CN109799821A - A kind of automatic Pilot control method based on state machine - Google Patents
A kind of automatic Pilot control method based on state machine Download PDFInfo
- Publication number
- CN109799821A CN109799821A CN201910074932.3A CN201910074932A CN109799821A CN 109799821 A CN109799821 A CN 109799821A CN 201910074932 A CN201910074932 A CN 201910074932A CN 109799821 A CN109799821 A CN 109799821A
- Authority
- CN
- China
- Prior art keywords
- lane
- decision
- state
- state machine
- condition
- 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
Abstract
The automatic Pilot control method based on state machine that the invention discloses a kind of, behaviour decision making module receive the information and vehicle CAN network information of environmental perception module acquisition；Automatic Pilot decision system is divided into lateral decision-making state machine, longitudinal decision-making state machine；Different states is separately included in lateral decision-making state machine, longitudinal decision-making state machine and corresponding state switching condition is set；The coupling of Full Vehicle Dynamics transverse and longitudinal, the signal of output control vehicle drive are carried out to the output result between lateral decision-making state machine and longitudinal decision-making state machine.The present invention has the advantages that realizing the automatic Pilot control for vehicle by finite state machine; structure is simple and clear, requires processor calculating low, real-time compared with strong, accuracy of determination is high, preferable for the processing of unusual service condition, is suitable for automatic Pilot scale volume production；System clear state determines control, and decision-making state information returns to environmental perception module simultaneously, advantageously reduces environmental perception module calculation amount.
Description
Technical field
The present invention relates to automatic Pilot field, in particular to a kind of automatic Pilot control method based on state machine.
Background technique
Intelligent vehicle fundamentally changes traditional vehicle drive mode, by driver from " driver vehicle's road closes
It is freed in loop system, controls vehicle driving using advanced electron and information technology, allowed conventional, persistently in driving-activity
And the operation of fatigue is automatically performed, and can greatly improve the efficiency of traffic system and the safety of personnel.Intelligent driving is main
Be divided into environment sensing, behaviour decision making, the big module of motion control three, wherein behaviour decision making control system similar to people brain, for
Automatic Pilot whole system plays a part of " commander in chief ".Behaviour decision making module mainly receives vehicle periphery from environmental perception module
Then environmental information issues control instruction to motion-control module.From domestic and foreign literature can be consulted, at present about behaviour decision making
Control algolithm mainly includes potential field method, region division method, deep learning, decision Tree algorithms.Potential field method is that a kind of pair of electric field carries out
The method of simulation, nearby environment is divided into safety zone and inevitable collision area to region division method automatic driving vehicle.This
Two class method calculation procedures are more complicated, and real-time is poor, it is difficult to meet vehicle rule grade automatic Pilot application.Deep learning is mesh
The algorithm that preceding comparison is popular is also strictly the decision-making technique for solving to meet the driving behavior habit of different type driver, still
It is more for training pattern data demand, to processor computing capability require it is larger, at present for be not particularly suited for driving automatically
Sail scale of mass production exploitation.Decision Tree algorithms, structure is complicated, need to all scenes of automatic Pilot and corresponding decision rule at
Tree, such decision making algorithm can be good at covering behaviour decision making system, but easily decision be caused to be overlapped.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of automatic Pilots based on finite state machine to determine
Plan control method carries out the switching of vehicle-state according to condition in the state of different finite state machines, realizes automatic Pilot.
To achieve the goals above, a kind of the technical solution adopted by the present invention are as follows: automatic Pilot based on finite state machine
Decision Control algorithm；Automatic Pilot decision system is divided into lateral decision-making state machine, longitudinal decision-making state machine；Finally to output
As a result the coupling of Full Vehicle Dynamics transverse and longitudinal is carried out.Wherein longitudinal decision-making state machine includes: cruising condition, following state, urgent system
Dynamic state.Lateral decision-making state machine includes: lane hold mode, lane-change state, abnormal modified line state.Believed according to the perception of vehicle
Breath carries out boundary condition calculating, and system switches between the different sub- state of transverse and longitudinal, to calculate vehicle target plus-minus
Speed, target steering angle, and then automatic driving vehicle is enable to drive safely.
A kind of automatic Pilot control method based on state machine, it is characterised in that: behaviour decision making module receives environment sensing
The information and vehicle CAN network information of module acquisition；
Automatic Pilot decision system is divided into lateral decision-making state machine, longitudinal decision-making state machine；In lateral decision-making state
Different states is separately included in machine, longitudinal decision-making state machine and corresponding state switching condition is set；
Full Vehicle Dynamics transverse and longitudinal coupling is carried out to the output result between lateral decision-making state machine and longitudinal decision-making state machine
It closes, the signal of output control vehicle drive.
Longitudinal decision-making state machine includes sub- state: cruising condition, following state, emergency braking condition；
Lateral decision-making state machine includes sub- state: lane hold mode, lane-change state, abnormal modified line state.
The condition of different conditions switching in lateral decision-making state machine is defined respectively, defines different shapes in longitudinal decision-making state machine
State switching condition, and information switches corresponding state according to the collected data.
In lateral decision-making state machine, lane hold mode is default conditions, by pre-defined state switching condition come
Switch different conditions, switching includes:
(1), lane hold mode enters lane-change state:
A: automatic driving vehicle generates lane-changing intention；
B: output decision lane-change direction；
C: lane-change feasibility meets；
When three above condition meets simultaneously, is entered by lane hold mode and change to state；
(2), lane-change state enters lane hold mode
Automatic driving vehicle enters lane hold mode needs by lane-change while meeting the following conditions, i.e. automatic driving vehicle
Lane-change is completed to enter lane hold mode condition are as follows:
A: the current centroid position of automatic driving vehicle and the lateral deviation of target lane center are less than calibration value；
B: automatic driving vehicle course angle and target lane centerlines are less than calibration value；
C: the lane-change time is more than or equal to calibration value；
Meet three above condition simultaneously, lane changes to completion and enters lane line hold mode；
(3), lane-change state enters abnormal modified line state
It is interrupted during automatic driving vehicle lane-change by environment vehicle midway, lane-change movement is unable to complete, automatic Pilot vehicle
Enter abnormal modified line to ensure the safety of driving status, vehicle enters the condition of abnormal modified line:
A, automatic driving vehicle lane-change target lane exception and vehicle TTC are less than 2.5s；
B: the positive side vehicle of automatic driving vehicle crosses line；
C: target lane TTC is less than the remaining lane-change time, the remaining lane-change time is greater than calibration value and TTC is less than calibration value；
Any satisfaction of three conditions enters abnormal modified line state；
(4) lane hold mode enters abnormal modified line state
Automatic driving vehicle normal lane keep when driving, driving cycle change automatic driving vehicle need force sail
From this lane；
(5), abnormal modified line state enters lane hold mode.
In longitudinal decision-making state machine, default original state is cruising condition, by pre-defined state switching condition come
Switch different conditions, including: the condition of following state is entered by cruising condition, enters the item of cruising condition by following state
Part, following state enter the condition of emergency braking condition, cruising condition enters the condition of emergency braking condition, emergency braking condition
Into the condition of following state.
The present invention has the advantages that realizing the automatic Pilot control for vehicle by finite state machine, structure is simple
It is illustrated, requires processor calculating low, real-time compared with strong, accuracy of determination is high, preferable for the processing of unusual service condition, is suitable for
Automatic Pilot scale volume production；System clear state determines control, and decision-making state information returns to environmental perception module simultaneously, favorably
In reduction environmental perception module calculation amount.Transverse state machine, longitudinal state machine respectively will be automatically controlled, not according to vehicle acquisition
Corresponding driving status is switched to data and the acceleration and deceleration of vehicle are controlled according to vehicle-state, thus realize automatic control,
Since full-vehicle control is divided into crosswise joint, longitudinally controlled, so that control is more accurate.
Detailed description of the invention
Below to each width attached drawing of description of the invention expression content and figure in label be briefly described:
Fig. 1 is the automatic Pilot decision schematic diagram of finite state machine of the present invention；
Fig. 2 is the longitudinal state machine diagram of the present invention；
Fig. 3 is transverse state of the present invention and schematic diagram；
Fig. 4 is that transverse state machine-cut of the present invention changes schematic diagram；
Fig. 5 is that lane keeps entering lane-change status diagram；
Fig. 6 is front vehicles lane-change feasibility schematic diagram；
Fig. 7 is side vehicle lane-changing feasibility schematic diagram；
Fig. 8 is front vehicle lane-change feasibility schematic diagram；
Fig. 9 is the left lane-change schematic diagram of special operation condition；
The right lane-change schematic diagram of Figure 10 special operation condition；
Figure 11 is that lane-change enters lane holding schematic diagram；
Figure 12 is that lane-change enters abnormal modified line schematic diagram；
Figure 13 is that lane keeps entering abnormal modified line schematic diagram.
Specific embodiment
A specific embodiment of the invention is made further detailed below against attached drawing by the description to optimum embodiment
Thin explanation.
This patent proposes a kind of automatic Pilot Decision Control algorithm based on finite state machine；Automatic Pilot decision system
It is divided into lateral decision-making state machine, longitudinal decision-making state machine；The coupling of Full Vehicle Dynamics transverse and longitudinal finally is carried out to output result.Its
Middle longitudinal direction decision-making state machine includes: cruising condition, following state, emergency braking condition.Lateral decision-making state machine includes: lane is protected
Hold state, lane-change state, abnormal modified line state.Boundary condition calculating is carried out according to the perception information of vehicle, system is in transverse and longitudinal
It is switched between different sub- states, to calculate vehicle target acceleration-deceleration, target steering angle, and then makes automatic Pilot vehicle
It can drive safely.
Automatic Pilot control method based on finite state machine, comprising: 1 behaviour decision making module receives environmental perception module
Object list information, thingness information and vehicle CAN network information.
2 automatic Pilot decision systems are divided into lateral decision-making state machine, longitudinal decision-making state machine.Wherein longitudinal decision shape
State machine includes sub- state: cruising condition, following state, emergency braking condition；Lateral decision-making state machine includes sub- state: lane is protected
Hold state, lane-change state, abnormal modified line state.
3 define the condition of sub- transverse state machine different conditions switching:
3.1 lanes keep (LKS) state to enter lane-change (CL) state, such as Fig. 5
Need to meet simultaneously following three conditions:
A: automatic driving vehicle generates lane-changing intention
B: output decision lane-change direction
C: lane-change feasibility meets
3.1.1 lane-changing intention judgment method:
It is expected that satisfaction, generated in automatic driving vehicle driving process because desired speed, expectation spacing are unsatisfactory for driver
Lane-changing intention.It is expected that the satisfaction of spacing: the actual range and driver of automatic driving vehicle and front vehicle it is expected the ratio of spacing
Value.
Note: φLFor the satisfaction for it is expected spacing
D1For the actual range of Ben Che and this lane front truck
LEFor the expectation spacing of Ben Che and this lane front truck
The satisfaction of desired speed: the ratio of automatic driving vehicle present speed and desired speed.
Note: φVFor the satisfaction of desired speed
V1For current automatic driving vehicle speed
VESatisfaction it is expected for automatic driving vehicle desired speed driver: being that expectation spacing satisfaction and desired speed are full
The linear combination of sufficient degree
φ=K1φL+K2φV
In formula, φ must indicate the expectation satisfaction of driver, K1、K2Respectively the influence of desired speed and desired spacing because
Son, and K1+K2=1 under normal circumstances, if practical spacing is much larger than desired spacing, K1> K2But different driver K1、
K2Value be not quite similar, cause its generate lane-changing intention driver it is expected satisfaction critical value be also not quite similar.
3.1.2 this three-lane road is abnormal
Can travel immediately ahead of this lane of automatic driving vehicle region due to being repaired the roads, the influences such as accident narrow.
3.1.3 target lane is changed
Score change is controlled by target Lane regulation module, and target Lane regulation module exports automatic driving vehicle row
Global object lane during sailing.
3.1.4 driver triggers
Automatic driving vehicle is in the process of moving since driver stirs turning-bar triggering vehicle lane-changing.
3.2 lane-change direction decisions
3.2.1 driver's activly request
Driver stirs the direction of turning-bar request as automatic driving vehicle lane-change.When driver's activly request lane-change
Whether vehicle lane-changing movement, which executes, has to meet left (right side) lane-change feasibility judgement, to prevent the driver in driving procedure from missing
Triggering.
3.2.2 score changes
Target Lane regulation module exports automatic driving vehicle global object lane, and automatic driving vehicle generates initiative lane change
It is intended to, exports left and right lane-change direction.
Priority: A > B
3.3 lane-change feasibility decisions
3.3.1 front vehicles lane-change feasibility judges, such as Fig. 6,
Automated driving system front vehicles lane-change feasibility decision is divided into left front vehicle, right front truck two parts, and front vehicles are changed
Road need to meet condition
A) this lane objects ahead (including static-obstacle) vehicle: TTC (collision time) is greater than automatic driving vehicle lane-change
Time
B) target lane front truck (not including static-obstacle): left front vehicle (right front truck) it is 2kph bigger than vehicle speed before this lane with
Upper and distance be greater than calibration value * operating distance (the initial expectation following distance of setting, using fuzzy control principle according to Ben Che with before
Vehicle relative velocity, relative distance calculate vehicle and carry out the relative distance point for dragging braking or hydraulic braking to shelves) or left front vehicle
(right front truck) speed is more than or equal to this vehicle Maximum speed limit and distance is greater than operating distance 50%
3.3.2 vehicle lane-changing feasibility in side judges that side is without vehicle, the positive side of automatic driving vehicle.
3.3.3 front vehicle lane-change feasibility judges
Target lane rear car TTC is greater than lane-change time * 2 and distance is greater than calibration value
3.3.4. left side lane-change is preferential
A) left front vehicle speed is greater than right front truck 10kph or left front vehicle speed is more than cruising speed 2kph or more
3.3.5. traffic rules
A) automatic driving vehicle lane-change traveling must abide by road traffic laws and regulations, such as: actual situation line, road speed limit, light loudspeaker
Deng requirement.
3.3.6. special operation condition lane-change
A) target lane is without exception and target lane side lane line 80cm within the scope of static-obstacle TTC be greater than calibration value
Target lane abnormal signal provides signal input by road anomalous identification module.
3.2 lane-changes (CL) state enters lane and keeps (LKS) state
Automatic driving vehicle enters lane holding (LKS) state needs by lane-change (CL) while meeting the following conditions, i.e., certainly
The dynamic vehicle lane-changing that drives is completed to enter lane hold mode condition
A: the current centroid position of automatic driving vehicle and the lateral deviation of target lane center are less than calibration value
B: automatic driving vehicle course angle and target lane centerlines are less than calibration value
C: the lane-change time is more than or equal to calibration value
3.3 lane-changes (CL) state enters abnormal modified line state (ALC)
It being interrupted (lane-change interrupts) during automatic driving vehicle lane-change by environment vehicle midway, lane-change movement is unable to complete,
Automatic driving vehicle enters abnormal modified line ALC (urgent avoidance state) to ensure the safety of driving status, and vehicle enters exception
The condition of modified line:
Automatic driving vehicle lane-change, which interrupts, during lane-change needs to meet one of A, B, C condition；
A: front environment vehicle interrupts
1. automatic driving vehicle lane-change target lane is abnormal (road anomalous identification module)
2. vehicle TTC is less than 2.5s (not including static-obstacle)
B: side vehicle interrupts
1. the positive side vehicle of automatic driving vehicle crosses line (TBDm)
C: rear environment vehicle interrupts
1. target lane TTC is less than the remaining lane-change time
2. the remaining lane-change time is greater than calibration value (this tailstock portion wheel does not cross line)
3.TTC is less than calibration value
3. 4 lanes keep (LKS) state to enter abnormal modified line (ALC) state
Automatic driving vehicle normal lane keeps (LKS) when driving, and driving cycle changes, and (such as: tunnel portal goes out circle
The operating conditions such as road, road interflow, environment vehicle CutIn) automatic driving vehicle need force sail out of this lane.
A: offset is forced
1. static-obstacle and distance be less than calibration value
2. distance objective ramp exit is less than calibration value
3. 1km does not enter target lane before tunnel
4. 500 meters do not sail out of the lane that narrows
B: dynamic deflection
1. automatic driving vehicle and front vehicles TTC are less than calibration value
(longitudinal TTC is less than calibration value & transverse direction closest approach and is less than 1.6m away from this lane center left side cut in
(longitudinal TTC is less than calibration value & transverse direction closest approach and is less than 1.6m away from this lane center right side cut in
2. front truck emergency braking (longitudinal TTC is less than calibration value)
3. line (0: not no, 1: yes) is crossed in side
4. side region is the positive side of this vehicle vehicle body
Line is crossed in left or right side
5. this lane pedestrian
C: lane shift
3.5 abnormal modified line (ALC) states enter lane and keep (LKS) state
After automatic driving vehicle exception modified line (ALC), vehicle enters lane hold mode, into lane hold mode
Condition it is different as follows according to state,
A1: offset is forced to cancel and (force incision failure)
1. crossing outlet, incision deceleratuib lane failure
It is less than calibration value away from outlet bifurcation distance and is greater than calibration value away from score lateral distance
2. entering 10m behind tunnel, target lane is not entered
Current lane is normal and does not enter target lane
A2: offset is forced to be completed
1. vehicle origin and lane center lateral deviation are less than calibration value
2. vehicle course and lane center angle are less than calibration value
B: lane shift is completed:
1. vehicle origin and lane center lateral deviation are less than calibration value
2. vehicle course and lane center angle are less than calibration value
C: dynamic deflection is completed:
1. vehicle origin and lane center lateral deviation are less than calibration value
2. vehicle course and lane center angle are less than calibration value
4, the switching condition of longitudinal state loom state is defined:
Default original state is cruising condition；
4.1, enter the condition of following state by cruising condition
Distance between automatic driving vehicle and target front truck is less than (the initial expectation of setting of automatic driving vehicle operating distance
Following distance, using fuzzy control principle according to Ben Che and front truck relative velocity, relative distance calculates vehicle and drag to shelves
The relative distance point of braking or hydraulic braking, operating distance is calibration value)
4.2. enter the condition of cruising condition by following state
4.2.1 distance between automatic driving vehicle and target front truck, greater than current max. speed setting operating distance (most
Big value)
4.2.2 before automatic driving vehicle and target vehicle speed be greater than Maximum speed limit and actual range be greater than front truck it is expected away from
From * calibration value
4.3 following states enter the condition of emergency braking condition
4.3.1 TTC is less than calibration value between automatic driving vehicle and target front truck
4.3.2 distance is less than speed difference between (operating distance * 0.1) and two vehicles between automatic driving vehicle and target front truck
Less than 5kph
4.4 cruising conditions enter the condition of emergency braking condition
4.4.1 TTC is less than calibration value between automatic driving vehicle and target front truck
4.4.2 distance is less than speed difference between (operating distance * 0.1) and two vehicles between automatic driving vehicle and target front truck
Less than 5kph
4.5 emergency braking conditions enter the condition of following state
4.5.1 TTC is greater than calibration value between automatic driving vehicle and target front truck
4.5.2 relative distance is greater than (operating distance * 0.2) between two vehicles
5 max. speed management: the current max. speed limitation (disengaged position machine) of output vehicle
6 each sub- states calculate separately out vehicle target acceleration-deceleration, target in corresponding sub- state according to boundary information
Steering angle.
This patent combination automobile dynamics, and anthropomorphic class driving behavior application state machine draw automatic Pilot decision system
It is divided into: longitudinal decision-making state machine, lateral decision-making state machine.Using the form of state machine make system structure it is simple and clear, to place
Reason device calculating requires low, real-time compared with strong, accuracy of determination is high, preferable for the processing of unusual service condition, is suitable for automatic Pilot
Scale volume production.
Obviously present invention specific implementation is not subject to the restrictions described above, as long as using method concept and skill of the invention
The improvement for the various unsubstantialities that art scheme carries out, it is within the scope of the present invention.
Claims (5)
1. a kind of automatic Pilot control method based on state machine, it is characterised in that: behaviour decision making module receives environment sensing mould
The information and vehicle CAN network information of block acquisition；
Automatic Pilot decision system is divided into lateral decision-making state machine, longitudinal decision-making state machine；In lateral decision-making state machine, indulge
Different states is separately included into decision-making state machine and corresponding state switching condition is set；
The coupling of Full Vehicle Dynamics transverse and longitudinal is carried out to the output result between lateral decision-making state machine and longitudinal decision-making state machine, it is defeated
The signal of vehicle drive is controlled out.
2. a kind of automatic Pilot control method based on state machine as described in claim 1, it is characterised in that: longitudinal decision shape
State machine includes sub- state: cruising condition, following state, emergency braking condition；
Lateral decision-making state machine includes sub- state: lane hold mode, lane-change state, abnormal modified line state.
3. a kind of automatic Pilot control method based on state machine as claimed in claim 2, it is characterised in that: definition is horizontal respectively
Different conditions switch into decision-making state machine condition defines different conditions switching condition in longitudinal decision-making state machine, and according to
The data information of acquisition switches corresponding state.
4. a kind of automatic Pilot control method based on state machine as claimed in claim 3, it is characterised in that: in lateral decision
In state machine, lane hold mode is default conditions, switches different conditions by pre-defined state switching condition, switches
Include:
(1), lane hold mode enters lane-change state:
A: automatic driving vehicle generates lane-changing intention；
B: output decision lane-change direction；
C: lane-change feasibility meets；
When three above condition meets simultaneously, is entered by lane hold mode and change to state；
(2), lane-change state enters lane hold mode
Automatic driving vehicle enters lane hold mode needs by lane-change while meeting the following conditions, i.e. automatic driving vehicle lane-change
It completes to enter lane hold mode condition are as follows:
A: the current centroid position of automatic driving vehicle and the lateral deviation of target lane center are less than calibration value；
B: automatic driving vehicle course angle and target lane centerlines are less than calibration value；
C: the lane-change time is more than or equal to calibration value；
Meet three above condition simultaneously, lane changes to completion and enters lane line hold mode；
(3), lane-change state enters abnormal modified line state
Interrupted by environment vehicle midway during automatic driving vehicle lane-change, lane-change movement is unable to complete, automatic driving vehicle into
Enter abnormal modified line to ensure the safety of driving status, vehicle enters the condition of abnormal modified line:
A, automatic driving vehicle lane-change target lane exception and vehicle TTC are less than 2.5s；
B: the positive side vehicle of automatic driving vehicle crosses line；
C: target lane TTC is less than the remaining lane-change time, the remaining lane-change time is greater than calibration value and TTC is less than calibration value；
Any satisfaction of three conditions enters abnormal modified line state；
(4) lane hold mode enters abnormal modified line state
Automatic driving vehicle normal lane is kept when driving, and the driving cycle automatic driving vehicle that changes needs to force to sail out of this
Lane；
(5), abnormal modified line state enters lane hold mode.
5. a kind of automatic Pilot control method based on state machine as claimed in claim 1 or 2, it is characterised in that: in longitudinal direction
In decision-making state machine, default original state is cruising condition, switches different conditions by pre-defined state switching condition,
In include: the condition of following state is entered by cruising condition, the condition that enters cruising condition by following state, following state enter
Condition, the cruising condition of emergency braking condition enter the condition of emergency braking condition, emergency braking condition enters following state
Condition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910074932.3A CN109799821A (en) | 2019-01-25 | 2019-01-25 | A kind of automatic Pilot control method based on state machine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910074932.3A CN109799821A (en) | 2019-01-25 | 2019-01-25 | A kind of automatic Pilot control method based on state machine |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109799821A true CN109799821A (en) | 2019-05-24 |
Family
ID=66558865
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910074932.3A Pending CN109799821A (en) | 2019-01-25 | 2019-01-25 | A kind of automatic Pilot control method based on state machine |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109799821A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110304074A (en) * | 2019-06-28 | 2019-10-08 | 电子科技大学 | A kind of hybrid type driving method based on stratification state machine |
| CN110780602A (en) * | 2019-09-09 | 2020-02-11 | 腾讯科技（深圳）有限公司 | Method, device and equipment for constructing simulated vehicle lane change track |
| CN111338361A (en) * | 2020-05-22 | 2020-06-26 | 浙江远传信息技术股份有限公司 | Obstacle avoidance method, device, equipment and medium for low-speed unmanned vehicle |
| CN113548049A (en) * | 2021-07-27 | 2021-10-26 | 武汉理工大学 | Intelligent vehicle driving behavior decision method and system based on finite-state machine |
| CN113704967A (en) * | 2021-07-23 | 2021-11-26 | 武汉光庭信息技术股份有限公司 | ADAS finite state machine design method and system based on stateflow |
| CN114415728A (en) * | 2022-01-21 | 2022-04-29 | 广东汇天航空航天科技有限公司 | Control method and device for aerocar, vehicle and storage medium |
| CN114550474A (en) * | 2020-11-24 | 2022-05-27 | 华为技术有限公司 | Transverse planning constraint determination method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080161969A1 (en) * | 2006-12-28 | 2008-07-03 | Industrial Technology Research Institute | Method for routing a robotic apparatus to a service station and robotic apparatus service system using thereof |
| CN106940933A (en) * | 2017-03-08 | 2017-07-11 | 北京理工大学 | A kind of intelligent vehicle decision-making lane-change method based on intelligent transportation system |
| CN107139917A (en) * | 2017-04-27 | 2017-09-08 | 江苏大学 | It is a kind of based on mix theory pilotless automobile crosswise joint system and method |
| CN107797534A (en) * | 2017-09-30 | 2018-03-13 | 安徽江淮汽车集团股份有限公司 | A kind of pure electronic automated driving system |
| CN108437988A (en) * | 2018-03-30 | 2018-08-24 | 吉利汽车研究院（宁波）有限公司 | A kind of transverse control device and method for intelligent navigation system |
| CN108725453A (en) * | 2018-06-11 | 2018-11-02 | 南京航空航天大学 | Control system and its switch mode are driven altogether based on pilot model and manipulation the man-machine of inverse dynamics |
-
2019
- 2019-01-25 CN CN201910074932.3A patent/CN109799821A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080161969A1 (en) * | 2006-12-28 | 2008-07-03 | Industrial Technology Research Institute | Method for routing a robotic apparatus to a service station and robotic apparatus service system using thereof |
| CN106940933A (en) * | 2017-03-08 | 2017-07-11 | 北京理工大学 | A kind of intelligent vehicle decision-making lane-change method based on intelligent transportation system |
| CN107139917A (en) * | 2017-04-27 | 2017-09-08 | 江苏大学 | It is a kind of based on mix theory pilotless automobile crosswise joint system and method |
| CN107797534A (en) * | 2017-09-30 | 2018-03-13 | 安徽江淮汽车集团股份有限公司 | A kind of pure electronic automated driving system |
| CN108437988A (en) * | 2018-03-30 | 2018-08-24 | 吉利汽车研究院（宁波）有限公司 | A kind of transverse control device and method for intelligent navigation system |
| CN108725453A (en) * | 2018-06-11 | 2018-11-02 | 南京航空航天大学 | Control system and its switch mode are driven altogether based on pilot model and manipulation the man-machine of inverse dynamics |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110304074A (en) * | 2019-06-28 | 2019-10-08 | 电子科技大学 | A kind of hybrid type driving method based on stratification state machine |
| CN110304074B (en) * | 2019-06-28 | 2020-07-31 | 电子科技大学 | Hybrid driving method based on layered state machine |
| CN110780602A (en) * | 2019-09-09 | 2020-02-11 | 腾讯科技（深圳）有限公司 | Method, device and equipment for constructing simulated vehicle lane change track |
| CN111338361A (en) * | 2020-05-22 | 2020-06-26 | 浙江远传信息技术股份有限公司 | Obstacle avoidance method, device, equipment and medium for low-speed unmanned vehicle |
| CN114550474A (en) * | 2020-11-24 | 2022-05-27 | 华为技术有限公司 | Transverse planning constraint determination method and device |
| CN114550474B (en) * | 2020-11-24 | 2023-03-03 | 华为技术有限公司 | Transverse planning constraint determination method and device |
| CN113704967A (en) * | 2021-07-23 | 2021-11-26 | 武汉光庭信息技术股份有限公司 | ADAS finite state machine design method and system based on stateflow |
| CN113704967B (en) * | 2021-07-23 | 2024-01-12 | 武汉光庭信息技术股份有限公司 | ADAS finite state machine design method and system based on stateflow |
| CN113548049A (en) * | 2021-07-27 | 2021-10-26 | 武汉理工大学 | Intelligent vehicle driving behavior decision method and system based on finite-state machine |
| CN114415728A (en) * | 2022-01-21 | 2022-04-29 | 广东汇天航空航天科技有限公司 | Control method and device for aerocar, vehicle and storage medium |
| CN114415728B (en) * | 2022-01-21 | 2023-11-03 | 广东汇天航空航天科技有限公司 | Control method and device for aerocar, vehicle and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109799821A (en) | A kind of automatic Pilot control method based on state machine | |
| CN108572642B (en) | Automatic driving system and transverse control method thereof | |
| CN109669461B (en) | Decision-making system for automatically driving vehicle under complex working condition and track planning method thereof | |
| CN108657189B (en) | Automatic driving steering system based on BP neural network and safe distance lane change working condition and control method thereof | |
| CN109035862B (en) | Multi-vehicle cooperative lane change control method based on vehicle-to-vehicle communication | |
| DE112019003322B4 (en) | vehicle control device | |
| CN110386152B (en) | Human-computer interaction display control method and system based on L2-level intelligent piloting driving | |
| KR101981350B1 (en) | Method for guiding a vehicle, and driver assistance system | |
| CN109808685B (en) | Automobile early warning automatic collision avoidance control method based on danger assessment | |
| CN106218638B (en) | Intelligent network-connected automobile cooperative lane change control method | |
| CN103754221B (en) | Vehicle adaptive cruise control system | |
| CN102027458B (en) | Method and apparatus for driver control of a limited-ability autonomous vehicle | |
| CN112040392B (en) | Multi-vehicle cooperative lane change control system and method based on vehicle-to-vehicle communication | |
| CN110001782A (en) | Automatic lane-change method, system and computer readable storage medium | |
| CN102292752B (en) | Row running control system and vehicle | |
| CN113291308B (en) | Vehicle self-learning lane-changing decision-making system and method considering driving behavior characteristics | |
| CN109649393A (en) | A kind of paths planning method and device of automatic Pilot changing Lane | |
| CN108819951A (en) | It is a kind of to consider that the man-machine of driver's driving efficiency drives transverse driving power distribution method altogether | |
| CN110187639A (en) | A kind of trajectory planning control method based on Parameter Decision Making frame | |
| CN104960524A (en) | Multi-vehicle coordinating lane changing control system and method based on vehicle-vehicle communication | |
| CN109804420B (en) | Vehicle control device | |
| CN109963760B (en) | Vehicle control device | |
| CN110304074A (en) | A kind of hybrid type driving method based on stratification state machine | |
| CN208393354U (en) | Line operating condition automatic Pilot steering system is moved based on BP neural network and safe distance | |
| CN108909710A (en) | It is a kind of to overtake other vehicles the driving assistance method and system of operating condition applied to piggybacking |
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: 20190524 |
|
| WD01 | Invention patent application deemed withdrawn after publication |