e.g., ± 12G), an abnormal event is determined (collision is determined), and the device is widely used for an in-vehicle device such as a car recorder).
Preferably, in the step (2), the excluding the irrelevant vehicle includes: the exclusion irrelevant vehicle is whether to exclude the oncoming vehicle when finding out the adjacent key vehicle; when the accident occurs on a one-way road, no oncoming vehicle exists, so that exclusion is not needed; when an accident occurs on a bidirectional road, if isolation zones exist among lanes and vehicles coming from opposite lanes cannot shoot the traffic accident due to the fact that the isolation zones are shielded, the vehicles coming from opposite lanes need to be excluded when adjacent key vehicles are found out, and only vehicles running in the same direction are considered; if the isolation belt does not exist, the oncoming car has certain evidence obtaining value, so the oncoming car is not excluded.
When a traffic accident occurs, because evidence collection on the accident site is inconvenient or insufficient to determine a responsible party, the method and the system for finding out the key data which can be provided by the adjacent vehicle when the accident occurs have certain advantages.
Preferably, in the step (3), the screening of the adjacent key vehicles comprises the following two modes:
in the first mode, a computing module of a cloud server inquires a vehicle data table;
in the second mode, a neighbor data table is inquired by a calculation module of the accident vehicle;
the first method is as follows:
after receiving the characteristic information of the accident vehicle, the cloud server selects a certain time interval before and after the occurrence of the traffic accident, from n seconds before the occurrence of the accident to m seconds before and after the occurrence of the accident, preferably, the certain time interval before and after the occurrence of the traffic accident is from 10 seconds before to 5 seconds after the occurrence of the accident; the method comprises the steps that driving behaviors 5-10 seconds before an accident occurs are inferred to be important characteristics of the accident, relevant vehicles in a search range are screened out by taking accident vehicle track sites (m sites in total) as centers, the search range is a continuous area coverage range formed by taking driving tracks of the accident vehicles n seconds before the accident occurs to m seconds after the accident occurs as the center of a circle and taking radius r meters, namely, adjacent key vehicles, and preferably, r is preset to be 100 m; also means a vehicle that overlaps the time of the accident vehicle at a point n seconds before the accident occurs. The screening mode is not limited, and can be implemented according to a programming mode; for example, the screening is carried out in SQL language or in a mode of traversing arrays;
the second method comprises the following steps:
the accident vehicle screens out related vehicles in a search range by taking the track locus of the accident vehicle as a center (m loci in total) within a certain time period before and after the occurrence of a traffic accident, wherein the search range is a continuous area coverage range formed by taking the running track of the accident vehicle from n seconds before the occurrence of the accident to m seconds after the occurrence of the accident as the center of a circle and by taking the radius r meter, namely the adjacent key vehicle, and also means the vehicles which overlap with the accident vehicle at the locus of n seconds before the occurrence of the accident in space and time, the screening mode is not limited and can be implemented according to a programming mode; for example, in the SQL language for screening, or in a manner that traverses arrays.
Further preferably, in step (4), there are 3 ways to request the uploading of the accident video from the adjacent key vehicle: a workshop searching method, a centralized searching method and a collaborative searching method;
(1) workshop searching method
The accident vehicle finds out the adjacent key vehicles by the second method, and then sends out searching commands to the adjacent key vehicles by vehicle-to-vehicle communication to perform the first searching; after receiving the instruction, the adjacent key vehicle replies confirmation to the accident vehicle, and directly uploads video information of a specific time period (for example, within the first 10 seconds to the later 5 seconds of the accident, the time period is consistent with the time period selection in the step (3)) when the accident happens, which is shot by the vehicle-mounted automobile data recorder, to the server; in order to avoid omission, if the accident vehicle does not receive the reply confirmation of all the adjacent key vehicles, more than two adjacent key vehicle searching commands are sent within a certain time until the accident vehicle receives the confirmation of all the adjacent key vehicles or the time is cut off, preferably, the time of the searching commands is 1-5 min; after uploading, the server can confirm the accident vehicle and the accident evidence obtaining is finished; the method is superior to the prior method in the condition of large traffic flow and crowded roads.
(2) Centralized searching method
The accident vehicle sends video information of the vehicle to the cloud server, and the cloud server screens out the adjacent key vehicles in a first mode, sends a request to the adjacent key vehicles through a remote communication technology and directly asks for the video information of the adjacent key vehicles; in order to avoid omission, the cloud server sends more than one instruction for searching the adjacent key vehicles if the cloud server does not receive reply confirmation of all the adjacent key vehicles within a certain time until the cloud server receives the confirmation of all the adjacent key vehicles or the time is up; after uploading, the cloud server confirms the accident vehicle and the adjacent key vehicles, and the accident evidence obtaining is finished; the method has wide application scenes, particularly small traffic flow and high-speed driving road sections;
(3) collaborative search method
The two methods are combined, and mainly used for making up the problem that in some scenes, part of adjacent key vehicles possibly exist in the workshop searching method, and cannot be confirmed to an accident vehicle within a specified time due to the fact that the adjacent key vehicles continuously run beyond a communication range or are in a disconnected state, so that omission is caused.
Preferably, in the step (4), after the cloud server receives the video information uploaded by the adjacent key vehicle, in order to reduce the size of the video information as much as possible, reduce the occupation of server resources and ensure sufficient evidence, the video information is filtered by using an information filter, and finally important features are obtained; the information filter is a module that uses a vehicle identification number (vehicle ID), an event number, or other parameters to filter repeatedly uploaded video. For example, the same vehicle may send videos to the server many times due to network communication, and the server may use the information filter to exclude the videos with repetition or high similarity.
Vehicles predicted to be more than 100m ahead of the accident vehicle are replaced when the r of the adjacent vehicle screening is 100.
The invention has the beneficial effects that:
the invention provides a method for searching adjacent key vehicles of traffic accidents, which can adapt to most traffic scenes, wherein the method comprises the following steps: the diversity of the current traffic accident evidence obtaining is increased, a set of complete searching methods for the adjacent key vehicles of the traffic accident are provided, and the method is suitable for a wide range of scenes; the second step is as follows: the accident evidence obtaining difficulty can be reduced, the accident scene is restored, the counterfeit evidence is avoided, and the accuracy and the fairness of the traffic accident responsibility identification are improved.
Drawings
Fig. 1 is a schematic view of communication between a cloud server and a vehicle-mounted terminal;
FIG. 2 is a schematic view of a traffic accident scene;
FIG. 3 is a schematic flow chart of step (2);
FIG. 4 is a schematic diagram of an accident vehicle A inquiring neighboring vehicles within 100m before the accident happens in 10 s;
FIG. 5 is a schematic diagram of an accident evidence collection process by searching neighboring key vehicles using a workshop searching method
FIG. 6 is a schematic diagram illustrating accident evidence collection by searching neighboring key vehicles using a centralized search method;
FIG. 7 is a schematic diagram illustrating a method for searching neighboring key vehicles by using a collaborative search method.
Detailed Description
The present invention will be further described by way of examples, but not limited thereto, with reference to the accompanying drawings.
Example 1:
a system for searching adjacent key vehicles in traffic accidents comprises a cloud server and a vehicle-mounted terminal, as shown in figure 1;
the cloud server comprises a communication module and a calculation module; the communication module is used for carrying out information interaction with the vehicle-mounted terminal, and the calculation module is used for generating a vehicle data table and a neighbor data table and calculating the position of a neighboring key vehicle;
the vehicle-mounted terminal comprises a communication module, a positioning module, a calculation module and a sensor module, wherein the positioning module is used for generating longitude and latitude coordinate positions of the vehicle, the calculation module is used for calculating the time and the speed of the vehicle, the sensor module is used for calculating the acceleration value of the vehicle, and the communication module is used for carrying out information interaction with the cloud server;
the vehicle is connected with the internet through a wireless network or a mobile network to form communication networks between vehicles and between the vehicles and a server, as shown in figure 1, and identity authentication, message interaction and data updating are carried out;
the identity authentication is that the vehicle utilizes a communication network to connect a server and a Block Chain (Block Chain) to carry out public key exchange (Upload Hash (PKA)); the message interaction is that the vehicle sends characteristic messages of the vehicle to the cloud server and adjacent vehicles according to a certain period so as to maintain a vehicle data table or a neighbor data table, wherein the characteristic messages comprise longitude and latitude coordinate positions, time, speed, track and acceleration values; one of the data updating operations is that any vehicle receives the characteristic message sent by the adjacent vehicle and updates the neighbor data table of the vehicle in real time; the data update step two is a vehicle data table of each vehicle real-time position updated by the server by using the characteristic message sent by the vehicle.
The period of message interaction is every 1-10 seconds. Depending on the situation, for example every 1 second, every 5 seconds, every 10 seconds.
The adjacent vehicles are vehicles with the mutual distance of 0-1000 m, and the vehicles can realize vehicle-to-vehicle direct connection communication without a transfer mode.
Example 2:
a method for searching adjacent key vehicles of traffic accidents comprises the following steps:
(1) the vehicle regularly sends the characteristic information of the vehicle to the adjacent vehicle and the cloud server by using a communication network so as to maintain a vehicle data table and update a neighbor data table in real time;
(2) when a traffic accident occurs, the accident vehicle uploads the characteristic information of the accident vehicle to a cloud server for storage and recording; meanwhile, a computing module of the cloud server acquires road characteristics and road section types by combining a high-precision electronic map according to longitude and latitude coordinate positions of accident vehicles, eliminates irrelevant vehicles, and preliminarily judges the search range of key vehicles adjacent to the accident; the road section types comprise double/single direction and isolation belts or not;
the scene of the traffic accident is shown in figure 2: the vehicle utilizes the communication network to connect the server and the Block Chain (Block Chain) to carry out public key exchange (PK)A))，And (4) performing identity authentication, and sending characteristic information (longitude and latitude coordinate positions, time, speed, track and acceleration values) of all vehicles to the cloud server every 1 second to maintain a vehicle data table (a black solid line in figure 2 represents that the vehicle characteristic information is uploaded regularly) or sending the characteristic information to adjacent vehicles to update a neighbor data table. The accident vehicle A rubs against the accident vehicle B due to illegal overtaking.
The vehicle-mounted terminals of the accident vehicle a and the accident vehicle B monitor a collision event (the variation value of the acceleration exceeds a threshold value (+ -12G)), an automatic uploading instruction is triggered, or a driver clicks a one-key uploading button to upload the characteristic information of the accident vehicle, namely longitude and latitude coordinate position (GPS), time, speed, track and acceleration value (G-Sensor), to a cloud Server (Server a) for storage and recording, and the cloud Server receives the information and confirms the information to the accident vehicle A, B (ACK in fig. 3). Meanwhile, the calculation module of the cloud server confirms road characteristics (double/single direction, isolation zones or no isolation zones) by combining a high-precision electronic map according to the longitude and latitude coordinates of the accident vehicle, eliminates irrelevant vehicles, and preliminarily determines the search range of key vehicles adjacent to the accident, wherein the process is shown in fig. 3.
The case of excluding the extraneous vehicle includes: the exclusion irrelevant vehicle is whether to exclude the oncoming vehicle when finding out the adjacent key vehicle; when the accident occurs on a one-way road, no oncoming vehicle exists, so that exclusion is not needed; when an accident occurs on a bidirectional road, if isolation zones exist among lanes and vehicles coming from opposite lanes cannot shoot the traffic accident due to the fact that the isolation zones are shielded, the vehicles coming from opposite lanes need to be excluded when adjacent key vehicles are found out, and only vehicles running in the same direction are considered; if the isolation belt does not exist, the oncoming car has certain evidence obtaining value, so the oncoming car is not excluded.
(3) Narrowing the search range and screening out adjacent key vehicles;
then, with different track points of the accident vehicle A, B from 10s before the accident happens ((t-9, t-8.. t) to 5s after the accident happens as centers, a continuous area coverage range formed by the radius of 100 meters is used for searching adjacent vehicles, adjacent key vehicles C, E, F are screened out, and vehicles D, G are excluded according to the premise that the vehicle D, G is always in front of the accident vehicle within 10s before the accident happens under the environment, and video information which can be provided is useless for evidence collection, so that the schematic diagram of the adjacent vehicles searched within 100m from 10s before the accident happens is excluded in the inquiry of the accident vehicle A. fig. 4 is a schematic diagram of the adjacent vehicles searched within 100m in 10s before the accident happens.
(4) Requesting the uploading of accident video from the neighboring key vehicles.
There are 3 ways to request that the nearby key vehicle upload the accident video: a workshop searching method, a centralized searching method and a collaborative searching method;
the screened neighboring key vehicles C, E, F are searched by a car search method to make accident evidence. As shown in fig. 5, the accident vehicle A, B issues a command to search for a neighboring key vehicle respectively by vehicle-to-vehicle communication, and performs a first neighboring key vehicle search. After receiving the command, the adjacent key vehicle C, E, F confirms (ACK) to the accident vehicle A, B, and directly uploads the video information of 15s to the server, so that in order to avoid missing, the accident vehicle A, B will issue multiple adjacent key vehicle searching commands within 1 minute, and the search is finished after receiving all the confirmations for the second time. After uploading, the server can confirm (ACK) to the accident vehicle, and the accident evidence obtaining is finished. It is assumed here that only the accident vehicle a has not received the acknowledgement of E for the first time and the accident vehicle B has successfully received the acknowledgement of C, E, F for the first time, by a car-to-car search.
The centralized search method may also be used to search the screened neighboring key vehicles C, E, F for accident evidence. As shown in fig. 6, the accident vehicle sends the video information of the vehicle to the cloud server, the cloud server sends a request to the neighboring key vehicle C, E, F by using the remote communication technology, and requests for the video information directly, and the cloud server sends out a command for searching for the neighboring key vehicle more than once within 5min until the cloud server receives confirmation of all the neighboring key vehicles or the time is up. After uploading, the cloud server may Acknowledge (ACK) the accident vehicle and the neighboring critical vehicle C, E, F, and the accident is forensics.
If the adjacent key vehicle E exceeds the communication range or is out of communication, the vehicle searching method fails because the adjacent key vehicle E cannot be confirmed to the accident vehicle A, B within 1min, and at this time, the cloud server needs to complete evidence obtaining, that is, a collaborative searching method is adopted. As shown in fig. 7, the accident vehicle a/B calls the cloud server to inform the cloud server that the forensics of the adjacent key vehicle E fails, the server sends a request to the adjacent key vehicle E by using a remote communication technology, requests video information directly, and after the uploading is finished, the server informs the accident vehicle a/B that the forensics of the accident vehicle is finished.
After the cloud server receives the video information uploaded by the adjacent key vehicles, in order to reduce the size of the video information as much as possible, reduce the occupation of server resources and ensure sufficient evidence, the video information is filtered by using an information filter, and finally important characteristics are obtained; the information filter is a module that uses a vehicle identification number (vehicle ID), an event number, or other parameters to filter repeatedly uploaded video. For example, the same vehicle may send videos to the server many times due to network communication, and the server may use the information filter to exclude the videos with repetition or high similarity.
Claims (10)
1. A system for searching adjacent key vehicles in traffic accidents is characterized by comprising a cloud server and a vehicle-mounted terminal;
the cloud server comprises a communication module and a calculation module; the communication module is used for carrying out information interaction with the vehicle-mounted terminal, and the calculation module is used for generating a vehicle data table and a neighbor data table and calculating the position of a neighboring key vehicle;
the vehicle-mounted terminal comprises a communication module, a positioning module, a calculation module and a sensor module, wherein the positioning module is used for generating longitude and latitude coordinate positions of the vehicle, the calculation module is used for calculating the time and the speed of the vehicle, the sensor module is used for calculating the acceleration value of the vehicle, and the communication module is used for carrying out information interaction with the cloud server;
the vehicle is connected with the internet through a wireless network or a mobile network to form communication networks between vehicles and between the vehicles and a server for identity authentication, message interaction and data updating;
the identity authentication is that the vehicle utilizes a communication network to connect a server and a block chain to carry out public key exchange; the message interaction is that the vehicle sends characteristic messages of the vehicle to the cloud server and adjacent vehicles according to a certain period so as to maintain a vehicle data table or a neighbor data table, wherein the characteristic messages comprise longitude and latitude coordinate positions, time, speed, track and acceleration values; one of the data updating operations is that any vehicle receives the characteristic message sent by the adjacent vehicle and updates the neighbor data table of the vehicle in real time; the data update step two is a vehicle data table of each vehicle real-time position updated by the server by using the characteristic message sent by the vehicle.
2. The system of claim 1, wherein the communication module employs a satellite cloud interconnected intelligent drive test terminal T-Station or a Hua Li Zhi Row MOCAR I-Classic RSE, the computing module employs Amazon EC2, the positioning module employs a satellite cloud interconnected intelligent vehicle-mounted terminal V-Box or a Hua Li Zhi Row MOCAR V-Classic OBE, and the sensor module employs a Beijing technology AKE 392B.
3. The system of claim 2, wherein the message interaction period is every 1-10 seconds.
4. A proximity-critical vehicle-searching system for traffic accidents according to claim 3, characterized in that the proximity vehicles are vehicles at a mutual distance between 0m and 1000 m.
5. A searching method of the adjacent key vehicle searching system for traffic accident according to claim 4, comprising the steps of:
(1) the vehicle regularly sends the characteristic information of the vehicle to the adjacent vehicle and the cloud server by using a communication network so as to maintain a vehicle data table and update a neighbor data table in real time;
(2) when a traffic accident occurs, the accident vehicle uploads the characteristic information of the accident vehicle to a cloud server for storage and recording; meanwhile, a computing module of the cloud server acquires road characteristics and road section types by combining a high-precision electronic map according to longitude and latitude coordinate positions of accident vehicles, eliminates irrelevant vehicles, and preliminarily judges the search range of key vehicles adjacent to the accident; the road section types comprise double/single direction and isolation belts or not;
(3) narrowing the search range and screening out adjacent key vehicles;
(4) requesting the uploading of accident video from the neighboring key vehicles.
6. The method according to claim 5, wherein in step (2), the uploading of the feature information of the accident vehicle comprises automatic vehicle uploading and manual vehicle occupant uploading; the automatic uploading of the vehicle is to trigger an automatic uploading instruction when the vehicle-mounted sensor module monitors abnormity.
7. The searching method of the adjacent key vehicle searching system for the traffic accident according to claim 5, wherein the excluding of the irrelevant vehicle in the step (2) comprises: when the accident occurs on a one-way road, no oncoming vehicle exists, and the exclusion is not needed; when an accident occurs on a bidirectional road, if isolation zones exist among lanes and vehicles coming from opposite lanes cannot shoot the traffic accident due to the fact that the isolation zones are shielded, the vehicles coming from opposite lanes need to be excluded when adjacent key vehicles are found out, and only vehicles running in the same direction are considered; if the isolation belt does not exist, the oncoming car has certain evidence obtaining value, so the oncoming car is not excluded.
8. The searching method of the adjacent key vehicle searching system for the traffic accident according to claim 5, wherein the step (3) of screening the adjacent key vehicles comprises the following two ways:
in the first mode, a computing module of a cloud server inquires a vehicle data table;
in the second mode, a neighbor data table is inquired by a calculation module of the accident vehicle;
the first method is as follows:
after receiving the characteristic information of the accident vehicle, the cloud server selects a certain time interval before and after the occurrence of the traffic accident, from n seconds before the occurrence of the accident to m seconds before and after the occurrence of the accident, preferably, the certain time interval before and after the occurrence of the traffic accident is from 10 seconds before to 5 seconds after the occurrence of the accident; screening out related vehicles in a search range by taking an accident vehicle track site as a center, wherein the search range is a continuous area coverage range formed by taking a running track of an accident vehicle from n seconds before an accident happens to m seconds after the accident happens as a circle center and taking a radius r meter as an adjacent key vehicle, and preferably, r is preset to be 100 m; the screening mode is that SQL language is used for screening or array traversal is used for realizing screening;
the second method comprises the following steps:
the accident vehicle screens out related vehicles in a search range by taking an accident vehicle track site as a center within a certain time period before and after a traffic accident, wherein the search range is a driving track of the accident vehicle from n seconds before the accident to m seconds after the accident as a circle center, and a continuous area coverage range formed by r meters in radius is an adjacent key vehicle, and the screening mode is realized by using an SQL language or a traversing array mode.
9. The searching method of the adjacent key vehicle searching system for traffic accident according to claim 8, wherein in the step (4), there are 3 ways to request the adjacent key vehicle to upload the accident video: a workshop searching method, a centralized searching method and a collaborative searching method;
(1) workshop searching method
The accident vehicle finds out the adjacent key vehicles by the second method, and then sends out searching commands to the adjacent key vehicles by vehicle-to-vehicle communication to perform the first searching; after receiving the instruction, the adjacent key vehicles reply confirmation to the accident vehicle and directly upload video information of the vehicle-mounted automobile data recorder shooting accident occurrence specific time period to the server; if the accident vehicle does not receive the reply confirmation of all the adjacent key vehicles, more than two adjacent key vehicle searching commands are sent within a certain time until the accident vehicle receives the confirmation or the time of all the adjacent key vehicles is cut off, preferably, the time of the searching commands is 1-5 min; after uploading, the server can confirm the accident vehicle and the accident evidence obtaining is finished;
(2) centralized searching method
The accident vehicle sends video information of the vehicle to the cloud server, and the cloud server screens out the adjacent key vehicles in a first mode, sends a request to the adjacent key vehicles through a remote communication technology and directly asks for the video information of the adjacent key vehicles; if the cloud server does not receive reply confirmation of all the adjacent key vehicles within a certain time, sending more than one instruction for searching the adjacent key vehicles until the cloud server receives confirmation of all the adjacent key vehicles or the time is up; after uploading, the cloud server confirms the accident vehicle and the adjacent key vehicles, and the accident evidence obtaining is finished;
(3) collaborative search method
The collaborative searching method is that a workshop searching method and a centralized searching method participate in searching together, firstly, the workshop searching method is used for searching, when an accident vehicle does not receive confirmation of all adjacent key vehicles by using the workshop searching method, the centralized searching method is used for searching, and a request is sent to the adjacent key vehicles through a cloud server to ask for video information.
10. The searching method of the system for searching vehicles close to the key vehicles in traffic accidents according to claim 9, wherein in the step (4), after the cloud server receives the video information uploaded by the close key vehicles, the video information is filtered by using an information filter, and finally the important features are obtained; the information filter is a module, and filters repeatedly uploaded videos by using vehicle identification codes and event numbers.
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