• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.1-9
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• 2009

Bus information system(BIS), as a part of the intelligent transportation system(ITS), is one of the most advanced public transportation systems which provide the real-time bus traffic information for the users waiting the buses at the bus stop. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc. are not provided for the bus users because the proper bus arrival time predictive models are not used yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan. Thus, the purpose in this study is to investigate real-time bus traffic characteristic data for identifying the bus operation characteristics on the arterial under the study in the metropolitan City of Ulsan, analyze real-time bus traffic characteristic data on the ID locations of the arterial under the study, construct the optimal unit segment models for the unit segments which are the bus stop, node and travel section using the exponential smoothing, weighted smoothing and Kalman Filter methods, respectively, and finally suggest the optimal integrated model for predicting the real-time bus arrival time at the bus stop of the arterial under the study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.127-136
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• 2023

Gyeonggi Province has established a bus information system to provide real-time bus arrival information, aiming to make bus usage convenient for its residents. While the Gyeonggi bus information system is becoming more advanced through the application of IT technology, there are still information-vulnerable groups finding it difficult to use. In particular, the elderly have a low level of digital information literacy and habe difficulty using it. In this regard, this study aims to address the information usage disparity among the elderly in public transportation by utilizing expert in-depth survey methodology known as the Delphi technique. The study classified the policy initiatives that Gyeonggi Province should undertake into three categories: user education and expanded promotion, technological development and dissemination, and providing convenient usage environment. Through two rounds of surveys, the study assessed the priority of ten specific sub-tasks within these categories. Additionally, it gathered opinions on the effectiveness and feasibility of each item. The results yielded prioritization and evaluation of effectiveness and feasibility for nine sub-tasks. Based on these outcomes, the study proposed future projects that Gyeonggi Province should implement to address the information disparity among the elderly, offering a comprehensive approach to bridge the gap.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.30-42
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• 2023

Various studies have been conducted using microtraffic simulation (VISSIM) to analyze the safety of traffic flow when introducing autonomous vehicles. However, no studies have analyzed traffic safety in mixed traffic while considering the driving behavior of general vehicles as a parameter in VISSIM. Therefore, the aim of this study was to optimize the input variables of VISSIM for non-autonomous vehicles through genetic algorithms to obtain realistic behavior. A traffic safety analysis was then performed according to the penetration rate of autonomous vehicles. In a 640 meter section of US highway I-101, the number of conflicts was analyzed when the trailing vehicle was a non-autonomous vehicle. The total number of conflicts increased until the proportion of autonomous vehicles exceeded 20%, and the number of conflicts decreased continuously after exceeding 20%. The number of conflicts between non-autonomous vehicles and autonomous vehicles increased with proportions of autonomous vehicles of up to 60%. However, there was a limitation in that the driving behavior of autonomous vehicles was based on the results of the literature and did not represent actual driving behavior. Therefore, for a more accurate analysis, future studies should reflect the actual driving behavior of autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.163-181
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• 2023

Improving the detection performance of facilities corresponding to the sensors of autonomous vehicles helps driving safety. In the road and transportation field, research is being conducted to improve the detection performance of sensors by road infrastructure or facilities. As part of this on the development of autonomous driving support infrastructure, the shape of traffic cones and drums to ensure sufficient LiDAR detection performance even rainy conditions and maintain the line-of-sight guidance function in construction zones improvement effect. The principle was to increase reflection performance and ensure no significant difference in shape from existing facilities. Traffic cones were manufactured in square pyramid shapes instead of cones, and drums were manufactured in hexagonal and octagonal pillar shapes instead of cylinders. LiDAR detection data for the facility was confirmed on a clear day and with 20 mm/h and 40 mm/h rainfall. The detection performance of the square pyramid-shaped traffic cone and octagonal column-shaped drum was to the existing facility. On the other hand, deviations occurred due to repeated measurements, and significance could not be confirmed through statistical analysis. By reflecting these results, future studies will seek a form in which data can be obtained uniformly despite the diversity of measurement environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.74-91
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• 2023

Several that analyzed the effectiveness of traffic safety facilities a method of comparing changes in the number of accidents, accident severity, speed through traffic accident data before and after installation or speed data collected from vehicle detection systems (VDS). , when traffic accident data is used, it takes a long time to collect because must be collected for at least one year before and after installation. , the road environment may change during this period, such as the addition of other traffic safety facilities in addition to the facilities to be analyzed. , the location of the VDSs for speed data is often different from the location where analysis is required, and there is a problem in that the investigators are exposed to the risk of traffic accident during on-site investigation. Therefore, this study a case study by establishing a methodology to determine effectiveness video images with a drone, extracting data using a program, and comparing vehicle driving speeds before and after speed reduction facilities. Vehicle speed surveys using drones are much safer than observational surveys conducted on highways and have the advantage of tracking speed changes along the vehicle, it is expected that they will be used for various traffic surveys in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.1-14
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• 2024

The most optimal route-search algorithm thus far has introduced a method of applying node labels and link labels. Node labels consider two nodes simultaneously in the optimal route-search process, while link labels consider two links simultaneously. This study proposes a turn-label-based optimal route-search technique that considers two turns simultaneously in the process. Turn-label-based optimal route search guarantees the optimal solution of dynamic programming based on Bellman's principle as it considers a two-turn search process. Turn-label-based optimal route search can accommodate the advantages of applying link labels because the concept of approaching the limit of link labels is applied equally. Therefore, it is possible to reflect rational cyclic traffic where nodes allow multiple visits without expanding the network, while links do not allow visits. In particular, it reflects the additional cost structure that appears in two consecutive turns, making it possible to express the structure of the travel-cost function more flexibly. A case study was conducted on the metropolitan urban railway network consisting of transportation card terminal readers, aiming to examine the scalability of the research by introducing parameters that reflect psychological resistance in travel with continuous pedestrian transfers into turn label optimal path search. Simulation results showed that it is possible to avoid conservative transfers even if the travel time and distance increase as the psychological resistance value for continuous turns increases, confirming the need to reflect the cost structure of turn labels. Nevertheless, further research is needed to secure diversity in the travel-cost functions of road and public-transportation networks.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.94-109
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• 2024

As autonomous vehicles are allowed to drive on public roads, there is an increasing amount of on-road data available for research. It has therefore become possible to analyze impacts of autonomous vehicles on traffic safety using real-world data. It is necessary to use indicators that are well-representative of the driving behavior of autonomous vehicles to understand the implications of them on traffic safety. This study aims to derive indicators that effectively reflect the driving stability of autonomous vehicles by analyzing the driving behavior using the Waymo Open Dataset. Principal component analysis was adopted to derive indicators with high explanatory capability for the dataset. Driving stability indicators were separated into longitudinal and lateral ones. The road segments on the dataset were divided into four based on the characteristics of each, which were signalized and unsignalized intersections, tangent road section, and curved road section. The longitudinal driving stability was 35.48% higher in the curved road sections compared to the unsignalized intersections. With regard to the lateral driving stability, the driving stability was 76.08% higher in the signalized intersections than in the unsignalized intersections. The comparison between curved and tangent road segments showed that tangent roads are 146.87% higher regarding lateral driving stability. The results of this study are valuable for the further research to analyze the impact of autonomous vehicles on traffic safety using real-world data.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.239-245
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• 2016

In the midst of continuing international recession, the rate of maritime traffic and marine leisure markets are consistently growing. The Republic of Korea controls the marine traffic volume through vessel traffic centers and various other management facilities. Nevertheless, the continuous growth and complexity of marine traffic is resulting in repeated occurrences of marine accidents. Recovery is very difficult in cases of human injuries or deaths caused by marine accidents due to its nature, and the scale of marine accidents is also becoming greater with advanced ship building technologies. Passenger ships, oil tankers, and other such vessels used for specific purposes requires a more detailed navigational status surveillance and analysis, and numerous research has been conducted with an objective for monitoring such special purpose vessels. However, the data elements transmitted from the ocean to the shore station are limited to AIS and ARPA. We are implementing IoT ship sensor collection and a syncing system capable of transmitting various ship sensing data to the shore station, and also proposing a Safe Navigation Status Analysis System utilizing the collected data.