• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.6
• /
• pp.1-12
• /
• 2009

Recently, as the importance of Economical Driving has been gradually growing up, the needs for research on automatic analysis of driving patterns that will ultimately provide drivers the methods for Economical Driving have been increasingly risen. Based on this purpose, we have executed two things in this paper. First, we have collected overall driving information such as date, distance, driving time, speed, idle time, sudden acceleration/deceleration count, and the amount of fuel consumption. Second, we have analyzed the influences of driving patterns on economical driving by employing the data mining techniques. These results can be applied in preventing bad driving patterns which will have consequently bad effects on Economical Driving in two aspects: by presenting some information on the terminal of the vehicles such as idle time, over-speed time, sudden acceleration/deceleration count continuously and by providing the drivers with alert information when the idle time ratio and the over-speed time ratio are excessive.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.3
• /
• pp.120-131
• /
• 2017

Recent studies have suggested that providing in-vehicle feedback on various driving behaviors promote eco-friendly driving behaviors. However, there was relatively little interest in cognitive overload that can be caused by the provision of information. Thus, the goal of this study was to investigate the relative effects of two types of feedback(visual feedback vs. visual-auditory feedback) to increase eco-driving performance while minimizing driving workload. Also, in this study, the complexity of the driving task was distinguished (secondary vs. tertiary task) in order to reflect the actual driving situation. The study adopted a counterbalancing design in which the two feedback types were delivered in a different order under the two different task conditions. Results showed that providing the visual-auditory feedback was more effective than the visual only feedback in both promoting eco-friendly driving behaviors and minimizing driving workload under both task conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.264-279
• /
• 2021

Most automated vehicle evaluation scenarios are developed based on the typical driving situations that automated vehicles will face. However, various situations occur during actual driving, and sometimes complex judgments are required. This study is to define a situation that requires complex judgment for safer driving of an automated vehicle as a dilemma situation, and to suggest a driving strategy necessary to secure driving safety in each situation. To this end, we defined dilemma situations based on the automated vehicle ethics guidelines, the criteria for recognition of error rate in automobile accidents, and suggestions from the automated vehicle developers. In addition, in the defined dilemma situations, the factors affecting movement for establishing driving strategies were explored, and the priorities of factors affecting driving according to the Road Traffic Act and driving strategies were derived accordingly.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.3
• /
• pp.147-159
• /
• 2023

In order to make autonomous vehicles more trustworthy, it is necessary to focus on the users of autonomous vehicles. By evaluating the preferences for driving behaviors of autonomous vehicles, we aim to identify driving behaviors that increase the acceptance of users in autonomous vehicles. We implemented two driving behaviors, aggressive and cautious, in a driving simulator and allowed users to experience them. Biometric data was collected during the ride, and pre- and post-riding surveys were conducted. Subjects were categorized into two groups based on their driving habits and analyzed against the collected biometric data. Both aggressive and cautious driving subjects preferred the cautious driving behavior of autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.284-298
• /
• 2023

With the rapid advances in automated driving technology, opportunities to experience automated driving directly or indirectly are being provided to the public. On the other hand, research on the preferred automated driving patterns from the user's perspective has not been conducted in Korea. This study used a driving simulator and an experimental vehicle capable of automated driving to evaluate the user satisfaction regarding longitudinal and lateral accelerations. Automated driving patterns were implemented in a virtual environment simulation using five values of longitudinal and lateral accelerations derived from driving experiments. Among these values, three were implemented through experimental vehicle-based automated driving to evaluate satisfaction and anxiety. The participants evaluated lateral acceleration more sensitively than longitudinal acceleration and showed higher levels of anxiety. Based on these results, the necessity of user-oriented evaluation research for automated driving patterns and the suitability of simulator-based evaluation methods were presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.543-547
• /
• 2005

In this paper, we designed a intelligent autonomous driving robot by using Fuzzy algorithm. The object of designed robot is recognition of obstacle, avoidance of obstacle and safe arrival. We append a suspension system to auxiliary wheel for improvement in stability and movement. The designed robot can arrive at destination where is wanted to go by the old and the weak and the handicapped at indoor hospital and building.

• Journal of Korean Society of Transportation
• /
• v.26 no.1
• /
• pp.155-164
• /
• 2008

Variable Message Signs (VMS) is one of the major components for Intelligent Transport Systems (ITS) services that provides real-time traffic and incident information to drivers. The objective of this research was to develop a method determining the optimal location of VMS considering safety and driving characteristics of various drivers. A driving simulator was utilized to evaluate how drivers can safely exit to off-ramp depending on various VMS locations while information relating route diversion was provided. The binary logistic regression and factor analysis were applied in developing a probability model that predicts the success of safe off-ramp exiting. Based on the developed probability model, a method to estimate the spacing between VMS and off-ramp is suggested. It is expected that the products of this study would be utilized as a tool in determining VMS locations for ITS planners and designers.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.6
• /
• pp.16-28
• /
• 2017

In this study, we analyzed the result of new inspection, accidents, penalties, and operation records of the elderly driver's driving aptitude test in the city bus using the Transport Workers Management System and the Digital Tachograph Analysis System(eTAS). As a result of the analysis, the results of the driver aptitude test were similar when compared with the traffic company which has many bus drivers and the well - And it was confirmed that the average number of serious injuries and slight injuries in case of accidents was small. Comparing the number of dangerous driving behaviors per 100 km of driving, the elderly driver of the excellent company showed that the number of dangerous driving behaviors is considerably smaller than other elderly and non - elderly drivers, and that the result of correcting the wrong driving habits.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.1
• /
• pp.91-104
• /
• 2022

The operational design domain (ODD) of autonomous vehicles needs to be expanded on highways and urban roads in light of the substantial commercialization of Level 3 autonomous vehicles. Therefore, this study developed a specific infrastructure autonomous vehicle-based cooperative driving service to ensure the driving safety of autonomous vehicles on city roads. The traffic operation efficiency, safety evaluation, and core evaluation indices for each service were selected and analyzed to study the effect of each service. The result of the analysis confirmed that the traffic operation efficiency and safety of autonomous vehicles were improved through the V2X communication-based autonomous cooperative driving service. On the whole, the significance of this study is in deriving the effect of the autonomous cooperative driving service based on V2X communication on urban roads with interrupting traffic flow.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.1
• /
• pp.182-196
• /
• 2024

This study introduces driving pattern analysis and change detection methods using smartphone sensors, based on contrastive learning. These methods characterize driving patterns without labeled data, allowing accurate classification with minimal labeling. In addition, they are robust to domain changes, such as different vehicle types. The study also examined the applicability of these methods to smartphones by comparing them with six lightweight deep-learning models. This comparison supported the development of smartphone-based driving pattern analysis and assistance systems, utilizing smartphone sensors and contrastive learning to enhance driving safety and efficiency while reducing the need for extensive labeled data. This research offers a promising avenue for addressing contemporary transportation challenges and advancing intelligent transportation systems.