• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.5
• /
• pp.203-208
• /
• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.5
• /
• pp.216-223
• /
• 2023

As the technology and level of autonomous vehicles advance and they drive in more diverse road environments, an intuitive and efficient interaction system is needed to resolve and respond to the situations the vehicle faces. The development of driving technology from the perspective of autonomous driving has the ultimate goal of responding to situations involving humans or more. In particular, in complex road environments where mutual concessions must be made, the role of a system that can respond flexibly through efficient communication methods to understand each other's situation between vehicles or between pedestrians and vehicles is important. In order to resolve the status of the vehicle or the situation being faced, the provision and method of information must be intuitive and the efficient operation of an autonomous vehicle through interaction with intention is required. In this paper, we explain the vehicle structure and functions that can display information about the situation in which the autonomous vehicle driving in a living lab can drive stably and efficiently in a diverse and complex environment.

• Phonetics and Speech Sciences
• /
• v.5 no.2
• /
• pp.93-97
• /
• 2013

This paper is on designing an indoor driving simulator to evaluate the performance of in-car speech recognizer when influenced by the elements, which lower the success rate of speech recognition. The proposed simulator simulates vehicle noise which was pre-recorded in diverse driving environments and driver's speech. Additionally, the proposed Lombard effect conversion module in this simulator enables the speech recorded in a studio environment to convert into various possible driving scenarios. The relevant experimental results have confirmed that the proposed simulator is a feasible approach for realizing an effective method as it achieved similar speech recognition results to the real driving environment.

• International Journal of Precision Engineering and Manufacturing
• /
• v.8 no.3
• /
• pp.3-7
• /
• 2007

There have been numerous studies directed toward the development of driving mechanisms for off-road mobility and rescue robots. To achieve surveillance, reconnaissance, and rescue, it is necessary for robots to have a driving mechanism that can handle off-road environments, We propose a new type of single-track driving mechanism with a variable geometry for a rescue robot, This mechanism has a symmetric configuration so that the robot can advance in two directions and also remain operable when overturned. By transforming its geometry, the robot can reduce energy consumption in steering and rotating as well as maximize its ability to climb obstacles such as stairs. The robot is also designed to have a compact size and low center of gravity to facilitate driving when on a set of stairs. In this paper, we analyzed the design parameters of the robot for the four phases of climbing stairs and determined the specifications needed to enhance its adaptability.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.17 no.4
• /
• pp.31-42
• /
• 2021

In the modern era, radio wave analysis is necessary for various fields of engineering, and interpretation of this is also indispensable. Self-driving cars need multiple different electronic components, and thus accurate and fast electromagnetic simulator for this kind of complex radio environment is required for self-driving simulations. Accordingly, the demand for self-driving simulators as well as existing electromagnetic analysis software has increased. This paper briefly describes the characteristics of numerical analysis techniques for electromagnetic analysis, self-driving simulation software, and conventional electromagnetic simulation software and also summarizes the characteristics of each software. Finally, the verification of the result from in-house code compared to HFSS is demonstrated.

• ETRI Journal
• /
• v.43 no.4
• /
• pp.603-616
• /
• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

• Journal of Drive and Control
• /
• v.19 no.4
• /
• pp.110-116
• /
• 2022

Recently, various studies have been conducted to apply deep learning and AI to various fields of autonomous driving, such as recognition, sensor processing, decision-making, and control. This paper proposes a controller applicable to path following, static obstacle avoidance, and pedestrian avoidance situations by utilizing reinforcement learning in autonomous vehicles. For repetitive driving simulation, a reinforcement learning environment was constructed using virtual environments. After learning path following scenarios, we compared control performance with Pure-Pursuit controllers and Stanley controllers, which are widely used due to their good performance and simplicity. Based on the test case of the KNCAP test and assessment protocol, autonomous emergency steering scenarios and autonomous emergency braking scenarios were created and used for learning. Experimental results from zero collisions demonstrated that the reinforcement learning controller was successful in the stationary obstacle avoidance scenario and pedestrian collision scenario under a given condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.1
• /
• pp.35-45
• /
• 2014

The driving environment of the vehicle has characteristics that the change of position, velocity and distance between vehicles is severe. The performance test of system must be carried out in the real road environments with consideration of the driving environment of vehicles to measure the performance correctly because the performance of vehicular communication systems is affected by the driving conditions of the vehicle. In this paper, we propose the test methods of V2V/V2I performance and V2V multi-hop transmission function and present the test results measured by the vehicular communication systems already developed. In the test result, we confirmed the fact that the distance of communication devices and the driving direction of vehicle are affecting the communication performance. We also confirmed the multi-hop transmission function using the driving vehicle in the limited area as the proposed test method.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.7
• /
• pp.153-161
• /
• 2015

In the present study, as part of the technology development (Quality of Life Technology, QoLT) to improve the socio-economic status of people with disabilities as an extension of these studies, we propose the development of the smart wheelchair system and navigation technology for stable and safe driving in various environments. For the disabled and the elderly make driving easy and convenient with manual/autonomous driving condition, we firstly develop the user-oriented smart wheelchair system with optimized sensors for environment recognition, and then we propose a navigation framework of a hierarchical structure to ensure real-time response, as well as driving stability when traveling to various environmental changes, and to enable a more efficient operation. From the result of several independent experiments, we ensure efficiency and safety of smart wheelchair and its navigation system.

• Korean Journal of Culture and Social Issue
• /
• v.8 no.1
• /
• pp.17-40
• /
• 2002

The purpose of this study is to investigate the differences in the traffic environments and driving behaviors in 5 regions of Korea. Data were collected through the survey research from 1387 passenger car drivers in 14 locations in Korea. The main findings of this research are as followings: First of all, There were significant differences in traffic environment factors(road topography, construction, road & safety facilities, pedestrian behaviors, surrounding drivers) among 5 regional areas. When we examined drivers factors, there were significant differences among 5 metropolitan areas on wearing seat belt, most of constructions related to drink driving, speed-limit violation. There were many differences in driving habits, intentions, behaviors including wearing seat belt, driving after drinking according to metropolitan area, and also in case of speed-limit violation and careless driving behavior. These results suggested that there are many differences in traffic environments and driver's behaviors among regional areas. These result suggests that traffic safety policy and practice should be prepared based upon the peculiarities of regional area. We discussed these resulte in terms of the regional traffic policy and the suggestions for future studies were added.