Lane Departure Warning System Research Articles

Detecting lane departures from steering wheel signal

Current lane departure warning systems are video-based and lose data when road- and weather conditions are bad. This study sought to develop a lane departure warning algorithm based on the signal drawn from the steering wheel. The rationale is that a car-based lane departure warning system should be robust regardless of road- and weather conditions. N=34 professional driver students drove in a high-fidelity driving simulator at 80km/h for 55min every third hour during 36h of sustained wakefulness. During each driving session we logged the steering wheel- and lane position signals at 60Hz. To derive the lane position signal, we quantified the transfer function of the simulated vehicle and used it to derive the absolute lane position signal from the steering wheel signal. The Pearson correlation between the derived- and actual lane position signals was r=0.48 (based on 12,000km). Next we designed an algorithm that alerted, up to three seconds before they occurred, about upcoming lane deviations that exceeded 0.2m. The sensitivity of the algorithm was 47% and the specificity was 71%. To our knowledge this exceeds the performance of the current video-based systems.

Fast lane detection based on bird’s eye view and improved random sample consensus algorithm

In order to ensure the safety of drivers, Advanced Driving Assistance System (ADAS) has drawn more and more attention. The Lane Departure Warning system is one of the most important parts of ADAS. However, fast and stable lane marking detection is the precondition of it under complex background. In this paper, we proposed a new lane detection method through bird's eye view and improved RANSAC (Random Sample Consensus) algorithm based on the inspiration that extraction of road features from remote sensed images. According to the bird's eye view of the road image, we can recognize the line marking through Progressive Probabilistic Hough transform instead of lane detection. Then, the detected lines are grouped by a new distance-based weighting scheme and we can get the fields of candidate lanes. For each of the fields, lanes are refined through improved RANSAC algorithm and fitted by double models. Hence, the road orientation can be predicted by the curvature and straight line's slope. At last, our experimental results indicated that the lane detection algorithm has good robustness and real-time under various road environment.

운전자-차량-환경에서 부호의 양립성에 대한 연구 -주행편의장치 부호의 다중평가-

자동차의 새로운 운전편의장치들이 급속히 적용됨으로서 관련된 자동차용 부호 개발의 필요성이 증가되고 있다. 좋은 자동차용 부호는 인간공학적인 측면에서 검출성, 식별성, 학습용이성, 반응성, 인식성, 이해성 등의 특성을 잘 갖추어 궁극적으로 그 자체가 잘 설명되면서 올바른 상황에서 잘 사용되어야한다. 이 연구에서는 자동차용 부호를 개발하거나 평가하고자 할 때 고려되는 이해성, 인지성, 적절성 등으로 구성된 다중평가를 포함하는 자동차용 부호의 개발절차 및 평가방법을 제시하였다. 또한 이를 적용하여 오늘날 비교적 새로운 추가 기능인 차선이탈경보시스템(LDWS), 정속주행시스템(CCS), 충돌경보시스템(CWS) 등의 주행편의장치를 중심으로 28가지 부호를 평가하였다. 평가의 결과, 대부분의 주행편의장치의 부호는 2개 회사의 자동차 보다 KS R ISO 2575의 부호가 이해성, 인지성, 적절성이 높았다. 그 외 선루프, 카메라 등의 부호는 KS R ISO 2575의 부호가 낮았고, 그리고 표준으로 제시되고 있는 않은 2개 회사의 자동차에서 사용되고 있는 지능형안전장치 등의 최신 기능의 부호는 이 세 가지 평가점수가 매우 낮아 표준의 개발이 필요한 것으로 나타났다. 이 연구의 자동차용 부호에 대한 인간공학적 측면에서의 다중평가의 방법은 수행도 예측 가능한 이론적 연구가 부족한 상황에서 관련 부호의 개발 및 평가에 대한 유효한 방법론을 제공할 것이다. Automotive symbols are more widely needed for new, convenient driving devices in automobiles. Good automotive symbols should be detectable, identifiable at first glance, easily learned, recognizable, and produce quick responses after practice. In this paper, a methodology for developing and evaluating automotive symbols is suggested. It includes multiple tests, such as comprehension, perceptual quality, appropriateness, and integrated evaluation. 28 symbols were tested and evaluated by the suggested methodology for convenient driving systems, such as a lane departure warning system (LDWS), cruise control (CCS), and a collision warning system (CWS). Most of the KS R ISO 2575 symbols had higher scores of comprehension, perceptual quality, and appropriateness, but the sunroof and camera symbols had lower scores. Standard symbols with several new functions should be developed. This methodology could be useful for developing and evaluating automotive symbols.

Influence of lane departure warnings onset and reliability on car drivers' behaviors

Lane departures represent an important cause of road crashes. The objective of the present study was to assess the effects of an auditory Lane Departure Warning System (LDWS) for partial and full lane departures (onset manipulation) combined with missed warnings (reliability manipulation: 100% reliable, 83% reliable and 66% reliable) on drivers' performances and acceptance. Several studies indicate that LDWS improves drivers' performances during lane departure episodes. However, little is known about the effects of the warning onset and reliability of LDWS. Results of studies which looked at forward collision warning systems show that early warnings tend to improve drivers' performances and receive a better trust judgement from the drivers when compared to later warnings. These studies also suggest that reliable assistances are more effective and trusted than unreliable ones. In the present study, lane departures were brought about by means of a distraction task whilst drivers simulated driving in a fixed-base simulator with or without an auditory LDWS. Results revealed steering behaviors improvements with LDWS. More effective recovery maneuvers were found with partial lane departure warnings than with full lane departure warnings and assistance unreliability did not impair significantly drivers' behaviors. Regarding missed lane departure episodes, drivers were found to react later and spend more time out of the driving lane when compared to properly warned lane departures, as if driving without assistance. Subjectively, LDWS did not reduce mental workload and partial lane departure warnings were judged more trustworthy than full lane departure ones. Data suggests the use of partial lane departure warnings when designing LDWS and that even unreliable LDWS may draw benefits compared to no assistance.

A NOVEL APPROACH TO CAMERA CALIBRATION METHOD FOR SMART PHONES UNDER ROAD ENVIRONMENT

Abstract. Monocular vision-based lane departure warning system has been increasingly used in advanced driver assistance systems (ADAS). By the use of the lane mark detection and identification, we proposed an automatic and efficient camera calibration method for smart phones. At first, we can detect the lane marker feature in a perspective space and calculate edges of lane markers in image sequences. Second, because of the width of lane marker and road lane is fixed under the standard structural road environment, we can automatically build a transformation matrix between perspective space and 3D space and get a local map in vehicle coordinate system. In order to verify the validity of this method, we installed a smart phone in the ‘Tuzhi’ self-driving car of Wuhan University and recorded more than 100km image data on the road in Wuhan. According to the result, we can calculate the positions of lane markers which are accurate enough for the self-driving car to run smoothly on the road.

A NOVEL APPROACH TO CAMERA CALIBRATION METHOD FOR SMART PHONES UNDER ROAD ENVIRONMENT

Monocular vision-based lane departure warning system has been increasingly used in advanced driver assistance systems (ADAS). By the use of the lane mark detection and identification, we proposed an automatic and efficient camera calibration method for smart phones. At first, we can detect the lane marker feature in a perspective space and calculate edges of lane markers in image sequences. Second, because of the width of lane marker and road lane is fixed under the standard structural road environment, we can automatically build a transformation matrix between perspective space and 3D space and get a local map in vehicle coordinate system. In order to verify the validity of this method, we installed a smart phone in the ‘Tuzhi’ self-driving car of Wuhan University and recorded more than 100km image data on the road in Wuhan. According to the result, we can calculate the positions of lane markers which are accurate enough for the self-driving car to run smoothly on the road.

Design and simuation of a vehicle test bed based on intelligent transport systems

As growing demand of vehicle safety system, especially regarding intelligent transport systems (ITS), automotive manufacturers are focusing more on driving safety and efficient transportation for vehicle users. Many safety systems have been launched in the market recently so, it is important to evaluate the vehicle safety systems and ITS. The ITS based intelligent vehicle test bed was constructed to meet the growing demand of test and verification for such ADAS and ITS systems. First, this paper describes in detail concept of the test-bed. This test-bed is carefully designed to meet the requirements of ISO/TC204 standards. In order to verify the design of the test-bed, virtual test with driving siulator was processed on a virtual test tracks. This test-bed will be used to conduct testing on various ITS and ADAS technologies, such as adaptive cruise control (ACC), lane departure warning system (LDWS), cooperative intersection warning system as well as rollover stability control (RSC) and electronic stability control (ESC), etc.

단일 차선표시선 기반 차선 이탈 경보 시스템

본 논문에서는 단일 차선표시선 검출 기반 차선 이탈 경보 시스템을 제안한다. 제안하는 방법은 어두운 조명이나 마모로 인하여 좌 우 차선표시선의 동시 검출이 불가능한 경우에도 단일 차선표시선의 검출 및 추적을 통해 강건한 차선이탈 감지를 목표로 한다. 실험을 통해 제안 방법이 한쪽 차선표시선만 검출된 경우에도 차선이탈을 감지하는 것을 확인하였다. A lane departure warning system based on single lane mark detection is presented in this paper. The proposed system is focused on the robust detection of lane departure, even when one of the left or the right lane mark cannot be detected because of poor illumination or abrasion. Experimental results show that the proposed system warns lane departure, even if only a single lane is detected.

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.

Lane Departure Warning and Prevention Systems in the U.S. Vehicle Fleet: Influence of Roadway Characteristics on Potential Safety Benefits

Road departure crashes account for one-tenth of all crashes but nearly one-third of all fatal crashes. Lane departure warning (LDW) and lane departure prevention (LDP) active safety systems could mitigate these crashes by warning the driver of a lane departure or automatically navigating the vehicle back into the lane. The objective of this study was to quantify the influence of certain roadway characteristics on the effectiveness of LDW and LDP systems within the U.S. vehicle fleet. This study used 478 real-world drift-out-of-lane road departure crashes and simulated them as if the vehicles had been equipped with LDW or LDP systems. The simulations were then repeated as if ( a) all of the roadways had lane markings, ( b) the roadway shoulders were expanded, and ( c) lane markings were present and the shoulder widths were expanded. With the existing roadway infrastructure, LDW and LDP were found to potentially prevent 28% to 32% of U.S. road departure crashes and 21% to 28% of cases of serious driver injury. When lane markings were added to the roadways, LDW and LDP could prevent 32% to 36% of crashes and 27% to 31% of cases of serious driver injury. When only shoulder widths were expanded, LDW and LDP could prevent 50% to 54% of crashes and 44% to 48% of cases of serious driver injury. When lane markings were present and the shoulders were expanded, LDW and LDP could prevent 72% to 78% of crashes and 60% to 65% of cases of serious driver injury. The findings of this study highlight the important influence of roadway infrastructure on the performance of LDW and LDP.

Research on the Algorithms of Lane Recognition based on Machine Vision

Lane recognition is a kind of technology which can reconstruct either continuous or discontinuous lanes in the driving region into the continuous curves from the images of the road containing the lane markings. It is the basis and prerequisite for the whole lane departure warning system and the key technology in intelligent traffic safety assistant driving now. Generally speaking, the road images which the camera captures are processed by three steps: image preprocessing, image threshold segment and lane recognition. This paper proposed an efficient system to detect the lanes and mainly made experimental research on the images simulation of the three kinds of algorithms of the threshold segment and used the principle of Hough Transform in the lane recognition. Finally, the relatively efficient and accurate lane recognition processing algorithm was obtained according to the experimental results. Undoubtedly, this would lay a theoretical foundation for putting lane detection algorithm into practical application.

Toward Next Active Safety Technology of Intelligent Vehicle

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/02.jpg"" width=""300"" /> Intelligent vehicle technologies</div>Autonomous driving has attracted attention in recent years from the viewpoint of energy consumption and traffic accident prevention; hence, its introduction has been desired. In Japan, various accident prevention safety technologies were developed for cooperative control between the driver and the vehicle system. For example, “adaptive cruise control system” and “lane departure warning system” were developed in the 1990s and “lane keeping assist system” and “braking control device for reducing collision damage” in the early stages of the 2000s. Later in Europe, autonomous driving systems were actively studied, and an automated braking system to avoid collisions was introduced in the market in the second half of the 2000s. Studies and development have been promoted for the practical use of active safety technologies based on autonomous driving technologies. Autonomous driving technologies could be applied to various cases, such as convoy travelling to compensate for the insufficient number of professional drivers or to improve their work environment, last-one-mile travelling from a public transportation station to home for the elderly, people who have children and people who need assistance, dead-man system for sudden illness of the driver, and automated parking for assisting the driver who is not good at it, or for the parking space to be effectively used. In this paper, an overview of the transition and history of vehicular technologies for safety and reliability is given. In particular, active safety technologies for traffic accident prevention and the necessary related technology trend are reviewed, and future problems are pointed out.

운전자 반응을 고려한 성능기반 기법 적용 차선이탈경보시스템 경보 시점 설계 연구

This article aims to provide a design method of warning thresholds for active safety systems based on the performance-based approach considering driver behaviors. Both positive and negative consequences of warnings are considered, and the main idea is to choose a warning threshold where the positive consequence is maximized, whereas the negative consequence is minimized. The process of the performance-based approach involves: Defining the operating scenarios; setting the trajectory models, including human characteristics; estimating the alert and nominal trajectories; estimating the performance metrics; generating a performance-metric plot; and determining the alert thresholds. This paper chose a lane-departure warning system as an example to show the usefulness of the performance-based approach. Both human and sensor characteristics were considered in the system design, and this paper provided a quantitative method to include human factors in designing active safety systems.

Lane departure warning for mobile devices based on a fuzzy representation of images

The use of driver assistance systems is a current trend in the car industry. However, most driver assistance systems require the use of multiple sensors, increasing the cost of their implementation in cars and making them inaccessible to many users. In this paper, we present an “efficient” Lane Departure Warning system for mobile devices, which is real-time, accurate and accessible to most users. On the one hand, the accuracy of the system relies on Line Detection based on Hough Transforms, a combination that has proven to be reliable for this goal in many approaches. On the other hand, the reduction of the computational time, to achieve real-time processing, is due mainly to a proposed fuzzy representation of images. Finally, we also present various tests that show that the system proposed runs at up to 20 FPS on a mobile device (with a dual-core CPU at 1.0 GHz) with a resolution of 320×240px.

Comparison of Expected Crash and Injury Reduction from Production Forward Collision and Lane Departure Warning Systems

Objectives: The U.S. New Car Assessment Program (NCAP) now tests for forward collision warning (FCW) and lane departure warning (LDW). The design of these warnings differs greatly between vehicles and can result in different real-world field performance in preventing or mitigating the effects of collisions. The objective of this study was to compare the expected number of crashes and injured drivers that could be prevented if all vehicles in the fleet were equipped with the FCW and LDW systems tested under the U.S. NCAP.Methods: To predict the potential crashes and serious injury that could be prevented, our approach was to computationally model the U.S. crash population. The models simulated all rear-end and single-vehicle road departure collisions that occurred in a nationally representative crash database (NASS-CDS). A sample of 478 single-vehicle crashes from NASS-CDS 2012 was the basis for 24,822 simulations for LDW. A sample of 1,042 rear-end collisions from NASS-CDS years 1997–2013 was the basis for 7,616 simulations for FCW. For each crash, 2 simulations were performed: (1) without the system present and (2) with the system present. Models of each production safety system were based on 54 model year 2010–2014 vehicles that were evaluated under the NCAP confirmation procedure for LDW and/or FCW. NCAP performed 40 LDW and 45 FCW tests of these vehicles.Results: The design of the FCW systems had a dramatic impact on their potential to prevent crashes and injuries. Between 0 and 67% of crashes and 2 and 69% of moderately to fatally injured drivers in rear-end impacts could have been prevented if all vehicles were equipped with the FCW systems. Earlier warning times resulted in increased benefits. The largest effect on benefits, however, was the lower operating speed threshold of the systems. Systems that only operated at speeds above 20 mph were less than half as effective as those that operated above 5 mph with similar warning times. The production LDW systems could have prevented between 11 and 23% of drift-out-of-lane crashes and 13 and 22% of seriously to fatally injured drivers. A majority of the tested LDW systems delivered warnings near the point when the vehicle first touched the lane line, leading to similar benefits. Minimum operating speed also greatly affected LDW effectiveness.Conclusions: The results of this study show that the expected field performance of FCW and LDW systems are highly dependent on the design and system limitations. Systems that delivered warnings earlier and operated at lower speeds may prevent far more crashes and injuries than systems that warn late and operate only at high speeds. These results suggest that future FCW and LDW evaluation should prioritize early warnings and full-speed range operation. A limitation of this study is that additional crash avoidance features that may also mitigate collisions—for example, brake assist, automated braking, or lane-keeping assistance—were not evaluated during the NCAP tests or in our benefits models. The potential additional mitigating effects of these systems were not quantified in this study.

Improved river flow and random sample consensus for curve lane detection

Accurate and robust lane detection, especially the curve lane detection, is the premise of lane departure warning system and forward collision warning system. In this article, an algorithm based on improved river flow and random sample consensus is proposed to detect curve lane under challenging conditions including the dashed lane markings and vehicle occlusion. The curve lanes are modeled as hyperbola pair. To determine the coefficient of curvature, an improved river flow method is presented to search feature points in the far vision field guided by the results of detected straight lines in near vision field or the curved lines from the last frame, which can connect dashed lane markings or obscured lane markings. As a result, it is robust on dashed lane markings and vehicle occlusion conditions. Then, random sample consensus is utilized to calculate the curvature, which can eliminate noisy feature points obtained from improved river flow. The experimental results show that the proposed method can accurately detect lane under challenging conditions.

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.

New Lane Departure Warning System Based on Side-View Cameras

This paper addressed a new lane departure warning system (LDWS). We used the side-view cameras to promote Advanced Driver Assistance Systems (ADAS). A left side-view camera detected the right lane next to vehicle, and a right side-view camera detected the right lane. Two cameras processed in their algorithm and gave warning message, independently and separately. Our algorithm combined those warning messages to analyze environment situations. At the end, we used the LUXGEN MPV to test and showed results of verifications and tests.

Research on effects of pattern, amplitude and frequency of pulse steering torque warnings for lane departure

Driver’s inattention is the main reason for lane departure accidents in highway traffic. In this paper, the pulse steering torque warnings technique is studied, and the effects of pattern, amplitude and frequency of pulse steering torque warnings on the effectiveness and customers’ acceptance are studied through in-door experiments based on a fixed-based driving simulator. Prototypes of lane departure warning system with twelve parameter settings were developed. Three-ways repeated measures ANOVAS and t-test are used to assess the effects of warning systems. The steering behaviors of 20 drivers during lane departure are analyzed. The experimental results show that both primary and secondary interaction of amplitude, frequency and pattern are not significant. The superimposed square pulse steering torque is more effective than triangular pulse one. There is little difference of drivers’ preference in pulse patterns. Although large amplitude is less accepted by drivers, it improves the correction maneuver greatly. 10Hz is a preferred frequency, which achieves a compromise between effectiveness and drivers’ acceptance. Thus, the combination of small amplitude, square and mid-frequency is the best compromise for practical application.

Development of Lane Departure Warning Traffic System

In road-transport terminology, a lane departure warning system (LDWS) is a mechanism designed to warn a driver when the vehicle begins to move out of its lane on freeways and arterial roads. These systems are designed to minimize accidents by addressing the main causes of collisions: driving error, distraction and drowsiness. In this work the authors present a system which has the potential to reduce fatalities which are caused by the common type of crashes called the Run –Off-Road (ROR) crash. The work is to build a lane Departure Warning System for use on roads and highways. The functioning of the system will be to constantly monitor the car placement in relation to the road marks (with the aid of infrared proximity sensor), detect when the driver drifts away from the current lane without an appropriate warn signal, and provide a quick and effective alert to the driver to take a corrective action. To provide an alert system to trigger the quickest response possible. So the aim of this work is to make an intelligent system in hope to design a safer mean of transportation to save lives wasted on roads yearly, especially with the increase in the number of cars introduced to the roads each year. So the need of such security systems in today’s intelligent cars is essential.