• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.238-245
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• 2001

This paper describes a method for detecting a close leading vehicle using the contour of the vehi-cles rear wheels. The contour of a leading vehicles rear wheels in 속 front road image from a B/W CCD camera mounted on the central front bumper of the vehicle, has vertical components and can be discerned clearly in contrast to the road surface. After extracting positive edges and negative edges using the Sobel op-erator in the raw image, every point that can be recognized as a feature of the contour of the leading vehicle wheel is determined. This process can detect the presence of a close leading vehicle, and it is also possible to calculate the distance to the leading vehicle and the lateral deviation angle. This method might be useful for developing and LSA (Low Speed Automation) system that can relieve drivers stress in the stop-and-go traffic conditions encoun-tered on urban roads.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.93-99
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• 2011

A PRT vehicle's control method is presented in this paper. In the asynchronous vehicle control system, vehicles follow their leading vehicles. Leading vehicles are defined differently among the different types of track. The main topic of this paper is to present a method to define the leading vehicle among different types of track and the calculation algorithm of the safety length the following vehicle must maintain. Simulation program is developed using the algorithm and the results of the test run are presented. An asynchronous PRT vehicle control algorithm was presented by Szillat in the paper "A low level PRT Microsimulation, Dissertation, University of Bristol, 2001". But it is different from the algorithm in this paper. In the algorithm proposed by Markus, vehicles in the merging track are controlled synchronously, and its safety distance between the leading and the following car is evaluated after the establishment of the complicated future time-location table instead of simple equations proposed in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.181-184
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• 1999

Leading vehicle states are useful and essential elements in adaptive cruise control (ACC) system, collision warning (CW) and collision avoidance (CA) system, and automated highway system (AHS). There are many approaches in ACC using Kalman filter. Mostly only distance to leading vehicle and velocity difference are estimated and used for the above systems. Applications in road vehicle in curved road need to obtain more informations such as yaw angle, steering angle which can be estimated using vision system. Since vision system is not robust to environment change, we used Kalman filter to estimate distance, velocity, yaw angle, and steering angle. Application to active tracking of target vehicle is shown.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.163-172
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• 2012

A driver assistance system is critical to improve a convenience and stability of vehicle driving. Several systems have been already commercialized such as adaptive cruise control system and forward collision warning system. Efficient vehicle detection is very important to improve such driver assistance systems. Most existing vehicle detection systems are based on a radar system, which measures distance between a host and leading (or oncoming) vehicles under various weather conditions. However, it requires high deployment cost and complexity overload when there are many vehicles. A camera based vehicle detection technique is also good alternative method because of low cost and simple implementation. In general, night time vehicle detection is more complicated than day time vehicle detection, because it is much more difficult to distinguish the vehicle's features such as outline and color under the dim environment. This paper proposes a method to detect vehicles at night time using analysis of a captured color space with reduction of reflection and other light sources in images. Four colors spaces, namely RGB, YCbCr, normalized RGB and Ruta-RGB, are compared each other and evaluated. A suboptimal threshold value is determined by Otsu algorithm and applied to extract candidates of taillights of leading vehicles. Statistical features such as mean, variance, skewness, kurtosis, and entropy are extracted from the candidate regions and used as feature vector for SVM(Support Vector Machine) classifier. According to our simulation results, the proposed statistical feature based SVM provides relatively high performances of leading vehicle detection with various distances in variable nighttime environments.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.3037-3047
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• 2000

This paper describes a method of tracking a close leading vehicle by color image processing using the pairs of tail and brake lights. which emit red light and are housed on the rear of the vehicle in stop-and-go traffic condition. In the color image converted as an HSV color model. candidate regions of rear lights are identified using the color features of a pair of lights. Then. the pair of tailor brake lights are detected by means of the geometrical features and location features for the pattern of the tail and brake lights. The location of the leading vehicle can be estimated by the location of the detected lights and the vehicle can be tracked continuously. It is also possible to detect the braking status of the leading vehicle by measuring the change in HSV color components of the pair of lights detected. In the experiment. this method tracked a leading vehicle successfully from urban road images and was more useful at night than in the daylight. The KAV-Ill (Korea Autonomous Vehicle- Ill) equipped with a color vision system implementing this algorithm was able to follow a leading vehicle autonomously at speeds of up to 15km!h on a paved road at night. This method might be useful for developing an LSA (Low Speed Automation) system that can relieve driver's stress in the stop-and-go traffic conditions encountered on urban roads.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.26-31
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• 2017

The current autonomous vehicle competitions are dominated by a few leading research institutions and universities. Since the leading research groups have been able to accumulate their knowledge and to develop their own algorithms for autonomous vehicle for many years, the technology gap seems too big for other followers to catch up with. On the other hand, recent researches predict that there would be a sharp rise in demand for engineers with background in autonomous vehicle technology. Therefore, it would be warranted to further expand the base of the academia and autonomous vehicle industry. In an effort to achieve this goal, it would be beneficial to hold a new format of autonomous vehicle competition event where undergraduate students can play a leading role. So, this study is to analyze the current autonomous vehicle competitions and thus to establish a strategic plan to develop a unique and improved competition event. This study investigates the pros and cons of the domestic and international autonomous vehicle competitions. Based on the analysis for the current autonomous vehicle competitions, the authors suggest a strategic plan to initiate an autonomous vehicle competition. To implement the aforementioned strategic plan, it is necessary to develop a systematic environment where the education and communication are actively available. Through the strategic plan the authors propose, the newly launching autonomous vehicle competition will able to encourage the undergraduate students and professors to dive in the cutting-edge technology thereby increasing technology competitiveness.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.134-140
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• 2008

Preceding vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based preceded vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an preceded vehicle detection system is developed using stereo vision sensors. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the preceded vehicles including a leading vehicle. Then, the position parameters of the preceded vehicles or leading vehicles can be obtained. The proposed preceded vehicle detection system is implemented on a passenger car and its performances is verified experimentally.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.1
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• pp.51-59
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• 2017

In 2014, there were approximately 4,762 fatalities on Korean roads. The fatality rate has decreased by 6.5 %, as compared to that of the previous year. The pedestrian-vehicle fatalities (1,795) have also decreased by 6 % over the previous year. However, the percentage of the pedestrian fatalities has increased from 37.9 % to 38.7 % during the same period. This is why further research is required, even though the KNCAP pedestrian safety assessment and KMVSS for pedestrian protection currently exist. This paper studied the Upper Legform to Bonnet Leading Edge Test at the front of the vehicles, which has not been introduced yet in Korea. The test method and procedure of the new BLE test in the Euro NCAP test protocol have been reviewed, and the physical tests on SUV and sedan with different bonnet leading edge heights have also been conducted and reviewed. In addition, the test results and characteristics have been analyzed via comparison with the former BLE test and each vehicle type.

• Advances in aircraft and spacecraft science
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• v.7 no.1
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• pp.1-17
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• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• Journal of Biosystems Engineering
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• v.27 no.5
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• pp.409-416
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• 2002

This study was conducted to develop a vehicle, leading or following a worker at a certain distance to assist laborious transporting works in greenhouses. A prototype vehicle, which consisted of the rear driving, the front steering and the console units, was designed and tested in the ideal indoor conditions. Results of this study were summarized as following: 1. The driving unit was designed to travel at the speed ranges of 0.3∼0.8 m/sec depending on the operating modes with a maximum payload of 100 kg. 2. The console unit consisted of a main-board including a 80C196KC microprocessor and peripheral devices, a power-board and safety interlock. Worker-leading, and following modes were available in automatic and manual modes. 3. Steering was achieved by turning the steering motor against the sensed direction. Proper steering angles for correcting travel direction were determined as 5 and 9 degrees when sensing cultivation beds and plants, respectively.