• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.186-201
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• 2021

As autonomous driving technology advances, the accuracy of the vehicle position is important for recognizing the environments around driving. Map-matching localization techniques based on high definition (HD) maps have been studied to improve localization accuracy. Because conventional map-matching techniques estimate the vehicle position based on an HD map reference dataset representing the center of the lane, the estimated position does not reflect the deviation of the lateral distance within the lane. Therefore, this paper proposes a localization system based on the reference lateral position dataset extracted using image processing and HD maps. Image processing extracts the driving lane number using inverse perspective mapping, multi-lane detection, and yellow central lane detection. The lane departure method estimates the lateral distance within the lane. To collect the lateral position reference dataset, this approach involves two processes: (i) the link and lane node is extracted based on the lane number obtained from image processing and position from GNSS/INS, and (ii) the lateral position is matched with the extracted link and lane node. Finally, the vehicle position is estimated by matching the GNSS/INS local trajectory and the reference lateral position dataset. The performance of the proposed method was evaluated by experiments carried out on a highway environment. It was confirmed that the proposed method improves accuracy by about 1.0m compared to GNSS / INS, and improves accuracy by about 0.04m~0.21m (7~30%) for each section when compared with the existing lane-level map matching method.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.2
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• pp.25-31
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• 2019

As artificial intelligence technology has been developed rapidly, many researchers who are interested in next-generation vehicles have been studying on applying the artificial intelligence technology to advanced driver assistance systems (ADAS). In this paper, a method of applying deep learning algorithm to the lane departure warning system which is one of the main components of the ADAS was proposed. The performance of the proposed method was evaluated by taking a comparative experiments with the existing algorithm which is based on the line detection using image processing techniques. The experiments were carried out for two different driving situations with image databases for driving on a highway and on the urban streets. The experimental results showed that the proposed system has higher accuracy and precision than the existing method under both situations.

• Journal of Auto-vehicle Safety Association
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• v.6 no.2
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• pp.23-28
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• 2014

Commercial vehicle ESC assessment for curvature road was conducted. The previous study of ESC activation condition for losing controllability utilizing the test protocols of double lane change and sine with dwell method was conducted without considering the geometric complexity of roadway design. Since critical rollover accidents were frequently observed in the exit ramp zone, variety of curve, slope and bank have been added for analysis conditions. Detailed feature of the ramp including location, dimension and design characteristics have been analyzed from the typical trumpet type ramp design. Analyzing accident data from 2008, two specific ramps have been selected due to their complexity in design and severity in steering operation.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.87-96
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• 2008

Wandering, variation of wheel tracks, has not been considered as an important factor for pavement designs and maintenance due to measuring difficulties. In order to investigate vehicle lateral displacements on roadways, this study measured wheel tracks on two-lane and four-lane National highways with lane widths 3.25m and 3.5m. The results showed that the tracks of left and right wheels were distributed into different forms, and those of left wheels were more concentrated. In the mean of the left distributions, 59.5cm and 80.7cm were obtained on lane widths 3.25m and 3.5m respectively by cars, and 58.4cm and 73.6cm were obtained by trucks. These mean differences seem to be generated from those between the lane widths. It is recommended to apply the distribution of left wheel tracks for pavement designs.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.195-202
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• 2011

The purpose of this study is to estimate the capacity of two-lane freeway work zone blocking one lane using traffic flow models of each vehicle-type. Firstly, three traffic flow models of three different vehicle-types were developed using the data collected from each at the beginning and the ending point of the work zone. For each model, the maximum flow rate of three vehicle-types were calculated respectively. Maximum flow rate at the work zone was recalculated using passenger car equivalent value and percentage of vehicle-type. Secondly, traffic flow model using passenger car equivalent volume data was developed using the data collected from each at the beginning and the ending point of the work zone. Maximum flow rate for the work zone was calculated along. Two values of maximum flow rates through the work zone were compared and evaluated as the capacity of the work zone. This study found that the maximum flow rate of the work zone at the beginning point was less than that at the ending point because of impedance such as lane changing behaviors before entering the work zone. The capacity of two-lane freeway work zone blocking one lane was estimated 1,800pcphpl.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.121-130
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• 2002

Purpose of this paper is proposing technical evaluation method for safety on two-lane rural highways, this method can contribute to an establishment of the safety evaluation criteria and eventually contribute to the highway safety. In this study, accident data and field data(grade, radius, speed factor) are collected and are analyzed. And new technical evaluation method is proposed by problem in review of existent methods and analysis result. Property of new method is verified by comparing with existent one. Following are results of this study. 1) Proposed technical evaluation method is Proposed by using difference of speed variance and difference of acceleration. 2) In range of field survey, proposed method is more proper than existent one by comparing. 3) Headways under 6 second affect speed of next vehicle. 4) A point with the lowest speed in curve is placed about 35m from the beginning point. 5) Correlation of speed variance and severity of highway(EPDO) is statistically significant. For using proposed method, more tests are needed on other locations with various geometries. Moreover, advanced study is needed about classifying and giving the weight of each criterion.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.493-504
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• 2007

This paper proposes a stereo vision-based forward obstacle detection and distance measurement method. In general, stereo vision-based obstacle detection methods in automotive applications can be classified into two categories: IPM (Inverse Perspective Mapping)-based and disparity histogram-based. The existing disparity histogram-based method was developed for stop-and-go applications. The proposed method extends the scope of the disparity histogram-based method to highway applications by 1) replacing the fixed rectangular ROI (Region Of Interest) with the traveling lane-based ROI, and 2) replacing the peak detection with a constant threshold with peak detection using the threshold-line and peakness evaluation. In order to increase the true positive rate while decreasing the false positive rate, multiple candidate peaks were generated and then verified by the edge feature correlation method. By testing the proposed method with images captured on the highway, it was shown that the proposed method was able to overcome problems in previous implementations while being applied successfully to highway collision warning/avoidance conditions, In addition, comparisons with laser radar showed that vision sensors with a wider FOV (Field Of View) provided faster responses to cutting-in vehicles. Finally, we integrated the proposed method into a longitudinal collision avoidance system. Experimental results showed that activated braking by risk assessment using the state of the ego-vehicle and measuring the distance to upcoming obstacles could successfully prevent collisions.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.67-73
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• 1990

Many distress mechanisms in pavement are known to be caused by the poor mechanical properties of bituminous concretes. Among many mechanical properties, tensile strength is one of the more important indicates that represent the resistance of pavement to traffic loading. However, there has been no relationship established between the strength and distress mechanisms. Therefore, this study was conducted to evaluate a correlation between the tensile strength value and the intensity of distress in bituminous concrete. Distress data were collected from an extensive field investigation over 77km of a four-lane highway in South Carolina, USA, and from laboratory prepared specimens in two phases of study. Strength data were obtained from a total of more than 400 field cores taken from the same highway and from 640marshall specimens of surface course mixture prepared in the laboratory. These data were analyzed using statistical test techniques. It was found from statistical analyses that the tensile strength of bituminous concrete had a strong relation with the pavement condition in the field. In the analysis of rutting and stripping, low strength concrete showed a higher distress rate in the mixture, and mixtures under distress in the field showed obviously reduced strength values. Stripping was found to be the most significant distress mechanism that was correlated with low strength bituminous concrete. Rutting appeared more frequently in a low strength pavement section of the highway as a sign of failure due to traffic loading.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.131-143
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• 2010

This study has aimed to develop accident modification factor(AMF) for rural two-lane roadway segments. Accident Modification Factor is a coefficient to assess roadway safety as reflecting characteristics of homogeneous roadway. It estimates accident frequency of roadway segments with developed base model and exposure. We found on items of such factors as crosswalk, driveway density, topography characteristic, land use and median through statistical models and literature review. To develop accident modification factors, we used statistical model methods and analyses of applicability and expert judgement method were practiced to validate it. Although expert judgement for land use item was questionable, most items were rated acceptable. Result of comparative analysis revealed crash frequencies of IHSDM and KHSEM were most similar with actual. However, accident distribution of KHSEM was more proper than IHSDM. Also overall estimated values of RSDS were found to be overestimated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.42-54
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• 2018

This study is to establish the traffic volume-based warrants of left-turn lanes in unsignalized intersections based on a risk probability methodology. This study applied a risk probability of a potential rear-end collision between a left-turn vehicle and the immediately following through vehicle. With the shifted negative exponential model and the compound probability theorem, the risk probability can be expressed as the function of directional volumes, opposing volumes and the percentage of left-turns for a two-lane and four-land highway, respectively. The warrants of installing left-turn lanes on unsignalized intersections were developed with the risk probability. The warrants define the total approaching and opposing volumes to encourage a left-turn lane as a function of operating speed, percentage of left-turn, and number of lanes.