• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.255-260
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• 2017

In Korea, traffic accidents between pedestrians and vehicles in 2015 account for 38.8% of all accidents. This study proposes a system design that can measure the risk of conflict between a vehicle and a pedestrian. Firstly the systemdetect and estimate the position, speed, and directional data of the vehicle and the pedestrian. And then it estimate the conflict point between a vehicle and a pedestrian. The risk of conflict is quantified by estimating the pedestrian safety margin (PSM), which is the time difference between the arrival of the pedestrian at the crossing point to the point of conflict and the vehicle approaching the point. In this system each data is acquired through an external monitoring based evaluation module and an individual wearing module. In the future, such a system can be used for decision making such as the design of road hazard improvement facilities and the designation of the elderly protection area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.9-21
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• 2009

This study presents a useful heuristic algorithm to classify vehicle classes using vehicle length information, which is extracted from inductive loop vehicle signatures. A high-speed scanning equipment was used to extract more detailed change of inductance magnitude for individual vehicles. Vehicle detection time and individual vehicle speeds were used to derive vehicle length information that is an input of the proposed algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm performance more systematically. It is expected that the proposed method would be useful for obtaining vehicle classification information from wide-spread existing loop infrastructure.

• Spatial Information Research
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• v.22 no.2
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• pp.89-97
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• 2014

This study investigated how much the spread of traffic control information affect the traffic congestion in order to identify the behavior of the individual drivers that impacts on the entire transport system. For this purpose, agent-based transportation model was constructed. GIS data were directly used for the transportation model and the processing steps of the simulation results are presented. The results showed that the average speed was not lowered when the traffic information was provided to 30 to 70% of total drivers. In contrast, the driver's average speed is reduced when he traffic information was provided to less than 20% or 80% or more. In summary, the provision of traffic information to drivers has an influence on the traffic flow and bypassing vehicles can generate local congestion. This results can be used as a basis for the future direction of road transport policy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.116-130
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• 2023

Expressways play pivotal roles in cargo transportation because of their superior accessibility and mobility compared to rail and air. On the other hand, there is a limit to the accurate calculation of cargo transportation performance using existing highways owing to the mixture of vehicle types and difficulty in identifying cargo loads of individual cargo vehicles. This paper presents an algorithm for calculating more reliable cargo transportation performance using big data. The traffic performance (veh·km/day) was derived using the data collected from Toll Collecting System. The average tolerance weight for each vehicle type and the cargo load unit (ton/unit) considering it was calculated using vehicle specification information data and high-speed and low-speed axis data. This study calculated the cargo transportation performance by section and type using various online integrated highway data and presented a method for calculating the transportation performance by linking open business offices and private highways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.14-34
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• 2023

The purpose of this study was to calculate the appropriate yellow-signal time for intersections, to find out the relationship between the approach speed and intersection width when calculating the time, and to secure safety by minimizing conflicts and dilemma sections in intersections that change according to the signal operation. For this purpose, 6,824 data points from 5 intersections were collected and analyzed. The main results of the study are as follows. First, the approach speed of individual vehicles in different lanes was analyzed, and the width of an intersection was defined by considering the conflict in each direction. Second, we developed a multiple regression model based on the approach speed and conflict points, which compensated for the problems of an existing formula. Third, a standard table is presented for applying the appropriate yellow-signal time according to the approach speed and intersection width based on a development formula. A method is also presented to determine the safety of the length of the dilemma according to the change in the yellow-light time by presenting a calculation table that can cross-analyze the yellow-signal time and a dilemma section using the relationship.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.655-666
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• 2021

Purpose: This study is to develop a method for measuring dynamic speeding risks using vehicle trajectory big data and to demonstrate the feasibility of the devised speeding index. Method: The speed behaviors of vehicles were analysed in microscopic space and time using individual vehicle trajectories, and then the boundary condition of speeding (i.e., boundary speed) was determined from the standpoint of crash risk. A novel index for measuring the risk exposure of speeding was developed in microscopic space and time with the boundary speed. Result: A validation study was conducted with vehicle-GPS trajectory big data and ground-truth vehicle crash data. As a result of the analysis, it turned out that the index of speeding-risk exposure has a strong explanatory power (R²=0.7) for motorway traffic accidents. This directly indicates that speeding behaviors should be analysed at a microscopic spatiotemporal dimension. Conclusion: The spatial and temporal evolution of vehicle velocity is very variable. It is, hence, expected that the method presented in this study could be efficaciously employed to analyse the causal factors of traffic accidents and the crash risk exposure in microscopic space using mobility trajectory data.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.849-856
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• 2020

Purpose: Greenhouse gases are one of the major causes of global warming, a global disaster. It aims to improve how effective the GHG reduction policy, which is the main cause of global warming in the transportation sector, has been effective on the highway and how to calculate GHG emissions. Method: Using the DSRC raw data, we estimate the emissions of Namhae Expressway (Yeongam-Suncheon) from 2017 to 2019 in two ways, a macro method (conventional) and a micro method (individual vehicle). Result: As a result of calculating the emission of the highway, the result was far exceeding the estimated emission, and it was found that when the calculation was performed for each vehicle, it was underestimated by more than 20%. Conclusion: If more emissions are continuously emitted than expected in the current transportation sector, additional emission reduction policies are needed to achieve the current greenhouse gas reduction targets. In addition, in the calculation of emissions, which is the basis of this policy, analysis was conducted for each individual vehicle using the current DSRC raw data, but using GPS afterwards will enable precise emission calculation through a more microscopic analysis.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.548-559
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• 2019

Purpose: Analysis method of V2I data driven motorway service area usage behavior to cope with manpower survey. Method: Segmentation of traveling state group and boundary using the distribution characteristics of traveling speed data of individual vehicles. Result: As a result of the verification, the use rate of resting places in lunchtime surged, and the boundary between the distribution status of the traffic speed data was clearly or unclear. Conclusion: The effect of the cost reduction is big because it can cope with the use of rest area survey by manpower and there is no limit in the time and space range of investigation. The dynamic utilization rate of each time sequence, such as a service area/drowsiness shelter/simple service area, with a V2I system, can be calculated. Identify illegal parking on highway section. Identify the unexpected situation in the road section. Identify the real-time service area utilization rate and congestion information.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.45-56
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• 2007

Automatic tracking of vehicles is important to accurately estimate the traffic information including vehicle speeds in video-based traffic measurement systems. Because of the limited field of view, the range of visual tracking with a single camera is restricted. In order to enlarge the tracking range for better chance of monitoring the vehicle behaviors, a tracking with consecutive multiple video sequences is necessary. This parer proposes a carefully designed rule-based vehicle racking scheme and apply it for the tracking for two well synchronized video sequences. In the scheme, almost all possible cases that can appear in the video-based vehicle tracking are considered to make rules. Also, the rule based scheme is augmented with Kalman filter. The result of tracking can be successfully used to collect data such as temporal variation of vehicle speed and behavior of individual vehicle behaviors in the enlarged tracking region.