Browse Topic: Lane keeping assistance

Items (27)

Vehicle Trajectory Prediction Based on Motion Model and Maneuver Model Fusion with Interactive Multiple Models

2020-01-01124/14/2020

Xiao, Wei, Zhang, Lijun, Meng, Dejian

Emotion Analytics for Advanced Driver Monitoring System

2019-26-00251/9/2019

From the recent advances in Driver Monitoring Systems (DMS) from automotive domain, research on Human Computer Interaction (HCI) based on emotion analytics has gained good interest from the research circles. Distraction and drowsiness will be causing more percentage of traffic accidents, but with the use of advanced DMS technology, we can significantly reduce these distractions and can make the driving a safer activity. Our proposed solution/approach with disguised emotion detection with analytics is enabled by machine learning and image processing algorithms to ensure that the detection of drowsiness or distraction is very accurate. The proposed method will inform the HMI system to provide an alert to wake up the driver if he or she is in drowsy state or take the proactive/necessary actions with the help of active safety systems. Emotion analytics is a technique which is used to analyze the emotion of an individual. It is used to recognize the change in the emotion. Deep Learning is used for the implementation of computer vision techniques which is implemented with the help of Convolutional Neural Network (CNN). In recent times, CNN has been successfully applied in analyzing visual images for many automotive applications. CNN model can be applied to recognize the emotion. We have trained CNN model with different depth using grayscale images. Emotions can be classified into following six categories i.e. Happy, Sad, Surprise, Angry, Neutral and Fear. After recognition, emotions are continuously analyzed. We recorded the emotion in particular time frame like how many times a person is Happy, Sad, Surprised etc. Standard & Tata Elxsi’s proprietary database is used for training the Emotion Recognition System. Proposed system is tested in Raspberry pi board and results found satisfactory. This analysis will help us to monitor the activity of driver. In case of any abnormal behavior we can take corrective measure to control the situation.

Nandyala, Sivaprasad, K, Gayathri, Bhushan, Chandra, Gandi, Varaprasad, Manalikandy, Mithun

Research on the Radiated Immunity Test Methods of ADAS Functions in Intelligent Vehicles

2018-01-16368/7/2018

According to the ISO 11451-2 [1], the immunity performance of passenger cars and commercial vehicle shall be validated to electrical disturbances from off-vehicle radiation sources. Typical vehicle electrical or electronic systems such as double flash, monitor, or audio and entertainments systems have been validated through a standardized immunity test process. As the development of ADAS (Automated Driver Assistance System) functions in the vehicle technology, the reliability and accuracy of these functions in the complex electromagnetic fields must be validated. Radar and Camera or Lidar sensor based functions of AEB (Automated Emerge Brake), ACC (Automated Cruise Control) or LDW (Lane Departure Warning) might be invalid, especially when these sensors were illuminated by electrical disturbances in the real word. This work presents a novel test methodology of whole-vehicle immunity to off-board electrical disturbances, considering the main ADAS functions. Target simulator and virtue driving-environment are designed to trigger AEB, ACC and LDW functions in an anechoic chamber. Under standardized off-board radiated sources, the reliability of ADAS functions in a real vehicle are invested.

Jia, Jin, Li, Biao, Li, Xu

Evaluation of Alternative Steering Devices with Adjustable Haptic Feedback for Semi-Autonomous and Autonomous Vehicles

2018-01-05724/3/2018

Emerging autonomous driving technologies, with emergency navigating capabilities, necessitates innovative vehicle steering methods for operators during unanticipated scenarios. A reconfigurable “plug and play” steering system paradigm enables lateral control from any seating position in the vehicle’s interior. When required, drivers may access a stowed steering input device, establish communications with the vehicle steering subsystem, and provide direct wheel commands. Accordingly, the provision of haptic steering cues and lane keeping assistance to navigate roadways will be helpful. In this study, various steering devices have been investigated which offer reconfigurability and haptic feedback to create a flexible driving environment. A joystick and a robotic arm that offer multiple degrees of freedom were compared to a conventional steering wheel. To evaluate the concept, human test subjects interacted with the experimental system featuring a driving simulator with target hardware, and completed post-test questionnaires. Based on the data collected, drivers’ lane keeping performance was superior using a haptic robotic arm with haptic feedback to the joystick and steering wheel with an improvement of up to 70.18% during extreme maneuvers. Haptic feedback, with a lane keeping algorithm, can assist the operator in steering the vehicle given the likely deterioration of driving skills when autonomous vehicles become prevalent.

Wang, Chengshi, Wang, Yue, Wagner, John R.

THE NAVIGATOR

17AUTP11_0811/1/2017

The uncanny valley of partially-automated driving Automated driving has the potential to be the most disruptive force in transportation since Henry Ford rolled out the Model T. The potential impact on an industry that generates an estimated $4 trillion in annual revenues globally is enormous. No company wants to be left without a chair when the music stops. However, in that rush to win the automation race, are automakers producing interim products that might be better left parked in the storage lot behind the research labs?

Abuelsamid, Sam

Stability Control of Autonomous Vehicles with Four In-Wheel Motor Drive for Severe Environments

2017-01-20019/23/2017

Research and development of autonomous functions for a road vehicle become increasingly active in recent years. However, the vehicle driving dynamics performance and safety are the big challenge for the development of autonomous vehicles especially in severe environments. The optimum driving dynamics can only be achieved when the traction torque on all wheels can be influenced and controlled precisely. In this study, we present a novel approach to this problem by designing an advanced torque vectoring controller for an autonomous vehicle with four direct-drive in-wheel motors to generate and control the traction torque and speed quickly and precisely, thus to improve the stability and safety of the autonomous vehicle. A four in-wheel motored autonomous vehicle equipped with Radar and camera is modelled in PanoSim software environment. Vehicle-to-Vehicle (V2V) communication is used in this software platform to avoid collision. Individual in-wheel motor control systems are integrated and networked together using a high-level advanced vectoring control system. The proposed vectoring control system can monitor and manage the behavior of the individual subsystems, assigning appropriate tasks to each of them according to the driving maneuver and road conditions. The performance and effectiveness of the proposed vectoring control system is evaluated using standard test maneuvers. Simulation results show that the proposed advanced torque vectoring controller can improve the vehicle steadiness and transient response properties, thereby enhancing the stability performance compared with the conventional central motor controller particularly for severe environment conditions.

Li, Xin, Situ, Lixin, Yu, Yongqiang, Chen, Feng

SUPPLIER EYE

17AUTP05_085/1/2017

Toward a “by wire” vehicle When President Kennedy proclaimed in 1961 that the U.S. would put a man on the moon by 1969, the engineers and scientists involved knew that building the delivery systems had to be a staged process of constant improvement. Creating the knowledge base, supplier capability, test regimens and importantly, the experience and reliability, were all tightly defined through the Mercury, Gemini and Apollo programs. Skipping a step or shortcutting any development phase would have resulted in failure. The road to autonomous driving is, to a lesser degree, a “moonshot” of its own. This is becoming evident as new “by wire” capabilities are integrated into the vehicle in stages. Automatic Emergency Braking (AEB), Lane Keeping Assistance (LKA) and other enhanced control/detection technologies require a host of new technologies: new sensors operating in “fusion” with others that are more flexible; offering vastly enhanced computing speed and capacity; and networked connectivity are vital building blocks in the incremental journey to SAE Level 4 and Level 5 vehicle autonomy. Virtually every subsystem will need to be modified-and in some cases, re-invented.

Robust Traffic Vehicle Lane Change Maneuver Recognition

2017-01-01103/28/2017

The ability to recognize traffic vehicles’ lane change maneuver lays the foundation for predicting their long-term trajectories in real-time, which is a key component for Advanced Driver Assistance Systems (ADAS) and autonomous automobiles. Learning-based approach is powerful and efficient, such approach has been used to solve maneuver recognition problems of the ego vehicles on conventional researches. However, since the parameters and driving states of the traffic vehicles are hardly observed by exteroceptive sensors, the performance of traditional methods cannot be guaranteed. In this paper, a novel approach using multi-class probability estimates and Bayesian inference model is proposed for traffic vehicle lane change maneuver recognition. The multi-class recognition problem is first decomposed into three binary problems under error correcting output codes (ECOC) framework. With probability estimates from the three binary classifiers, multi-class probability estimates are obtained through paired team comparisons. A sequence of the multi-class probability estimates are then fed into the Bayesian inference model. The Bayesian inference model views the input as sample of a random variable, and the output of the Bayesian inference model is used for the final recognition. A data set which is collected from a real-time driving simulation platform is used for the training of the binary classifiers. Typical samples are used to evaluate the performance of the proposed approach. The experimental results have demonstrated the improvement of robustness when using the proposed approach, and the approach is able to recognize lane change maneuver of the traffic vehicle with an average prediction horizon of 1.51 seconds.

Sun, Hao, Deng, Weiwen, Su, Chen, Wu, Jian

Driving Path Planning System under Vehicular Active Safety Constraint

2016-01-81059/27/2016

Path planning system, which is one of driver assistance systems, can calculate the driving paths and estimate the driving time through the road information provided by information source. Traditional path planning systems calculate the driving paths through Dijsktra's algorithm or A* algorithm but only consider the road information from electronic maps. It is not safe enough for operating vehicles because of the insufficient information of vehicle performance as well as the driver's willingness. This study is based on the Dijsktra's algorithm, which comprehensively considered vehicular active safety constraints such as road information, vehicle performance and the driver's willingness to optimize the Dijsktra's algorithm. Then the path planning system can calculate the optimal driving paths that would satisfy the safety requirement of the vehicle. This study used LabVIEW as a visual host computer and MATLAB to calculate dynamic property of the vehicle. MapX was used as a source of road information. Then built a path planning system based on the Dijsktra's algorithm. This study researched the effects of vehicular active safety constraints with different vehicle parameters and driver's willingness on the planned driving paths. Then evaluated the paths rationally. The results of this study showed that the optimized path planning system can provide satisfied driving paths under different safety constraints. Compared with the traditional path planning algorithm, using the optimized Dijsktra's algorithm might slightly decrease the calculation of response speed. However, it meets the actual situation and it's better for drivers to choose safer paths.

Xiong, Shengguang, Tan, Gangfeng, Guo, Xuexun, Yang, Mengying, Xu, Yongbing, Huang, Bo

Lateral State Estimation for Lane Keeping Control of Electric Vehicles Considering Sensor Sampling Mismatch Issue

2016-01-19009/14/2016

Vehicle lateral states such as lateral distance at a preview point and heading angle are indispensable for lane keeping control systems, and such states are normally estimated by fusing signals from an onboard vision system and inertial sensors. However, the sampling rates and measurement delays are different between the two kinds of sensing devices. Most of the conventional methods simply neglect measurement delay and reduce sampling rate of the estimator to adapt to the slow sensors/devices. However, the estimation accuracy is deteriorated, especially considering the delay of visual signals may not be constant. In case of electric vehicles, the actuators for steering and traction are motors that have high control frequency. Therefore, the frequency of vehicle state feedback may not match the control frequency if the estimator is infrequently updated. In this paper, a multi-rate estimation algorithm based on Kalman filter is proposed to provide lateral states with high frequency. First of all, a combined vehicle and vision model for lateral position estimation is introduced, and then, the necessity to compensate uneven sampling delay for lane keeping control is briefly explained. Next, a measurement reconstruction algorithm is introduced to solve the uneven delay and multi-rate issues of the sensing devices. That is, real-time and precise vehicle lateral position and heading angle signals are available for lane keeping control systems with the proposed method. Finally, the effectiveness of the proposed estimation algorithm is verified by simulations.

Wang, Yafei, Fujimoto, Hiroshi, Hori, Yoichi

Robust Prediction of Lane Departure Based on Driver Physiological Signals

2016-01-01154/5/2016

Lane change events can be a source of traffic accidents; drivers can make improper lane changes for many reasons. In this paper we present a comprehensive study of a passive method of predicting lane changes based on three physiological signals: electrocardiogram (ECG), respiration signals, and galvanic skin response (GSR). Specifically, we discuss methods for feature selection, feature reduction, classification, and post processing techniques for reliable lane change prediction. Data were recorded for on-road driving for several drivers. Results show that the average accuracy of a single driver test was approx. 70%. It was greater than the accuracy for each cross-driver test. Also, prediction for younger drivers was better.

Kochhar, Dev S., Zhao, Hong, Watta, Paul, Murphey, Yi

Autonomous vehicles: IMPACT ON SOCIETY

16MEIP03_013/1/2016

Self-driving technology offers plenty of promise, but not everything about autonomous vehicles will be a panacea. Other than emissions control, probably nothing is keeping auto-company leaders and engineers awake at night more than the challenges surrounding development of self-driving, or autonomous, vehicles. Increased competition among global competitors has practically recast this “good-to-have” functionality into a virtual necessity for the consumer. Moreover, the prospect of driverless vehicles also presents potential environmental and safety benefits that generate a positive regulatory push. Before delving into the intricacies of their societal impact, some basics outlining the four-stage evolution of autonomous vehicle (AV) development: Level 1 has just one function automated (e.g. the cruise control feature we find in many Indian cars today). Level 2 has multiple automated functions, e.g. adaptive cruise control with lane-keeping assist. Level 2 vehicles can follow another vehicle, automatically braking and accelerating in response to the leading vehicle's actions while maintaining a comfortable distance. The vehicle also can self-steer to remain in its driving lane.

Driver-Vehicle Interface Considerations for Lane Keeping Assistance Systems

J3048_201602 (Current)2/24/2016

The purpose of this document is to provide guidance for the implementation of driver-vehicle interfaces (DVI) for intervention-type lane keeping assistance systems (LKAS), as defined by ISO 11270. LKAS provide support for safe lane keeping operations by drivers via momentary intervention in lane keeping actions, but do not automate part or all of the dynamic driving task on a sustained basis (see SAE J3016). Thus they are not classified as a driving automation system per SAE J3016 - Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems, nor do they prevent possible lane or roadway departures, as drivers can always override an LKAS intervention and road conditions may be such that they cannot support an LKAS intervention (e.g., too slippery, curve to tight, lateral velocity too high, etc.). As used in this document, the term LKAS refers to lateral control driver assistance features that automatically intervene to hinder a lane departure if the driver either fails to signal intent to change lanes (i.e., via turn signal activation) or fails to initiate corrective action to prevent the lane departure. It does not include lane centering-type systems (with or without required minimum steering torque input by the driver), which perform constant steering correction to maintain lane positioning (i.e., within a given lane). This document addresses DVI parameters for intervention-type LKAS equipped on vehicles designed for use on public roadways. The responsibility for the safe operation of the vehicle always remains with the driver. LKAS is intended to operate on highways and equivalent roads. This document applies to original equipment LKAS for light-duty vehicles (i.e., passenger cars and light trucks) with GVWR of less than 10000 pounds. This document does not apply to the installation of LKAS on motorcycles or medium- and heavy-duty vehicles. Finally, this document does not address system or operational requirements for LKAS systems, which are specified by ISO 11270.

Advanced Driver Assistance Systems (ADAS) Committee

A Robust Lane-Keeping ‘Co-Pilot’ System Using LBMPC Method

2015-01-03224/14/2015

To provide a feasible transitional solution from all-by-human driving style to fully autonomous driving style, this paper proposed concept and its control algorithm of a robust lane-keeping ‘co-pilot’ system. In this a semi-autonomous system, Learning based Model Predictive Control (LBMPC) theory is employed to improve system's performance in target state tracking accuracy and controller's robustness. Firstly, an approximate LTI model which describes driver-vehicle-road closed-loop system is set up and real system's deviations from the LTI system resulted by uncertainties in the model are regarded as bounded disturbance. The LTI model and bounded disturbances make up a nominal model. Secondly, a time-varying model which is composed of LTI model and an ‘oracle’ component is designed to observe the possible disturbances numerically and it is online updated using Extended Kalman Filter (EKF). Thirdly, LBMPC method is used to decouple controller's optimal control performance and its robustness. Constraints are applied to states predicted by nominal system, while states predicted by oracle model are used for computation of cost function. In the end, this paper presents simulation results obtained by Matlab/Simulink. Straight road and curved road are two typical driving conditions used for verification. The results show the conclusion that the EKF algorithm can estimate the un-modeled uncertain dynamics effectively and the proposed lane-keeping copilot based on the oracle model can successfully assist driver to stay in an expected driving zone.

Ding, Jieyun, Li, Keqiang, Hedrick, Karl

Driver Lane Change Prediction Using Physiological Measures

2015-01-14034/14/2015

Side swipe accidents occur primarily when drivers attempt an improper lane change, drift out of lane, or the vehicle loses lateral traction. Past studies of lane change detection have relied on vehicular data, such as steering angle, velocity, and acceleration. In this paper, we use three physiological signals from the driver to detect lane changes before the event actually occurs. These are the electrocardiogram (ECG), galvanic skin response (GSR), and respiration rate (RR) and were determined, in prior studies, to best reflect a driver's response to the driving environment. A novel system is proposed which uses a Granger causality test for feature selection and a neural network for classification. Test results showed that for 30 lane change events and 60 non lane change events in on-the-road driving, a true positive rate of 70% and a false positive rate of 10% was obtained.

Murphey, Yi lu, Kochhar, Dev S., Watta, Paul, Wang, Xipeng, Wang, Tianyu

Steering Wheel Torque Rendering: Measure of Driver Discrimination Capabilities

2014-01-04474/1/2014

By the action on the steering wheel, the driver has the capability to control the trajectory of its vehicle. Nevertheless, the steering wheel has also the role of information provider to the driver. In particular, the torque level at the steering wheel informs the driver about the interaction between the vehicle and the road. This information flow is natural due to the mechanical chain between the road and the steering wheel. Many studies have shown that steering wheel torque feedback is crucial to ensure the control of the vehicle. In the context of uncoupled steering (steer-by-wire vehicle or driving simulators), the torque rendering on the steering wheel is a major challenge. In addition, of the trajectory control, the quality of this torque is a key for the immersion of drivers in virtual environment such as in driving simulators. The torque-rendering loop is composed of different steps. At first, a vehicle dynamics model computes the torque level at the steering wheel regarding the vehicle state (steering wheel position, vehicle speed, etc.). The second step is a control strategy, which ensures that the torque-rendering device achieves the torque demand. In this paper, we propose to study the capability of driver to discriminate different torque levels in steady state condition. A specific control strategy was implemented in order to ensure high quality torque rendering. We measured the Just Noticeable Differences for different torque levels: 1, 3 and 5 Nm, in both directions (clockwise and counter-clockwise). This experiment involved 18 subjects. The results of this experiment are compared with the literature and give cues to validate torque rendering control strategies from a driver point of view. It also helps to understand how driver perceives the steering wheel torque.

Deborne, Renaud, Khouri Silva, Skárlet, Kemeny, Andras

Integration of Lane Keeping Assistance with Steering

2013-01-23899/24/2013

A novel speed and position dependent Lane Keeping Assistance (LKA) control strategy for heavy vehicles is proposed. This LKA system can be implemented with any torque overlay system capable of accepting external position or torque commands. The proposed algorithm tackles the problem of lane keeping in two ways from a heavy vehicle's perspective. First, it stabilizes the vehicle's lateral position by bringing it to the center of the lane and giving it the correct heading to stay there. This is done using a speed and position dependent control strategy that becomes less aggressive as the vehicle's speed increases and as it gets closer to the center of the lane. Such speed and position dependency is especially critical in heavy vehicles where unnecessary aggressive control can lead to oscillations about the lane's centerline when cruising at high speeds. Furthermore, the proposed controller allows the vehicle to negotiate the road's curvature efficiently while tracking the lane's centerline. This is achieved using a feed-forward strategy based on the angle of attack needed to negotiate a road of a particular curvature at a particular speed. Ultimately, the new LKA system was implemented into a torque overlay system [1, 2], and tested on a heavy vehicle. As a result, significant improvement in lane center tracking was noted, as well as in negotiating road curvature. These capabilities are expected to make driving heavy vehicles such as tractor-trailers and motor homes less strenuous, and have the potential to be the basis for autonomous heavy vehicle applications.

Nhila, Amine, Williams, Daniel, Gupta, Vishi

Design and Evaluation of Emergency Driving Support Using Motor Driven Power Steering and Differential Braking on a Virtual Test Track

2013-01-07264/8/2013

This paper presents the design and evaluation of an emergency driving support (EDS) algorithm. The control objective is to assist driver's collision avoidance maneuver to overcome a hazardous situation. To support driver, electrically controllable chassis components such as motor driven power steering (MDPS) and differential braking and surrounding sensor systems such as radar and camera are used. The EDS algorithm is designed for 3 parts: monitoring, decision, and control. The proposed EDS algorithm recognizes a collision danger using minimum lateral acceleration to avoid collision and time-to-collision (TTC) and driver's intention using sensor systems. The control mode is determined using the indices from monitoring process and the collision avoidance trajectory is derived with trapezoidal acceleration profile (TAP). Using the collision avoidance trajectory, the MDPS overlay torque is determined to support the driver's response of collision avoidance and differential braking is determined to maximize minimum vehicle-to-vehicle distance. Vehicle behavior and the interactions between the vehicle, the controller, and the human driver are investigated through a full-scale driving simulator on the virtual test track (VTT) which consists of a real-time vehicle simulator, a visual animation engine, a visual display, and suitable human-vehicle interfaces. The success rate of collision avoidance is investigated with test drivers and it has been increased for all test drivers.

Choi, Jaewoong, Yi, Kyongsu

Development of a Coordinated Strategy of Steering Torque Overlay and Differential Braking for Unintended Lane Departure Avoidance

2012-01-02814/16/2012

This paper describes a lane departure avoidance system to help the driver avoid the lane departure during drowsiness or inattention. The lane departure avoidance system proposed in this paper consists of unintended lane departure decision part, upper level controller part and lower level controller part. The index used in unintended lane departure decision part is proposed to monitor a driver's intention with steering behaviors. The desired dynamics is calculated in upper level controller part. When the desired dynamics is calculated, it is considered to guarantee a driver's safety and smooth ride feel simultaneously as possible. The lower level controller distributes the desired control input to actuators, motor driven power steering (MDPS) module and vehicle stability control (VSC) module. The proposed lane departure avoidance system has been evaluated via human driver model-in the loop simulation.

Lee, Junyung, Yi, Kyongsu

Development of a Model Based Predictive Controller for Lane Keeping Assistance

2008-01-14544/14/2008

Lane keeping assistant system (LKAS) is expected to reduce the driver workload with assisting the driver during driving and is regarded as a promising active safety system. For the proposed LKAS which requires cooperative driving between driver and the assistance system, a Model Based Predictive Controller (MBPC) is proposed to minimize the effect of system overshoot caused by the time delay from the vision-based lane detection system. In order to validate the proposed LKAS controller, a HIL (Hardware In the Loop) simulator is built using steering mechanism, single camera, torque motor, sensors, etc. The performance of the proposed system is demonstrated in various roadways.

Hwang, Junyeon, Huh, Kunsoo, Na, Hyukmin, Jung, Hogi, Kang, Hyungjin, Yoon, Paljoo

Vision Based Path-Following Control System Using Backstepping Control Methodology

2008-01-02024/14/2008

This paper describes an automated path following system using vision sensor. Lateral control law for path following is especially underlined which is developed by using the backstepping control design methodology. To establish the proposed control system, the lateral offset to the reference path, the heading angle of vehicle relative to tangent line to the path, and path curvature are required. Those inputs to the controller have been calculated through Kalman filter which is frequently adopted for the purpose. The lane mark detection has been achieved in an ECU (Electric Control Unit) platform with vision sensor. The yaw rate and side-slip angle also needed in the controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speeds, experiment has been conducted on a proving ground having straight and curve sections with the curvature of about 260m.

Shin, Dongho, Sim, Sungbo, Ryu, Jaehoon, Lee, Jaekwan, Lee, Insik

A Markov Model for Driver Turn Prediction

2008-01-01954/14/2008

This paper describes an algorithm for making short-term route predictions for vehicle drivers. It uses a simple Markov model to make probabilistic predictions by looking at a driver's just-driven path. The model is trained from the driver's long term trip history from GPS data. We envision applications including driver warnings, anticipatory information delivery, and various automatic vehicle behaviors. The algorithm is based on discrete road segments, whose average length is 237.5 meters. In one instantiation, the algorithm can predict the next road segment with 90% accuracy. We explore variations of the algorithm and find one that is both simple and accurate.

Krumm, John

Compensation of Power Supply Fluctuations in Electric Power Steering (EPS) Systems

2007-01-264711/28/2007

Due to lower tax rates there are in Brazil many vehicles equipped with 1.0L engines. Nevertheless, consumers still want in these cars air conditioning, steering assistance and embedded electronic devices. The low power developed by such engines can, in some cases, compromise the quality of the electrical power supply in the vehicle, leading to voltage fluctuations, which could interfere with the dynamic behavior of Electric Power Steering (EPS) systems. In the worst case, voltage dips could induce undesired torque pulses on the steering wheel, causing an unpleasant feeling for the driver. The present work demonstrates a power supply fluctuation compensation strategy that electronically minimizes the consequences of sudden voltage dips in vehicles equipped with 1.0L engines. Simulations and experimental results are also included.

Kelber, Christian R., Quevedo, João Francisco, Lessa, Leonardo

Experimental Study on DGPS/RTK Based Path Following System Using Backstepping Control Methodology

2007-01-35798/5/2007

This paper mainly focuses on a lateral control law for pre-given path following which is developed by using the backstepping control design methodology. The position information of the vehicle is obtained by Real Time Kinematic DGPS, and the yaw rate and side-slip angle used in controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speed and various path curvature conditions, the results are given through experiments which are executed on proving ground especially designed for high maneuvering test of which minimum radius of curvature is about 60 m.

Shin, Dongho, Sim, Sungbo, Ryu, Jaehoon, Lee, Jaekwan, Lee, Insik

Development of Lane Recognition Algorithm for Steering Assistance System

2005-01-16064/11/2005

This paper gives an outline of the steering assistance system (hereinafter, SAS) and a description of its key technology: the lane recognition algorithm. To accommodate a variety of driving styles, the SAS is equipped with a lane keeping assistance mode (LKA mode) and a lane departure warning mode (LDW mode) that can be selectively set by the driver. The former mode works in combination with adaptive cruise control (ACC) and carries the advantage of relieving the driving load that is placed on the driver. The latter mode has the benefit of reducing the danger of lane departure accidents caused by the driver dozing off and taking his eyes off the road. The newly developed lane recognition ECU has a simple hardware set-up of two 32-bit microcomputers. The lane recognition algorithm was constructed on the basis of a logic process that analyzes pattern edge points and selects a set of edge points that most closely resemble lanemarks. As a result, it is able to recognize lanemarks precisely at complex lanemarks, such as multiple lanemarks and interchange (IC) and service area (SA) branch roads. This allowed us to achieve an extremely high rate of lane recognition.

Nishida, Makoto, Kawakami, Seiji, Watanabe, Akihiro

Key Drivers for a Future System Architecture in Vehicles

2004-21-002510/18/2004

Reichart, Günter, Haneberg, Michael

Development of a Driver Assistance System

2003-01-02793/3/2003

The dual concepts of driver-vehicle cooperative operation and interaction were applied to a driver assistance device intended to lighten the operation load on the driver and reduce the occurrence of accidents. This addressed the concern that such devices would reduce driver motivation or cause other such problems. A full-scale driver assistance device capable of use throughout the expressway system was put into commercial production as the Honda Intelligent Driver Assistance System (HIDS) and installed on the Accord in October 2002. The lane keeping assistance employs the integration (cooperation) of driver operation and system support together with a new concept called the Human/Machine Interaction System (HMIS). The system has newly acquired approval from the Ministry of Land, Infrastructure and Transport. This article will report on the conceptual approach and substance of this system, and present the results of a survey on its effectiveness and influence on the driver.

Ishida, Shinnosuke, Tanaka, Jun, Kondo, Satoshi, Shingyoji, Masahito

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