• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.143-160
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• 2023

It is important to secure the golden time of emergency vehicles for quick responses in disaster situations, such as fire, rescue, and first aid. This study proposes plans Emergency Vehicle Preemption (EVP) based on the analysis of emergency vehicle operation to secure the golden time of emergency vehicles and increase driving safety. The emergency vehicle dispatch statistics, emergency vehicle traffic accident statistics, and survey were used for the analysis. As a result of the analysis, the frequency of dispatch of emergency vehicles and traffic accidents are increasing gradually, but the rate of securing the golden time of emergency vehicles is approximately half, indicating that improvement measures are urgent. In the questionnaire survey, most citizens consent to the necessity of introducing EVP. In addition, the criteria for the range of emergency vehicles that could provide EVP and the allowable time for waiting were derived. These results could be used to prepare EVP operation strategies, and it is expected to contribute to improving emergency vehicle operation safety and increasing the golden time securing rate through a rapid expansion of EVP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.44-53
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• 2023

Recently, serious parking problems are occurring due to the difficulty of securing sufficient parking space, and it may lead to other traffic or social problems. In order to solve the parking problem in areas and districts beyond a certain range, a study on-roads and off-street parking lots reflecting regional characteristics is necessary. Therefore, this study establishing a parking demand calculation model for use as a basic study in establishing on-road and off-road characteristics. In order to conduct the study, Dong-fu, Daegu Metropolitan City was divided into dongs, and parking facilities and parking demand were investigated. The survey time was divided into daytime and nighttime on weekdays, and the types of vehicles were divided into three types: passenger car, small trucks and buses, large trucks and buses. As explanatory variables for calculating parking demand, the total floor area of buildings for each of six purposes was used, including detached houses, apartment houses, neighborhood living facilities, cultural and assembly facilities, business facilities, and sales facilities. As a result of the correlation analysis, among the six explanatory variables, the total area of neighborhood living facilities showed a significant correlation with on- and off-street parking demand. A regression analysis model was constructed using the total area of neighborhood living facilities as an explanatory variable, and statistically significant results were obtained.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.159-181
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• 2022

Today, people in cities use differentthe types of transportation that rangepeople use in cities have diversified from existing public transportation, cars, taxis to shared bicycles and shared electric kickboards. In addition, with the development of mobile platform -based search, order, and payment services, and transportation services have also begun to change into platform-based integrated services. In particular, MaaS, which has emerged as an integrated mobile service and, is currently being studied and operated worldwide., However, MaaS but remains at the level of the integrated provision of the existing public transportation. As a result of Specifically, the results of a literature review on this issue reveal that, the First/Last Mile problem raised at the current level of MaaS is likely to be solved by establishing an improved policy incorporating new means of transportation. Therefore, this study aims to establish a First/Last Mile transportation supply plan for successful MaaS provision. This establishment is realized by analyzing the traffic patterns of urban populations usingbased on the ABATA system,, an activity-based traffic analysis model withevaluated as having higher analysis power on people's traffic.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.1-19
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• 2023

Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.20-37
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• 2023

Although traffic signal installations are continuously expanding, the effect of preventing traffic accidents remains unverified. Totally, 7,045 traffic accident data (such as signal violations) registered with TCS were manually searched for a 7-year period from 2013 to 2019 for 1,602 traffic signals in Daejeon Metropolitan City. The top 20 traffic accident intersections were identified, the traffic accident investigation records and field maps were viewed to compare the driving direction and signal phase of the violated vehicle, and the cause of the traffic accident was divided into insufficient signal operation design (operation) and driver negligence (intentional). Results of the analysis revealed that 75% of traffic accidents occurred in thru-left-turn traffic signals and overlap; moreover, extending the yellow time or operating all red signals due to countermeasures against traffic accidents occurring in yellow signals resulted in reduced traffic accidents. Data indicated that Permissive Left Turn requires improvement with the signal operation. In addition, since The Korean National Police Agency is not computerized for traffic accident sites and signal-related data, the lack of manpower necessitates improvement and utilization of TCS when establishing traffic accident prevention measures. It is believed that it will contribute to signal operation by analyzing vast amounts of data collected in the field and presenting improvement measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.73-87
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• 2023

Furnishing traffic safety information can contribute to providing hazard warnings to drivers, thereby avoiding crashes. A smart road lighting platform that instantly recognizes road conditions using various sensors and provides appropriate traffic safety information has therefore been developed. This study analyzes the short-term traffic safety improvement effects of the smart road lighting's tunnel traffic safety information service using surrogate safety measures (SSM). Individual driving behavior was investigated by applying the vehicle trajectory data collected with RADAR in the Anin Avalanche 1 and 2 tunnel sections in Gangneung. Comparing accumulated speeding, speed variation, time-to-collision, and deceleration rate to avoid the crash before and after providing traffic safety information, all SSMs showed significant improvement, indicating that the tunnel traffic safety information service is beneficial in improving traffic safety. Analyzing potential crash risk in the subdivided tunnel and access road sections revealed that providing traffic safety information reduced the probability of traffic accidents in most segments. The results of this study will be valuable for analyzing the short-term quantitative effects of traffic safety information services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.38-50
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• 2023

Recent advances in artificial intelligence (AI) technology have enabled the integration of AI technology into image sensors, such as Closed-Circuit Television (CCTV), to detect specific traffic incidents. However, most incident detection methods have been carried out using fixed equipment. Therefore, there have been limitations to incident detection for all roadways. Nevertheless, the development of mobile image collection and analysis technology, such as image sensors and edge-computing, is spreading. The purpose of this study is to estimate the reducing effect of the incident detection time according to the introduction level of mobile image collection and analysis equipment (or connected vehicles). To carry out this purpose, we utilized data on the number of incidents collected by the Suwon branch of the Gyeongbu expressway in 2021. The analysis results showed that if the market penetration rate (MPR) of connected vehicles is 4% or higher for two-lane expressway and 3% or higher for three-lane expressways, the incident detection time was less than one minute. Furthermore, if the MPR is 0.4% or higher for two-lane expressways and 0.2% or higher for three-lane expressways, the incident detection time decreased compared to the average incident detection time announced by the Korea Expressway Corporation for both two-lane and three-lane expressways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.