• International Journal of Highway Engineering
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• v.18 no.5
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• pp.63-73
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• 2016

PURPOSES : The objective of this study was to analyze variations in the vehicle driving behavior characteristics on signalized intersections according to the use of traffic enforcement camera (red light camera). METHODS : In order to analyze the driving behavior characteristics on signalized intersections when red light camera are installed, the target sites for investigation were selected depending on whether the red light camera is installed and accident rates increased after the installation. In particular, to analyze the characteristics of dilemma zones in signalized intersections, approach speed and deceleration speed of 3 type vehicles (passing vehicles during a yellow light, stopping at a yellow light, passing vehicles during a green light) were examined. Based on these data, the starting point, ending point, and distance of the dilemma zones were calculated. Also, the locations of increased traffic accidents and decreased accidents after the installation of the equipment were distinguished when analyzing the traffic accident characteristics. RESULTS : Analysis results revealed that there was a tendency for the dilemma zone distance to decrease after the installation of equipment(red light camera) in most sites. This tendency was found to be due to the decrease in the approaching speed of vehicles at intersections after the installation of equipment, resulting in the starting and ending points of dilemma zone to become closer to the stop line. Moreover, analysis showed that the number of traffic accidents decreased for most intersections after the installation of equipment and safety of the intersections increased somewhat. CONCLUSIONS : In general, installation of equipment(red light camera) caused the intersections approaching speed and dilemma zone distance to decrease. Decision-making is difficult for drivers in the dilemma zone, so the decrease in the dilemma zone distance implies an improvement in traffic safety. Furthermore, the number of accidents within intersections significantly decreased after the equipment was installed, leading to the conclusion that installation of the equipment affected the decrease in traffic accidents.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.115.5-115
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• 2002

In this paper, we introduce a system that detects all kinds of violations at a street intersection such as red light running, speed violation, stop line violation and lane violation by tracking individual vehicles. Two cameras are used for defecting violations. One is an analog camera for real-time tracking and the other is a digital camera for license plate reading. This system is connected to the traffic signal system controller and monitors the red, arrow, yellow and green phases of an approach. Two loops in the road are used to detect vehicle approach and speed. The system takes pictures of all vehicles passing a second loop and tracks the vehicles until they go out a street intersection...

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.29-42
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• 2016

Speeding is an important factor in traffic safety. Speed not only affects crash severity, but is also related to the possibility of crash occurrence. This study presents results from an analysis of 27,968 speed violation cases collected from 36 red light and speed enforcement cameras at signalized intersections in the city of Cheongju. Data included details of their violation history such as speeding tickets within a recent 3-year span and their demographic characteristics. The goal of this analysis is to understand the correlation between speed violations and various factors in terms of humans, vehicles and road environments. This study used descriptive statistics and Binary Logistics Regression(BLR) analysis with SPSS 20.0 software. The major results of this study are as follows. First, speed violations occurred at rural and suburban area. Second, about 25.6% of the violators committed to more than 20km/h over a speed limit. Third, the difference between speed violators and normal drivers clearly appeared in location of intersection(urban/rural/suburban area), gender and age. Finally, a statistically significant model(Hosmer and Lemeshow test: 11.586, p-value: 0.171) was developed through the BLR.