Lane Departure Warning System Research Articles

Tactile stimulations and wheel rotation responses: toward augmented lane departure warning systems.

When an on-board system detects a drift of a vehicle to the left or to the right, in what way should the information be delivered to the driver? Car manufacturers have so far neglected relevant results from Experimental Psychology and Cognitive Neuroscience. Here we show that this situation possibly led to the sub-optimal design of a lane departure warning system (AFIL, PSA Peugeot Citroën) implemented in commercially available automobile vehicles. Twenty participants performed a two-choice reaction time task in which they were to respond by clockwise or counter-clockwise wheel-rotations to tactile stimulations of their left or right wrist. They performed poorer when responding counter-clockwise to the right vibration and clockwise to the left vibration (incompatible mapping) than when responding according to the reverse (compatible) mapping. This suggests that AFIL implements the worse (incompatible) mapping for the operators. This effect depended on initial practice with the interface. The present research illustrates how basic approaches in Cognitive Science may benefit to Human Factors Engineering and ultimately improve man-machine interfaces and show how initial learning can affect interference effects.

Potential Occupant Injury Reduction in the U.S. Vehicle Fleet for Lane Departure Warning–Equipped Vehicles in Single-Vehicle Crashes

Objective: Single-vehicle collisions involve only 10 percent of all occupants in crashes in the United States, yet these same crashes account for 31 percent of all fatalities. Along with other vehicle safety advancements, lane departure warning (LDW) systems are being introduced to mitigate the harmful effects of single-vehicle collisions. The objective of this study is to quantify the number of crashes and seriously injured drivers that could have been prevented in the United States in 2012 had all vehicles been equipped with LDW.Methods: In order to estimate the potential injury reduction benefits of LDW in the vehicle fleet, a comprehensive crash and injury simulation model was developed. The model's basis was 481 single-vehicle collisions extracted from the NASS-CDS for year 2012. Each crash was simulated in 2 conditions: (1) as it occurred and (2) as if the driver had an LDW system. By comparing the simulated vehicle's off-road trajectory before and after LDW, the reduction in the probability of a crash was determined. The probability of a seriously injured occupant (Maximum Abbreviated Injury Score [MAIS] 3+) given a crash was computed using injury risk curves with departure velocity and seat belt use as predictors. Each crash was simulated between 18 and 216 times to account for variable driver reaction, road, and vehicle conditions. Finally, the probability of a crash and seriously injured driver was summed over all simulations to determine the benefit of LDW.Results and Conclusions: A majority of roads where departure crashes occurred had 2 lanes and were undivided. As a result, 58 percent of crashes had no shoulder. LDW will not be as effective on roads with no shoulder as on roads with large shoulders. LDW could potentially prevent 28.9 percent of all road departure crashes caused by the driver drifting out of his or her lane, resulting in a 24.3 percent reduction in the number of seriously injured drivers.The results of this study show that LDW, if widely adopted, could significantly mitigate a harmful crash type. Larger shoulder width and the presence of lane markings, determined by manual examination of scene photographs, increased the effectiveness of LDW. This result suggests that highway systems should be modified to maximize LDW effectiveness by expanding shoulders and regularly painting lane lines.

Research on Lane Departure Warning System

Lane departure warning system includes lane identification and lane departure determination. Lane identification is crucial for lane departure warning system. In this paper, A linear mode which can only bring out small distance error and angle error is used to detect lane boundaries. A region of interest (ROI) appropriate is set to reduce nonessential cost of computation. According to the characteristics of lane position, we improve the Hough transform, reduce the detection and tracking transform angle and raise the speed of calculation. Parameter angle form Hough transform is used to lane departure determination, this method does not calibrate the camera and can get the lane departure rate. Experiments show that the system is well to detect and track the lane line and give alarm correctly.

Fleetwide Safety Benefits of Production Forward Collision and Lane Departure Warning Systems

Fleetwide Safety Benefits of Production Forward Collision and Lane Departure Warning Systems

Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

A reconfigurable embedded vision system for advanced driver assistance

Computer vision technologies can contribute in many ways to the development of smart cities. In the case of vision applications for advanced driver assistance systems (ADAS), they can help to increase road traffic safety, which is a major concern nowadays. The design of an embedded vision system for driver assistance is not straightforward; several requirements must be addressed such as computational performance, cost, size, power consumption or time-to-market. This paper presents a novel reconfigurable embedded vision system that meets the requirements of ADAS applications. The developed PCB board contains a System on Chip composed of a programmable logic that supports parallel processing necessary for a fast pixel-level analysis, and a microprocessor suited for serial decision making. A lane departure warning system was implemented in the case study, obtaining a better computational performance than the rest of the works found in the literature. Moreover, thanks to the reconfiguration capability of the proposed system a more flexible and extensible solution is obtained.

Lane departure warning system based on future driving path prediction

Based on computer vision technology, a lane departure warning system proposed in this research comprises three parts: the first part contains a lane model, which is constructed to mark the potential locations of the lanes in the images. The second part relates to lane marking detection on the basis of the constructed lane model, in which the edge of the lane marking has been detected through Hough transformation. Then the extended Kalman filter is used to reduce the range of the constructed lane model. Finally, a recursive operation finds the locations of the lane path. The third part is the alerting system. The deviation between the past driving path and the detected lane is used as a baseline; and Grey theory is used to estimate the future driving path and to predict the deviation between time and distance. Warnings are then given in response to dangerous driving behaviour in order to avoid accidents.

Towards understanding the development of driver's mental model of a Lane Departure Warning system while driving

Towards understanding the development of driver's mental model of a Lane Departure Warning system while driving

Seamless Implementation of ECU Software based on ISO 26262

As a standard for the development of safety-related applications in the automotive industry, ISO 26262 [1] defines a basic framework for development processes and methods. Functional safety is viewed as an integral component of system development and is integrated in this process from the start [2]. To assure full coverage of safety goals and to document their fulfillment, the traceability of requirements must be documented down to the level of individual software work products such as code modules or test cases. If more complex systems are being developed, an integrated tool support is almost mandatory. In the following sections, these aspects are explained in greater detail, and the benefits an integrated tool support for system and software engineering are described. The technical example used for illustration purposes is a Lane Departure Warning (LDW) system.

안전주행을 위한 DGPS/GIS 기반의 차량제어 연구

In recent days, vehicles have become equipped with electric systems that assist and help drivers driving safe by reducing possible accidents. LDWS(Lane Departure Warning System) and LKAS(Lane Keeping Assistant System) are involved in assist systems, especially for lateral motion of vehicles. Sudden and inattentive lateral motion of vehicles due to drivers' fatigue, illness, inattention, and drowsiness are major causes of accidents in highway. LDWS and LKAS provide drivers with warnings or assisting power to reduce any possibilities of accidents. In order to prevent or minimize the possibilities of accidents, lateral motion control of vehicles has been introduced in this research. DGPS/RTK(Differential Global Positioning System/Real Time Kinematics) and GIS(Geographic Information System) have been used to obtain the current position of vehicles and decide when activate controlling lateral motion of vehicles. The presented lateral motion control has been validated with actual vehicle tests.

Real-time lane departure warning system based on a single FPGA

Abstract Abstract This paper presents a camera-based lane departure warning system implemented on a field programmable gate array (FPGA) device. The system is used as a driver assistance system, which effectively prevents accidents given that it is endowed with the advantages of FPGA technology, including high performance for digital image processing applications, compactness, and low cost. The main contributions of this work are threefold. (1) An improved vanishing point-based steerable filter is introduced and implemented on an FPGA device. Using the vanishing point to guide the orientation at each pixel, this algorithm works well in complex environments. (2) An improved vanishing point-based parallel Hough transform is proposed. Unlike the traditional Hough transform, our improved version moves the coordinate origin to the estimated vanishing point to reduce storage requirements and enhance detection capability. (3) A prototype based on the FPGA is developed. With improvements in the vanishing point-based steerable filter and vanishing point-based parallel Hough transform, the prototype can be used in complex weather and lighting conditions. Experiments conducted on an evaluation platform and on actual roads illustrate the effective performance of the proposed system.

An Improved Lane Detection and Tracking Method for Lane Departure Warning Systems

Lane detection and tracking are very crucial treatments in lane departure warning systems as they help the vehicle-mounted system to keep its lane. In this context, the authors’ work aims to develop vision-based lane detection and tracking method to detect and track lane limits in highways and main roads. The authors’ contribution focuses on the detection step. By exploiting the fact that, in an image, the road can be formed by linear and curvilinear portions, the authors propose two types of appropriate treatments to detect the lane limits. The authors’ method offers high precision rates independently of the painted lane marking’s characteristics, of the time of acquisition and in different weather conditions. Besides the challenges it overcomes, the authors’ method has the advantage of operating with a timing complexity that is reasonable for real-time applications. As shown experimentally, compared to three leading methods from the literature, the authors’ method has a higher efficiency.

Implementation of Lane Departure Warning System Based on Machine Vision

Purpose of this paper raise a vehicle lane departure warning system based on the machine vision. It does not need to use the parameters of the camera which do the road marking recognition system installed in the interior of the camera by algorithms. Regarding the time line of the intelligent transport system, it is to solve the various problems possibly arising from driving on the road. This system is mainly for the warning of the unexpected departure of vehicle. The method is to use the digital camera to capture continuous images and identify the vehicle moving direction by the detection of the left and right markings, as well as forecast the driving direction of the vehicle for the reference of vehicle departure warning. In this paper, the used algorithms include brightness adjustment, binarization, dilation, erosion, and edge detection image processing techniques.

Secure solution of collision warning system integration with use of vehicular communications within intelligent transportation systems

The article deals with connection of Lane Departure Warning System (LDWS) assistance service to a C2C (Car-to-Car) unit, which actively monitors the state of kinetic properties of vehicle using VANET. It describes possible solutions of finding horizontal road marking using segmentation method based on Hough's transformation. The algorithm designed in Matlab programming environment detects deviation of vehicle from its driving lane, triggers the resulting alarm which is transferred in a form of an authorised message between vehicles via C2C communication.

Methodology for Using Advanced Event Data Recorders to Reconstruct Vehicle Trajectories for Use in Safety Impact Methodologies (SIM)

Objective: Safety impact methodologies (SIMs) have the goal of estimating safety benefits for proposed active safety systems. Because the precrash movements of vehicles involved in real-world crashes are often unknown, previous SIMs have taken the approach to reconstruct collisions from incomplete information sources, such as scaled scene diagrams and photographic evidence. The objective of this study is to introduce a novel methodology for reconstructing the precrash vehicle trajectories using data from advanced event data recorders (EDRs). Methods: Some EDRs from model year 2009 and newer Ford vehicles can record steering wheel angle in addition to precrash vehicle speed, accelerator pedal, and throttle input prior to the crash. A model was constructed using these precrash records and a vehicle model developed in the simulation software PreScan. The model was validated using the yaw rate and longitudinal and lateral accelerations also recorded by this type of Ford EDR but not used to develop the models. Results: In general, the model was able to approximate the dynamics recorded on the EDR. The model did not match the observed dynamics when either the vehicle departed the paved surface or when electronic stability control was active. Modifying the surface friction at the estimated point at which the vehicle departed the road produced better simulation results. The developed trajectories were used to simulate 2 road departure crashes, one into a fixed object and one into a vehicle traveling in the opposite direction, as if the departing vehicle were equipped with a lane departure warning (LDW) system. This example application demonstrates the utility of this method and its potential application to a SIM. Conclusions: This study demonstrated a novel method for crash reconstruction that can be applied to a SIM for active safety systems. Benefits of this method are that the driver inputs do not need to be inferred from other reconstructions because they are recorded directly by the EDR. Currently, there are too few cases with the advanced EDR data to estimate fleet-wide benefits of a system. Because of recent regulation (49 CFR Part 563), EDRs are likely to be downloaded in more real-world crashes, making this method a potentially valuable and low-cost method for developing SIMs in the future. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

Developing Parallel Application on Multi-core Mobile Phone

One cannot imagine daily life today without mobile devices such as mobile phones or PDAs. They tend to become your mobile computer offering all features one might need on the way. As a result devices are less expensive and include a huge amount of high end technological components. Thus they also become attractive for scientific research. Today multi-core mobile phones are taking all the attention. Relying on the principles of tasks and data parallelism, we propose in this paper a real-time mobile lane departure warning system (M-LDWS) based on a carefully designed parallel programming framework on a quad-core mobile phone, and show how to increase the utilization of processors to achieve improvement on the system’s runtime.

Lane Marking Recognition for Constructing a Multi-information Map

For the lane departure warning system or the lane keeping system, it is important to detect lane lines stably in images from vehicle onboard cameras. We have developed the lane line detection system for platooning. This system can detect various kinds of lane markings stably and robustly because it uses a multi-information map containing road marking information, such as a kind of road marking, the width of a lane line or degree of blur, to detect lane markings. A multi-information map is tied to position data obtained from global positioning system (GPS). Therefore, a vehicle can obtain information about lane markings to detect at the present position from a multi-information map. This paper proposes the method to construct a multi-information map automatically by recognizing road markings in images from an onboard front camera. Input images are transformed to inverse perspective projection images. In these transformed images, seven features, such as the histogram of line angles, the number of corner points, the histogram of a lane line width, the histogram of a lane line height, the histogram of the horizontal distance between markings, the histogram of the vertical distance between markings and the color of a maker, are extracted to discriminate road markings. Experiments conducted in real road scenes show the effectiveness of the proposed method for constructing a multi-information map.

On-Board Driver Assistance System for Lane Departure Warning and Vehicle Detection

Computer vision and image processing based intelligent transportation systems have become very popular for the last decade. Vehicle manufacturers and automotive industry are interested in vision-based systems. This kind of systems could warn drivers and prevent accidents caused by inattentive driving. This paper introduces a single-board computer system for lane departure warning and vehicle detection. Our system employs the lane departure warning system based on geometrical cues which is implemented widely in the literature. For vehicle detection, we propose a cascade object detector trained by using car rear images. Our main contribution is to implement our system on an embedded single board computer which runs in real time. This system can be mounted into the car with a camera and can be used in practice. 

An empirical investigation of the development of driver's mental model of a Lane Departure Warning system while driving

Abstract Like all man-made artefacts, Advanced Driver Assistance Systems have certain limitations beyond which they cannot function properly or work at all. The users in the driving domain have diverse backgrounds and it is likely that many of them start interacting with the technology without having gained detailed knowledge, such as by reading user manuals. This study explores whether drivers with only minimal knowledge of the Lane Departure Warning system can recognize the system's speed threshold and update themselves about this in a dynamic driving environment. Since drivers are not always single-mindedly focused on driving, a group of participants was also prompted to perform a secondary task while driving. Our investigation allowed us to estimate the effects of 1) drivers' minimal mental model of the system's working and 2) insufficient knowledge concerning the system capacities, upon their situation awareness and their capabilities of learning from experience. It was assumed that the demands of multitasking would impair the driver's ability to observe the system's state and delay the mental model improvement process, compared to a setting in which driving was the only task. Experiment results using a driving simulator have been presented.

A Novel Lane Departure Warning System Based on Surrounding View

Lane departure warning system based on surrounding view is a human-made decision such as solution to avoid lane departure fatalities with low cost and high reliability. In this paper, the key parameters of time to lane crossing (TLC) and distance to lane crossing (DLC) are all calculated from image processing(the corner detect and the optic flow). In the warning module, two strategies are proposed to improve the reliability of the system. After adjusting the threshold values on abundance frames of consecutive images, the refined threshold of the two strategies are determined. Finally, the proposed strategies are incorporated into our lane departure warning system to be tested in off-line simulation. The results indicate the efficiency and feasibility of our system.