• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.5
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• pp.308-321
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• 2024

The government aims to commercialize Level 4 autonomous buses and shuttles by 2025, expanding the demonstration of Level 3 autonomous buses on urban streets, where various factors affecting the driving conditions raise safety concerns. This study used actual driving data from autonomous buses in Pangyo to identify the disengagement locations and analyzed the static and dynamic road environment factors. The results showed that the disengagement of autonomous buses frequently occurs near intersections and bus stops, with those at the bus stops due primarily to operational procedures requiring driver intervention. Excluding these, the analysis identified crosswalks and driveways as static factors, whereas fog and rain are dynamic factors affecting disengagements. Based on these findings, recommendations were proposed to minimize disengagements, aiming to improve the operational safety of autonomous buses in Korea and address upcoming challenges.

• Journal of the Korean Society of Safety
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• v.10 no.4
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• pp.13-21
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• 1995

On mini-bus with diesel engine, at idle rpm for taking measurement to reduce gear rattle noise, was tested by the three clutch disc samples by turns, then measured the fluctuation of revolution of engine & transmission and parallel vibration of differential gear & transmission. By analyzing the measured data, the gear rattle noise, the matching design and tuning technic of transmission are comprehended and established. Conclusions of this test are as follows ; (1) Fluctuation of revolution on transmission is greatly affected by torsion of clutch disc according to fluctuation of engine revolution transmit to transmission through clutch system. Especially, gear rattle noise can be reduced by minimaizing the fluctuation of the revolution of transmission using pre-damper type clutch disc. (2) The reason of gear rattle noise is higher in summer than winter and driving longer period than initial driving is due to affection by drag torque changing. So, it is necessary for manufacturer to choose proper oil to transmission. (3) It can be occurred jumping and crash noise by applying the pre-damper type clutch disc for reducing the gear rattle noise. So, it is necessary to do test with actual vehicle according to test procedure.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.16-22
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• 2023

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.85-95
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle accidents explains 3.5 percent of the total number of traffic accidents of the year. Compared to other types of vehicles commercial vehicles may provide more serious damages to both driver himself and passengers. Thus, they generate more serious social and economic problems. There have been various forms of systems such as a digital speedometer or a black box to meet the social requirement for reducing traffic accidents and improving safe driving. However, since the current systems are based on the data often accidents happened, there are lots of limitations to control drivers in real-time. Also, the current speedometers provide drivers with only speeds of vehicles and RPM information regardless of actual dangerous drive behaviors. Therefor, they lack of the effectiveness in terms of safety. In this research, real-time information systems for improving driver safety based on automatic risky driving behaviors, and thresholds to determine risky driving patterns were studied.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.133-140
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• 2016

The Ministry of Land, Infrastructure and Transport has introduced low-floor buses, which are convenient for passengers getting on and off the bus and for the handicapped. The standard bus model is 11 m long and uses compressed natural gas (CNG). However, this model has drawbacks in narrow rural road conditions such as those in farming and fishing villages and mountainous areas, as well as difficulty in refueling since CNG facilities are not readily available. In this study, running resistance values were obtained by coasting performance tests on actual roads using a Tata Daewoo LF-40 model with three different weight conditions: curb vehicle weight (CVW), half vehicle weight (HVW), and gross vehicle weight (GVW).The test methods include WHVC, NIER-06, and constant-speed driving at 60 km/h. These tests were used to measure the fuel economy of vehicles other than the target vehicles to obtain the combined fuel economy. The energy efficiency was highest in the case of CVW. In the WHVC mode, the fuel consumption rates of HVW and GVW were typically 3.5% and 12% higher than that of CVW, respectively. In constant-speed driving, the fuel efficiency of HVW was higher than that of CVW. Further research is required to analyze the exhaust gas data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.1-15
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• 2016

This study aims to develop a model by which city bus drivers who are likely to cause an accident can be figured out based on the information about their actual driving records. For this purpose, from the information about the actual driving records of the drivers who have caused an accident and those who have not caused any, significance variables related to traffic accidents are drawn, and the accuracy between models is compared for the classification models developed, applying a discriminant analysis and logistic regression analysis. In addition, the developed models are applied to the data on other drivers' driving records to verify the accuracy of the models. As a result of developing a model for the classification of drivers who are likely to cause an accident, when deceleration ($X_{deceleration}$) and acceleration to the right ($Y_{right}$) are simultaneously in action, this variable was drawn as the optimal factor variable of the classification of drivers who had caused an accident, and the prediction model by discriminant analysis classified drivers who had caused an accident at a rate up to 62.8%, and the prediction model by logistic regression analysis could classify those who had caused an accident at a rate up to 76.7%. In addition, as a result of the verification of model predictive power of the models showed an accuracy rate of 84.1%.