• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.4
• /
• pp.50-61
• /
• 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
• /
• v.21 no.3
• /
• pp.73-82
• /
• 2022

Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.3
• /
• pp.83-95
• /
• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.57-69
• /
• 2022

Even though demand to charge EV(electric vehicles) is increasing, there are some problems to construct EV charging stations and problems from deficient them. Typical problem of EV charging stations is discordance for EV charging station location with its demand. This study investigates methods to determine the optimized location for fast EV charging stations considering charging demand in Seoul. Firstly, variables influencing on determination of determine the optimized location for fast EV charging stations were decided, and then evaluation of weights of the variables and data collection were conducted. Using the weights, location potential scores for each area-cell were calculated and optimized locations for fast EV charging stations were resulted.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.4
• /
• pp.63-77
• /
• 2023

This study applies reinforcement learning to effectively operate expressway hard shoulder running (HSR). An HSR algorithm was developed, and its effectiveness was evaluated using the VISSIM microscopic simulation program. The simulation evaluated two aspects: mobility and safety. The DQN-based HSR algorithm found speed improvement of up to 26 km/h. Compared to the current method, the difference in the number of conflicts was not significant. Considering the results, a DQN-based HSR operation has a clear effect, and it is necessary to consider adjusting the current operational criteria.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.4
• /
• pp.132-144
• /
• 2023

European and American countries are actively promoting eco-friendly cars to reduce exhaust emissions from internal combustion engines. In Korea, the "4th Basic Plan for Eco-Friendly Vehicles" aims to promote eco-friendly cars by improving charging infrastructure, expanding incentive systems, and targeting the supply of 1.13 million eco-friendly cars by 2025. As rapid growth in the number of electric vehicles sold is expected, estimates are required of this growth and corresponding power demands. In this study, the authors used a growth model to predict future growth in the electric vehicle market and a previously derived electricity generation model to estimate corresponding power demands up to 2036, the target year of the "10th Basic Plan for Power Supply and Demand". The results obtained provide useful basic research data for future electric vehicle infrastructure planning.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.25-38
• /
• 2023

Seoul Metropolitan Urban Railroad has an undecided route that does not estimate the passenger transportation route. For this reason, the fare of the urban railroad is calculated by the assumption that passengers pass through the minimum distance. Therefore, if a transfer station on the urban railroad is added, the trip shortest distance could be decreased and the fare also reduced. In this study, this phenomenon defines the fare paradox(Shin, 2022) and estimates the impact of the fare paradox by opening the GTX-A. For this purpose, a scenario before and after the opening of the GTX-A has been established, and an additional fare has been estimated by proportional planning of the Seoul Metropolitan Integrated Distance Based Fare Policy. Fare Paradox was analyzed to about 0.024 % of daily income. It is expected to be used as a plan to determine a rate policy, such as the establishment of a GTX-A, B, C, D, and a light rail line.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.291-310
• /
• 2023

This study explores the factors which affect user acceptance for Robo Taxi, an electricity-based Autonomous Vehicles based on a Value based Adoption Model. The three main factors of benefit (usefulness and enjoyment), sacrifice (technicality and perceived fee level), and user experience about mobility services such as car sharing, taxi, and autonomous vehicles, were finally selected as independent variables as a influential factors on perceived values and adoption intention of Robo taxi. The study found that usefulness, enjoyment, and perceived fee had a significant effects on adoption intention, and some user experiences had a significant effect on benefit factors. This study has important implications for incorporating the Value-based Adoption Model results into the service design for the activation of Robo taxi, and furthermore, they can provide a theoretical basis for effective use of the research findings.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.3
• /
• pp.175-189
• /
• 2023

Fault detection and diagnosis (FDI) algorithms are actively being researched for ensuring the integrity and reliability of environment perception sensors in autonomous vehicles. In this paper, a fault detection algorithm based on a multi-sensor perception system composed of radar, camera, and lidar is proposed to guarantee the safety of an autonomous vehicle's perception system. The algorithm utilizes reference generation filters and residual generation filters based on finite impulse response (FIR) filter estimates. By analyzing the residuals generated from the filtered sensor observations and the estimated state errors of individual objects, the algorithm detects faults in the environment perception sensors. The proposed algorithm was evaluated by comparing its performance with a Kalman filter-based algorithm through numerical simulations in a virtual environment. This research could help to ensure the safety and reliability of autonomous vehicles and to enhance the integrity of their environment perception sensors.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.1
• /
• pp.1-16
• /
• 2022

Recently, e-scooters have been attracting attention as eco-friendly modes of transportation in cities due to an increasing interest in the environment. Accordingly, various studies on usage behavior are being conducted, but studies that reflect individual travel attitudes are insufficient. Therefore, this study surveyed commuters in Seoul and analyzed respondents' traveling attitudes through factor analysis. It also built a binary logistic regression model for the intention to use shared e-scooters to determine how individual travel behaviors are affected. In particular, the model results showed that age, the main mode of transportation (car), walking time to the bus stop, and four travel attitude variables (disutility of travel, preference to self-drive, internet/smartphone friendliness, and willingness to pay extra money for services) significantly affected the intention to use shared e-scooters. This study is expected to be used as basic data, with aspect to travel behavior, for the efficient operation and use of shared e-scooters in the future.