CN111845777A - Big data vehicle control method - Google Patents
Big data vehicle control method Download PDFInfo
- Publication number
- CN111845777A CN111845777A CN202010781925.XA CN202010781925A CN111845777A CN 111845777 A CN111845777 A CN 111845777A CN 202010781925 A CN202010781925 A CN 202010781925A CN 111845777 A CN111845777 A CN 111845777A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- target vehicle
- speed
- license plate
- target
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
Abstract
The invention discloses a big data-based unmanned vehicle control method, which comprises the following steps: determining a license plate number of a first vehicle located in front of and immediately adjacent to the target vehicle; acquiring a license plate number of a second vehicle which is positioned in front of and adjacent to the first vehicle based on the first vehicle; acquiring the speed of the second vehicle in real time according to the license plate number of the second vehicle; acquiring a vehicle distance between a target vehicle and a first vehicle in real time; and adjusting the speed of the target vehicle in real time according to the speed of the second vehicle and the distance between the target vehicle and the first vehicle. So set up, travelling comfort in the time of can improving the speed governing reduces the occurence of failure.
Description
The patent application of the invention is divisional application. The original patent number is 201910612152X, the application date is 7/8 in 2019, and the name of the invention is an unmanned safe driving method based on big data.
Technical Field
The invention relates to the technical field of unmanned driving, in particular to an unmanned vehicle control method based on big data.
Background
The unmanned vehicle integrates a plurality of technologies such as automatic control, a system structure, artificial intelligence, visual calculation and the like, is a product of high development of computer science, mode recognition and intelligent control technologies, is an important mark for measuring national scientific research strength and industrial level, and has wide application prospect in the fields of national defense and national economy.
The unmanned vehicle can avoid traffic accidents caused by the error of a driver, and can reduce the occurrence of behaviors such as drunk driving and the like, thereby effectively improving the safety of road traffic and reducing the probability of traffic jam caused by the accident. However, the current research on the comfort of the unmanned vehicle during the gear shifting is still in the blank period.
Disclosure of Invention
The invention discloses a big data-based unmanned vehicle control method, which is used for solving the problem that the unmanned vehicle is poor in comfort during speed change in the prior art.
In order to solve the problems, the invention adopts the following technical scheme:
provided is a big data-based unmanned vehicle control method, including the steps of:
determining a license plate number of a first vehicle located in front of and immediately adjacent to the target vehicle;
acquiring a license plate number of a second vehicle which is positioned in front of and adjacent to the first vehicle based on the first vehicle;
acquiring the speed of the second vehicle in real time according to the license plate number of the second vehicle;
acquiring a vehicle distance between a target vehicle and a first vehicle in real time;
and adjusting the speed of the target vehicle in real time according to the speed of the second vehicle and the distance between the target vehicle and the first vehicle.
Optionally, determining the license plate number of the first vehicle located in front of and immediately adjacent to the target vehicle includes the steps of:
a license plate number scanner of a target vehicle scans and sends license plate number information of a first vehicle;
a controller of a target vehicle receives license plate number information of a first vehicle;
the controller of the target vehicle sends the license plate number information of the controller, the license plate number information of the first vehicle and the first sequencing identification to the server, wherein the first sequencing identification is identification information associated with the license plate number information of the target vehicle.
Optionally, based on the first vehicle, obtaining a license plate number of a second vehicle located in front of and immediately adjacent to the first vehicle, including the steps of:
a license plate number scanner of a first vehicle scans and sends license plate number information of a second vehicle;
a controller of a first vehicle receives license plate number information of a second vehicle;
the controller of the first vehicle sends the license plate number information of the controller, the license plate number information of the second vehicle and the second sequencing identification to the server, and the server calls and sends the license plate number information of the second vehicle according to the license plate number information of the target vehicle, the first sequencing identification, the license plate number information of the first vehicle and the second sequencing identification, wherein the second sequencing identification is identification information associated with the license plate number information of the first vehicle;
the controller of the target vehicle receives license plate number information of the second vehicle.
Optionally, the method for acquiring the vehicle speed of the second vehicle in real time according to the license plate number of the second vehicle includes the steps:
the controller of the target vehicle sends the license plate number information of the second vehicle to the server;
the server calls and sends the speed of the second vehicle according to the license plate number information of the second vehicle;
the controller of the target vehicle receives a vehicle speed of the second vehicle.
Optionally, the method for adjusting the speed of the target vehicle in real time according to the speed of the second vehicle and the distance between the target vehicle and the first vehicle includes:
the method comprises the steps that a controller of a target vehicle obtains the speed of a second vehicle before speed change and the speed of the second vehicle after speed change;
the controller of the target vehicle acquires the current speed of the target vehicle and acquires the speed of the target vehicle after speed change according to the speed of the second vehicle after speed change;
the method comprises the steps that a controller of a target vehicle determines the distance between the target vehicle and a first vehicle at the current time, and the safe speed change distance of the target vehicle is determined according to the distance between the target vehicle and the first vehicle;
and the target vehicle calls a speed change algorithm to adjust the speed of the target vehicle, wherein the speed of the target vehicle before speed change, the speed of the target vehicle after speed change and the safe speed change distance are substituted into the speed change algorithm.
Optionally, the speed change algorithm is as follows: y ═ kx | x2-x1|×[(ab)^1/6]，
Wherein: y is the safe shift distance in m;
k is the slope;
x2the unit is the speed of the target vehicle 1 before speed change, and the unit is kilometers per hour;
x1the unit is the speed of the target vehicle 1 after speed change and is kilometer/hour;
a is the age of the target vehicle 1 in years;
b is the vehicle weight of the target vehicle 1 in tons.
Optionally, a safety distance is left between the target vehicle and the first vehicle after the speed of the target vehicle is changed, wherein the safety distance is a distance traveled by the target vehicle when the target vehicle is stopped emergently after the first vehicle is stopped emergently.
Optionally, the method further comprises the steps of:
a camera of a target vehicle monitors whether a vehicle changes a lane in front in real time;
and if the vehicles change the lane, the controller of the target vehicle reacquires the license plate number of the first vehicle and the license plate number of the second vehicle.
Optionally, the method further comprises the steps of:
and after the target vehicle passes through each intersection, the license plate number of the first vehicle and the license plate number of the second vehicle are obtained again.
Optionally, the method further comprises the steps of:
and if the first vehicle does not acquire the license plate number of the second vehicle, the target vehicle adjusts the speed of the target vehicle in real time according to the speed of the first vehicle and the distance between the target vehicle and the first vehicle.
The technical scheme adopted by the invention can achieve the following beneficial effects:
the target vehicle changes the speed according to the speed of the second vehicle, so that the target vehicle and the first vehicle change the speed basically at the same time, the time difference of the target vehicle changing the speed again after the first vehicle changes the speed is saved, more speed regulation time is reserved for the target vehicle, the target vehicle can regulate the speed more stably, and the comfort of the target vehicle in speed regulation is improved. And when the second vehicle is emergently stopped, the first vehicle and the target vehicle can be emergently stopped at the same time, so that the possibility of collision between the first vehicle and the target vehicle is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below to form a part of the present invention, and the exemplary embodiments and the description thereof illustrate the present invention and do not constitute a limitation of the present invention. In the drawings:
FIG. 1 is a flow chart of a big data based unmanned vehicle control method disclosed in an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a vehicle according to an embodiment of the present invention during normal driving;
fig. 3 is a schematic structural diagram of a second vehicle changing lanes according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The technical solutions disclosed in the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
The unmanned vehicle control method based on big data of the invention, as shown in fig. 1 and fig. 2, comprises the following steps.
In step S1, the controller of the target vehicle 1 determines the license plate number of the first vehicle 2 located immediately in front of and in close proximity to the target vehicle 1.
In this step, a license plate number scanner 4 may be provided in front of the target vehicle 1, and the license plate number scanner 4 of the target vehicle 1 is connected to the controller of the target vehicle 1. When the license plate number scanner 4 of the target vehicle 1 receives a license plate number scanning instruction sent by the controller of the target vehicle 1, the license plate number scanner 4 of the target vehicle 1 scans the license plate number of the first vehicle 2, converts the license plate number into license plate number information (e.g., an electric signal), and sends the license plate number information to the controller of the target vehicle 1.
The controller of the target vehicle 1 prestores the license plate number information thereof. When the controller of the target vehicle 1 receives the license plate number information of the first vehicle 2, a first ranking identification is generated, and the first ranking identification is identification information associated with the license plate number information of the target vehicle 1, such as a digital identification. Of course, the first ranking indicator may also be pre-stored in the target vehicle 1 controller. Then, the controller of the target vehicle 1 transmits the own license plate number information, the license plate number information of the first vehicle 2, and the first ranking mark to the server.
The license plate scanner 4 has the same principle as the mobile phone scanner 4, but is different in that the license plate scanner 4 has a higher pixel and a longer shooting distance. The license plate number scanner 4 can be arranged on the vehicle through a cardan shaft, the cardan shaft is driven by a motor, and when the license plate number scanner 4 scans the license plate number, the license plate number scanner rotates from the starting end to the tail end of the license plate number.
It should be noted that the scanning distance of the license plate number scanner 4 can be within 100m, the driving speed of the vehicle usually does not exceed 120 km/h, and the safety distance between two vehicles is 100 m. If the license plate number scanner 4 of the target license plate does not scan the license plate number, the front of the target vehicle 1 is defaulted to have no running vehicle. At this time, the target vehicle 1 controls the vehicle speed according to the sign of the road sign or the like.
The front of the target vehicle 1 is also provided with a camera 5, the camera 5 can be arranged at two sides in front of the target vehicle 1, and the camera 5 is connected with the controller of the target vehicle 1. The camera 5 of the target vehicle 1 monitors in real time whether a vehicle in front of the target vehicle changes a lane, and the specific monitoring mode may be, as shown in fig. 3, the camera 5 of the target vehicle 1 monitors in real time a lane which is located on both sides of the target vehicle 1 and is adjacent to the lane, and if it is monitored that a vehicle passes through the lane, it is determined that a vehicle changes a lane. When the target vehicle 1 detects that the vehicle in front changes the lane, the controller of the target vehicle 1 acquires the vehicle number of the first vehicle 2 again. The target vehicle 1 reacquires the license plate number of the first vehicle 2 in the same manner as described above for the first vehicle 2.
In addition, at the intersection, the vehicle may change the route, and therefore the license plate number of the first vehicle 2 is also acquired again after the target vehicle 1 passes through the intersection each time.
In step S2, based on the first vehicle 2, the controller of the target vehicle 1 acquires the license plate number of the second vehicle 3 located immediately in front of the first vehicle 2.
In this step, the license plate number scanner 4 of the first vehicle 2 is connected to the controller of the first vehicle 2. The controller of the target vehicle 1 sends a license plate number scanning instruction to the server, the server sends the received license plate number scanning instruction to the controller of the first vehicle 2, the controller of the first vehicle 2 sends a license plate number scanning instruction to the license plate number scanner 4 of the first vehicle 2, the license plate number scanner 4 of the first vehicle 2 scans the license plate number of the second vehicle 3, converts the license plate number into license plate number information (such as an electric signal), and sends the license plate number information to the controller of the first vehicle 2.
The controller of the first vehicle 2 prestores the license plate number information thereof. When the controller of the first vehicle 2 receives the license plate number information of the second vehicle 3, a second ranking identifier is generated, and the second ranking identifier is identifier information associated with the license plate number information of the first vehicle 2, such as a numerical identifier. Of course, the second ranking indicator may also be pre-stored in the first vehicle 2 controller. Then, the controller of the first vehicle 2 sends the license plate number information of itself, the license plate number information of the second vehicle 3, and the second sort flag to the server. And after receiving the license plate number information of the first vehicle 2, the license plate number information of the second vehicle 3 and the second sequencing identifier, the server finds the license plate number information of the second vehicle 3 and sends the license plate number information of the second vehicle 3 to the target vehicle 1 according to the second sequencing identifier.
It should be noted that the scanning distance of the license plate number scanner 4 of the first vehicle 2 may be within 100 m. If the license plate number scanner 4 of the first vehicle 2 does not scan the license plate number in front, the first vehicle 2 is defaulted to have no running vehicle in front. At this time, the target vehicle 1 adjusts the vehicle speed of the target vehicle 1 based on the vehicle speed of the first vehicle 2 and the vehicle distance between the target vehicle 1 and the first vehicle speed. The vehicle speed of the adjustment target vehicle 1 may be calculated using a linear function.
When the target vehicle 1 reacquires the license plate number of the first vehicle 2, the license plate number of the second vehicle 3 is also reacquired.
In step S3, the controller of the target vehicle 1 obtains the speed of the second vehicle 3 in real time according to the license plate number of the second vehicle 3.
In the step, the target vehicle 1 sends the acquired license plate number information of the second vehicle 3 to the server and sends a vehicle speed acquisition command to the server, and after receiving the vehicle speed acquisition command, the server calls the vehicle speed corresponding to the license plate number information of the second vehicle 3 and sends the vehicle speed to the target vehicle 1, so that the target vehicle 1 acquires the vehicle speed of the second vehicle 3 in real time.
In step S4, the controller of the target vehicle 1 acquires the inter-vehicle distance between the target vehicle 1 and the first vehicle 2 in real time.
In this step, the vehicle distance between the target vehicle 1 and the first vehicle 2 may be acquired in real time by radar ranging, laser ranging, video ranging, or the like.
In step S5, the controller of the target vehicle 1 adjusts the vehicle speed of the target vehicle 1 in real time according to the vehicle speed of the second vehicle 3 and according to the vehicle distance between the target vehicle 1 and the first vehicle 2.
In this step, the controller of the target vehicle 1 acquires the vehicle speed before the gear shift and the vehicle speed after the gear shift of the second vehicle 3. The controller of the target vehicle 1 obtains the current vehicle speed, and obtains the vehicle speed after the gear change of the target vehicle 1 according to the vehicle speed after the gear change of the second vehicle 3, for example, the vehicle speeds of the two vehicles can be the same or have a phase difference, and the analysis can be carried out according to big data. The controller of the target vehicle 1 determines the vehicle distance between the target vehicle 1 and the first vehicle 2 at the present time, and determines the safe shift distance of the target vehicle 1 according to the vehicle distance between the target vehicle 1 and the first vehicle 2. Then, the target vehicle 1 calls a gear shift algorithm to adjust the vehicle speed of the target vehicle 1, wherein the vehicle speed before the gear shift, the vehicle speed after the gear shift, and the safe gear shift distance of the target vehicle 1 are substituted in the gear shift algorithm.
It should be noted that, when determining the safe shift distance of the target vehicle 1, analysis may be performed based on the big data to analyze the safe shift distance at different vehicle speeds and different vehicle distances. And a safety distance is reserved between the target vehicle 1 and the first vehicle 2 after the speed change, wherein the safety distance is a distance which is traveled when the target vehicle 1 is emergently stopped after the first vehicle 2 is emergently stopped. The safe distance may be calculated by a 4-second method, for example, 100m when the vehicle speed is 100 km/h.
The speed change algorithm is as follows: y ═ kx | x2-x1|×[(ab)^1/6]，
Wherein: y is the safe shift distance in m;
k is the slope;
x2the unit is the speed of the target vehicle 1 before speed change, and the unit is kilometers per hour;
x1the unit is the speed of the target vehicle 1 after speed change and is kilometer/hour;
a is the age of the target vehicle 1 in years;
b is the vehicle weight of the target vehicle 1 in tons.
For example, when the safe shift distance y of the target vehicle 1 is 50m, the vehicle speed before the shift is 50 km/h, the vehicle speed after the shift is 40 km/h, the vehicle age is 2 years, and the vehicle weight is 1.8 tons, the slope k is calculated according to the shift algorithm 50 ═ kxi 50-40| × [ (2 × 1.8) ^1/6], and the constant speed shift is performed with the slope k.
Through the speed change algorithm, the safe speed change distance can be a numerical value obtained by subtracting the safe distance from the current distance between the target vehicle 1 and the first vehicle 2, and the calculated amount is reduced; the speed of the target vehicle 1 is gradually accelerated or gradually decelerated at a certain slope value, and the stability during speed change is further improved.
When the vehicle is a truck, the weight of the truck is the weight when the truck is unloaded, and when the truck is loaded with goods, the weight of the truck is the total weight when the truck is loaded with goods. When the vehicle is a car, the number of people carried by the car is small, and the weight of the car can be considered as the weight of the car in the idle state. When the vehicle is a passenger car, the weight of the car is the sum of the weight of the truck and the weight of the guest.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (1)
1. A big data-based unmanned vehicle control method is characterized by comprising the following steps:
determining a license plate number of a first vehicle located in front of and immediately adjacent to the target vehicle;
acquiring a license plate number of a second vehicle which is positioned in front of and adjacent to the first vehicle based on the first vehicle;
acquiring the speed of the second vehicle in real time according to the license plate number of the second vehicle;
acquiring a vehicle distance between a target vehicle and a first vehicle in real time;
adjusting the speed of the target vehicle in real time according to the speed of the second vehicle and the distance between the target vehicle and the first vehicle;
the method comprises the following steps of adjusting the speed of a target vehicle in real time according to the speed of a second vehicle and the distance between the target vehicle and a first vehicle, and comprises the following steps:
the method comprises the steps that a controller of a target vehicle obtains the speed of a second vehicle before speed change and the speed of the second vehicle after speed change;
the controller of the target vehicle acquires the current speed of the target vehicle and acquires the speed of the target vehicle after speed change according to the speed of the second vehicle after speed change;
the method comprises the steps that a controller of a target vehicle determines the distance between the target vehicle and a first vehicle at the current time, and the safe speed change distance of the target vehicle is determined according to the distance between the target vehicle and the first vehicle;
the target vehicle calls a speed change algorithm to adjust the speed of the target vehicle, wherein the speed of the target vehicle before speed change, the speed of the target vehicle after speed change and the safe speed change distance are substituted into the speed change algorithm;
after the target vehicle is subjected to speed change, a safety distance is reserved between the target vehicle and the first vehicle, wherein the safety distance is a distance traveled by the target vehicle when the target vehicle is subjected to emergency braking after the first vehicle is subjected to emergency braking;
wherein the speed change algorithm is as follows: y ═ kx | x2-x1|×[(ab)^1/6]，
Wherein: y is the safe shift distance in m;
k is the slope;
x2the unit is the speed of the target vehicle 1 before speed change, and the unit is kilometers per hour;
x1the unit is the speed of the target vehicle 1 after speed change and is kilometer/hour;
a is the age of the target vehicle 1 in years;
b is the vehicle weight of the target vehicle 1 in tons.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010781925.XA CN111845777A (en) | 2019-07-08 | 2019-07-08 | Big data vehicle control method |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910612152.XA CN110209178B (en) | 2019-07-08 | 2019-07-08 | Unmanned vehicle control method based on big data |
| CN202010781925.XA CN111845777A (en) | 2019-07-08 | 2019-07-08 | Big data vehicle control method |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910612152.XA Division CN110209178B (en) | 2019-07-08 | 2019-07-08 | Unmanned vehicle control method based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111845777A true CN111845777A (en) | 2020-10-30 |
Family
ID=67796754
Family Applications (4)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010781751.7A Withdrawn CN111857159A (en) | 2019-07-08 | 2019-07-08 | Vehicle control method based on big data |
| CN202010781925.XA Pending CN111845777A (en) | 2019-07-08 | 2019-07-08 | Big data vehicle control method |
| CN202010781748.5A Withdrawn CN111857158A (en) | 2019-07-08 | 2019-07-08 | Big data unmanned vehicle control method |
| CN201910612152.XA Active CN110209178B (en) | 2019-07-08 | 2019-07-08 | Unmanned vehicle control method based on big data |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010781751.7A Withdrawn CN111857159A (en) | 2019-07-08 | 2019-07-08 | Vehicle control method based on big data |
Family Applications After (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010781748.5A Withdrawn CN111857158A (en) | 2019-07-08 | 2019-07-08 | Big data unmanned vehicle control method |
| CN201910612152.XA Active CN110209178B (en) | 2019-07-08 | 2019-07-08 | Unmanned vehicle control method based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (4) | CN111857159A (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111221341B (en) * | 2020-02-16 | 2021-02-05 | 深圳市京弘全智能科技股份有限公司 | Safe driving control method for automatic driving vehicle and vehicle-mounted controller |
| CN114999165A (en) * | 2021-03-01 | 2022-09-02 | 上海博泰悦臻网络技术服务有限公司 | Vehicle speed determination method, system, medium, and apparatus |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102009654A (en) * | 2010-11-12 | 2011-04-13 | 清华大学 | Longitudinal speed evaluation method of full-wheel electrically-driven vehicle |
| CN105799512A (en) * | 2016-05-06 | 2016-07-27 | 深圳市中天安驰有限责任公司 | Vehicle overspeed reminding method and system |
| CN106828492A (en) * | 2013-05-03 | 2017-06-13 | 谷歌公司 | Predictive reasoning to controlling the speed of vehicle |
| CN107972668A (en) * | 2017-11-21 | 2018-05-01 | 杭州容大智造科技有限公司 | A kind of vehicle is from motion tracking drive manner, device and a kind of automobile |
| CN108039065A (en) * | 2017-12-25 | 2018-05-15 | 重庆冀繁科技发展有限公司 | Vehicle operation safety monitoring method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3597418B2 (en) * | 1999-07-28 | 2004-12-08 | 本田技研工業株式会社 | Platoon running equipment |
| CN102778223A (en) * | 2012-06-07 | 2012-11-14 | 沈阳理工大学 | License number cooperation target and monocular camera based automobile anti-collision early warning method |
| CN107831496B (en) * | 2017-11-01 | 2020-11-20 | 驭势科技（北京）有限公司 | Method and system for intelligent automobile to automatically acquire front speed |
| CN108957460B (en) * | 2018-06-27 | 2023-09-05 | 努比亚技术有限公司 | Method and device for detecting vehicle distance and computer readable storage medium |
-
2019
- 2019-07-08 CN CN202010781751.7A patent/CN111857159A/en not_active Withdrawn
- 2019-07-08 CN CN202010781925.XA patent/CN111845777A/en active Pending
- 2019-07-08 CN CN202010781748.5A patent/CN111857158A/en not_active Withdrawn
- 2019-07-08 CN CN201910612152.XA patent/CN110209178B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102009654A (en) * | 2010-11-12 | 2011-04-13 | 清华大学 | Longitudinal speed evaluation method of full-wheel electrically-driven vehicle |
| CN106828492A (en) * | 2013-05-03 | 2017-06-13 | 谷歌公司 | Predictive reasoning to controlling the speed of vehicle |
| CN105799512A (en) * | 2016-05-06 | 2016-07-27 | 深圳市中天安驰有限责任公司 | Vehicle overspeed reminding method and system |
| CN107972668A (en) * | 2017-11-21 | 2018-05-01 | 杭州容大智造科技有限公司 | A kind of vehicle is from motion tracking drive manner, device and a kind of automobile |
| CN108039065A (en) * | 2017-12-25 | 2018-05-15 | 重庆冀繁科技发展有限公司 | Vehicle operation safety monitoring method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110209178A (en) | 2019-09-06 |
| CN110209178B (en) | 2020-09-15 |
| CN111857159A (en) | 2020-10-30 |
| CN111857158A (en) | 2020-10-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111845744B (en) | Vehicle following control method and device, electronic equipment and storage medium | |
| CN107867283B (en) | Integrated FCW/ACC/AEB system based on prediction model and vehicle | |
| EP2698776B1 (en) | Vehicle control device and vehicle control method | |
| CN105946620A (en) | Electric automobile and active speed-limiting control method and system thereof | |
| CN110316198A (en) | A kind of safe-guard system and operation method for highway speed-raising | |
| CN110209178B (en) | Unmanned vehicle control method based on big data | |
| CN112298136B (en) | Driving control method, device and equipment for automatic driving vehicle and readable medium | |
| EP3600999B1 (en) | Distance control for a vehicle with trailer | |
| CN111127920A (en) | Vehicle-mounted communication-based rear-end collision prevention early warning and control method and system | |
| CN112078576A (en) | Adaptive cruise control method for simulating driver characteristics based on fuzzy control | |
| EP2830921A1 (en) | Method and system for spacing adjustment in a moving vehicle train | |
| CN113428180A (en) | Method, system and terminal for controlling single-lane running speed of unmanned vehicle | |
| JP4725565B2 (en) | Information providing apparatus, information providing system, and information providing method | |
| JPH10307997A (en) | Device and method for controlling travelling in files | |
| EP4180297A1 (en) | Automatic driving control method and apparatus | |
| CN205706232U (en) | Electric automobile and actively speed limit control system | |
| CN112874517B (en) | Vehicle AEB brake control method and vehicle | |
| CN110827559A (en) | Safety early warning method, device and system for highway traffic accidents | |
| CN115402312A (en) | Speed limiting device and method for automatic driving vehicle | |
| CN113888902A (en) | V2X technology-based loose coupling model for intersection dynamic bus priority feedback control and forward collision early warning | |
| CN117184081B (en) | Parking control method and device, electronic equipment and storage medium | |
| CN115639562B (en) | Commercial vehicle blind spot detection system, braking method, commercial vehicle and storage medium | |
| CN114863698B (en) | Active collision accident prevention and control system and method based on vehicle-road cooperation | |
| JP2002163779A (en) | Method and device for controlling stoppage of plural vehicles | |
| CN116605218B (en) | Control method and device, equipment and computer readable storage medium |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20201030 |
|
| WD01 | Invention patent application deemed withdrawn after publication |