CN115346370A - Intersection anti-collision system and method based on intelligent traffic - Google Patents
Intersection anti-collision system and method based on intelligent traffic Download PDFInfo
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
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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
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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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
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
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Abstract
The invention relates to the technical field of traffic safety, and particularly discloses an intersection anti-collision system and method based on intelligent traffic, wherein the method comprises the following steps: s1, acquiring traffic information of a crossing; s2, identifying a lane where the vehicle is located and a license plate number; s3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not, and if so, marking as an abnormal vehicle; s4, judging whether the identified license plate number contains a pre-stored license plate number of the target vehicle, and if so, estimating the running track of the target vehicle passing through the intersection; s5, judging whether the license plate number identified contains the license plate number of the abnormal vehicle, if so, estimating the running track of the abnormal vehicle passing through the intersection; and S6, judging whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection or not based on the running tracks of the target vehicle and the abnormal vehicle, and if so, pushing early warning information to the mobile terminal of the target vehicle. By adopting the technical scheme of the invention, the potential danger around the target vehicle can be early warned in advance.
Description
Technical Field
The invention relates to the technical field of traffic safety, in particular to an intersection anti-collision system and method based on intelligent traffic.
Background
With the increasing number of traffic participants, road condition information is becoming more and more complex, and in order to reduce the probability of accidents, two main types of existing traffic intersection collision prevention early warning systems are provided, one type is that a camera, a millimeter wave radar and other sensors are utilized at the vehicle end to collect data around a vehicle body and analyze and process the data, so that a collision prevention early warning result is obtained. The method has the defects that the calculated pressure of the vehicle end is large, the early warning range is small, and the response time left for the vehicle end is short. The other method is that GPS data of vehicles and pedestrians are received by using a roadside communication unit and edge calculation on the roadside, collision prevention early warning is obtained through analysis, and then the alarm is transmitted to the vehicles.
Therefore, there is a need for an intelligent traffic-based intersection collision avoidance system and method that can early warn of potential hazards around a target vehicle.
Disclosure of Invention
One of the purposes of the invention is to provide an intersection anti-collision method based on intelligent traffic, which can early warn potential dangers around a target vehicle in advance.
In order to solve the technical problem, the present application provides the following technical solutions:
the intersection anti-collision method based on intelligent traffic comprises the following steps.
S1, acquiring traffic information of a road junction from road side equipment;
s2, identifying the lane where the vehicle is located and the license plate number according to the traffic information;
s3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not according to the traffic information, if so, marking the vehicle as an abnormal vehicle, and recording the license plate number;
s4, judging whether the identified license plate number contains a pre-stored license plate number of the target vehicle, and if so, acquiring a navigation route of the target vehicle from a mobile terminal corresponding to the target vehicle; estimating the running track of the target vehicle passing through the intersection according to the lane where the target vehicle is located and the navigation route;
s5, judging whether the identified license plate number contains the license plate number of the abnormal vehicle, if so, estimating the running track of the abnormal vehicle passing through the intersection according to the lane where the abnormal vehicle is located;
and S6, judging whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection or not based on the running tracks of the target vehicle and the abnormal vehicle, and if so, pushing early warning information to the mobile terminal of the target vehicle.
The basic scheme principle and the beneficial effects are as follows:
in the scheme, vehicles with abnormal running tracks are identified in advance and recorded, after a target vehicle enters a monitoring range of an intersection, whether recorded abnormal vehicles exist is judged, if the recorded abnormal vehicles exist, the abnormal vehicles do not run according to traffic rules and possibly interfere with normal running of the target vehicle, so that the running tracks of the target vehicle and the abnormal vehicles are estimated, whether the target vehicle and the abnormal vehicles are in adjacent lanes when passing through the intersection is judged, if the abnormal vehicles are in the adjacent lanes, the possibility of interfering the target vehicle exists in the abnormal vehicles, and early warning can be given to the target vehicle in advance by pushing early warning information to a mobile terminal of the target vehicle, so that a driver of the target vehicle can avoid the abnormal vehicles in advance.
Therefore, the potential danger around the target vehicle can be early warned in advance, and the accident probability is reduced.
Further, in step S6, it is further determined whether the target vehicle and the abnormal vehicle intersect with each other on the basis of the traveling tracks of the target vehicle and the abnormal vehicle, and if the traveling tracks intersect with each other, the warning information is pushed to the mobile terminal of the target vehicle.
Further, in the step S3, matching the actual running track of the vehicle passing through the intersection according to a preset rule of violation running, if the matching is successful, determining that the vehicle is abnormal, and recording the license plate number and the violation type of the abnormal vehicle; the violation types comprise solid line lane changing and turning lane changing;
in step S6, when the violation type of the abnormal vehicle is a solid line lane change or a turning lane change, whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection is judged based on the running track of the abnormal vehicle, and if the target vehicle and the abnormal vehicle are in the adjacent lanes, early warning information is pushed to the mobile terminal of the target vehicle.
For example, both the target vehicle and the abnormal vehicle wait for a left turn at the intersection, when the target vehicle is located on the left side of the abnormal vehicle; and early warning information of turning attention to the lane change of the right vehicle is pushed to the mobile terminal of the target vehicle so as to remind a driver of paying attention to the abnormal right vehicle, and if the abnormal right vehicle invades the running route of the target vehicle, the abnormal right vehicle can be timely disposed.
Further, in step S3, the violation type further includes an emergency stop; acquiring the speed of a vehicle from traffic information, judging whether the vehicle suddenly stops at a stop line of an intersection or not based on the change of the speed, acquiring traffic light information from roadside equipment if the vehicle suddenly stops, judging whether the remaining time of a green light of a traffic light is within a preset range or not when the vehicle suddenly stops, marking the vehicle as an abnormal vehicle if the vehicle suddenly stops, and recording the violation type of the abnormal vehicle as the sudden stop;
in step S6, whether the target vehicle and the abnormal vehicle are in the same lane when passing through the intersection is judged based on the running tracks of the target vehicle and the abnormal vehicle, if so, whether the abnormal vehicle is a front vehicle of the target vehicle is judged, if so, whether the remaining time of a traffic light green light is within a preset range when the abnormal vehicle reaches an intersection stop line is judged based on the current speed of the abnormal vehicle, and if so, early warning information is pushed to a mobile terminal of the target vehicle.
For example, the remaining time of the green light at the time of the scram is 2 seconds, when the vehicle can normally pass, but the scram is selected to indicate whether the vehicle can judge that there is a deviation by the traffic light, so that the vehicle is marked as an abnormal vehicle. When the target vehicle runs along with the abnormal vehicle and the current speed of the abnormal vehicle reaches the intersection stop line, the remaining time of the traffic light is within the preset range, the abnormal vehicle can adopt emergency braking because the judgment is inaccurate, the target vehicle can be easily caused to collide with the rear, and the target vehicle can be reminded by pushing early warning information.
Further, in step S6, when the abnormal vehicle reaches the intersection stop line, and the remaining time of the traffic light green is within the preset range, the warning information is pushed to the mobile terminal of the target vehicle, the driving experience information of the driver is also acquired from the mobile terminal of the target vehicle, and the processing advice is generated based on the driving experience information and pushed to the mobile terminal of the target vehicle.
For example, for a novice driver, the generated processing suggestion is the deceleration of an original lane, and for an acquaintance driver, the generated suggestion information is lane change on the premise of ensuring safety so as to improve the traffic efficiency of a road.
Further, still include:
s7, identifying the pedestrian according to the traffic information, judging whether the pedestrian is in the road, and if so, estimating the moving track of the pedestrian according to the current moving direction of the pedestrian;
and S8, judging whether the moving track of the pedestrian is crossed with the running track of the target vehicle, if so, judging whether the pedestrian is in a blind area of the target vehicle, and if so, pushing early warning information to a mobile terminal of the target vehicle.
Further, in the step S7, the current state of the pedestrian is also identified, whether the pedestrian is in an uncontrollable state is determined, and if the pedestrian is in an uncontrollable state, the pedestrian is marked;
in step S8, if the moving track of the pedestrian intersects with the traveling track of the target vehicle, it is determined whether the pedestrian is marked, if so, the warning information is pushed to the mobile terminal of the target vehicle, and if not, it is determined whether the pedestrian is in the blind area of the target vehicle.
For example, a pedestrian is in a state of looking at a mobile phone, and is determined to be in an uncontrollable state without paying attention to a road condition. Under the condition, even if the driver does not have a vision blind area, the marked pedestrians need to be paid more attention, and the driver can be reminded to pay attention to observation in advance by pushing early warning information, so that the accident probability is reduced.
Further, still include:
s9, judging whether the moving track of the pedestrian is crossed with the running tracks of other vehicles at the intersection or not, and if the moving track of the pedestrian is crossed with the running tracks of the other vehicles at the intersection, marking the crossed vehicle as a vehicle to be reminded;
and judging whether the target vehicle shields the vehicle to be reminded to observe the pedestrian, if so, pushing a reminding operation suggestion to the mobile terminal of the target vehicle according to the relative position of the target vehicle and the vehicle to be reminded.
The to-be-reminded vehicle can not observe the pedestrian in advance because of the visual blind area that the target vehicle caused, does not have enough time to slow down and collide with the pedestrian when leading to observing the pedestrian, through reminding the operation suggestion to the propelling movement of target vehicle, can let the driver of target vehicle treat according to reminding the operation suggestion and remind the vehicle of reminding, reduces the probability that the accident took place.
Further, in the step S9, after it is determined that the target vehicle blocks the vehicle to be reminded from observing pedestrians, the driving experience information of the driver is obtained from the mobile terminal of the target vehicle, a reminding operation suggestion is generated according to the relative position between the target vehicle and the vehicle to be reminded and the driving experience information, and the reminding operation suggestion is pushed to the mobile terminal of the target vehicle.
The invention also aims to provide an intersection anti-collision system based on intelligent traffic and use the method.
Drawings
Fig. 1 is a logic block diagram of an intersection collision avoidance system based on intelligent transportation according to an embodiment.
Detailed Description
The following is further detailed by way of specific embodiments:
example one
As shown in fig. 1, the intersection anti-collision method based on intelligent transportation of the embodiment includes the following contents:
s1, acquiring traffic information of a road junction from road side equipment; in this embodiment, the acquired traffic information includes a monitoring video of the intersection and a speed of the vehicle.
S2, identifying the lane where the vehicle is located and the license plate number according to the traffic information; specifically, the identification is performed through monitoring videos.
S3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not according to the traffic information, if so, marking the vehicle as an abnormal vehicle, and recording the license plate number;
specifically, the violation types comprise solid line lane changing, turning lane changing and sudden stop; the identification modes of the solid line lane changing and the turning lane changing are as follows: matching the actual running track of the vehicle passing through the intersection according to preset illegal running rules including solid line lane changing and turning lane changing, if the matching is successful, judging that the vehicle is abnormal, and recording the license plate number and the illegal type of the abnormal vehicle;
for example, when a vehicle turns left at an intersection, left-turning lanes are sequentially recorded as a lane 1 and a lane 2 from right to left, and correspondingly, lanes after left-turning are sequentially recorded as a lane 3 and a lane 4 from right to left, under a normal condition, the vehicle on the lane 1 turns left and enters the lane 3, and the vehicle on the lane 2 turns left and enters the lane 4, and if the vehicle turns left, the vehicle enters the lane 3 from the lane 2 and is considered to turn and change lanes.
The identification mode of the sudden stop is as follows: the method comprises the steps of obtaining the speed of a vehicle from traffic information, judging whether the vehicle suddenly stops at a stop line of an intersection or not based on the change of the speed, obtaining traffic light information from roadside equipment if the vehicle suddenly stops, judging whether the remaining time of a green light of a traffic light is within a preset range or not during sudden stop, marking the vehicle as an abnormal vehicle if the vehicle suddenly stops, recording the license plate number of the abnormal vehicle, and recording the violation type of the abnormal vehicle as sudden stop. In the embodiment, the vehicle speed is decelerated to 0km/h from more than or equal to 30km/h hour, and the deceleration time is less than 3 seconds, so that the vehicle is regarded as being suddenly stopped at the stop line of the intersection.
S4, judging whether the identified license plate number contains a pre-stored license plate number of the target vehicle, and if so, acquiring a navigation route of the target vehicle from a mobile terminal corresponding to the target vehicle; estimating a running track of the target vehicle when the target vehicle passes through the intersection according to the lane where the target vehicle is located and the navigation route;
s5, judging whether the identified license plate number contains the license plate number of the abnormal vehicle, if so, estimating the running track of the abnormal vehicle passing through the intersection according to the lane where the abnormal vehicle is located;
and S6, when the violation type of the abnormal vehicle is a solid line lane change or a turning lane change, judging whether the target vehicle and the abnormal vehicle are in an adjacent lane when passing through the intersection or not based on the running track of the abnormal vehicle, and if so, pushing early warning information to the mobile terminal of the target vehicle. In this embodiment, different warning information is pushed under different conditions.
For example, the target vehicle and the abnormal vehicle both wait for left turn at the intersection, and at this time, the target vehicle is located in lane No. 2, and the abnormal vehicle is located in lane No. 1; and early warning information of turning attention right-side vehicle lane change is pushed to a mobile terminal of the target vehicle to remind a driver of paying attention to the right-side abnormal vehicle, and if the abnormal vehicle invades the running route of the target vehicle, the abnormal vehicle can be disposed in time.
And when the violation type of the abnormal vehicle is a solid line lane change or a turning lane change, judging whether the target vehicle and the abnormal vehicle are crossed on the basis of the running tracks of the target vehicle and the abnormal vehicle, and if so, pushing early warning information to the mobile terminal of the target vehicle. For example, the abnormal vehicle is a certain black SUV, the license plate number is yu AXXXXX, the target vehicle passes through the intersection straight, the abnormal vehicle turns right at the intersection, the target vehicle and the abnormal vehicle are converged after passing through the intersection, and the pushed early warning information is "attention to the certain black SUV converged on the right side".
When the violation type of the abnormal vehicle is sudden stop, whether the target vehicle and the abnormal vehicle are in the same lane when passing through the intersection is judged based on the running tracks of the target vehicle and the abnormal vehicle, if so, whether the abnormal vehicle is a front vehicle of the target vehicle is judged, if yes, whether the remaining time of a traffic light green light is within a preset range is judged when the abnormal vehicle reaches an intersection stop line based on the current speed of the abnormal vehicle, and if yes, early warning information is pushed to a mobile terminal of the target vehicle. In this embodiment, the predetermined range is 1 to 4 seconds. For example, when it is determined that an abnormal vehicle reaches an intersection stop line, the remaining time of the traffic light is 2 seconds, and the pushed early warning information is "the vehicle ahead has an emergency stop risk, please keep the distance between the vehicles, and control the speed of the vehicle".
In this embodiment, driving experience information of the driver is also acquired from the mobile terminal of the target vehicle, and a processing advice is generated and pushed to the mobile terminal of the target vehicle based on the driving experience information. The driving experience information includes novice or acquaintance, which is entered in advance by the driver. When the driver is a new driver, the pushed processing suggestion is 'suggestion waiting for next green light', when the driver is an old driver, whether the target vehicle has a lane change condition (the condition of having the lane change indicates that the current lane can be changed and the adjacent lane has a space) is judged according to the monitoring video, and if the target vehicle has the lane change condition, the pushed processing suggestion is 'suggestion of changing the lane after observation'.
S7, identifying the pedestrian according to the monitoring video in the traffic information, judging whether the pedestrian is in the road, and if so, estimating the moving track of the pedestrian according to the current moving direction of the pedestrian; the road referred to in the present embodiment is a road on which motor vehicles travel. And identifying the current state of the pedestrian, judging whether the pedestrian is in an uncontrollable state, and marking the pedestrian if the pedestrian is in the uncontrollable state. In this embodiment, when the pedestrian is in a state of looking at the mobile phone, carrying the article, or using the vehicle (e.g., balance car, skateboard), it is determined as an uncontrollable state.
S8, judging whether the moving track of the pedestrian is crossed with the running track of the target vehicle or not, if so, judging whether the pedestrian is marked or not, if so, pushing early warning information to the mobile terminal of the target vehicle, if not, judging whether the pedestrian is in the blind area of the target vehicle or not, and if not, pushing the early warning information to the mobile terminal of the target vehicle. For example, the warning information is "pedestrian caution".
S9, judging whether the moving track of the pedestrian is crossed with the running tracks of other vehicles at the intersection or not, and if the crossing exists, marking the crossed vehicle as a vehicle to be reminded;
and judging whether the target vehicle shields the vehicle to be reminded to observe the pedestrian, if so, pushing a reminding operation suggestion to the mobile terminal of the target vehicle according to the relative position of the target vehicle and the vehicle to be reminded.
For example, the target vehicle and the vehicle to be reminded are ready to go straight at the intersection, the straight lane is sequentially marked as lane 1 and lane 2 from right to left, the target vehicle is located on lane 2, the vehicle to be reminded is located on lane 1, that is, the target vehicle is located on the left side of the vehicle to be reminded, the pedestrian crosses the road from the left side of the target vehicle, there is a risk of collision with the target vehicle or the vehicle to be reminded, at this time, the target vehicle observes the pedestrian after receiving the warning information and starts to decelerate, the vehicle to be reminded beside does not decelerate, because the target vehicle obstructs the left view of the vehicle to be reminded, if the vehicle to be reminded continues to keep running at the current speed, collision with the pedestrian may occur.
Based on the method, the embodiment further provides an intersection anti-collision system based on intelligent transportation, as shown in fig. 1, including a server, roadside equipment, and a mobile terminal.
The roadside device comprises a monitoring camera and a speed measuring camera, wherein the monitoring camera is used for acquiring a monitoring video of the intersection, analyzing the monitoring video, and identifying and marking vehicles, pedestrians and obstacles in the monitoring video. The speed measuring camera is used for collecting the speed of the vehicle.
In this embodiment, the mobile terminal is a smart phone loaded with an APP and is connected to the server through the internet. The mobile terminal is used for uploading the navigation route of the target vehicle, allowing a driver to input driving experience information, and displaying early warning information and reminding operation suggestions. The server is adapted to perform the steps of the above-described methods S1-S9.
Example two
The difference between the present embodiment and the first embodiment is that, in the method in the present embodiment, in step S9, after it is determined that the target vehicle blocks the vehicle to be reminded from observing pedestrians, the driving experience information of the driver is obtained from the mobile terminal of the target vehicle, a reminding operation suggestion is generated according to the relative position between the target vehicle and the vehicle to be reminded and the driving experience information, and the reminding operation suggestion is pushed to the mobile terminal of the target vehicle.
For example, the target vehicle and the vehicle to be reminded are ready to go straight at the intersection, the target vehicle is located in lane 2, the vehicle to be reminded is located in lane 1, that is, the target vehicle is located on the left side of the vehicle to be reminded, and the pedestrian crosses the road from the left side of the target vehicle, so that there is a risk of collision with the target vehicle or the vehicle to be reminded.
For another example, the target vehicle and the vehicle to be reminded are ready to go straight at the intersection, the target vehicle is located in lane 1, the vehicle to be reminded is located in lane 2, that is, the target vehicle is located on the right side of the vehicle to be reminded, and the pedestrian crosses the road from the right side of the target vehicle, so that there is a risk of collision with the target vehicle or the vehicle to be reminded. That is, the expert will suggest to make a lane change to the left in the original lane, as opposed to the novice. When the vehicle to be reminded observes that the target vehicle tends to change lane to the left, the observation is usually enhanced, and the speed is reduced, so that the risk of collision with the pedestrian is reduced.
EXAMPLE III
The difference between the embodiment and the second embodiment is that in the method of the embodiment, step S3, it is further determined whether the speed of the vehicle passing through the intersection is greater than the preset speed according to the traffic information, and if the speed is greater than the preset speed, the vehicle is marked as a concerned vehicle, and the license plate number is recorded. The preset speed can be set according to the actual speed limit of the intersection. In the embodiment, the speed limit of the intersection is 30km/h, the preset speed is 28km/h, and in other embodiments, the preset speed can be reduced to 25km/h to expand the screening range.
Step S9, after the target vehicle is judged to shield the vehicle to be reminded from observing pedestrians, whether the vehicle to be reminded is a concerned vehicle is judged according to the license plate number, if not, a reminding operation suggestion is generated according to the relative position of the target vehicle and the vehicle to be reminded and the driving experience information, and the reminding operation suggestion is pushed to the mobile terminal of the target vehicle;
and if so, pushing a fixed reminding operation suggestion to the mobile terminal of the target vehicle. In this embodiment, the fixed reminder operation suggestion is a whistling reminder.
For most drivers, the observation is enhanced, as well as the deceleration, after observing the intention of the vehicle in the side lane to merge into the own lane. But there is still a portion of the driving style that is relatively aggressive for the driver, choosing to accelerate to prevent the merging of vehicles in the side lanes. In the embodiment, the drivers with relatively sharp driving styles can be screened out by judging whether the speed of the vehicles passing through the intersection is greater than the preset speed, and only whistling reminding is carried out when the vehicles driven by the drivers are to be reminded, so that adverse effects are avoided.
The above are merely examples of the present invention, and the present invention is not limited to the field related to this embodiment, and the common general knowledge of the known specific structures and characteristics in the schemes is not described herein too much, and those skilled in the art can know all the common technical knowledge in the technical field before the application date or the priority date, can know all the prior art in this field, and have the ability to apply the conventional experimental means before this date, and those skilled in the art can combine their own ability to perfect and implement the scheme, and some typical known structures or known methods should not become barriers to the implementation of the present invention by those skilled in the art in light of the teaching provided in the present application. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The intersection anti-collision method based on intelligent traffic is characterized by comprising the following contents:
s1, acquiring traffic information of a road junction from road side equipment;
s2, identifying the lane where the vehicle is located and the license plate number according to the traffic information;
s3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not according to the traffic information, if so, marking the vehicle as an abnormal vehicle, and recording the license plate number;
s4, judging whether the identified license plate number contains a prestored license plate number of the target vehicle, and if so, acquiring a navigation route of the target vehicle from a mobile terminal corresponding to the target vehicle; predicting the running track of the target vehicle passing through the intersection according to the lane of the target vehicle and the navigation route;
s5, judging whether the identified license plate number contains the license plate number of the abnormal vehicle, if so, estimating the running track of the abnormal vehicle passing through the intersection according to the lane where the abnormal vehicle is located;
and S6, judging whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection or not based on the running tracks of the target vehicle and the abnormal vehicle, and if so, pushing early warning information to the mobile terminal of the target vehicle.
2. The intelligent transportation based intersection collision prevention method as claimed in claim 1, wherein: in the step S6, whether the target vehicle and the abnormal vehicle are crossed in the running track is further determined based on the running tracks of the target vehicle and the abnormal vehicle, and if the running tracks are crossed, the early warning information is pushed to the mobile terminal of the target vehicle.
3. The intelligent transportation based intersection anti-collision method according to claim 2, wherein: in the step S3, matching the actual running track of the vehicle passing through the intersection according to a preset violation running rule, if the matching is successful, judging that the vehicle is abnormal, and recording the license plate number and the violation type of the abnormal vehicle; the violation types comprise solid line lane changing and turning lane changing;
in step S6, when the violation type of the abnormal vehicle is a solid line lane change or a turning lane change, whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection is judged based on the running track of the abnormal vehicle, and if the target vehicle and the abnormal vehicle are in the adjacent lanes, early warning information is pushed to the mobile terminal of the target vehicle.
4. The intelligent transportation based intersection anti-collision method according to claim 3, wherein: in the step S3, the violation type further includes an emergency stop; acquiring the speed of a vehicle from traffic information, judging whether the vehicle suddenly stops at a stop line of an intersection or not based on the change of the speed, acquiring traffic light information from roadside equipment if the vehicle suddenly stops, judging whether the remaining time of a green light of a traffic light is within a preset range or not when the vehicle suddenly stops, marking the vehicle as an abnormal vehicle if the vehicle suddenly stops, and recording the violation type of the abnormal vehicle as the sudden stop;
and S6, judging whether the target vehicle and the abnormal vehicle are in the same lane when passing through the intersection or not based on the running tracks of the target vehicle and the abnormal vehicle, judging whether the abnormal vehicle is a front vehicle of the target vehicle or not if the abnormal vehicle is in the same lane, judging whether the residual time of a traffic light is in a preset range or not when the abnormal vehicle reaches an intersection stop line based on the current speed of the abnormal vehicle if the abnormal vehicle is in the same lane, and pushing early warning information to a mobile terminal of the target vehicle if the abnormal vehicle reaches the intersection stop line.
5. The intelligent transportation based intersection collision prevention method as claimed in claim 4, wherein: in step S6, when the abnormal vehicle reaches the intersection stop line, the remaining time of the traffic light green light is within the preset range, the warning information is pushed to the mobile terminal of the target vehicle, the driving experience information of the driver is also acquired from the mobile terminal of the target vehicle, and the processing advice is generated based on the driving experience information and pushed to the mobile terminal of the target vehicle.
6. The intelligent transportation based intersection anti-collision method according to claim 5, wherein: further comprising:
s7, identifying the pedestrian according to the traffic information, judging whether the pedestrian is in the road, and if so, estimating the moving track of the pedestrian according to the current moving direction of the pedestrian;
and S8, judging whether the moving track of the pedestrian is crossed with the running track of the target vehicle, judging whether the pedestrian is in a blind area of the target vehicle if the moving track of the pedestrian is crossed with the running track of the target vehicle, and pushing early warning information to the mobile terminal of the target vehicle if the pedestrian is in the blind area of the target vehicle.
7. The intelligent transportation based intersection anti-collision method as claimed in claim 6, wherein: in the step S7, the current state of the pedestrian is also identified, whether the pedestrian is in an uncontrollable state is determined, and if the pedestrian is in an uncontrollable state, the pedestrian is marked;
in step S8, if the moving track of the pedestrian intersects with the traveling track of the target vehicle, it is determined whether the pedestrian is marked, if the pedestrian is marked, the warning information is pushed to the mobile terminal of the target vehicle, and if the pedestrian is not marked, it is determined whether the pedestrian is in the blind area of the target vehicle.
8. The intelligent transportation based intersection anti-collision method according to claim 7, wherein: further comprising:
s9, judging whether the moving track of the pedestrian is crossed with the running tracks of other vehicles at the intersection or not, and if the crossing exists, marking the crossed vehicle as a vehicle to be reminded;
and judging whether the target vehicle shields the vehicle to be reminded to observe the pedestrian, if so, pushing a reminding operation suggestion to the mobile terminal of the target vehicle according to the relative position of the target vehicle and the vehicle to be reminded.
9. The intelligent transportation based intersection anti-collision method according to claim 8, wherein: in the step S9, after it is determined that the target vehicle blocks the vehicle to be reminded from observing pedestrians, the driving experience information of the driver is obtained from the mobile terminal of the target vehicle, a reminding operation suggestion is generated according to the relative position of the target vehicle and the vehicle to be reminded and the driving experience information, and the reminding operation suggestion is pushed to the mobile terminal of the target vehicle.
10. An intelligent traffic based intersection collision avoidance system, characterized in that the method of any of claims 1-9 is used.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116894225A (en) * | 2023-09-08 | 2023-10-17 | 国汽(北京)智能网联汽车研究院有限公司 | Driving behavior abnormality analysis method, device, equipment and medium thereof |
Citations (48)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008097413A (en) * | 2006-10-13 | 2008-04-24 | Mitsubishi Electric Corp | In-vehicle system for providing safety support information |
| JP2009134334A (en) * | 2007-11-28 | 2009-06-18 | Denso Corp | Vehicle control device |
| US20100063725A1 (en) * | 2008-08-07 | 2010-03-11 | Aisin Aw Co., Ltd. | Safe driving evaluation system, method, and program |
| US20110102166A1 (en) * | 2009-10-30 | 2011-05-05 | Ford Global Technologies, Llc | Vehicle and method of advising a driver therein |
| CN202480973U (en) * | 2012-02-02 | 2012-10-10 | 王林 | Device for hinting appreciation during lane-changing and turning of vehicle |
| WO2014084593A1 (en) * | 2012-11-29 | 2014-06-05 | 한국교통연구원 | Apparatus and method for supporting safe driving |
| CN104537860A (en) * | 2015-01-12 | 2015-04-22 | 小米科技有限责任公司 | Traffic safety prompting method and device |
| CN105448094A (en) * | 2015-12-31 | 2016-03-30 | 重庆云途交通科技有限公司 | Wrong-direction running warning and risk avoiding method based on vehicle and road cooperation technology |
| CN105844965A (en) * | 2016-05-06 | 2016-08-10 | 深圳市元征科技股份有限公司 | Vehicle distance prompting method and device |
| CN105989745A (en) * | 2015-02-05 | 2016-10-05 | 华为技术有限公司 | Acquisition method, apparatus and system of vehicle violation information |
| CN106494409A (en) * | 2016-11-04 | 2017-03-15 | 大连文森特软件科技有限公司 | Based on AR augmented realities and the drive assist system of the wagon control of big data |
| CN106530831A (en) * | 2016-12-15 | 2017-03-22 | 江苏大学 | System and method for monitoring and early warning of high-threat vehicles |
| US20170113665A1 (en) * | 2015-10-27 | 2017-04-27 | GM Global Technology Operations LLC | Algorithms for avoiding automotive crashes at left and right turn intersections |
| US20170113683A1 (en) * | 2015-10-27 | 2017-04-27 | GM Global Technolgy Operations LLC | Methods of improving performance of automotive intersection turn assist features |
| WO2018032642A1 (en) * | 2016-08-19 | 2018-02-22 | 深圳市元征科技股份有限公司 | Driving vehicle collision warning method and device |
| CN108289108A (en) * | 2016-09-05 | 2018-07-17 | 西安艾润物联网技术服务有限责任公司 | Information presentation system and method |
| CN109005239A (en) * | 2018-08-21 | 2018-12-14 | 哈尔滨工业大学 | Intelligent information exchange method, system and device for assisting vehicle travel |
| JP2019032710A (en) * | 2017-08-08 | 2019-02-28 | パイオニア株式会社 | Determination device, method for determination, and program |
| CN109658700A (en) * | 2019-03-05 | 2019-04-19 | 上汽大众汽车有限公司 | Intersection anti-collision prewarning apparatus and method for early warning |
| CN109979239A (en) * | 2017-12-28 | 2019-07-05 | 北京百度网讯科技有限公司 | Violation vehicle based reminding method, device and equipment |
| CN110310481A (en) * | 2019-06-28 | 2019-10-08 | 浙江吉利控股集团有限公司 | A kind of vehicle collision prewarning method, device and equipment |
| CN110502012A (en) * | 2019-08-20 | 2019-11-26 | 武汉中海庭数据技术有限公司 | His a kind of wheel paths prediction technique, device and storage medium |
| CN209708113U (en) * | 2018-11-15 | 2019-11-29 | 郭涵之 | Driver reminds the alarm set of pedestrian or vehicle evacuation |
| CN111127950A (en) * | 2019-12-27 | 2020-05-08 | 北京万集智能网联技术有限公司 | Vehicle collision early warning processing method and device |
| JP2020076642A (en) * | 2018-11-07 | 2020-05-21 | ヤフー株式会社 | Information processing device, information processing method, and information processing program |
| US20200168099A1 (en) * | 2017-06-07 | 2020-05-28 | Mitsubishi Electric Corporation | Hazardous vehicle prediction device, hazardous vehicle warning system, and hazardous vehicle prediction method |
| CN111540237A (en) * | 2020-05-19 | 2020-08-14 | 河北德冠隆电子科技有限公司 | Method for automatically generating vehicle safety driving guarantee scheme based on multi-data fusion |
| CN211642010U (en) * | 2019-09-19 | 2020-10-09 | 罗霞 | Light projection alarm for automobile glass |
| CN111915914A (en) * | 2019-05-09 | 2020-11-10 | 奥迪股份公司 | Vehicle driving assistance system and method, and corresponding computer-readable storage medium |
| CN111932941A (en) * | 2020-08-24 | 2020-11-13 | 重庆大学 | Intersection vehicle early warning method and system based on vehicle-road cooperation |
| KR20200133122A (en) * | 2019-05-17 | 2020-11-26 | 현대모비스 주식회사 | Apparatus and method for preventing vehicle collision |
| CN112581791A (en) * | 2019-09-27 | 2021-03-30 | 英特尔公司 | Potential collision warning system based on road user intention prediction |
| CN112700470A (en) * | 2020-12-30 | 2021-04-23 | 上海智能交通有限公司 | Target detection and track extraction method based on traffic video stream |
| CN112918471A (en) * | 2021-03-22 | 2021-06-08 | 昆山宝创新能源科技有限公司 | Anti-collision control method, device and equipment for vehicle and storage medium |
| CN113112805A (en) * | 2021-04-16 | 2021-07-13 | 吉林大学 | Intersection monitoring and early warning method based on base station communication and intersection camera positioning |
| US20210221385A1 (en) * | 2018-08-31 | 2021-07-22 | Beijing Didi Infinity Technology And Development Co., Ltd. | Methods and systems for information recommendation |
| CN113313948A (en) * | 2021-05-31 | 2021-08-27 | 国汽智控(北京)科技有限公司 | Vehicle driving track prompting method and device |
| CN113823120A (en) * | 2021-08-18 | 2021-12-21 | 深圳市元征科技股份有限公司 | Vehicle danger early warning method and related device |
| CN113851017A (en) * | 2021-08-19 | 2021-12-28 | 复旦大学 | Pedestrian and vehicle identification and early warning multifunctional system based on road side RSU |
| CN113870551A (en) * | 2021-08-16 | 2021-12-31 | 清华大学 | Roadside monitoring system capable of identifying dangerous and non-dangerous driving behaviors |
| CN113990105A (en) * | 2021-10-22 | 2022-01-28 | 数字广东网络建设有限公司 | Vehicle track processing method and device, computer equipment and storage medium |
| WO2022024208A1 (en) * | 2020-07-28 | 2022-02-03 | 日本電気株式会社 | Traffic monitoring device, traffic monitoring system, traffic monitoring method, and program |
| WO2022057645A1 (en) * | 2020-09-21 | 2022-03-24 | 华为技术有限公司 | Assisted driving reminding method and apparatus, map assisted driving reminding method and apparatus, and map |
| CN114283587A (en) * | 2021-12-29 | 2022-04-05 | 安徽达尔智能控制***股份有限公司 | Crossroad vehicle violation lane change early warning management and control method and system based on radar vision monitoring |
| CN114519931A (en) * | 2020-11-17 | 2022-05-20 | 郑州宇通客车股份有限公司 | Method and device for predicting behavior of target vehicle in intersection environment |
| CN114694416A (en) * | 2022-03-24 | 2022-07-01 | 东风汽车集团股份有限公司 | Violation vehicle avoidance method and avoidance system based on cloud server |
| CN114782921A (en) * | 2022-04-21 | 2022-07-22 | 吉林大学 | Pedestrian and vehicle collision early warning system and method in internet connection environment based on pedestrian intention identification |
| CN114771250A (en) * | 2022-05-05 | 2022-07-22 | 深圳市威视创电子有限公司 | Muck truck driving display screen control device and method |
-
2022
- 2022-08-10 CN CN202210956054.XA patent/CN115346370B/en active Active
Patent Citations (48)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008097413A (en) * | 2006-10-13 | 2008-04-24 | Mitsubishi Electric Corp | In-vehicle system for providing safety support information |
| JP2009134334A (en) * | 2007-11-28 | 2009-06-18 | Denso Corp | Vehicle control device |
| US20100063725A1 (en) * | 2008-08-07 | 2010-03-11 | Aisin Aw Co., Ltd. | Safe driving evaluation system, method, and program |
| US20110102166A1 (en) * | 2009-10-30 | 2011-05-05 | Ford Global Technologies, Llc | Vehicle and method of advising a driver therein |
| CN202480973U (en) * | 2012-02-02 | 2012-10-10 | 王林 | Device for hinting appreciation during lane-changing and turning of vehicle |
| WO2014084593A1 (en) * | 2012-11-29 | 2014-06-05 | 한국교통연구원 | Apparatus and method for supporting safe driving |
| CN104537860A (en) * | 2015-01-12 | 2015-04-22 | 小米科技有限责任公司 | Traffic safety prompting method and device |
| CN105989745A (en) * | 2015-02-05 | 2016-10-05 | 华为技术有限公司 | Acquisition method, apparatus and system of vehicle violation information |
| US20170113683A1 (en) * | 2015-10-27 | 2017-04-27 | GM Global Technolgy Operations LLC | Methods of improving performance of automotive intersection turn assist features |
| US20170113665A1 (en) * | 2015-10-27 | 2017-04-27 | GM Global Technology Operations LLC | Algorithms for avoiding automotive crashes at left and right turn intersections |
| CN105448094A (en) * | 2015-12-31 | 2016-03-30 | 重庆云途交通科技有限公司 | Wrong-direction running warning and risk avoiding method based on vehicle and road cooperation technology |
| CN105844965A (en) * | 2016-05-06 | 2016-08-10 | 深圳市元征科技股份有限公司 | Vehicle distance prompting method and device |
| WO2018032642A1 (en) * | 2016-08-19 | 2018-02-22 | 深圳市元征科技股份有限公司 | Driving vehicle collision warning method and device |
| CN108289108A (en) * | 2016-09-05 | 2018-07-17 | 西安艾润物联网技术服务有限责任公司 | Information presentation system and method |
| CN106494409A (en) * | 2016-11-04 | 2017-03-15 | 大连文森特软件科技有限公司 | Based on AR augmented realities and the drive assist system of the wagon control of big data |
| CN106530831A (en) * | 2016-12-15 | 2017-03-22 | 江苏大学 | System and method for monitoring and early warning of high-threat vehicles |
| US20200168099A1 (en) * | 2017-06-07 | 2020-05-28 | Mitsubishi Electric Corporation | Hazardous vehicle prediction device, hazardous vehicle warning system, and hazardous vehicle prediction method |
| JP2019032710A (en) * | 2017-08-08 | 2019-02-28 | パイオニア株式会社 | Determination device, method for determination, and program |
| CN109979239A (en) * | 2017-12-28 | 2019-07-05 | 北京百度网讯科技有限公司 | Violation vehicle based reminding method, device and equipment |
| CN109005239A (en) * | 2018-08-21 | 2018-12-14 | 哈尔滨工业大学 | Intelligent information exchange method, system and device for assisting vehicle travel |
| US20210221385A1 (en) * | 2018-08-31 | 2021-07-22 | Beijing Didi Infinity Technology And Development Co., Ltd. | Methods and systems for information recommendation |
| JP2020076642A (en) * | 2018-11-07 | 2020-05-21 | ヤフー株式会社 | Information processing device, information processing method, and information processing program |
| CN209708113U (en) * | 2018-11-15 | 2019-11-29 | 郭涵之 | Driver reminds the alarm set of pedestrian or vehicle evacuation |
| CN109658700A (en) * | 2019-03-05 | 2019-04-19 | 上汽大众汽车有限公司 | Intersection anti-collision prewarning apparatus and method for early warning |
| CN111915914A (en) * | 2019-05-09 | 2020-11-10 | 奥迪股份公司 | Vehicle driving assistance system and method, and corresponding computer-readable storage medium |
| KR20200133122A (en) * | 2019-05-17 | 2020-11-26 | 현대모비스 주식회사 | Apparatus and method for preventing vehicle collision |
| CN110310481A (en) * | 2019-06-28 | 2019-10-08 | 浙江吉利控股集团有限公司 | A kind of vehicle collision prewarning method, device and equipment |
| CN110502012A (en) * | 2019-08-20 | 2019-11-26 | 武汉中海庭数据技术有限公司 | His a kind of wheel paths prediction technique, device and storage medium |
| CN211642010U (en) * | 2019-09-19 | 2020-10-09 | 罗霞 | Light projection alarm for automobile glass |
| CN112581791A (en) * | 2019-09-27 | 2021-03-30 | 英特尔公司 | Potential collision warning system based on road user intention prediction |
| CN111127950A (en) * | 2019-12-27 | 2020-05-08 | 北京万集智能网联技术有限公司 | Vehicle collision early warning processing method and device |
| CN111540237A (en) * | 2020-05-19 | 2020-08-14 | 河北德冠隆电子科技有限公司 | Method for automatically generating vehicle safety driving guarantee scheme based on multi-data fusion |
| WO2022024208A1 (en) * | 2020-07-28 | 2022-02-03 | 日本電気株式会社 | Traffic monitoring device, traffic monitoring system, traffic monitoring method, and program |
| CN111932941A (en) * | 2020-08-24 | 2020-11-13 | 重庆大学 | Intersection vehicle early warning method and system based on vehicle-road cooperation |
| WO2022057645A1 (en) * | 2020-09-21 | 2022-03-24 | 华为技术有限公司 | Assisted driving reminding method and apparatus, map assisted driving reminding method and apparatus, and map |
| CN114519931A (en) * | 2020-11-17 | 2022-05-20 | 郑州宇通客车股份有限公司 | Method and device for predicting behavior of target vehicle in intersection environment |
| CN112700470A (en) * | 2020-12-30 | 2021-04-23 | 上海智能交通有限公司 | Target detection and track extraction method based on traffic video stream |
| CN112918471A (en) * | 2021-03-22 | 2021-06-08 | 昆山宝创新能源科技有限公司 | Anti-collision control method, device and equipment for vehicle and storage medium |
| CN113112805A (en) * | 2021-04-16 | 2021-07-13 | 吉林大学 | Intersection monitoring and early warning method based on base station communication and intersection camera positioning |
| CN113313948A (en) * | 2021-05-31 | 2021-08-27 | 国汽智控(北京)科技有限公司 | Vehicle driving track prompting method and device |
| CN113870551A (en) * | 2021-08-16 | 2021-12-31 | 清华大学 | Roadside monitoring system capable of identifying dangerous and non-dangerous driving behaviors |
| CN113823120A (en) * | 2021-08-18 | 2021-12-21 | 深圳市元征科技股份有限公司 | Vehicle danger early warning method and related device |
| CN113851017A (en) * | 2021-08-19 | 2021-12-28 | 复旦大学 | Pedestrian and vehicle identification and early warning multifunctional system based on road side RSU |
| CN113990105A (en) * | 2021-10-22 | 2022-01-28 | 数字广东网络建设有限公司 | Vehicle track processing method and device, computer equipment and storage medium |
| CN114283587A (en) * | 2021-12-29 | 2022-04-05 | 安徽达尔智能控制***股份有限公司 | Crossroad vehicle violation lane change early warning management and control method and system based on radar vision monitoring |
| CN114694416A (en) * | 2022-03-24 | 2022-07-01 | 东风汽车集团股份有限公司 | Violation vehicle avoidance method and avoidance system based on cloud server |
| CN114782921A (en) * | 2022-04-21 | 2022-07-22 | 吉林大学 | Pedestrian and vehicle collision early warning system and method in internet connection environment based on pedestrian intention identification |
| CN114771250A (en) * | 2022-05-05 | 2022-07-22 | 深圳市威视创电子有限公司 | Muck truck driving display screen control device and method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116894225A (en) * | 2023-09-08 | 2023-10-17 | 国汽(北京)智能网联汽车研究院有限公司 | Driving behavior abnormality analysis method, device, equipment and medium thereof |
| CN116894225B (en) * | 2023-09-08 | 2024-03-01 | 国汽(北京)智能网联汽车研究院有限公司 | Driving behavior abnormality analysis method, device, equipment and medium thereof |
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