Lane-keeping Assistance System Research Articles

A Method to Develop the Driver-Adaptive Lane-Keeping Assistance System Based on Real Driver Preferences.

To satisfy the preference of each driver, the development of a Lane-Keeping Assistance (LKA) system that can adapt to individual drivers has become a research hotspot in recent years. However, existing studies have mostly relied on the assumption that the LKA characteristic aligned with the driver's preference is consistent with this driver's naturalistic driving characteristic. Nevertheless, this assumption may not always hold true, causing limitations to the effectiveness of this method. This paper proposes a novel method for a Driver-Adaptive Lane-Keeping Assistance (DALKA) system based on drivers' real preferences. First, metrics are extracted from collected naturalistic driving data using action point theory to describe drivers' naturalistic driving characteristics. Then, the subjective and objective evaluation method is introduced to obtain the real preference of each test driver for the LKA system. Finally, machine learning methods are employed to train a model that relates naturalistic driving characteristics to the drivers' real preferences, and the model-predicted preferences are integrated into the DALKA system. The developed DALKA system is then subjectively evaluated by the drivers. The results show that our DALKA system, developed using this method, can enhance or maintain the subjective evaluations of the LKA system for most drivers.

State of the Art: Ongoing Research in Assessment Methods for Lane Keeping Assistance Systems

A safe, comfortable and intelligent Lane Keeping Assistance System (LKAS) is fundamental on the way to realizing full automated driving. In spite of the current high market penetration of LKAS, vehicle manufacturers, suppliers and researchers are still working on improving the system to reach a higher customer acceptance. To achieve this goal more efficiently, a systematic and ideally objective assessment procedure of the system needs to be established. Till date, a thorough review study of the assessment procedures of LKAS does not exist, especially of those which also take the subjective impression of the driver into consideration. The motivation of this paper is to benchmark the state-of-the-art assessment methods of LKAS and identify where problems and research potentials lie. The paper summarizes the relevant characteristics of LKAS based on representative research in the past decades. It also compares the characterization of LKAS with the field of steering feel and vehicle handling in the aspects of procedure, strategy, as well as their advantages and disadvantages. This paper contributes to transferring the know-hows and valuable experiences from other well-developed fields of vehicle dynamics into the rapid-evolving branch of Advanced Driver Assistance System (ADAS), in order to help standardizing its assessment procedure and give insights on system design from a human-centered perspective in the early development phase, thus shortening the ADAS development cycles.

Driver-Centric Lane-Keeping Assistance System Design: A Noncertainty-Equivalent Neuro-Adaptive Control Approach

Vehicle roadway departure accidents are a major traffic safety concern as they oftentimes result in severe injuries and fatalities. To address such an issue, this article originates a novel driver-centric and neuro-adaptive-control-based lane-keeping assistance system (LKAS). The proposed control strategy synergizes a noncertainty-equivalent adaptive control design scheme, an adaptive radial-basis-function-based neural network (RBFNN) that captures the human driver's lane-keeping steering behavior, and a Gudermannian-function-based smooth parameter projection operator. The benefit and uniqueness of the proposed solution are threefold. First and foremost, the noncertainty-equivalent adaptive control design, which leverages the immersion-and-invariance-like methodology, ensures the asymptotical convergence of the parameter-estimation-error-induced perturbation despite the reference signal's persistency of excitation condition. Second, the LKAS is devised to be driver-centric, i.e., an adaptive RBFNN-based human driver steering model is embedded inside the LKAS's algorithm such that a human driver is assisted in a personalized and adaptive manner. Third, the Gudermannian-function-based smooth parameter projection operator ascertains the prescribed boundedness of the control parameters while maintaining the control action's smoothness. A pilot human-subject study using a high-fidelity moving-base driving simulator is conducted to validate the proposed LKAS. Further, its performance is compared with a baseline certainty-equivalent neuro-adaptive controller.

Stability Analysis of Lane-Keeping Assistance System for Trucks under Crosswind Conditions

To enhance the control accuracy of lane-keeping assistance systems for trucks encountering crosswind-induced lateral deviations to improve the lateral stability of the vehicle, this study proposes a control strategy based on a linear quadratic regulator (LQR) using a path-tracking preview model. First, the lateral deviation is calculated using the path-tracking preview model. Then, an observer for the vehicle’s sideslip angle is designed using a vehicle lateral tracking deviation model and a Kalman filter controller, and this is used to solve the deviation of the sideslip angle. Finally, a feedforward controller is designed based on the LQR controller and a linear two-degrees-of-freedom vehicle model to eliminate steady-state errors arising from LQR optimization, thereby obtaining the steering angle of the vehicle when subjected to crosswind conditions. Comparing the test results of the sideslip angle, yaw rate, and lateral acceleration demonstrates that this strategy effectively improves the control accuracy of lane-keeping under crosswind conditions. The proposed method is validated through hardware-in-the-loop experiments on a test bench, yielding results consistent with simulations.

Ground vehicle lane-keeping assistance system via differential flatness output feedback control and algebraic derivative estimation

Vehicle run-off-road is one of the most frequent and fatal traffic accidents in the United States. Various lane-keeping assistance (LKA) systems have been developed in the last decade to help drivers stay on the road. Most of them are built upon linear driver–vehicle–road (DVR) models and treat road curvature as a disturbance. Albeit effective, their control performance would degrade if road curvature varies rapidly. This paper proposes a novel nonlinear DVR model by integrating a driver steering model into vehicle–road kinematics, which explicitly considers road curvature. Particularly, this nonlinear DVR system has been proven to be differentially flat, and a flatness-based LKA system is designed. Additionally, Model-Free Control is introduced to compensate for system modeling errors. Hardware-in-the-loop simulations and diver-in-the-loop experiments validate the proposed control framework and demonstrate the performance enhancement with respect to a representative linear robust LKA system.

Stability and [formula omitted] performance of human-in-the-loop control systems through hidden semi-Markov human behavior modeling

In this paper, a stochastic framework of analysis and synthesis is proposed for the stability and H∞ performance of linear human-in-the-loop (HiTL) control systems which involve both human’s discrete internal states and machine’s continuous-time dynamics. Initially, a hidden semi-Markov model (HS-MM) is used for the human behavior modeling, which takes into account the random nature of human internal state (HIS) reasoning and the sojourn time of HIS, as well as the uncertainty from HIS observation. Subsequently, by integrating human model, machine model, and their interaction, a hidden semi-Markov jump system (HS-MJS) model is constructed to describe the HiTL control system. By the tools of stochastic Lyapunov functional and linear matrix inequalities (LMIs), a sufficient and necessary condition for the stochastic stability of the HiTL control system via state feedback is then given on the basis of the HS-MJS model. Besides, an LMI-based human-assistance stabilizing control design is developed. For the prescribed disturbance attenuation level, a human-assistance H∞ controller synthesis method of the HiTL control system is proposed in terms of LMIs. Finally, the developed theoretical results are applied to the steering control of the lane-keeping assistance system.

Design and implementation of human driving data-based lane-keeping assistance system for electric bus

This paper describes design, implementation, and evaluation of human driving data-based Lane Keeping Assistance System (LKAS) for electric bus equipped with a hybrid electric power steering system. The hybrid electric-power steering system used in this study means a steering system in which an Electric Power Steering (EPS) system and an Electro-Hydraulic Power Steering (EHPS) system are integrated into a ball-nut. A dynamic model of hybrid EPS system including EHPS system and EPS system has been developed to generate EPS torque and EHPS force corresponding to the input torque. In order to determine proper timing of LKAS intervention, driving data of electric bus drivers were collected and driving patterns were analyzed using a 2-D normal distribution probability density function. Lane information necessary for the lane-keeping assistance system is obtained from a vision camera mounted on the electric bus. Sliding mode control is used to get a Steering Wheel Angle (SWA) required for LKAS. A Proportional–Integral (PI) control is used to obtain an overlay torque required to track the target SWA. A proposed DLC threshold has been validated using vehicle simulation software, TruckSim, and MATLAB/Simulink. It is shown that the proposed DLC threshold shows good performance in both cases of slow lane departure and fast lane departure. The proposed algorithm has been successfully implemented on the electric bus and evaluated via real-world driving tests. Test scenario setting and the evaluation of performance were carried out by ISO 11270 criteria. It is shown that the algorithm successfully prevented the electric bus from unintended lane departure satisfying ISO 11270 criteria.

Test Evaluation Method for Lane Keeping Assistance System Using Dual Cameras

Recently, the number of vehicles equipped with the Lane Keeping Assistance System (LKAS) is increasing. Therefore, safety evaluation to validate the LKAS has become more important. However, the actual vehicle test for safety evaluation has disadvantages such as the need for professional manpower, the use of expensive equipment, and environmental constraints. Therefore, we attempted to solve this problem using the dual cameras system with only inexpensive and accessible cameras. The optimal position of the dual cameras, image and focal length correction, and lane detection methods proposed in previous studies were used, and a theoretical equation for calculating the distance from the front wheel of the vehicle to the driving lane was proposed. For the actual vehicle testing, LKAS safety evaluation scenarios proposed in previous studies were used. According to the test results, the maximum error was 0.17 m, which indicated the reliability of the method because all errors in the tested scenarios exhibited similar trends and values. Therefore, through the use of the proposed theoretical equations in conjunction with inexpensive cameras, it is possible to reduce time, cost, and environmental problems in the development, vehicle application, and safety evaluation of LKAS components.

User-centred design evaluation of symbols for adaptive cruise control (ACC) and lane-keeping assistance (LKA)

Advanced driving assistance systems (ADAS) are now numerous, each relieving drivers of their responsibility for the control of different aspects of the driving task. Notably, adaptive cruise control (ACC) for longitudinal control, or lane departure prevention (LDP) and lane centring control (LCC) for lateral control, two variations of the lane-keeping assistance (LKA) system. Drivers must familiarise themselves with various symbols to correctly identify and activate the system they wish to be using and the existing standard graphical symbols for ACC and LKA are often replaced by manufacturers in favour of their own symbols. With a user-centred approach in mind, we previously conducted a focus group where drivers were invited to design their own symbols and discuss those symbols currently in-use. In the present research, we administered an online survey and analysed the responses from 328 drivers regarding different levels of knowledge about ADAS, to evaluate the usability of a selection of these symbols. Our results indicate that the standard ACC symbol would not be the most suitable of the four symbols tested, whereas, the standard LKA/LDP symbol was greatly confused with any of the four LCC symbols we tested, especially if hands were present on the symbol. Finally, drivers without prior knowledge of ADAS had more difficulties interpreting those symbols in general. Considerations for the development and evaluation of graphical symbols are discussed.

Development and model-based calibration of the lateral controllers “steer-by-angle” and “steer-by-torque” of a lane keeping assistance system

Advanced Driver Assistance Systems (ADAS) such as Lane Keeping Assistance (LKA) systems are in the focus of current vehicle developments. Of special interest is the calibration task, which plays an increasingly decisive role in early development stages. At this point it is essential to analyze the pre-calibrated controller concepts by appropriate simulation methods. A software toolchain is introduced, using Model-in-the-Loop (MiL) for the evaluation and calibration of the LKA system. Within, a Design-of-Experiment (DoE) tool is integrated together with the simulation environment. This enables the examination of the two different lateral controller concepts Steer-by-Angle (SbA) and Steer-by-Torque (SbT). Their lateral guidance performance is characterized by Key Performance Indicators (KPI), which are derived from simulation quantities of straight-line and cornering maneuvers. Further, statistical behavior models are generated based on those KPI and controller design variables (DV). The subsequent optimization process leads to high performances of both controllers. In particular, the SbA controller shows higher efficiency under the impact of disturbances as well as the reference reaction with lower settling times. Overall, the achieved lateral guidance performances indicate the potential of both control algorithms in an early development stage. With the software toolchain, a platform for further LKA system calibration and lateral guidance performance optimization is established.

Shared control for lane keeping assistance system based on multiple-phase handling inverse dynamics

To achieve user-friendly design, a novel shared control scheme for Lane Keeping Assistance (LKA) system is proposed in this paper. Instead of adjusting the control authority allocation, the proposed scheme achieves shared control by adjusting the displacement interval between each phase. Through this scheme, we aim to design a LKA system which can realize continuously shared control between assistant controller and human driver with a fixed driving authority allocation strategy. Firstly, the shared control problem is formulated as a multiple-phase inverse dynamics problem; then we covert the inverse dynamics problem into an Optimal Control Problem (OCP). Secondly, by applying Radau Pseudospectral Method (RPM), the OCP is converted into a Nonlinear Programming Problem (NLP), which is then solved by Sequential Quadratic Programming (SQP). Finally, simulations under two typical conditions are implemented to validate the effectiveness of the proposed shared control approach.

Improving stability and lane-keeping performance for multi-articulated vehicles using vector follower control

ABSTRACT The present study discusses the effects of stability control for multi-articulated vehicles on the lane-keeping performance. Vector follower control (VFC) compensates the direction difference angles between the velocity vector at the front articulation point and the trailer using active steering of the trailer wheels. The control effects are evaluated by examining computer simulation with the driver-vehicle system, which consists of a multi-articulated vehicle model, a driver model, and VFC. VFC prevents amplification of the lateral displacements of rearward trailers, whereas the lane-keeping performance of a vehicle without VFC deteriorates. VFC does not, however, contribute to the performance of the tractor or the steering operation of the driver. A lane-keeping-assistance (LKA) system using direct yaw-moment control is applied to the tractor. The LKA system suppresses the lateral deviation of the tractor and the steering effort of the driver. In addition, the combination of VFC and the LKA system makes it possible to reduce the lateral deviations of all of the vehicles, as well as the steering effort of the driver.

Modelling the Intrusive Feelings of Advanced Driver Assistance Systems Based on Vehicle Activity Log Data: Case Study for the Lane Keeping Assistance System

Although the automotive industry has been among the sectors that best-understands the importance of drivers' affect, the focus of design and research in the automotive field has long emphasized the visceral aspects of exterior and interior design. With the adoption of Advanced Driver Assistance Systems (ADAS), endowing 'semi-autonomy' to the vehicles, however, the scope of affective design should be expanded to include the behavioural aspects of the vehicle. In such a 'shared-control' system wherein the vehicle can intervene in the human driver's operations, a certain degree of 'intrusive feelings' are unavoidable. For example, when the Lane Keeping Assistance System (LKAS), one of the most popular examples of ADAS, operates the steering wheel in a dangerous situation, the driver may feel interrupted or surprised because of the abrupt torque generated by LKAS. This kind of unpleasant experience can lead to prolonged negative feelings such as irritation, anxiety, and distrust of the system. Therefore, there are increasing needs of investigating the driver's affective responses towards the vehicle's dynamic behaviour. In this study, four types of intrusive feelings caused by LKAS were identified to be proposed as a quantitative performance indicator in designing the affectively satisfactory behaviour of LKAS. A metric as well as a statistical data analysis method to quantitatively measure the intrusive feelings through the vehicle sensor log data.

Driver adaptation to lane keeping assistance systems: Do drivers become less vigilant?

Driver adaptation to semi-autonomous vehicles is examined in this study using a longitudinal driving simulator study with 18 subjects randomly assigned to a control (n = 9) and treatment (n = 9) group. A Tactile Detection Response Task (TDRT) was used to measure cognitive workload while drivers engaged in visual-manual distracting tasks using an in-vehicle information system, with and without a lane-keeping assistance system (baseline, intervention, and withdrawal period). Measures of miss rate and reaction time to the TDRT stimuli suggest that drivers in both groups showed decreases in cognitive workload as they gained experience. Participants in the treatment group experienced higher cognitive workload when the lane keeping assistance system was withdrawn. On average, there were greater decreases in cognitive workload over time for the difficult tasks as compared to the easy tasks for both the control and treatment groups. The effect was more pronounced in the control group with larger decreases in cognitive workload. The NASA TLX was also comparable to the task accuracy. These results suggest that adaptations in driver behavior due to exposure to automation may have transfer effects on cognitive workload and thus may lead to safety implications.

승용자동차 차로유지지원장치의 주행 성능 평가

Lane Keeping Assistance System (LKAS) is a kind of Advanced Driver Assistance Systems (ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in the international committees such as ISO (the International Organization for Standardization) and UNECE (United Nations Economic Commission for Europe). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP (Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed and proposed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System (LDWS). And then, to evaluate the validity of the proposed test procedures, a series of experiments were conducted using commercially available two vehicles equipped with LKAS. Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

Drivers’ Reliance on Lane-Keeping Assistance Systems as a Function of the Level of Assistance

We investigated drivers’ willingness to allocate control to a lane-keeping assistance system as a function of the level of assistance. Operators were found to increasingly rely on automation with higher reliability. We assume a similar effect of the level of assistance on reliance resulting from operators’ perception of a reduced need to engage in automation controlled processes. Forty five participants drove in a moving base driving simulator wiTheither a lane-keeping control (LKC) system (high level of assistance), a lane departure warning (LDW) system (low level of assistance) or without lane-keeping assistance. The allocation of visual attention away from the road scene towards an in-vehicle display of a secondary task was used as an indicator of drivers’ reliance on the systems. We found that drivers diff ered significantly in their reliance on and trust in the LKC system. Individual driver characteristics, i.e., self reported driving style, had a significant influence on drivers’ trust. Drivers placed more trust in the LKC system the more they regarded themselves as anxious and unconfident drivers, and more trust in the LDW system the more they regarded themselves as unobservant drivers. A major conclusion is that self-reported driving style is an important factor to predict if drivers are prone to place their trust in, and rely on, higher level driving assistance. Study results call for transparency in the design of driver assistance systems to avoid false expectations regarding system capabilities. Functional system limits should be made easily identifiable for drivers in order to reduce the likelihood of overreliance.

Control effects of steer-by-wire system for motorcycles on lane-keeping performance

This study discusses the control effects of the steer-by-wire (SBW) system for motorcycles on the lane-keeping performance by examining computer simulation with a rider-vehicle system which consists of a simplified vehicle model, a rider control model and the controller of the SBW system. The SBW system, which compensates the rolling angle deviation between the desired rolling angle intended by the rider and the actual rolling angle, improves the lane-keeping performance of the rider-vehicle system under the steering torque disturbance. The SBW system is, on the other hand, not effective in the lane-keeping performance under the lateral force disturbance. In addition, the lane-keeping assistance (LKA) system is applied to the SBW system and the cooperativeness of the SBW and the LKA systems is examined. The LKA system improves the lane-keeping performance of the SBW system under not only the steering torque disturbance but also the lateral force disturbance.

Driver distraction based lane-keeping assistance

Abstract Driver assistance systems could be much more effective, if they were adaptive to the driver’s state. Following the idea of a lane-keeping assistance system, which is adaptive to the use of in-vehicle information systems (IVIS), two field experiments were conducted. The first experiment concerned the influence of typical IVIS tasks on lane-keeping. Most IVIS tasks increased the lateral deviations, but in the majority of cases the drivers were still able to stay in their lane. The second experiment concerned two questions: (1) how much lateral support would be needed and (2) how drivers accept this kind of support. The results show that all lateral support algorithms increased the lane-keeping performance with the algorithms providing a higher amount of assistance proving the most useful. All assistance systems were rated as helpful and were considered to increase driver safety, both by the drivers who did not have problems in lane-keeping without assistance. In light of these results an adaptation of a lateral support system to the IVIS-use seems to be useful and worthwhile.

1218 二輪車の車線維持性能向上に関する研究 : ステアバイワイヤの車線維持性能への影響(OS3-1:操舵系制御,OS3:交通・物流システムの制御,オーガナイズド・セッション(OS),第18回交通・物流部門大会(TRANSLOG2009))

This study examines the effects of the Steer-By-Wire (SBW) technology on lane keeping performance of motorcycles by examining computer simulation using multibody-dynamics model. The lane keeping performance is evaluated by the rider-in-the-loop system consisting of the motorcycle, the SBW controller, and the rider control model. The SBW technology improves the lane keeping performance of motorcycles in comparison with the conventional motorcycles. In addition, the Lane-Keeping-Assistance (LKA) system is applied to the SBW motorcycle and the cooperativeness of the SBW and the LKA systems is examined. The LKA system improves the lane keeping performance of the SBW motorcycle.

A driver-distraction-based lane-keeping assistance system

Single-vehicle roadway departure (SVRD) accidents occur in many cases owing to driver distraction or drowsiness constituting a substantial share of today's road vehicle accidents and casualties. This paper describes a distraction-based lane-keeping support system, which intervenes only when the driver is positively detected as being distracted. Distraction here is understood as cognitive and visual distraction, and the focus of this system is on the latter one. In order to estimate the driver's visual distraction level, a video-based driver monitoring system is used. Lane-keeping support is provided by an additional torque applied on the steering shaft in order to regain an appropriate lane position. In this manner the system only intervenes when the vehicle has drifted out of its lane and while the driver is distracted. Test track investigations indicate large opportunities for such a system from a driver perspective, provided that sufficient reliability of the employed vision sensor for lane and face tracking can be obtained.