• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.208-222
• /
• 2023

With the recent revision of 「Act on Promotion of the Transportation Convenience of Mobility Disadvantaged Persons」 and the Enforcement Regulations of the Act, bus business operators must introduce low-floor buses when scrapping buses. On the other hand, in the case of routes where low-floor buses cannot be operated, bus business operators can be exempted from introducing low-floor buses with the approval of their transportation administrative agency according to Article 4-2 of 「Enforcement Regulation of the Act on Promotion of the Transportation Convenience of Mobility Disadvantaged Persons」. According to the data from the Korea Bus Transportation Associations Federation, approximately 5.9% of all city bus routes were surveyed as the exceptions to introducing low-floor buses. Nevertheless the proportion is expected to increase because some regions with difficulties introducing low-floor buses are not included when calculating the proportion. By confirming the process of approving exceptions for introducing low-floor buses through local governments, there was no specific examination method or standard for approval of exceptions. Hence, there is the problem that some routes are approved as exceptions to introducing low-floor buses, even though low-floor buses can be operated on those routes. Therefore, this study aims to develop a manual that can objectively diagnose the overall operation environment of low-floor buses, such as road geometry and road facilities. Future research plans to apply it to more cases and improve it for more precise application in various contexts.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.32-48
• /
• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.246-263
• /
• 2023

The stabilization time of take-over refers to the time it takes for driving to stabilize after the take-over. Following a take-over request from an automated driving system, the driver must become aware of the road driving environment and perform manual driving, making it crucial to clearly understand the relationship between the driving environment and stabilization time of take-over. However, previous studies specifically focusing on stabilization time after take-over are rare, and research considering the driving environment is also lacking. To address this, our study conducted experiments using a driving simulator to observe take-over transitions. The results were analyzed using a liner mixed model to quantitatively identify the driving environment factors affecting the stabilization time of take-over. Additionally, coefficients for stabilization time based on each influencing factor were derived.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.3
• /
• pp.1-16
• /
• 2024

In the present highway design guidelines suggest that the capacity of one-lane hi-pass lanes is 2,000 veh/h for mainline toll plaza and 1,700 veh/h for interchange toll plaza. However, in a study conducted in early 2010, capacity of the mainline toll plaza was presented with 1,476 veh/h/ln to 1,665 veh/h/ln, and capacity of the interchange toll plaza was presented as 1,443 veh/h/ln. Accordingly, this study examined the feasibility of the capacity of the currently proposed highway one-lane hi-pass lane. Based on the 2021 individual vehicle passing data collected from the one-lane hi-pass gantry, the speed-traffic volume relationship graph and headway were used to calculate and compare capacity. In addition, the bootstrapping technique was introduced to utilize the headway and new processing methods for collected data were reviewed. As a result of the analysis, the one-lane hi-pass capacity could be estimated at 1,700 veh/h/ln for the interchange toll plaza, and at least 1,700 veh/h/ln for the mainline toll plaza. In addition, by using the bootstrap technique when using headway data, it was possible to present an estimated capacity similar to the observed capacity.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.110-126
• /
• 2024

Several studies have focused on developing the safest and most efficient path from the current location to the available parking area for vehicles entering a parking lot. In the present study, the parking lot structure and parking environment such as the lane width, width, and length of the parking space, were vaired by referring to the actual parking lot with vertical and horizontal parking. An automatic parking path planning model was proposed by collecting path data by various setting angles and environments such as a starting point and an arrival point, by putting the collected data into a deep learning model. The existing algorithm(Hybrid A-star, Reeds-Shepp Curve) and the deep learning model generate similar paths without colliding with obstacles. The distance and the consumption time were reduced by 0.59% and 0.61%, respectively, resulting in more efficient paths. The switching point could be decreased from 1.3 to 1.2 to reduce driver fatigue by maximizing straight and backward movement. Finally, the path generation time is reduced by 42.76%, enabling efficient and rapid path generation, which can be used to create a path plan for autonomous parking during autonomous driving in the future, and it is expected to be used to create a path for parking robots that move according to vehicle construction.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.16-36
• /
• 2024

This study, developed a dynamic hard shoulder running(HSR) algorithm that includes ending speed and minimum operation time in addition to the starting speed for HSR, and presented an operation plan. The first stage of the algorithm was red, which means vehicles are prohibited from HSR. The second stage is red/amber, in which drivers are notified of HSR, and operators are given time to check whether there is any obstacle to HSR. Stage 3 is green, which vehicles are permitted for HSR. Stage 4 is amber, in which a signal is given to drivers that the end of HSR is imminent. In addition, a minimum time is applied to green and red, but if congestion is severe, red is terminated early to prevent congestion from worsening. The upstream and downstream traffic flow is managed stably through main line ramp metering and lane number matching. The operating standard speed reflects the characteristics of vehicles and drivers, and based on simulation results, 7090 was selected as the optimal operating standard speed considering traffic flow and safety aspects. Therefore it is desirable to apply the travel time divided by the minimum speed of the HSR link as the minimum operating time in order to ensure continuity of traffic flow

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.37-53
• /
• 2024

This study selected bicycle road hazard detection factors for mobile IoT sensor device operation and developed service application plans. Twelve bicycle road hazard detection factors were derived through a focused group interview, and a fuzzy AHP-based importance analysis was conducted on 30 road and transportation experts. As a result, 'damage to pavement' (1st overall) and 'environmental obstacle' (2nd) with low visibility but a high risk of accidents were selected the most. The factors in terms of facility management, such as 'disconnected route occurrence' (4th), 'artificial obstacle' (5th), 'effective width' (6th), and 'poor drainage' (7th), were selected as the upper and middle areas. Factors that are not direct accident-inducing factors, such as 'loss of road markings' (11th) and 'free space width' (12th), were selected the least. Based on this, a plan was presented to apply the bicycle road hazard detection service and a service operation strategy according to real-time performance. Nevertheless, follow-up studies, such as human behavioral analysis based on bicycle operators, analysis according to the bicycle road type, service demonstration, and pilot operation, will be needed to develop safe bicycle road management is expected.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.94-109
• /
• 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 Korea Society of Industrial Information Systems
• /
• v.18 no.6
• /
• pp.61-70
• /
• 2013

This paper proposes a design of SARPE(Speed and Azimuth based Routing Protocol for Emergency) system which transfers an emergency message rapidly and accurately by minimizing path disconnection with a vehicle's speed and azimuth in case of accidents. The SARPE system accomplishes the path search based on an azimuth in order to minimize unnecessary messages and workload. It also selects the paths with the lowest probability that the path disconnection will happen by using the difference between the speed(maximum, minimum) of intermediate nodes and the average speed of a source node and destination node. Therefore, this paper minimizes the path resetting work happening due to path disconnection and transfers an emergency message rapidly and accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.11
• /
• pp.5522-5540
• /
• 2018

Vehicular license plate (LP) recognition system has risen as a significant field of research recently because various explorations are currently being conducted by the researchers to cope with the challenges of LPs which include different illumination and angular situations. This research focused on restricted conditions such as using image of only one vehicle, stationary background, no angular adjustment of the skewed images. A real time vehicular LP recognition scheme is proposed for the skewed images for detection, segmentation and recognition of LP. In this research, a polar co-ordinate transformation procedure is implemented to adjust the skewed vehicular images. Besides that, window scanning procedure is utilized for the candidate localization that is based on the texture characteristics of the image. Then, connected component analysis (CCA) is implemented to the binary image for character segmentation where the pixels get connected in an eight-point neighbourhood process. Finally, optical character recognition is implemented for the recognition of the characters. For measuring the performance of this experiment, 300 skewed images of different illumination conditions with various tilt angles have been tested. The results show that proposed method able to achieve accuracy of 96.3% in localizing, 95.4% in segmenting and 94.2% in recognizing the LPs with an average localization time of 0.52s.