• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.391-398
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• 2019

In general, truck-involved crashes increase severity in terms of both injury level and crash impact level. Recently, although the frequency and fatality of truck-involved crashes in Korea are rising, their associative studies are very limited. Therefore, the objective of this study is to identify critical factors influencing on injury severity of truck-involved crashes on Korean freeway system. To carry out this objective, this study uses an ordered probit model (OPM) based on a 6-year crash dataset from 2012 to 2017. From the analysis, eight variables were found to have a great effect on injury severity: older driver, crash speed, rear-end collision, number of vehicles involved, drowsy driving, nighttime (0:00 to 6:00) driving, overturn or rollover, and vehicle's fire after crash. However, injury severity was less severe in crashes under snowy condition and crashes to traffic facilities (i.e., crash alone).

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.699-708
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• 2021

In this paper, a steering control and speed control algorithm was presented for autonomous driving based on two vision sensors and road speed sign board. A car speed control algorithm was developed to recognize the speed sign by using TensorFlow, a deep learning program provided by Google to the road speed sign image provided from vision sensor B, and then let the car follows the recognized speed. At the same time, a steering angle control algorithm that detects lanes by analyzing road images transmitted from vision sensor A in real time, calculates steering angles, controls the front axle through PWM control, and allows the vehicle to track the lane. To verify the effectiveness of the proposed algorithm's steering and speed control algorithms, a car's prototype based on the Python language, Raspberry Pi and OpenCV was made. In addition, accuracy could be confirmed by verifying various scenarios related to steering and speed control on the test produced track.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.781-789
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• 2021

In this paper, we quantitatively analyzed the required UAV(Unmanned Aerial Vehicle) failure rate of small UAV (≤25kg) based on the harm to human caused by UAV crash to fly over the populated area. We compute the number of harm to human when UAV falls to the ground at certain descent point by using population density, car traffic, building to land ratio, number of floors of building data of urban area and UAV descent trajectory modeling. Based on this, the maximum allowable UAV failure rate is calculated to satisfy the Target Level of Safety(TLS) for each UAV descent point. Then we can generate the failure rate requirement in the form of map. Finally, we divide UAV failure rate into few categories and analyze the possible flight area for each failure rate categories. Considering the Youngwol area, it is analyzed that the UAV failure rate of at least 10^-4 (failure/flight hour) is required to access the residential area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.83-89
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• 2021

To improve the performance of self-driving cars, the introduction of V2X, a communication technology that connects vehicles, infrastructure, and vehicles, is essential. Even if traffic information of the other vehicle is known, the structure of the intersection and a distance calculation algorithm are required for accurate calculations at roundabouts. This paper proposes a design algorithm for a rotating intersection and implemented in Matlab that complies with the national design rules and enables accurate calculations. Assuming the roundabout and the entrance/exit path to be a circle, a method for measuring the distance between vehicles at an arbitrary point was proposed using the horizontal shift of the entrance circle to the main circle. The algorithm could be used in fully autonomous vehicles by designing a roundabout suitable for the terrain by arbitrarily varying the angle between branches and the radius of curvature of the entrance and exit roads, and transmitting a warning signal when a collision between two driving vehicles is expected.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.29-39
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• 2021

As a means of solving traffic congestion in the downtown of large city, the interest in urban air mobility (UAM) using electric vertical take-off landing personal aerial vehicle (eVTOL PAV) is increasing. eVTOL configurations that will be used for UAM are classified by lift-and-cruise, tilt rotors, tilt-wings, tilted-ducted fans, multicopters, depending on propulsion types. This study tries to perform preliminary conceptual design for a given mission profile using reverse engineering techniques by taking the multicopter type Airbus's CityAirbus as a basic model. Wetted area, lift to drag ratio, drag coefficients were calculated using the OpenVSP which is an aerodynamic analysis software. The power required for each mission section of CityAirbus were calculated, and the corresponding battery and motor were selected. Also, total weight was predicted by estimating component weights of eVTOL.

• Journal of Environmental Science International
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• v.31 no.4
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• pp.329-339
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• 2022

Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22^nd December, 2020 and 29^th January, and 25^th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

• Smart Structures and Systems
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• v.30 no.6
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• pp.661-671
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• 2022

Stayed cables are the key components for transmitting loads in cable-stayed bridges. Therefore, it is very important to evaluate the cable force condition to ensure bridge safety. An online condition assessment and anomaly localization method is proposed for cables based on the spatiotemporal correlation of grouped cable forces. First, an anomaly sensitive feature index is obtained based on the distribution characteristics of grouped cable forces. Second, an adaptive anomaly detection method based on the k-nearest neighbor rule is used to perform dissimilarity measurements on the extracted feature index, and such a method can effectively remove the interference of environment factors and vehicle loads on online condition assessment of the grouped cable forces. Furthermore, an online anomaly isolation and localization method for stay cables is established, and the complete decomposition contributions method is used to decompose the feature matrix of the grouped cable forces and build an anomaly isolation index. Finally, case studies were carried out to validate the proposed method using an in-service cable-stayed bridge equipped with a structural health monitoring system. The results show that the proposed approach is sensitive to the abnormal distribution of grouped cable forces and is robust to the influence of interference factors. In addition, the proposed approach can also localize the cables with abnormal cable forces online, which can be successfully applied to the field monitoring of cables for cable-stayed bridges.

• Smart Structures and Systems
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• v.29 no.1
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• pp.167-179
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• 2022

This article develops a long-term condition assessment method for stay cables in cable stayed bridges using the monitored cable tension forces under operational condition. Based on the concept of influence surface, the matched cable tension ratio of two cables located at the same side (either in the upstream side or downstream side) is theoretically proven to be related to the condition of stay cables and independent of the positions of vehicles on the bridge. A sensor grouping scheme is designed to ensure that reliable damage detection result can be obtained even when sensor fault occurs in the neighbor of the damaged cable. Cable forces measured from an in-service cable-stayed bridge in China are used to demonstrate the accuracy and effectiveness of the proposed method. Damage detection results show that the proposed approach is sensitive to the rupture of wire damage in a specific cable and is robust to environmental effects, measurement noise, sensor fault and different traffic patterns. Using the damage sensitive feature in the proposed approach, the metrics such as accuracy, precision, recall and F1 score, which are used to evaluate the performance of damage detection, are 97.97%, 95.08%, 100% and 97.48%, respectively. These results indicate that the proposed approach can reliably detect the damage in stay cables. In addition, the proposed approach is efficient and promising with applications to the field monitoring of cables in cable-stayed bridges.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.233-252
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• 2022

Recently, various studies have been conducted to improve automated vehicle (AV) safety for AVs commercialization. In particular, the scenario method is directly related to essential safety assessments. However, the existing scenario do not have objectivity and explanability due to lack of data and experts' interventions. Therefore, this paper presents the AVs safety assessment extended scenario using real traffic accident data and vision transformer (ViT), which is explainable artificial intelligence (XAI). The optimal ViT showed 94% accuracy, and the scenario was presented with Attention Map. This work provides a new framework for an AVs safety assessment method to alleviate the lack of existing scenarios.