• 자동차안전학회지
• /
• 제11권2호
• /
• pp.17-22
• /
• 2019

This paper describes the tracking algorithm performance evaluation for autonomous vehicle using a safety envelope based path. As the level of autonomous vehicle technologies evolves along with the development of relevant supporting modules including sensors, more advanced methodologies for path generation and tracking are needed. A safety envelope zone, designated as the obstacle free regions between the roadway edges, would be introduced and refined for further application with more detailed specifications. In this paper, the performance of the path tracking algorithm based on the generated path would be evaluated under safety envelop environment. In this process, static obstacle map for safety envelope was created using Lidar based vehicle information such as current vehicle location, speed and yaw rate that were collected under various driving setups at Seoul National University roadways. A level of safety was evaluated through CarSim simulation based on paths generated with two different references: a safety envelope based path and a GPS data based one. A better performance was observed for tracking with the safety envelop based path than that with the GPS based one.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권6호
• /
• pp.2483-2503
• /
• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.163-163
• /
• 2000

The tracking system on the moving vehicle is made up of two parts. One is a stabilizer which is flatting the system against the moving vehicle, the other is a tracker which is tracking the target. This makes use of the geometric information of the tracking target and that utilizes the dynamic information of the moving vehicle equipping the tracking system. Especially the stabilizer is very important for an ocean vehicle affected by wave, wind, and current. In this paper, the stabilizer of sun tracking system for a ship is developed.

• 한국항공운항학회지
• /
• 제21권1호
• /
• pp.23-29
• /
• 2013

This paper presents a tracking filter of radar beacon system (RBS) for automatic takeoff and landing of an unmanned aerial vehicle. The proposed tracking filter is designed as the decoupled tracking filter to reduce the computational burden. Also, an adaptive estimation method of the measurement error covariance is proposed to provide an improved tracking performance compared to the conventional decoupled tracking filter whenever the accuracy of RBS observations is degraded. 100 times Monte Carlo runs performed to analyze the performance of the proposed tracking filter in case of normal operation and degraded operations, respectively. The simulation results show that the proposed tracking filter provides the improved tracking accuracy in comparison with the conventional decoupled tracking filter.

• 한국항행학회논문지
• /
• 제11권4호
• /
• pp.359-370
• /
• 2007

무인 자동차 시스템에 있어 차선추적과 물체회피 기술은 중요한 핵심기술 이다. 본 논문에서는 차량제어와 모델링, 센서 실험을 통하여 차선추적 및 물체회피 방법을 제안하고자 한다. 첫 번째 물체회피는 가/감속을 위한 종 방향 제어와 조향제어에 의한 횡 방향 제어 두 개의 부분으로 구성되어 진다. 각각의 시스템은 무인자동차의 제어를 위하여 차량의 위치, 주변환경 인식, 상황에 따른 빠른 처리를 요구한다. 차량의 제어 전략이 작동되는 동안 도로에서의 물체인식과 회피는 차량의 속도에 달려 있다. 두 번째 영상시스템을 통한 차선추석방법을 설명한다. 이 또한 두 부분으로 구성된다. 첫 번째 횡/종 제어를 위한 로도 모델이 포함된다. 두 번째 차선추적방법, 영상처리 알고리즘, 필터링 방법 및 영상처리 방법을 다룰 것이다. 마지막으로 본 논문에서는 실차실험을 통한 차선추적 및 물체회피 차량제어 및 모델링 방법을 제안한다.

• 반도체디스플레이기술학회지
• /
• 제22권3호
• /
• pp.161-165
• /
• 2023

One of the difficult works in an autonomous driving system is detecting road lanes or objects in the road boundaries. Detecting and tracking a vehicle is able to play an important role on providing important information in the framework of advanced driver assistance systems such as identifying road traffic conditions and crime situations. This paper proposes a vehicle detection scheme based on deep learning to classify and tracking vehicles in a complex and diverse environment. We use the modified YOLO as the object detector and polynomial regression as object tracker in the driving video. With the experimental results, using YOLO model as deep learning model, it is possible to quickly and accurately perform robust vehicle tracking in various environments, compared to the traditional method.

• 정보처리학회논문지D
• /
• 제9D권6호
• /
• pp.1071-1082
• /
• 2002

무선 컴퓨팅 기술 및 이동 객체의 위치를 정확하게 추적할 수 있는 GPS 기술의 발달로 인하여 물류 차량 관리, 항공 교통 통제, 위치 기반 서비스 등과 같은 실시간 환경의 위치 정보 응용 시스템의 개발이 활발해지고 있다. 특히, 차량의 위치를 관제 센터에서 실시간으로 파악하는 차량 위치 추적 시스템에 관한 연구가 대표적인 응용 시스템으로 등장하였다. 그런데 기존의 차량 위치 추적 시스템은 데이터베이스에 저장되지 않은 특정 시간의 차량 위치 정보를 사용자에게 제공하지 못하는 문제점을 갖는다. 따라서 이 논문에서는 PDA와 같은 모바일 인터페이스를 통하여 실시간으로 차량의 위치 추적이 가능한 시스템을 설계한다. 제안 시스템은 차량 위치 검색 서버와 모바일 인터페이스로 구성되며, 이동 차량의 현재 위치뿐만 아니라 데이터베이스에 저장되지 않은 과거 및 미래 위치 정보까지 사용자에게 제공하는 장점을 갖는다.

• International Journal of Control, Automation, and Systems
• /
• 제4권5호
• /
• pp.529-538
• /
• 2006

Separating a reentry vehicle into warhead and body is a conventional and efficient means of producing a huge decoy and increasing the kinetic energy of the warhead. This procedure causes the radar to track the body, whose radar cross section is larger, and ignore the warhead, which is the most important part of the reentry vehicle. However, the procedure is difficult to perform using standard tracking criteria. This study presents a novel tracking algorithm by integrating input estimation and modified probabilistic data association filter to solve this difficulty in a clear environment. The proposed algorithm with a new defined association probability in this filter provides a good tracking capability for the warhead ignoring the radar cross section. The simulation results indicate that the errors between the estimated and the warhead trajectories are reduced to a small interval in a short time. Therefore, the radar can produce a beam to illuminate to the right area and keep tracking the warhead all the way. In conclusion, this algorithm is worthy of further study and application.

• ETRI Journal
• /
• 제37권3호
• /
• pp.617-625
• /
• 2015

In this paper, a steering control system for the path tracking of autonomous vehicles is described. The steering control system consists of a path tracker and primitive driver. The path tracker generates the desired steering angle by using the look-ahead distance, vehicle heading, and a lateral offset. A method for applying an autonomous vehicle to path tracking is an advanced pure pursuit method that can reduce cutting corners, which is a weakness of the pure pursuit method. The steering controller controls the steering actuator to follow the desired steering angle. A servo motor is installed to control the steering handle, and it can transmit the steering force using a belt and pulley. We designed a steering controller that is applied to a proportional integral differential controller. However, because of a dead band, the path tracking performance and stability of autonomous vehicles are reduced. To overcome the dead band, a dead band compensator was developed. As a result of the compensator, the path tracking performance and stability are improved.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권2호
• /
• pp.710-726
• /
• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.