• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.101-106
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• 2024

For the commercialization of automated vehicles, it is necessary to create various scenarios that can evaluate driving safety and establish a data system that can verify them. Depending on the vehicle's ODD (Operational Design Domain), there are numerous scenarios with various parameters indicating vehicle driving conditions, but no systematic methodology has been proposed to create and combine scenarios to test them. Therefore, projects are actively underway abroad to establish a scenario library for real-world testing or simulation of autonomous vehicles. However, since it is difficult to obtain data, research is being conducted based on simulations that simulate real road. Therefore, in this study, parameters calculated through individual vehicle trajectory data extracted based on roadside CCTV image-based driving environment DB was proposed through the extracted data. This study can be used as basic data for safety standards for scenarios representing various driving behaviors.

• Proceedings of the KOR-KST Conference
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• 2003.02a
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• pp.119-126
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• 2003

The aim of this research was to compare driver's workload among AHS (Automate Highway Systems) road sections in a virtual AHS environment that is based on a re Korean expressway in order to predict and compare the workloads imposed by the change (driver-vehicle interface and vehicle control authority. Road sections included the M (Manual Lane), TL1 (Transition Lane to enter the automated lane), AL (Automated Lane TL2 (Transition Lane to enter the manual lane after the end of automated driving), an post-AHS manual lane.

• Journal of Auto-vehicle Safety Association
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• v.9 no.1
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• pp.6-12
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• 2017

Regulation for the testing and operation of automated vehicles on public roadways has been recently developed all over the world. For example, the licensing standards and the evaluation technology for automated vehicles have been proposed in California, Nevada and EU. But specific safety evaluation scenarios for automated vehicles have not been proposed yet. This paper presents safety evaluation scenarios for extraordinary service permission of automated vehicles on highways. A total of seven scenarios are selected in consideration of safety priority and real traffic situation. Six scenarios are relevant with lane keeping and one scenario is relevant with lane change. All scenarios are developed based on existing ADAS evaluation scenarios and repeated simulation of automated vehicle algorithm. Safety evaluation factors as well as scenarios are developed. The safety factors are based on existing ADAS ISO requirements, ADAS safety factors and current traffic regulations. For the scenarios, a hunter vehicle is needed in addition to automated vehicle evaluated. The hunter vehicle performs multiple roles like preceding vehicle, cut-in vehicle and so on. The hunter vehicle is also automated vehicle equipped with high performance GPS, radar and Lidar. All the scenarios can be implemented by driving a lap on a KATRI ITS test track. These scenarios and safety evaluation factors are investigated via both a computer simulation and an experimental vehicle test on the test track. The experimental vehicle test was conducted with two automated vehicles, which are the evaluated vehicle and the hunter vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.108-114
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• 2015

Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.

• ETRI Journal
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• v.37 no.5
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• pp.1032-1043
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• 2015

ETRI's Co-Pilot project is aimed at the development of an automated vehicle that cooperates with a driver and interacts with other vehicles on the road while obeying traffic rules without collisions. This paper presents a core block within the Co-Pilot system; the block is named "Co-Pilot agent" and consists of several main modules, such as road map generation, decision-making, and trajectory generation. The road map generation builds road map data to provide enhanced and detailed map data. The decision-making, designed to serve situation assessment and behavior planning, evaluates a collision risk of traffic situations and determines maneuvers to follow a global path as well as to avoid collisions. The trajectory generation generates a trajectory to achieve the given maneuver by the decision-making module. The system is implemented in an open-source robot operating system to provide a reusable, hardware-independent software platform; it is then tested on a closed road with other vehicles in several scenarios similar to real road environments to verify that it works properly for cooperative driving with a driver and automated driving.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1399-1410
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• 2003

In this paper, we develop a joystick manual driving algorithm for an electric vehicle called Cycab. Cycab is developed as a public transportation vehicle, which can be driven either by a manual joystick or an automated driving mode. The vehicle uses six motors for driving four wheels, and front/rear steerings. Cycab utilizes one industrial PC with a real time Linux kernel and four Motorola MPC555 micro controllers, and a CAN network for the communication among the five processors. The developed algorithm consists of two automatic vehicle speed control algorithms for normal and emergency situations that override the driver's joystick command and an open loop torque distribution algorithm for the traction motors. In this study, the algorithm is developed using SynDEx, which is a system level CAD software dedicated to rapid prototyping and optimizing the implementation of real-time embedded applications on distributed architectures. The experimental results verify the usefulness of the two automatic vehicle control algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.306-306
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• 2000

This paper analyze the dynamic characteristics of Automated Guided Vehicle(AGV) which is being developed as a part of automation in port through DADS, one of the multi-dynamic analysis program, Previous evaluation of a vehicle is carried out through the continuous driving test of a real vehicle, however this method raise the loss of finance and time. If it is possible to analyze the dynamic characteristics of vehicle before construction completely we can compensate the loss of money and time during constructing. AGV contained containers is very heavy and its center of gravity can be easily changed with the disturbance from road or cornering. It makes AGV unsatisfied, therefore we evaluate the handling characteristics and stability of the full vehicle model. This paper contribute to establish the foundation of the development of a new system like a AGV which have a special structure.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.14-19
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• 2022

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which communicate with outsides of a vehicle not only in uni-directional way but also in bi-directional way. It is necessary to examine the electromagnetic immunity of vehicles equipped with those communication systems. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside electromagnetically. In this study, additional test environments were designed and tested and as a result they are shown to be effective to create test environments in an experimental chamber for electromagnetic immunity tests of vehicles equipped with communication systems.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.625-635
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• 2006

From a viewpoint of human factors, automated highway systems(AHS) can be defined as one of the newly developing human-machine systems that consist of humans(drivers and operators), machines(vehicles and facilities), and environments(roads and roadside environments). AHS will require a changed vehicle control process and driver-vehicle interface(DVI) comparing with conventional driving. This study introduces a fixed-based AHS simulator and provides questionnaire-based human factors evaluation results after three kinds of automated driving speed experiences in terms of road configuration, operation policies, information devices, and overall AHS use. In the simulator, the "shared space-at-grade" concept-based road configuration was virtually implemented on a portion of the Kyungbu highway in Korea, and heads-up display(HUD), AHS information display, and variable message signs(VMS) were installed for appropriate AHS DVI implementation. As the results, the subjects expressed positive opinions on the implemented road configuration, operation policies, and the overall use of AHS. The results of this study would be helpful in developing the road configuration and DVI design guideline as the basic human factors research for the future implementation of AHS.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.