• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.71-78
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• 2012

The digital tachograph is a device that automatically records speed and distance of a vehicle, together with the driver's activity and vehicle status at an accident. It records vehicle speed, break status, acceleration, engine RPM, longitude and latitude of GPS, accumulated distance, and so on. European Commission regulation made digital tachographs mandatory for all trucks from 2005. Republic of Korea made digital tachographs mandatory for all new business vehicles from 2011 and is widening the range of vehicles that must install digital tachographs year by year. This device is used to analyze driver's daily driving information and car accidents. Under a car accident that makes the device reliability unpredictable, it is very important to store driving information with maximum reliability for its original mission. We designed and implemented a practical digital tachograph. This paper presents a storage scheme that consists of a first storage device with small capacity at a high reliability and a second storage device with large capacity at a low cost in order to reliably records data with a hardware at a low cost. The first storage device records data in a SLC NAND flash memory in a log-structured style. We present a reverse partial scan that overcomes the slow scan time of log-structured storages at the boot stage. The scheme reduced the scan time of the first storage device by 1/50. In addition, our design includes a scheme that fast stores data at a moment of accident by 1/20 of data transfer time of a normal method.

• The Journal of Bigdata
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• v.4 no.2
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• pp.207-220
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• 2019

Recent developments in information and communication technology has enabled the deployment of sensor based data to provide real-time services. In Korea, The Korea Transportation Safety Authority is collecting driving information of all commercial vehicles through a fitted digital tachograph (DTG). This information gathered using DTG can be utilized in various ways in the field of transportation. Notably in autonomous driving, the real-time analysis of this information can be used to prevent or respond to dangerous driving behavior. However, there is a limit to processing a large amount of data at a level suitable for real-time services using a traditional database system. In particular, due to a such technical problem, the processing of large quantity of traffic big data for real-time commercial vehicle operation information analysis has never been attempted in Korea. In order to solve this problem, this study optimized the new database server system and confirmed that a real-time service is possible. It is expected that the constructed database system will be used to secure base data needed to establish digital twin and autonomous driving environments.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.47-56
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• 2022

The safe driving reward system aims to reduce the loss of life and property by reducing the occurrence of accidents by motivating safe driving and encouraging active participation by providing direct reward to vehicle drivers who have performed safe driving. In the case of the existing digital tachograph, the goal is to limit dangerous driving by recording the driving status of the vehicle whereas the safe driving reward system is a support measure to increase the effect of accident prevention and induces safe driving with financial reward when safe driving is performed. In other words, in an area where accidents due to speeding are high, direct reward is provided to motivate safe driving to prevent traffic accidents when safe driving instructions such as speed compliance, maintaining distance between vehicles, and driving in designated lanes are performed. Since these safe operation data and reward histories must be managed transparently and safely, the reward evidences and histories were constructed using the closed blockchain Hyperledger Fabric. However, while transparency and safety are guaranteed in the blockchain system, low data processing speed is a problem. In this study, the sequential block generation speed was as low as 10 TPS(transaction per second), and as a result of applying the acceleration function a high-performance network of 1,000 TPS or more was implemented.

• Transportation Technology and Policy
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• v.13 no.1
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• pp.31-36
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• 2016

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.55-66
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• 2020

This study developed four algorithms and their associated indices that can quantify and qualify road hazards along roadways. Initially, relevant raw data can be collected from commercial vehicles by camera and DTG. Well-processed data, such as potholes, road freezing, and fog, can be generated from the Integrated management system. Road hazard algorithms combine these data with road inventory data in the Data Sharing Platform. Depending on well-processed data, four different road hazard algorithms and their associated indices were developed. To test the algorithms, an experimental plan based on passive DTG attached in probe vehicles was performed at two different test locations. Selection of the test routes was based on historical data. Although there were limitations using random data for commercial vehicles, hazardous roadways sections, such as fog, road freezing, and potholes, were generated based on actual historical data. As a result, no algorithm error was found in the entire test. Because this study provides road hazard information according to a section, not a point, it can be practically helpful to road users as well as road agencies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.164-175
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• 2019

Installation of digital tachograph, black box, and ADAS have been enforced to commercial vehicles for preventing violent driving and accidents by the Traffic Safety Act in Korea. Nevertheless, the damage caused by road hazards has increased 1.5 times in 2016 compared to 2013. So, developing new technologies that can identify road hazard using the sensors installed in commercial vehicles are conducting by the Ministry of Land, Infrastructure and Transport. As a part of the technologies, this research analyze the error range of GPS installed in commercial vehicles that vary according to the driving speed. As a result, the average error was 9.72m at the driving speed of 100km/h, and the error was 2.1 times larger than the average error of 4.69m at the driving speed of 40km/h. The event point proper integration/separation range(m) was analyzed to be 20m with a recognition rate of 90% or more at the same point regardless of driving speed. The results of this research can be used as basic data for improving the accuracy of location-based data would be collected using commercial vehicles.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.103-109
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• 2012

Digital speedometer which is supposed to provide the basic data for analyzing human factors of drivers has a limitation for human behavior studies of drivers, because it records limited driving information including GPS velocities. Besides, Black Box, which is currently being actively commercialized in the market, records mostly vehicles' risky patterns rather than drivers' behaviors. As a result, it also shows a limit to analyze dangerous driving patterns. This study performed a risky driving study for human factor analysis. This study conducted before and after comparisons for real time warning study using a risky driving judgment device. The analysis was conducted based on Longitudinal acceleration, Lateral acceleration, and Yaw rate of vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.1-11
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• 2019

The accident of mass transit such as a bus could draw the large casualties and this induces social and economic losses. Recently, severe bus accidents caused by tiredness and inattention of bus drivers occurred and those lead to growing interest in bus accidents and the drivers' work environment. Therefore, this study analyzes the accident based on the work environment of bus drivers and route-bus categories. For the research, this study collected digital tachograph data and the bus company information for 271 domestic bus companies in 2017 and used ANOVA test and chi-square test as statistical methodologies. As a result, we figured out there are statistically significant differences in the accident according to the working environments. Especially, the present study confirmed the intracity bus with working every other day has the most frequent accidents. We expect that the results of this study be used as foundations for the improvement of working conditions to reduce route-bus accidents in the future.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.30-42
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• 2021

The amount of compensation and the number of cases owing to car damage from pot holes on highways across the country increased by about 4.2 times and 3.5 times, respectively, in 2019 compared to 2015. Due to the increase in damage caused by these road hazards, the Ministry of Land, Infrastructure and Transport is developing technologies and services that can collect road hazard information by using devices on commercial vehicles (DTGs, black boxes, ADASs). In preparation for the development of these technologies, this study conducted an integrated assessment of algorithms developed for interrupted-flow and uninterrupted-flow traffic under three scenarios in order to provide road hazard information to drivers and road managers. As a result, the overall accuracy of the integrated assessment was derived at 81.88%. Errors generated in this integrated assessment reflect only missing data in less than 1 minute, GPS coordinate location and algorithm related errors, taking into account the purpose and assumptions of the assessment. Among them, we derive an accuracy of 90.15%overall by calibrating GPS error data. The results of this study can be used as basic data for improving the accuracy of location-based information collected by commercial vehicles and for policy development.