PURPOSES : This study aimed to compare the object detection performance based on various analysis methods using point-cloud data collected from LiDAR sensors with the goal of contributing to safer road environments. The findings of this study provide essential information that enables automated vehicles to accurately perceive their surroundings and effectively avoid potential hazards. Furthermore, they serve as a foundation for LiDAR sensor application to traffic monitoring, thereby enabling the collection and analysis of real-time traffic data in road environments. METHODS : Object detection was performed using models based on different point-cloud processing methods using the KITTI dataset, which consists of real-world driving environment data. The models included PointPillars for the voxel-based approach, PartA2-Net for the point-based approach, and PV-RCNN for the point+voxel-based approach. The performance of each model was compared using the mean average precision (mAP) metric. RESULTS : While all models exhibited a strong performance, PV-RCNN achieved the highest performance across easy, moderate, and hard difficulty levels. PV-RCNN outperformed the other models in bounding box (Bbox), bird’s eye view (BEV), and 3D object detection tasks. These results highlight PV-RCNN's ability to maintain a high performance across diverse driving environments by combining the efficiency of the voxel-based method with the precision of the point-based method. These findings provide foundational insights not only for automated vehicles but also for traffic detection, enabling the accurate detection of various objects in complex road environments. In urban settings, models such as PV-RCNN may be more suitable, whereas in situations requiring real-time processing efficiency, the voxelbased PointPillars model could be advantageous. These findings offer important insights into the model that is best suited for specific scenarios. CONCLUSIONS : The findings of this study aid enhance the safety and reliability of automated driving systems by enabling vehicles to perceive their surroundings accurately and avoid potential hazards at an early stage. Furthermore, the use of LiDAR sensors for traffic monitoring is expected to optimize traffic flow by collecting and analyzing real-time traffic data from road environments.

PURPOSES : This study aims to calculate the estimation of travel time saving benefits from smart expressway construction by considering the willingness to pay for automated vehicles. METHODS : In this study, data were collected from 809 individual drivers through a stated preference survey. A multinomial logit model was constructed to analyze the choice behavior between arterial roads, expressways, and smart expressways. Through this, the values of time and benefits were estimated. RESULTS : The value of time was calculated at 19,379 won per vehicle per hour for arterial roads and expressways and 23,061 won per vehicle per hour for smart expressways. Applying these values to the Jungbu Naeryuk expressway, we evaluated the demand change and benefits resulting from the improvement to the smart expressways. The results show that the traffic volume on the Jungbu Naeryuk expressway is expected to increase by 4.7% to 20.7% depending on the changes in capacity. CONCLUSIONS : The travel time saving benefits are estimated as positive, resulting from the construction of smart expressways. The benefits resulting from the construction of new smart expressways are expected to be enhanced due to the anticipation of more significant time-saving effects.

본 연구에서는 운전 시뮬레이션을 사용하여 자율주행 환경을 구현한 후 3-수준 자율주행 조건에서 자율주행 차량 (automated vehicle: AV)으로부터 운전자에게 전달되는 제어권 인수 요구(takeover request: TOR) 정보의 양상(시각, 청각 및 시각+청각) 및 도로 형태(직선도로와 곡선도로)에 따라 운전자의 제어권 인수 시간(takeover time: TOT) 및 정신적 작업부하(제어권 인수 이후에 운전자들이 경험한 주관적 작업부하와 심장박동수에서의 변화)가 어떻게 차별 화되는지 분석하였다. 본 연구의 결과를 요약하면 다음과 같다. 먼저, AV로부터 TOR이 제시된 이후 실험참가자들 이 보인 TOT에 대한 분석 결과, TOR 정보양상의 측면에서는 시각 정보가 가장 빠른 TOT를 이끌어 낸 반면 청각 정보 조건에서 가장 느렸고, 도로 형태 측면에서는 직선도로 조건에 비해 곡선도로 조건에서의 TOT가 유의하게 더 느렸으며, 특히 청각 정보 조건에서 도로 형태에 따른 TOT에서의 차이가 가장 컸다. 둘째, 정신적 작업부하에 대한 분석 결과, TOR 정보가 시각 혹은 시각+청각적으로 제시된 조건에 비해 청각적으로 제시된 조건에서 주관적 작업부 하 측정치와 심장박동수 변화 크기 모두 전반적으로 더 낮았고 특히, 심장박동수 변화의 경우 이러한 경향은 곡선도 로 조건에서만 관찰되었다. 이러한 결과는 TOR 정보의 양상과 도로 형태에 따라 운전자의 TOT와 정신적 작업부하 수준이 달라질 수 있고, 특히 TOT가 빠를수록 정신적 작업부하 수준은 상대적으로 더 높아질 수 있음을 시사한다.

PURPOSES : This study aims to develop a congestion mitigation strategy at lane drop bottleneck with low Connected and Automated Vehicle (CAV) penetration. METHODS : The proposed strategy is designed to assign a role of a moving bottleneck to CAVs to reduce low-speed lane changes at bottleneck locations, which are the main cause of bottleneck capacity drop. Through this, it aims to induce proactive upstream lane changes for Human-Driven Vehicles (HDVs,). Therefore, this study includes the control algorithm for CAVs, and the evaluation of the strategy assumes penetration rates of 5% and 10% in a Microsimulation VISSIM environment. The assessment is conducted by comparing the capacity drop and total travel time. Additionally, a sensitivity test for the parameter of the CAV control algorithm, reduced speed, is performed to find the optimal parameter. RESULTS : In this study, three scenarios, a) Base, b) CAV with no control, and c) CAV with control, are designed to evaluate the effects of the CAV control strategy. Analysis of segment density and lane change distribution reveals that the control strategy effectively prevented vehicle congestion due to the bottleneck effect. Additionally, the analysis of capacity changes before and after the bottleneck and total travel time shows the effectiveness of the control strategy. The sensitivity test on CAV control speed emphasized the importance of selecting an appropriate speed for maintaining efficient traffic flow. Lastly, as the CAV penetration rate increased, the control strategy exhibited greater effectiveness in mitigating capacity drop. CONCLUSIONS : The proposed strategy is intended for use at low CAV penetration rates and is expected to provide assistance in mitigating congestion at bottlenecks during the early stages of CAV commercialization. Furthermore, since the role of CAV in the strategy can be performed by CVs or even HDVs, it can be applied not only immediately but also in the near future.

Automated Guided Vehicle (AGV) is commonly used in manufacturing plant, warehouse, distribution center, and terminal. AGV is self-driven vehicle used to transport material between workstations in the shop floor without the help of an operator, and AGV includes a material transfer system located on the top and driving system at the bottom to move the vehicle as desired. For navigation, AGV mostly uses lane paths, signal paths or signal beacons. Various predominant sensors are also used in the AGV. However, in the conventional AGV, there is a problem of not turning or damaging nearby objects or AGV in a narrow space. In this paper, a new driving system is proposed to move the vehicle in a narrow space. In the proposed driving system, two sets of the combined steering-drive unit are adopted to solve the above problem. A prototype of AGV with the new driving system is developed for the comparative analysis with the conventional AGV. In addition, the experimental result shows the improved performance of the new driving system in the maximum speed, braking distance and positioning precision tests.

As interest in automated vehicles increases, there is a need for automated vehicles and traffic management for them in transportation field is being raised, and related researches are being actively carried out. Traffic management for automated vehicles can be divided into longitudinal and lateral directions as in existing traffic management, but traffic management detailed strategies can be different for each direction. In this study, automated vehicles are applied to the variable speed limit, which is one of the longitudinal traffic management techniques, and the possibility of using automated vehicles in the variable speed limiting system is examined. Manual vehicles can receive traffic information by VMS, while V2X is used for automated vehicles. Therefore, various traffic information including speed limit information can be received from the road infrastructure ahead of manual vehicles. Simulation of how such a vehicle-infrastructure cooperation system can be utilized in a variable speed limit system is conducted and analyzed by market penetration rate (MPR) of automated vehicles. It is expected that the variable speed limit system of automated vehicles utilization, which is invetigated in this study, will be utilized for transportation management in the automated vehicles future.

PURPOSES : This study is to develop a automate road mapping system using ARASEO(Automated Road Analysis and Safety Evaluation TOol) for road management. METHODS: The road survey van named ARASEO(Automated Road Analysis and Safety Evaluation TOol) was used to generate highway drawings for Korea National Road number 37 automatically. In order to generate the highway drawings for purpose of road management, it is required to acquired the information for highway alignment, road width and road facilities such as safety barrier and road sign. Therefore the survey van acquired and analyzed the road width, median and guardrail data using rear side laser sensor of ARASEO and recognized the traffic control sign and chevron sign using foreside camera images. Also the highway alignment which is the basic information for highway drawing can be analyzed by acquisition the every 1m positional and attitude data using GPU and IMU sensor and developed algorithm. Finally, in this research the CAD based drawing software was developed to draw highway drawing using the analysis result from ARASEO. RESULTS : This study showed the comparison result of the surveyed road width and drawing data. To make the drawing of the road, we made the Autocad ARX program witch run in CAD menu interface. CONCLUSIONS : Using this program we can create the road center line, every 500m horizontal and vertical ground plan drawing automatically.

The conventional shifting map is developed to enhance the driving performance and fuel economy. According to the driver’s pedaling of accelerator, TCU controls gear ratio in view point of economy or driving performance. In this paper, various reverse engineering is applied to the driving test results of heavy duty AMT vehicle. With the test results, the performance of propulsion source is estimated and basic performance of vehicle is analized. Also the method to derive the shifting schedule according to power or fuel efficient, is developed and compared with the actual shifting map, and various shifting states is estimated. The developed numerical analysis model will be a stepping stone for the shift pattern development and various shift control research

This paper is to analyze the travel distance and the transport size of the vehicle when the AGV carries multiple-load in the tandem automated guided vehicle systems. The size of multiple-load represents the number of load that the AGV can carry simultaneo

Modem automated manufacturing processes employ automated guided vehicles(AGVs) for material handing, which serve several machining centers(MCs) in a factory. Optimal scheduling of AGVs can significantly help to increase the efficiency of the manufacturing

Modern automated manufacturing processes employ automated guided vehicles(AGVs) for material handling, which serve several machining centers(MCs) in a factory. Optimal scheduling of AGVs can significantly help to increase the efficiency of the manufacturing process by minimizing the idle time of MCs waiting for the raw materials. In this paper, we will analyse the requirements for an optimal schedule and then provide a mathematical framework for an efficient schedule of material delivery by an AGV. With this model, the optimal number of MCs to be utilized will also be determined. Finally, the material delivery schedule employing multiple journeys to the MCs by the AGV will be carried out. Through rigorous analysis and simulation experiments, we shall show that such a delivery strategy will optimize the overall performance.

본 연구는 운전자가 자율주행자동차로부터 신뢰감을 형성할 수 있는 인터페이스 디자인 구성요소의 추출에 그 목적이 있 다. 또한 추출된 디자인 구성요소의 지각이 밀레니엄 세대와 뉴 실버 세대 간의 차이를 평가하였다. 자율주행자동차의 신뢰 감을 2차 구성개념으로 정의하여 심성모형과 전문가/전문지식, 공통목적, 교육, 의인화, 피드백, 인과관계 정보, 그리고 에러 정보를 포함하는 8개의 1차 구성개념을 추출하였다. 이해타당도를 평가하기 위하여 설문조사 데이터(N=548)에 대한 확인적 요인분석을 수행하였다. 평가결과, 심성모형과 전문지식, 공통목적, 의인화, 피드백, 인과관계/에러 정보를 포함하는 6개의 1차 구성개념은 2차 구성개념인 신뢰감을 설명할 수 있는 것으로 조사되었다. 다중집단분석 결과, 뉴 실버세대에게는 의인화와 인과관계/에러정보가 밀레니엄 세대와 비교하여 신뢰감 형성에 보다 큰 기여를 하는 것으로 평가되었다. 이와는 반면에, 밀레니엄 세대에게는 심성모형과 전문지식, 공통목적, 그리고 피드백이 신뢰감 형성에 보다 높은 영향을 미치는 것으로 나타났다.