Among the recent advancements in car safety technologies, the adaptive cruise control feature is one of the most important and useful. It greatly minimizes the pressure of the driver as it helps to control the speed of the car and maintains a safe distance from other cars to avoid a crash. But still, this adaptive control should not be used in bad weather conditions and in tunnels as they might not work efficiently. So, if you want to know all about the adaptive cruise control system in your car, then give some time to watch the following slide show.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Among the recent advancements in car safety technologies, the adaptive cruise control feature is one of the most important and useful. It greatly minimizes the pressure of the driver as it helps to control the speed of the car and maintains a safe distance from other cars to avoid a crash. But still, this adaptive control should not be used in bad weather conditions and in tunnels as they might not work efficiently. So, if you want to know all about the adaptive cruise control system in your car, then give some time to watch the following slide show.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Today, a typical automobile on the road has computer controlled electronic systems, and the most commonly used embedded systems in a vehicle include Airbags, anti-lock braking system, black box, adaptive cruise control, drive by wire, satellite radio, telematics, emission control, traction control, automatic parking, in-vehicle entertainment systems, night vision, heads up display, back up collision sensors, navigational systems, tyre pressure monitor, climate control, etc
This helps you to know the advance technology of automotive.In this paper, I address the influence of ICT based Intelligent Automobile Safety System reduce the proportion of Highway Accidents due to human factor (i.e. 95%). These systems make use of ICT to provide solutions for improving road safety in particular in the pre-crash phase. These systems operate either autonomously on board of the vehicle or co-operatively through vehicle to vehicle or vehicle to infrastructure communications. They make it possible to ensure safe speed, lane support, pedestrian protection, night improved vision, driver information system, GPS & GIS navigation, emergency braking system, hill ascending & descending holders, traction control, roll over and its protection and wine smell detector.
After decades of anticipation, practical self-driving cars are here. Drive.ai will deploy a self-driving car service for public use in Texas starting in July.
We can continue pushing self-driving forward by focusing on three key elements: industry-leading AI technology, local partnerships, and people-centric safety.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
Hill Start Assist is an automatic system that operates the brakes to stop your vehicle rolling back when it is starting on a steep hill. The DAC system assists engine braking to help improve directional control during descent on steep or slippery surfaces.
Today, a typical automobile on the road has computer controlled electronic systems, and the most commonly used embedded systems in a vehicle include Airbags, anti-lock braking system, black box, adaptive cruise control, drive by wire, satellite radio, telematics, emission control, traction control, automatic parking, in-vehicle entertainment systems, night vision, heads up display, back up collision sensors, navigational systems, tyre pressure monitor, climate control, etc
This helps you to know the advance technology of automotive.In this paper, I address the influence of ICT based Intelligent Automobile Safety System reduce the proportion of Highway Accidents due to human factor (i.e. 95%). These systems make use of ICT to provide solutions for improving road safety in particular in the pre-crash phase. These systems operate either autonomously on board of the vehicle or co-operatively through vehicle to vehicle or vehicle to infrastructure communications. They make it possible to ensure safe speed, lane support, pedestrian protection, night improved vision, driver information system, GPS & GIS navigation, emergency braking system, hill ascending & descending holders, traction control, roll over and its protection and wine smell detector.
After decades of anticipation, practical self-driving cars are here. Drive.ai will deploy a self-driving car service for public use in Texas starting in July.
We can continue pushing self-driving forward by focusing on three key elements: industry-leading AI technology, local partnerships, and people-centric safety.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
Hill Start Assist is an automatic system that operates the brakes to stop your vehicle rolling back when it is starting on a steep hill. The DAC system assists engine braking to help improve directional control during descent on steep or slippery surfaces.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
Improved Control Design for Autonomous VehiclesIJITCA Journal
Call for papers ....!!!
International Journal of Information Technology, Control and Automation (IJITCA)
ISSN : 1839-6682
Web page :https://airccse.org/journal/ijitca/ijitca.html
Submission Deadline : December 30, 2023
Contact us: E-mail: ijitcajournal@yahoo.com or ijitca@wireilla.com
Paper submission link :https://airccse.org/journal/ijitca/submission.html
Current issue link :https://airccse.org/journal/ijitca/vol12.html
Paper pdf link : http://wireilla.com/papers/ijitca/V12N3/12322ijitca01.pdf
International Journal of Information Technology, Control and Automation (IJITCA)IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
IMPROVED CONTROL DESIGN FOR AUTONOMOUS VEHICLESIJITCA Journal
In this paper, the autonomous vehicle presented as a discrete-time Takagi-Sugeno fuzzy (T-S) model. We
used the discrete-time T-S model since it is ready for the implementation unlike the continuous T-S fuzzy
model. The main goal is to keep the autonomous vehicle in the centreline of the lane regardless the
external disturbances. These disturbances are the wind force and the unknown curvature; they are applied
to test if the autonomous vehicle moves from the centreline. To ensure that the autonomous vehicle remain
on the centreline we propose two discrete-time fuzzy lateral controllers called also steering controllers.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of automatic navigation control system for agricultural vehicleeSAT Journals
Abstract The tractor automatic navigation technology is one of the hottest research fields of precision agriculture as well as a major means for realizing intelligent operating of agricultural vehicle in future. This paper presents a thorough research on GPS automatic navigation technology of agricultural vehicle considering that working conditions and field conditions for the tractor are complex and that there is a high requirement on the precision of the driving path of the tractor. Major contents of the research are as follows: The hydraulic control valve was selected by testing. A hydraulic control valve test platform specific to navigation was designed. The test platform can gather information about the flow and pressure of each measured hydraulic valve in a real-time manner. A navigation valve block was developed. Finally, the navigation valve block was used in electro-hydraulic transformation of model vehicle, realizing the control of electrical signal in tractor steering. A hardware platform for the automatic navigation system was built. A navigation controller based on ARM chip, the RTK-GPS positioning system and the angle sensor constitute the hardware platform of the autopilot system of the tractor. The hardware platform is the basis for realizing automatic navigation of the tractor. The navigation control algorithm was studied, pure pursuit model tracking algorithm were analyzed; the navigation decision-making control system based on the pure pursuit model tracking algorithm was designed; the kinematics model of the tractor was established. The pure tracking model has been simulated by MATLAB software, and the system has good stability and sensitivity. The experimental research on the automatic navigation system of the tractor was conducted. Based on the automatic navigation platform developed above, experiments on the control of the tractor walking straight at the flat road have been done. The results proved that the automatic navigation system has the capability of tracking the straight path of the tractor in a real-time and stable manner and meets the requirements of precision agriculture. Keywords: Automatic Navigation, Precision Agriculture, Steering Control System, Path Tracking
Smart vehicle and smart signboard system with zonal speed regulationIAEME Publication
To control the accident highway department have placed the signboards. Increasing number of accidents at busy junctions are a major threat faced by today’s world. Nowadays people are driving very fast; we lost our valuable life by making small mistake while driving (school zone, hills area, and highways). Most of accidents are occur due to two wheelers Speed control is required at busy junctions.
ACTIVE SAFETY CONTROL TECHNIQUE TO PREVENT VEHICLE CRASHINGP singh
Alertness during driving is a key aspect. Even a small distraction for the driver may lead to genuine mishaps. The possible reasons can be obstacle, inadequate vehicle control system or human reflexes (e.g. shock) during sudden distraction. Therefore "Active" and "Passive" systems for vehicle control play a significant role in automotive safety. In this paper, we have discussed an active control technique to prevent the vehicle from crashing. Three different cases of vehicle speed are considered. The presented technique is designed to evaluate the possibility of collision for both front and rear side. The control action will be taken for safe and smooth driving under different situations like parking, urban driving and highway driving.
Fuzzy rules incorporated skyhook theory based vehicular suspension design for...IJERA Editor
The vehicle suspension system supports and isolate the vehicle body and payload from road vibrations due to surface roughness by maintaining a controllable damping traction force between tires and road surface. In modern luxury vehicles semi active suspension system are offering both the reliability and accuracy that has enhanced the passenger ride comfort with less power demand. In this paper we have proposed the design of a hybrid control system having a combination of skyhook theory with fuzzy logic control and applied on a semi-active vehicle suspension system for its ride comfort enhancement. A two degree of freedom dynamic model is simulated using Matlab/Simulink for a vehicle equipped with semi-active suspension system with focused on the passenger‟s ride comfort performance.
Comprehensive program for Agricultural Finance, the Automotive Sector, and Empowerment . We will define the full scope and provide a detailed two-week plan for identifying strategic partners in each area within Limpopo, including target areas.:
1. Agricultural : Supporting Primary and Secondary Agriculture
• Scope: Provide support solutions to enhance agricultural productivity and sustainability.
• Target Areas: Polokwane, Tzaneen, Thohoyandou, Makhado, and Giyani.
2. Automotive Sector: Partnerships with Mechanics and Panel Beater Shops
• Scope: Develop collaborations with automotive service providers to improve service quality and business operations.
• Target Areas: Polokwane, Lephalale, Mokopane, Phalaborwa, and Bela-Bela.
3. Empowerment : Focusing on Women Empowerment
• Scope: Provide business support support and training to women-owned businesses, promoting economic inclusion.
• Target Areas: Polokwane, Thohoyandou, Musina, Burgersfort, and Louis Trichardt.
We will also prioritize Industrial Economic Zone areas and their priorities.
Sign up on https://profilesmes.online/welcome/
To be eligible:
1. You must have a registered business and operate in Limpopo
2. Generate revenue
3. Sectors : Agriculture ( primary and secondary) and Automative
Women and Youth are encouraged to apply even if you don't fall in those sectors.
What Exactly Is The Common Rail Direct Injection System & How Does It WorkMotor Cars International
Learn about Common Rail Direct Injection (CRDi) - the revolutionary technology that has made diesel engines more efficient. Explore its workings, advantages like enhanced fuel efficiency and increased power output, along with drawbacks such as complexity and higher initial cost. Compare CRDi with traditional diesel engines and discover why it's the preferred choice for modern engines.
Core technology of Hyundai Motor Group's EV platform 'E-GMP'Hyundai Motor Group
What’s the force behind Hyundai Motor Group's EV performance and quality?
Maximized driving performance and quick charging time through high-density battery pack and fast charging technology and applicable to various vehicle types!
Discover more about Hyundai Motor Group’s EV platform ‘E-GMP’!
Why Is Your BMW X3 Hood Not Responding To Release CommandsDart Auto
Experiencing difficulty opening your BMW X3's hood? This guide explores potential issues like mechanical obstruction, hood release mechanism failure, electrical problems, and emergency release malfunctions. Troubleshooting tips include basic checks, clearing obstructions, applying pressure, and using the emergency release.
"Trans Failsafe Prog" on your BMW X5 indicates potential transmission issues requiring immediate action. This safety feature activates in response to abnormalities like low fluid levels, leaks, faulty sensors, electrical or mechanical failures, and overheating.
Symptoms like intermittent starting and key recognition errors signal potential problems with your Mercedes’ EIS. Use diagnostic steps like error code checks and spare key tests. Professional diagnosis and solutions like EIS replacement ensure safe driving. Consult a qualified technician for accurate diagnosis and repair.
Things to remember while upgrading the brakes of your carjennifermiller8137
Upgrading the brakes of your car? Keep these things in mind before doing so. Additionally, start using an OBD 2 GPS tracker so that you never miss a vehicle maintenance appointment. On top of this, a car GPS tracker will also let you master good driving habits that will let you increase the operational life of your car’s brakes.
In this presentation, we have discussed a very important feature of BMW X5 cars… the Comfort Access. Things that can significantly limit its functionality. And things that you can try to restore the functionality of such a convenient feature of your vehicle.
What Does the Active Steering Malfunction Warning Mean for Your BMWTanner Motors
Discover the reasons why your BMW’s Active Steering malfunction warning might come on. From electrical glitches to mechanical failures and software anomalies, addressing these promptly with professional inspection and maintenance ensures continued safety and performance on the road, maintaining the integrity of your driving experience.
What Does the PARKTRONIC Inoperative, See Owner's Manual Message Mean for You...Autohaus Service and Sales
Learn what "PARKTRONIC Inoperative, See Owner's Manual" means for your Mercedes-Benz. This message indicates a malfunction in the parking assistance system, potentially due to sensor issues or electrical faults. Prompt attention is crucial to ensure safety and functionality. Follow steps outlined for diagnosis and repair in the owner's manual.
5 Warning Signs Your BMW's Intelligent Battery Sensor Needs AttentionBertini's German Motors
IBS monitors and manages your BMW’s battery performance. If it malfunctions, you will have to deal with an array of electrical issues in your vehicle. Recognize warning signs like dimming headlights, frequent battery replacements, and electrical malfunctions to address potential IBS issues promptly.
𝘼𝙣𝙩𝙞𝙦𝙪𝙚 𝙋𝙡𝙖𝙨𝙩𝙞𝙘 𝙏𝙧𝙖𝙙𝙚𝙧𝙨 𝙞𝙨 𝙫𝙚𝙧𝙮 𝙛𝙖𝙢𝙤𝙪𝙨 𝙛𝙤𝙧 𝙢𝙖𝙣𝙪𝙛𝙖𝙘𝙩𝙪𝙧𝙞𝙣𝙜 𝙩𝙝𝙚𝙞𝙧 𝙥𝙧𝙤𝙙𝙪𝙘𝙩𝙨. 𝙒𝙚 𝙝𝙖𝙫𝙚 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙥𝙡𝙖𝙨𝙩𝙞𝙘 𝙜𝙧𝙖𝙣𝙪𝙡𝙚𝙨 𝙪𝙨𝙚𝙙 𝙞𝙣 𝙖𝙪𝙩𝙤𝙢𝙤𝙩𝙞𝙫𝙚 𝙖𝙣𝙙 𝙖𝙪𝙩𝙤 𝙥𝙖𝙧𝙩𝙨 𝙖𝙣𝙙 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙛𝙖𝙢𝙤𝙪𝙨 𝙘𝙤𝙢𝙥𝙖𝙣𝙞𝙚𝙨 𝙗𝙪𝙮 𝙩𝙝𝙚 𝙜𝙧𝙖𝙣𝙪𝙡𝙚𝙨 𝙛𝙧𝙤𝙢 𝙪𝙨.
Over the 10 years, we have gained a strong foothold in the market due to our range's high quality, competitive prices, and time-lined delivery schedules.
1. S245408 Waiyuntian Lou
S253778 Huanyu Su
Under the instruction of:
Prof. Massimiliana Carello
Lane Keeping Assist (LKA)
Academic Year 2018-2019
14/12/2018
2. Chapter 1 Introduction
2
-LKA is a feature that take step to keep the vehicle stay in its
lane. If it detect that the vehicle is drifting out of the lane, it may
gently steer the vehicle back into it.
What is Lane Keeping Asist system (LKA/LKAS)
- According to NHTSA, about 80% of the accidents are caused by the
drivers.
- 20% of traffic accidents are caused by departure of vehicle from its lanes.
- Up to 26% of all relevant accidents with injuries and fatalities can be
prevented by lane keeping support.
Why?
3. Chapter 1 Introduction
3
- The LKA system is a auxiliary function, not a autonomous
function. The driver should always touch the steering wheel.
Drivers with hands-off is a misuse.
- The activation condition of LKA system is at least 60km/h. The
curvature should be at least 250m.
UN/ECE Regulations
[1] Regulation No 79 of the Economic Commission for Europe of the United Nations (UN/ECE)
— Uniform provisions concerning the approval of vehicles with regard to steering equipment
[2] Regulation No 130 of the Economic Commission for Europe of the United Nations (UN/ECE)
— Uniform provisions concerning the approval of motor vehicles with regard to the Lane Departure Warning System (LDWS).
4. Reference
4
[1] Guo Hongqiang, Chen Hui, Chen Jiayu. Design of Lane-based Lane Maintenance System Based on EPS[J].
Automotive Technology, 2018(08): 33-38.
[2]Yu Lijiao. Design and experimental verification of lane-based auxiliary control algorithm based on EPS [D]. Jilin
University, 2016.
Structure of LKA control system
[1]Baharom M B, Hussain K, Day A J. Design of full electric power steering with enhanced performance over that of
hydraulic power-assisted steering[J]. Proceedings of the Institution of Mechanical Engineers Part D Journal of
Automobile Engineering, 2013, 227(3):390-399.
[2] Zhang Hailin. Lane keeping system based on electric steering [D]. Tsinghua University, 2012.
[3]Cheng Shuliang. Modeling and simulation analysis of electric power steering system [D]. Chongqing University,
2016
EPS model
[1]Prof. Nicola Amati. Chassis A notes. High speed cornering simplified approach
[2]Yu Lijiao. Design and experimental verification of lane-based auxiliary control algorithm based on EPS [D]. Jilin
University, 2016.
2 d.o.f. vehicle model
5. Reference
5
[1] Carlo Novara. Automatic control. Lecture 21 Lane Keeping
[2] Zhang Hailin. Lane keeping system based on electric steering [D]. Tsinghua University, 2012.
Driver model
[1] Ziegler, J.G & Nichols, N. B. (1942). "Optimum settings for automatic controllers’’ Transactions of the ASME. 64:
759–768.
[2] Nyquist, H. (1932). "Regeneration Theory". Bell System Tech. J. USA: American Tel. & Tel. 11 (1): 126–147
Design of PID controller
7. Chapter 2 System structure
7
- It is the information acquisition system, includes various
sensors and image processing modules
Sensing layer
- Including the information processing, the lane departure
warning algorithm, the driver operation state identification
algorithm and the lane keeping active control algorithm.
Decision layer
- Uses the steering system or the braking system to control the
vehicle motion
Execution layer
8. Chapter 2 Sensing layer
8
- Steering wheel angle sensor
- Steering torque sensor
Steering
- Acceleration sensors
- Yaw rate sensor
- Wheel speed sensors
Dynamic of the vehicle
- Camera is commonly used.
Lane information & car’s relative position
9. Chapter 2 Execution layer
9
- Audible
- Visual
- Tactile
Execution for warning
- Electric Power Steering (EPS).
- Electric Stability Program (ESP).
Execution for steering
12. Chapter 3 State Decision Strategy
12
- Shutdown
- Standby
- Intervention
Target: define system state
- α----Activation condition coefficient
- β----Intervention condition coefficient
In order to identify the system state, we introduce 2
auxiliary coefficients.
13. Chapter 3 State Decision Strategy
13
- Determine when the LKA system should
intervene the vehicle control.
- Reduce false warning.
- Avoid collisions between LKA system and the
driver.
This strategy is important
14. Chapter 3 Criteria for activation
14
- Switch state (ON/OFF)
- The clarity of the lane marking.
- Lane change (Ex. Turning light is on)
3 criteria should be taken into consideration
The target is to define the value of coefficient α
15. Chapter 3 Criteria of intervention
15
The target is to define β
- For intervention:
𝑇𝐿𝐶 < 𝑡ℎ𝑟𝑒𝑠ℎ𝑜𝑙𝑑
- The system control the vehicle until the
vehicle steer back to lane centre.
The criteria for intervention and for exit are
different.
TLC -----a time interval estimated according to the Time to Line Crossing
algorithm. Which indicate that if the car maintains the current dynamic
condition, after TLC seconds the left/right front wheel will touch the lane
marking.
18. Chapter 3 Path error controller
18
Target road centerline function Ytarget =0
Predicted driver model
θtarget depends on predicted lateral displacement(the
predicted lateral displacement of vehicle a certain time)
21. Chapter 3 EPS model
21
States:
Current of electric motor Ie
Angle of motor θe
Rotation speed of motor
Inputs:
Voltage of electric motor U
Equivalent self aligning torque Tsa
State space equation of EPS model
WHAT
Why.-----It is mostly for safety reasons. It is critical especially for sleepy or distracted drivers. Here is some statistics.
80%, ……
20%.........
So, nowadays, some countries have already introduced regulations to promote this feature.
For deeper studying, we decided to reconstructed a LKA system by using Simulink and Carsim.
Then, we read some papers. The structure of the control system is based on these two papers.
Following shows the models we used and the papers where these models come from.
we used a 2 d.o.f. vehicle model, EPS model, driver model and PID controller.
Decision layer Execution layer we will introduce later.
In order to realize the lane keeping feature. Sensors are required to obtain lane information, vehicle dynamic and steering information.
Execution layer
2 types of execution ,first is the execution for warning.
When the system detect that the vehicle has a risk of running out of the lane, the system will alert the driver first.
It can alert the driver by using audible devices, for example alarms, or visual devices, for example, a screen in dashboard.
But, the most effective way is by using tactile warning. For example the vibration of steering wheel or seat.
Then, if the driver does not react in time. The LKA will control the vehicle and steer it back to the lane center. This action is accomplished by using these two types of executions. EPS or ESP, or we can using them together for steering.
This is the structure of the decision layer. As you can see, two controllers inside it which are State decision controller and Path error PID controller. Now, I will focus on the state decision controller. Why we need state decision block? Because the LKA system shouldn’t always turned on. For example it should swithced off when the driver intends to change the lane. So we need this block to verify the interfere condition.
The target of this strategy is to define the system state. The system has 3 states. (Shutdown, standby and intervention)
念ppt
The picture on your right hand side represent the logic of the strategy.
If the activation condition is not satisfied, alpha=0,the system is shutdown. Otherwise, alpha=1.
When alpha=1, the system is activated. Then, if the intervention condition is not satisfied, beta=0, the system standby. When beta=1, the system shift to intervention state and start controlling the vehicle.
This strategy is important.
Why?
Firstly, through state decision, this strategy determine when the system should intervene the vehicle control and when the system should just standby and keep monitoring the vehicle status.
In this way, we can reduce false warning and avoid collision.
Now, what we need to do is to define the value of alpha and beta.
The flowchart represent the logic for the estimation of alpha.
As you can see, 3 criteria should be considered. The first is the switch state. It means that there is a interface on the dashboard which the driver can turn on or turn off the system.
The second criterion is the clarity of the lane marking. As I said before, the system is highly depend on the lane marking. If the marking is not clear, the system should not be activated.
The third criterion is lane change. It means that, if the driver want to change lane, the system should not interfere the operation.
The problem is how to judge whether the driver is intentionally change lane or not.
Then , How to define beta.
So, TLC is a time that after which the vehicle will drift out of the lane.
Now let’s have an overview of the whole control loop, my colleague has already introduced the state decision block. Once it decides that LKA system should interfere, the path error PID controller will request a target steering angle from the EPS module which is proportional to the lateral displacement.
After that the electric power steering module which contains a EPS controller and EPS model(which we will discuss it later) will determine the actual steering angle base on the required steering angle. We notice that the self-aligning torque is also an input for the EPS module because we need it to solve the dynamic equation of the steering system.
Finally the actual steering angle will be the only input to the Vehicle model, here we exploit the simplest 2 d.o.f model which doesn’t consider the self-aligning torque and the aerodynamics. The output which is the vehicle dynamic information will be the input of the state decision block.
Now let’s have an overview of the whole control loop, my colleague has already introduced the state decision block. Once it decides that LKA system should interfere, the path error PID controller will request a target steering angle from the EPS module which is proportional to the lateral displacement.
After that the electric power steering module which contains a EPS controller and EPS model(which we will discuss it later) will determine the actual steering angle base on the required steering angle. We notice that the self-aligning torque is also an input for the EPS module because we need it to solve the dynamic equation of the steering system.
Finally the actual steering angle will be the only input to the Vehicle model, here we exploit the simplest 2 d.o.f model which doesn’t consider the self-aligning torque and the aerodynamics. The output which is the vehicle dynamic information will be the input of the state decision block.
First the assumption is that the road centerline function in the global reference frame is known. In this case we consider the vehicle is on a highway so the road is straight. The road centerline function is simply Y=0.While the actual vehicle path function in the global reference frame can be determined from the vehicle dynamic information.
Here we exploited a predicted driver model. Because during this project we found that if we determine the required steering angle based on the current lateral displacement, the control is not stable, because the steering correction is too late. So according to the predicted driver.The required steering wheel angle is not base on the current lateral displacement, but based on the predicted lateral displacement after for example 0.5 second. And the stability problem is solved.
Now let’s have an overview of the whole control loop, my colleague has already introduced the state decision block. Once it decides that LKA system should interfere, the path error PID controller will request a target steering angle from the EPS module which is proportional to the lateral displacement.
After that the electric power steering module which contains a EPS controller and EPS model(which we will discuss it later) will determine the actual steering angle base on the required steering angle. We notice that the self-aligning torque is also an input for the EPS module because we need it to solve the dynamic equation of the steering system.
Finally the actual steering angle will be the only input to the Vehicle model, here we exploit the simplest 2 d.o.f model which doesn’t consider the self-aligning torque and the aerodynamics. The output which is the vehicle dynamic information will be the input of the state decision block.
EPS system contains EPS model and EPS PID controller.
The from this electric circuit equation. Here we assume that the steering mechanism is rigid, and we neglect the damping, friction of the steering system. We can write the dynamic equation of the electric motor and in this equation we need the self-aligning torque equivalent at the electric motor shaft to solve this equation.
After that we are able to write the state space equation of the EPS model. From the this equation we are able to derive the actual electric motor angle and thus the actual steering angle. The states are….. And the inputs are…
About the PID controller of the EPS, we also use a simple Proportional control. The input voltage of the electric motor is proportional to the steering angle error. A problem is how to define Kp, of course for a PID control you can tune the parameter to have a trade-off between overshoot and response time. But first you should know Kp is in which order of magnitude, it’s around 0.1 or 100? In this case we solve the transfer function of this system and determine Kp so that this system is in critical damping, after we tune Kp around this value However, in this case we found that optimum Kp for EPS is not the optimum Kp for the whole system. In order to have a more stable behavior of the vehicle, we should have a short response time of EPS.
Now let’s have an overview of the whole control loop, my colleague has already introduced the state decision block. Once it decides that LKA system should interfere, the path error PID controller will request a target steering angle from the EPS module which is proportional to the lateral displacement.
After that the electric power steering module which contains a EPS controller and EPS model(which we will discuss it later) will determine the actual steering angle base on the required steering angle. We notice that the self-aligning torque is also an input for the EPS module because we need it to solve the dynamic equation of the steering system.
Finally the actual steering angle will be the only input to the Vehicle model, here we exploit the simplest 2 d.o.f model which doesn’t consider the self-aligning torque and the aerodynamics. The output which is the vehicle dynamic information will be the input of the state decision block.
Here we only exploited the simplest 2 d.o.f car model not considering self-aligning torque and aerodynamics which is not precise. Later we will see that there are some differences between the results when we substitute the 2 d.o.f model with a more precise model imported from CarSim.
The structure of the simulink model is just the same as that we have introduce before. T
The test condition is 60km/h and between first and second seconds we apply a disturbance to the steering system.
Blue line is the lateral displacement with respect. Red curve is yaw angle psi, orange curve is the steering wheel angle in rad. And purple line indicates the LKA interfere condition, at high level means LKA is interfering. Here we can see that after the disturbance is applied to the steering wheel at 1s, LKA doesn’t interfere immediately, since the vehicle is still near the centerline. When the vehicle continuosly deviates from the centerline LKA starts to interfere and we can see a obvious correction of the steering wheel angle in the orange line. Which is due to the activation of the electric power steering. And also, we can see with the correction the lateral displacement and yaw angle decreases to zero which means the vehicle is back to the centerline.
After designing the control algorithm based on the 2 d.o.f vehicle model. It’s possible to have a verification by substituting the vehicle model with a more precise model imported from CarSim. We just replace the vehicle model with CarSim model, we also need to set the input and output of this model to compatible with the algorithm.
This curve indicates the lateral displacement when we use 2 d.o.f and CarSim as the car model. The curve with CarSim has a smaller oscillation and longer response time. Since we only use a simple unprecise 2 d.o.f, the difference is quite large. Maybe after if we have time we can try to exploit 2 d.o.f model consideration self-aligning torque and aerodynamics or even 10 d.o.f model to see if the difference can be reduced.
Finally I want to make a conclusion with what we have learned in this project.
Studied the LKA and SAE levels
Studied and Realized the state decision strategy using Stateflow
Designed the path error controller
Established EPS model and designed the EPS controller
Established vehicle model
Verified the algorithm
解释一下stateflow图形函数就是logic flow