• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.251-261
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• 2019

The importance of autonomous driving systems that utilize V2X services such as V2V(Vehicle to Vehicle) and V2I(Vehicle to Infrastructure) for safer and more comfortable driving is increasing with the recent development of autonomous vehicles. Partly autonomous vehicles based on environmental sensors have limitations for predicting and determining areas beyond the recognition distance of the mounted sensors and in response to atypical objects that are difficult to detect. Therefore, it is important to utilize the V2X service to improve the limit of sensor detection performance and to make driving safer and more comfortable. However, there may be an accident risk of autonomous vehicles due to incorrect information provided by V2X. Thus, the application of technology to prevent this needs to be considered. In this pater, we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to derive the risk sources of autonomous vehicles due to V2I malfunctions by using the communication between vehicles and infrastructure among V2X. We also developed ASIL ratings based on the simulations and real vehicle tests of the malfunctions of major cases of usnig V2I.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.67-85
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• 2018

Vehicle platooning through wireless communication and automated driving technology has become realized. Platooning is a technique in which several vehicles travel at regular intervals while maintaining a minimum safety distance. Truck platooning is of keen interest because it contributes to preventing truck crashes and reducing vehicle emissions, in addition to the increase in truck flow capacity. However, it should be noted that interactions between vehicle platoons and adjacent manually-driven vehicles (MV) significantly give an impact on the performance of traffic flow. In particular, when vehicles entering from on-ramp attempt to merge into the mainstream of freeway, proper interactions by adjusting platoon size and inter-platoon spacing are required to maximize traffic performance. This study developed a methodology for establishing operational strategies for truck platoonings on freeway on-ramp areas. Average speed and conflict rate were used as measure of effectiveness (MOE) to evaluate operational efficiency and safety. Microscopic traffic simulation experiments using VISSIM were conducted to evaluate the effectiveness of various platooning scenarios. A decision making process for selecting better platoon operations to satisfy operations and safety requirements was proposed. It was revealed that a platoon operating scenario with 50m inter-platoon spacing and the platoon consisting of 6 vehicles outperformed other scenarios. The proposed methodology would effectively support the realization of novel traffic management concepts in the era of automated driving environments.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.32-37
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• 2018

This paper proposes autonomous speed control strategy for an Electric Vehicle on urban road. SNU campus road is used to reperesent urban road situation. Motor efficiency of driving on campus circulation road can be improved by controlling velocity properly. Given information of campus road, especially slope of road, acceleration is selected from candidate, considering consumed power, human factor and driving time. To apply urban situation, preceding vehicle is also considered. With preceding vehicle, acceleration is defined according to clearance and relative velocity. Acceleration is bounded in normal range. Proposed acceleration control method is activated with proper velocity range for campus circulation road. With acceleration control, motor efficiency becomes better than driving with constant vehicle. To evaluate the performance of proposed acceleration controller, simulation study is conducted via MATLAB.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.20-25
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• 2022

This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole automated driving system consists of numerous modules and subdivisions of module occur, it is necessary to consider the characteristics, complexity, and limitations of each module. Furthermore, Light Detection And Ranging (Lidar) sensors require a considerable amount of time. In view of these limitations, division of submodule is inevitable to represent high real-time performance for stable system. This paper proposes ROI to reduce the number of data respect to computation time. ROI is set by a road's design speed and the corresponding ROI is applied differently to each vehicle considering its speed. The simulation model is constructed by ROS, and overall data analysis is conducted by Matlab. The algorithm is validated using real-time driving data in urban environment, and the result shows that ROI provides low computational costs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.62-73
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• 2022

As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.319-327
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• 2016

Purpose: Automated guidance systems (AGSs) for mobile farm machinery have several advantages over manual operation in the crop production industry. Many researchers and companies have tried to develop such a system. However, it is not easy to evaluate the performance of an AGS because there is no established device used to evaluate it that complies with the ISO 12188 standard. The objective of this study was to develop a tracking sensor system using five laser distance measurement sensors. Methods: One sensor-for long-range distance measurement-was used to measure travel distance and velocity. The other four sensors-for mid-range distance measurement-were used to measure lateral deviation. Stationary, manual driving, and A-B line tests were conducted, and the results were compared with the real-time kinematic differential global positioning system (RTK-DGPS) signal used by the AGS. Results: For the stationary test, the average error of the tracking sensor system was 1.99 mm, and the average error of the RTK-DGPS was 15.19 mm. For the two types of driving tests, the data trends were similar. A comparison of the changes in lateral deviation showed that the data stability of the developed tracking system was better. Conclusions: Although the tracking system was not capable of measuring long travel distances under strong sunlight illumination because of the long-range sensor's limitations, this dilemma could be overcome using a higher-performance sensor.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.50-57
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• 2023

Autonomous driving technologies have been gradually improved for road traffic owing to the development of artificial intelligence. Since the truck platooning is beneficial in terms of the associated transporting expenses, the Connected-Automated Vehicle technology is rapidly evolving. The structural performance is, however, rarely investigated to capture the effect of truck platooning on civil infrastructures.In this study, the dynamic behavior of bridges under truck platooning was investigated, and the amplification factor of responses was estimated considering several parameters associated with the driving conditions. Artificial intelligence techniques were used to estimate the maximum response of the mid span of a bridge as the platooning vehicles passing, and the importance of the parameters was evaluated. The most suitable algorithm was selected by evaluating the consistency of the estimated displacement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.147-163
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• 2023

Recently, there has been an increase in the research and development of automated vehicles worldwide. Research focused on automated vehicles in Korea is steadily progressing as a national R&D project. Since automated driving technology comprises diverse technology fields, it is necessary to identify the current position of the research. In this study, we propose a methodology for analyzing research trends using the NTIS data. In addition, we review the effectiveness of the currently developed research trend methodology by deriving primary keywords and major topics using the proposed method. We expect that the methodology developed in this study can be applied to identify and analyze future automated vehicle research trends.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.59-60
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• 2023

The automation of container terminals is an important factor that determines port competitiveness, and global advanced ports tend to strengthen their competitiveness through container terminal automation. The operational efficiency of the AGV, which is an essential transport equipment of the automated terminal, can improve the productivity of the automated terminal. The operation of AGVs in automated container terminals differs from that of conventional container terminals, as it is based on an automated system in which AGVs travel along designated paths and operate according to assigned tasks, requiring consideration of factors such as workload, congestion, and collisions. To prevent such problems and improve the efficiency of AGV operations, a more sophisticated model is necessary. Thus, this paper proposes an AGV scheduling model that takes into account the AGV travel path and task assignment within the terminal The model prevent the problem of deadlock and. various cases are generated by changing AGV algebra and number of tasks to create AGV driving situations and evaluate the proposed algorithm through algorithm and optimization analysis.