• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.137-148
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• 2005

The position information of individual vehicles on a road at every time instant can be used to analyze the microscopic behaviors of driving of each vehicle. The limited information obtained from previous imaging technology such as traffic volume and interval velocity cannot be used to explore such microscopic traffic conditions. Also, information gathering for the microscopic behaviors by manual analysis of captured video takes large amount of time and man-power. In the paper we develop the rule-based vehicle tracking technology from which the position information of individual vehicles on a road at every time instant can be automatically obtained. Also, we extract the position data of driving vehicles on a road, length of 130m for every 0.05 second, and calculate the velocity of each traced vehicles to compare with the real velocity for the verification of accuracy. In the future, this type of tracking techniques based on video analysis can be widely used to provide the practically important information of road traffic conditions and to analyze the academically important microscopic behaviors of driving patterns.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.249-252
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• 2004

The automatic determination of vehicle operation status as well as continuous tracking of vehicle location with intelligent management is one of major elements to achieve the goals. Especially, vehicle operation status can only be analyzed in terms of expert experiences with real-time location data with scheduling information. However the scheduling information of individual vehicle is very difficult to be interpreted immediately because there are hundreds of thousand vehicles are run at the same time in the national wide range workplace. In this paper, we propose the location-based knowledge management system(LKMs) using the active trajectory analysis method with routing and scheduling information to cope with the problems. This system uses an inference technology with dispatching and geographic information to generate the logistics knowledge that can be furnished to the manager in the central vehicle monitoring and controlling center.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.177-186
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• 2008

Video Image Detection System can be used for various traffic managements including traffic operation and traffic safety. Video Image Detection Technique can be divide by Tripwire System and Tracking System. Autoscope, which is widely used in the market, utilizes the Tripwire System. In this study, we developed an individual vehicle tracking system that can collect microscopic traffic information and also developed another image detection technology under the Tripwire System. To prove the accuracy and reliability of the newly developed systems, we compared the traffic data of the systems with those generated by Autoscope. The results showed that 0.35% of errors compared with the real traffic counts and 1.78% of errors with Autoscope. Performance comparisons on speed from the two systems showed the maximum errors of 1.77% with Autoscope, which confirms the usefulness of the newly developed systems.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.251-264
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• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Ocean and Polar Research
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• v.36 no.4
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• pp.465-473
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• 2014

This paper proposes a formation control method by which multi-mining robots maintain a specified formation and follow a path. To secure the path tracking performance, a pure-pursuit algorithm is considered for each individual robot, and to minimize the deviation from the reference path, speed reduction in the steering motion is added. For the formation, in which two robots are parallel in a lateral direction, the robots track the specified path at a constant distance. In this way, the Leader-Follower method is adopted and the following robot knows the position and heading angle of the leader robot. Through the experimental test using two ground vehicle models, the performance is verified.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.