CN115346370B - Intersection anti-collision system and method based on intelligent traffic - Google Patents
Intersection anti-collision system and method based on intelligent traffic Download PDFInfo
- Publication number
- CN115346370B CN115346370B CN202210956054.XA CN202210956054A CN115346370B CN 115346370 B CN115346370 B CN 115346370B CN 202210956054 A CN202210956054 A CN 202210956054A CN 115346370 B CN115346370 B CN 115346370B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- target vehicle
- abnormal
- intersection
- judging whether
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 29
- 230000002159 abnormal effect Effects 0.000 claims abstract description 101
- 230000008859 change Effects 0.000 claims description 28
- 238000012544 monitoring process Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 6
- 239000007787 solid Substances 0.000 claims description 4
- 230000000694 effects Effects 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000010348 incorporation Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
Classifications
-
- 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
- G08G1/0108—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
-
- 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
-
- 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
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The application 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 an intersection; s2, identifying a lane where a vehicle is located and a license plate number; s3, judging whether the actual running track of the vehicle passing through the intersection is abnormal, and if so, marking the vehicle 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 driving track of the target vehicle passing through the intersection; s5, judging whether the identified license plate number contains the license plate number of the abnormal vehicle, and 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 application, the potential danger around the target vehicle can be early warned in advance.
Description
Technical Field
The application relates to the technical field of traffic safety, in particular to an intersection anti-collision system and method based on intelligent traffic.
Background
Along with the increasing number of traffic participants, road condition information is increasingly complex, and in order to reduce the probability of accidents, two existing systems related to traffic intersection collision prevention and early warning are mainly available, one system is that a series of sensors such as cameras and millimeter wave radars are utilized at a vehicle end to collect data around a vehicle body and analyze and process the data to obtain collision prevention and early warning results. The method has the defects that the calculation pressure of the vehicle end is large, the early warning range is small, and the reflection time reserved for the vehicle end is short. The other is that GPS data of vehicles and pedestrians are received by using roadside communication units and edge calculation at the roadside, anti-collision early warning is obtained by analysis, and then the warning 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 in advance.
Disclosure of Invention
The application aims to provide an intersection anti-collision method based on intelligent traffic, which can early warn potential hazards around a target vehicle in advance.
In order to solve the technical problems, the application provides the following technical scheme:
the intelligent traffic-based intersection anti-collision method comprises the following steps.
S1, acquiring traffic information of an intersection from road side equipment;
s2, identifying a lane where a vehicle is located and a license plate number according to traffic information;
s3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not according to traffic information, if so, marking the vehicle as an abnormal vehicle, and recording license plate numbers;
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 the target vehicle enters the monitoring range of the intersection, whether the recorded abnormal vehicles exist or not is judged, if the recorded abnormal vehicles exist, the abnormal vehicles do not run according to traffic rules, and the normal running of the target vehicle can be possibly interfered, 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 or not is judged, if the abnormal vehicles are in the adjacent lanes, the possibility of interfering the target vehicle exists, early warning can be carried out to the target vehicle in advance by pushing early warning information to the mobile terminal of the target vehicle, and a driver of the target vehicle can avoid the abnormal vehicles in advance.
In summary, the scheme can early warn potential hazards around the target vehicle in advance, and reduce the probability of accident occurrence.
Further, in the step S6, it is further determined whether the target vehicle and the abnormal vehicle have a cross running track based on the running tracks of the target vehicle and the abnormal vehicle, and if the cross running track occurs, the warning information is pushed to the mobile terminal of the target vehicle.
Further, in the step S3, the actual running track of the vehicle passing through the intersection is matched according to a preset rule of offending running, if the matching is successful, the vehicle is judged to be abnormal, and the license plate number and the offending type of the abnormal vehicle are recorded; the violation types include solid lane changes and turn lane changes;
in step S6, when the violation type of the abnormal vehicle is a solid line lane change or a turning lane change, it is determined whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection based on the running track of the abnormal vehicle, and if so, the warning information is pushed to the mobile terminal of the target vehicle.
For example, the target vehicle and the abnormal vehicle both wait for left turn at the intersection, while the target vehicle is located on the left side of the abnormal vehicle; the early warning information of turning attention to right-side vehicle lane change is pushed to the mobile terminal of the target vehicle so as 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.
Further, in the step S3, the violation type further includes scram; acquiring the speed of the vehicle from the traffic information, judging whether the vehicle is suddenly stopped at a stop line of an intersection based on the change of the speed, acquiring traffic light information from road side equipment if the vehicle is suddenly stopped, judging whether the remaining time of a traffic light green light is in a preset range when the vehicle is suddenly stopped, if so, marking the vehicle as an abnormal vehicle, and recording the illegal type of the abnormal vehicle as the sudden stop;
in step S6, it is determined whether the target vehicle and the abnormal vehicle are in the same lane when passing through the intersection based on the running track of the target vehicle and the abnormal vehicle, if so, it is determined whether the abnormal vehicle is a front vehicle of the target vehicle, if so, it is determined whether the remaining time of the traffic light green light is within a preset range when the abnormal vehicle reaches the intersection stop line based on the current speed of the abnormal vehicle, and if so, the warning information is sent to the mobile terminal of the target vehicle.
For example, the remaining time of the green light remains for 2 seconds when the vehicle can pass normally, but the emergency stop is selected to indicate whether the vehicle has deviation to judging whether the vehicle can pass the traffic light, and thus the vehicle is marked as an abnormal vehicle. When the target vehicle follows the abnormal vehicle and the current speed of the abnormal vehicle reaches the stop line of the intersection, the remaining time of the traffic light green light is in the preset range, the abnormal vehicle can take sudden braking again because of inaccurate judgment, the target vehicle is easy to rear-end collision, and the target vehicle can be reminded by pushing early warning information.
Further, in the step S6, when the abnormal vehicle reaches the stop line of the intersection, the remaining time of the traffic light green light is within the preset range, the early warning information is pushed to the mobile terminal of the target vehicle, the driving experience information of the driver is also obtained from the mobile terminal of the target vehicle, and the processing suggestion is generated based on the driving experience information to push to the mobile terminal of the target vehicle.
For example, for novice drivers, the generated processing advice is original road deceleration, and for acquaintance drivers, the generated advice information is road change under the premise of ensuring safety, so as to improve the road passing efficiency.
Further, the method further comprises the following steps:
s7, identifying pedestrians according to traffic information, judging whether the pedestrians are on a road, and if so, estimating the moving track of the pedestrians according to the current moving direction of the pedestrians;
and S8, judging whether the moving track of the pedestrian crosses the running track of the target vehicle, if so, judging whether the pedestrian is in the blind area of the target vehicle, and if so, pushing the early warning information to the mobile terminal of the target vehicle.
Further, in the step S7, the current status of the pedestrian is also identified, whether the status is an uncontrollable status is determined, and if the status is an uncontrollable status, the pedestrian is marked;
in step S8, if the moving track of the pedestrian crosses the running track of the target vehicle, then 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 has a state of looking at a mobile phone, and the attention is not used for observing the road condition, and is judged as an uncontrollable state. Under the condition, even if a driver does not have a visual blind area, the driver needs to pay more attention to marked pedestrians, and the driver can be reminded to pay attention to observe in advance by pushing early warning information, so that the probability of accident occurrence is reduced.
Further, the method further comprises the following steps:
s9, judging whether the moving track of the pedestrian crosses the running tracks of other vehicles at the intersection, and if so, marking the crossed vehicles as vehicles to be reminded;
judging whether the target vehicle shields the vehicle to be reminded to observe pedestrians, and if so, pushing reminding operation suggestions to the mobile terminal of the target vehicle according to the relative positions of the target vehicle and the vehicle to be reminded.
The vehicle to be reminded can be because of the visual blind area that target vehicle caused, can't observe the pedestrian in advance, does not have sufficient time to slow down and collide with the pedestrian when leading to observing the pedestrian, through to the operation suggestion is reminded in propelling movement to target vehicle, can let the driver of target vehicle wait to remind the vehicle according to the operation suggestion of reminding, reduces the probability of accident.
Further, in step S9, after the target vehicle is determined to block the vehicle to be reminded from observing the pedestrian, driving experience information of the driver is obtained from the mobile terminal of the target vehicle, and according to the relative position of the target vehicle and the vehicle to be reminded and the driving experience information, a reminding operation suggestion is generated, and the reminding operation suggestion is pushed to the mobile terminal of the target vehicle.
The second object of the application is to provide an intelligent traffic-based intersection anti-collision system, which uses the method.
Drawings
Fig. 1 is a logic block diagram of an intelligent traffic-based intersection collision avoidance system according to an embodiment.
Detailed Description
The following is a further detailed description of the embodiments:
example 1
As shown in fig. 1, the intersection anti-collision method based on intelligent traffic of the embodiment includes the following contents:
s1, acquiring traffic information of an intersection 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 a lane where a vehicle is located and a license plate number according to traffic information; specifically, the identification is performed through a monitoring video.
S3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not according to traffic information, if so, marking the vehicle as an abnormal vehicle, and recording license plate numbers;
specifically, the violation types include solid lane change, turning lane change and scram; the solid line lane change and turning lane change recognition modes are as follows: matching the actual running track of the vehicle passing through the intersection according to a preset rule of illegal running comprising solid lane change and turning lane change, if the matching is successful, judging that the vehicle is abnormal, and recording the license plate number and the type of the illegal vehicle;
for example, the vehicle turns left at the intersection, the left turn lanes are sequentially marked as a lane 1 and a lane 2 from right to left, the corresponding left turn rear lanes are sequentially marked as a lane 3 and a lane 4 from right to left, the vehicle in the lane 1 turns left into the lane 3, the vehicle in the lane 2 turns left into the lane 4, and if the vehicle turns left, the vehicle enters the lane 3 from the lane 2, and the vehicle is regarded as turning lane change.
The identification mode of the emergency stop is as follows: the method comprises the steps of obtaining the speed of a vehicle from traffic information, judging whether the vehicle stops suddenly at an intersection on the basis of the change of the speed, obtaining traffic light information from road side equipment if the vehicle stops suddenly, judging whether the remaining time of a traffic light green light is in a preset range when the vehicle stops suddenly, if so, marking the vehicle as an abnormal vehicle, recording the license plate number of the abnormal vehicle, and recording the offence type of the abnormal vehicle as sudden stop. In the embodiment, the speed of the vehicle is reduced from 30km/h or more to 0km/h, and the reduction time is less than 3 seconds, so that the vehicle is regarded as suddenly stopping 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, judging whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection or not based on the running track of the abnormal vehicle when the violation type of the abnormal vehicle is solid line lane change or turning lane change, and pushing early warning information to the mobile terminal of the target vehicle if the target vehicle and the abnormal vehicle are in the adjacent lanes. In this embodiment, different pre-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 2, and the abnormal vehicle is located in lane 1; the early warning information of turning attention to right-side vehicle lane change is pushed to the mobile terminal of the target vehicle so as 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.
When the violation type of the abnormal vehicle is solid line lane change or turning lane change, judging whether the running track crossing of the target vehicle and the abnormal vehicle occurs or not based on the running track of the target vehicle and the abnormal vehicle, and if the running track crossing occurs, pushing early warning information to the mobile terminal of the target vehicle. For example, the abnormal vehicle is a black certain-brand SUV, the license plate number is Yuan AXXXXX, the target vehicle directly passes through the crossroad, the abnormal vehicle turns right at the crossroad, the target vehicle and the abnormal vehicle are converged after passing through the crossroad, and the pushed early warning information is "the black certain-brand SUV which is remitted on the right side".
When the offence type of the abnormal vehicle is sudden stop, 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 track of the target vehicle and the abnormal vehicle, if so, judging whether the abnormal vehicle is the front vehicle of the target vehicle or not, if so, judging whether the residual time of the traffic light green light is in a preset range or not when the abnormal vehicle reaches the stop line of the intersection based on the current speed of the abnormal vehicle, and if so, pushing early warning information to the mobile terminal of the target vehicle. In this embodiment, the preset range is 1-4 seconds. For example, when the abnormal vehicle reaches the stop line of the intersection, the remaining time of the traffic light green light is 2 seconds, and the pushed early warning information is that the front vehicle is at risk of sudden stop, the vehicle distance is kept, and the vehicle speed is controlled.
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 based on the driving experience information to be pushed to the mobile terminal of the target vehicle. The driving experience information includes novice or acquaintance, which is entered in advance by the driver. When the driver is a novice, the pushed processing proposal is 'proposal for waiting for a next green light', when the driver is a acquainted hand, whether the target vehicle has a lane change condition (the lane change condition means that the current lane is changeable and the side lane has space) is judged according to the monitoring video, and if the target vehicle has the lane change condition, the pushed processing proposal is 'proposal for changing lanes after observation'.
S7, identifying pedestrians according to the monitoring video in the traffic information, judging whether the pedestrians are on the road, and if so, estimating the moving track of the pedestrians according to the current moving direction of the pedestrians; the road referred to in this embodiment is a road on which the motor vehicle travels. 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 a pedestrian is in a state of looking at a mobile phone, carrying an article, and using a carrier (e.g., a balance car, a skateboard), the pedestrian is determined to be in an uncontrollable state.
And S8, judging whether the moving track of the pedestrian crosses the running track of the target vehicle, if so, judging whether the pedestrian is marked, if so, pushing the 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, and if so, pushing the early warning information to the mobile terminal of the target vehicle. For example, the warning information is "pedestrian care".
S9, judging whether the moving track of the pedestrian crosses the running tracks of other vehicles at the intersection, and if so, marking the crossed vehicles as vehicles to be reminded;
judging whether the target vehicle shields the vehicle to be reminded to observe pedestrians, and if so, pushing reminding operation suggestions to the mobile terminal of the target vehicle according to the relative positions of the target vehicle and the vehicle to be reminded.
For example, the target vehicle and the vehicle to be reminded are prepared to go straight at the intersection, the straight lanes are sequentially marked as a lane 1 and a lane 2 from right to left, the target vehicle is located in the lane 2, the vehicle to be reminded is located in the lane 1, namely, the target vehicle is located at the left side of the vehicle to be reminded, a pedestrian traverses the road from the left side of the target vehicle, the risk of collision with the target vehicle or the vehicle to be reminded exists, at this moment, the target vehicle observes the pedestrian after receiving the early warning information and starts decelerating, the next vehicle to be reminded is not decelerated, because the target vehicle shields the left side view of the vehicle to be reminded, if the vehicle to be reminded continues to run at the current speed, collision with the pedestrian is possible, in the embodiment, the pushed reminding operation is suggested as a "suggested whistle, the right turn lamp is turned on, and the right vehicle is reminded.
Based on the method, the embodiment also provides an intersection anti-collision system based on intelligent traffic, as shown in fig. 1, comprising a server, road side equipment and a mobile terminal.
The road side equipment comprises a monitoring camera and a speed measuring camera, wherein the monitoring camera is used for collecting monitoring videos of intersections, analyzing the monitoring videos, and identifying vehicles, pedestrians and obstacles in the monitoring videos and marking the vehicles, the pedestrians and the obstacles. The speed measuring camera is used for collecting the speed of the vehicle.
In this embodiment, the mobile terminal is a smart phone with an APP, and is connected to a server through the internet. The mobile terminal is used for uploading a navigation route of the target vehicle, inputting driving experience information by a driver, and displaying early warning information and reminding operation advice. The server is adapted to perform the steps of the above-described methods S1-S9.
Example two
In the method of this embodiment, step S9, after determining that the target vehicle shields the vehicle to be reminded from observing the pedestrian, obtains driving experience information of the driver from the mobile terminal of the target vehicle, generates a reminding operation suggestion according to the relative position of the target vehicle and the vehicle to be reminded and the driving experience information, and pushes the reminding operation suggestion 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 at the left side of the vehicle to be reminded, the pedestrian traverses 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, and if the driving experience information is a novice, the pushed reminding operation is suggested as "suggest turning on the right turn lamp, remind the vehicle on the right side" in this embodiment.
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, the pedestrian traverses the road from the right side of the target vehicle, and there is a risk of collision with the target vehicle or the vehicle to be reminded. That is, the acquaintance will suggest to make a lane change to the left in the original lane, as opposed to the novice. When a vehicle to be reminded observes a tendency of a target vehicle to change lanes to the left, the observation is generally enhanced, and the vehicle is decelerated, so that the risk of collision with pedestrians is reduced.
Example III
The difference between the present embodiment and the second embodiment is that, in the method of the present embodiment, step S3 further determines whether the speed of the vehicle passing through the intersection is greater than a preset speed according to the traffic information, if so, marks the vehicle as attention, and records the license plate number. The preset speed can be set according to the actual speed limit of the intersection. In this embodiment, the speed limit at the intersection is 30km/h, the preset speed is 28km/h, and in other embodiments, the preset speed can be reduced to 25km/h, so as to expand the screening range.
In step S9, after the target vehicle is judged to block the vehicle to be reminded to observe pedestrians, whether the vehicle to be reminded is a concerned vehicle is also 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;
if yes, pushing a fixed reminding operation suggestion to the mobile terminal of the target vehicle. In this embodiment, the fixed alert operation is suggested as a whistling alert.
For most drivers, the observation is enhanced, as well as the deceleration, after observing that the vehicle next to the lane has the intention to incorporate the own lane. There is still a portion of the driving style that is relatively aggressive to the driver and acceleration is selected to prevent the incorporation of a sideways vehicle. In this embodiment, by judging whether the speed of the vehicle passing through the intersection is greater than the preset speed, drivers with relatively aggressive driving styles can be screened out, and when the vehicle driven by the driver is a vehicle to be reminded, only whistle reminding is performed, so that adverse effects are avoided.
The foregoing is merely an embodiment of the present application, the present application is not limited to the field of this embodiment, and the specific structures and features well known in the schemes are not described in any way herein, so that those skilled in the art will know all the prior art in the field before the application date or priority date of the present application, and will have the capability of applying the conventional experimental means before the date, and those skilled in the art may, in light of the present application, complete and implement the present scheme in combination with their own capabilities, and some typical known structures or known methods should not be an obstacle for those skilled in the art to practice the present application. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present application, and these should also be considered as the scope of the present application, which does not affect the effect of the implementation of the present application and the utility of the patent. The protection scope of the present application is subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (6)
1. The intersection anti-collision method based on intelligent traffic is characterized by comprising the following steps of:
the method for identifying and recording the vehicles with abnormal running tracks in advance comprises the following steps:
s1, acquiring traffic information of an intersection from road side equipment;
s2, identifying a lane where a vehicle is located and a license plate number according to traffic information;
s3, judging whether the actual running track of the vehicle passing through the intersection is abnormal or not according to traffic information, if so, marking the vehicle as an abnormal vehicle, and recording license plate numbers; the method comprises the steps of matching actual running tracks of vehicles passing through an intersection according to preset rule of illegal running, judging that the vehicles are abnormal if the matching is successful, and recording license plate numbers and types of the abnormal vehicles;
after the target vehicle enters the monitoring range of the intersection, judging whether the recorded abnormal vehicle exists, if so, judging whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection, and if so, pushing early warning information to the mobile terminal of the target vehicle, wherein the early warning information comprises the following steps:
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;
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 method further comprises the steps of:
s7, identifying pedestrians according to traffic information, judging whether the pedestrians are on a road, and if so, estimating the moving track of the pedestrians according to the current moving direction of the pedestrians; 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; wherein the uncontrollable state includes: the pedestrian looks at the mobile phone, carries the state of the article and uses the carrier;
s8, judging whether the moving track of the pedestrian crosses the running track of the target vehicle, if so, judging whether the pedestrian is marked, 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, and if so, pushing early warning information to the mobile terminal of the target vehicle;
s9, judging whether the moving track of the pedestrian crosses the running tracks of other vehicles at the intersection, and if so, marking the crossed vehicles as vehicles to be reminded;
judging whether the target vehicle shields the vehicle to be reminded to observe pedestrians, if so, acquiring driving experience information of a driver from a mobile terminal of the target vehicle, generating reminding operation advice according to the relative position of the target vehicle and the vehicle to be reminded and the driving experience information, and pushing the reminding operation advice to the mobile terminal of the target vehicle; when the target vehicle and the vehicle to be reminded go straight at the intersection, the target vehicle is positioned at the left side of the vehicle to be reminded, a pedestrian traverses the road from the left side of the target vehicle, and the risk of collision with the target vehicle or the vehicle to be reminded exists, if the driving experience information of the target vehicle is a novice, a reminding operation suggestion is pushed, a right turn lamp is turned on, and the right vehicle is reminded;
when the target vehicle and the vehicle to be reminded go straight at the crossroad, the target vehicle is positioned on the right side of the vehicle to be reminded, a pedestrian crosses the road from the right side of the target vehicle, and the risk of collision with the target vehicle or the vehicle to be reminded exists, if the driving experience information of the target vehicle is a acquaintance, pushing a reminding operation suggestion to turn on a left turn lamp, approaching a boundary to the left, and reminding the left vehicle.
2. The intelligent traffic-based intersection collision avoidance method of claim 1 wherein: in step S6, it is further determined whether the target vehicle and the abnormal vehicle have a cross running track based on the running tracks of the target vehicle and the abnormal vehicle, and if the cross running track occurs, the early warning information is pushed to the mobile terminal of the target vehicle.
3. The intelligent traffic-based intersection collision avoidance method of claim 2 wherein: in the step S3, the violation types comprise solid lane change and turning lane change;
in step S6, when the violation type of the abnormal vehicle is a solid line lane change or a turning lane change, it is determined whether the target vehicle and the abnormal vehicle are in adjacent lanes when passing through the intersection based on the running track of the abnormal vehicle, and if so, the warning information is pushed to the mobile terminal of the target vehicle.
4. The intelligent traffic-based intersection collision avoidance method of claim 3 wherein: in the step S3, the violation type further includes scram; acquiring the speed of the vehicle from the traffic information, judging whether the vehicle is suddenly stopped at a stop line of an intersection based on the change of the speed, acquiring traffic light information from road side equipment if the vehicle is suddenly stopped, judging whether the remaining time of a traffic light green light is in a preset range when the vehicle is suddenly stopped, if so, marking the vehicle as an abnormal vehicle, and recording the illegal type of the abnormal vehicle as the sudden stop;
in step S6, it is determined whether the target vehicle and the abnormal vehicle are in the same lane when passing through the intersection based on the running track of the target vehicle and the abnormal vehicle, if so, it is determined whether the abnormal vehicle is a front vehicle of the target vehicle, if so, it is determined whether the remaining time of the traffic light green light is within a preset range when the abnormal vehicle reaches the intersection stop line based on the current speed of the abnormal vehicle, and if so, the warning information is sent to the mobile terminal of the target vehicle.
5. The intelligent traffic-based intersection collision avoidance method of claim 4 wherein: in step S6, when the abnormal vehicle reaches the stop line of the intersection, the remaining time of the traffic light green light is within the preset range, the early warning information is pushed to the mobile terminal of the target vehicle, the driving experience information of the driver is obtained from the mobile terminal of the target vehicle, and the processing suggestion is generated and pushed to the mobile terminal of the target vehicle based on the driving experience information.
6. An intelligent traffic-based intersection collision avoidance system, characterized in that the method of any of claims 1-5 is used.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210956054.XA CN115346370B (en) | 2022-08-10 | 2022-08-10 | Intersection anti-collision system and method based on intelligent traffic |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210956054.XA CN115346370B (en) | 2022-08-10 | 2022-08-10 | Intersection anti-collision system and method based on intelligent traffic |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115346370A CN115346370A (en) | 2022-11-15 |
| CN115346370B true CN115346370B (en) | 2023-11-03 |
Family
ID=83951022
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210956054.XA Active CN115346370B (en) | 2022-08-10 | 2022-08-10 | Intersection anti-collision system and method based on intelligent traffic |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115346370B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
Citations (42)
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | 安徽达尔智能控制系统股份有限公司 | 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 |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2151808A1 (en) * | 2008-08-07 | 2010-02-10 | Aisin Aw Co., Ltd. | Safe driving evaluation system and safe driving evaluation method |
| US8258934B2 (en) * | 2009-10-30 | 2012-09-04 | Ford Global Technologies, Llc | Vehicle and method of advising a driver therein |
| US9751506B2 (en) * | 2015-10-27 | 2017-09-05 | GM Global Technology Operations LLC | Algorithms for avoiding automotive crashes at left and right turn intersections |
| US9688273B2 (en) * | 2015-10-27 | 2017-06-27 | GM Global Technology Operations LLC | Methods of improving performance of automotive intersection turn assist features |
| JP6698945B2 (en) * | 2017-06-07 | 2020-05-27 | 三菱電機株式会社 | Dangerous vehicle prediction device, dangerous vehicle warning system, and dangerous vehicle prediction method |
| CN110875937A (en) * | 2018-08-31 | 2020-03-10 | 北京嘀嘀无限科技发展有限公司 | Information pushing method and system |
-
2022
- 2022-08-10 CN CN202210956054.XA patent/CN115346370B/en active Active
Patent Citations (42)
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | 安徽达尔智能控制系统股份有限公司 | 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 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115346370A (en) | 2022-11-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108883725B (en) | Driving vehicle alarm system and method | |
| CN107077795B (en) | Auxiliary system for detecting driving obstacles appearing in vehicle surroundings | |
| CN111210662A (en) | Intersection safety early warning system and method based on machine vision and DSRC | |
| CN110400478A (en) | A kind of road condition notification method and device | |
| CN104678832A (en) | Device For Driving Assist And Method For Activating The Function Automatically By The Device | |
| KR20180086632A (en) | Apparatus amd method of determining action of an autonomous vehicle | |
| CN107111950B (en) | Collision avoidance system | |
| CN107958605B (en) | Road condition information acquisition method | |
| CN114023077B (en) | Traffic monitoring method and device | |
| US20230118619A1 (en) | Parking-stopping point management device, parking-stopping point management method, and vehicle device | |
| CN111731296A (en) | Travel control device, travel control method, and storage medium storing program | |
| CN113022441A (en) | Vehicle blind area detection method and device, electronic equipment and storage medium | |
| JP3740524B2 (en) | Driving support road system | |
| CN111260915B (en) | Early warning reminding method for pedestrian stay in expressway traffic abnormal area | |
| CN115346370B (en) | Intersection anti-collision system and method based on intelligent traffic | |
| CN113665483A (en) | Collision danger warning system for vehicle | |
| CN112382100A (en) | Crossing safe passing method and related equipment | |
| CN110827575A (en) | Cooperative vehicle safety system and method | |
| CN110660271B (en) | Identification of conditions of importance for driving over greater distances | |
| CN111915914B (en) | Vehicle driving assistance system and method, and corresponding computer-readable storage medium | |
| CN113269990A (en) | Early warning method for vehicle collision and vehicle control system | |
| CN107310559A (en) | A kind of device for reminding vehicle to avoid taking left-hand lane for a long time | |
| CN116461525A (en) | Vehicle lane changing method, device, equipment, medium and vehicle | |
| CN115331442B (en) | Intelligent traffic information self-defining system and method | |
| CN111223334A (en) | Pedestrian reminding method and device applied to unmanned vehicle |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |