• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.60-65
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• 2021

The event data recorders (EDR) have been used as a device to help understand traffic accidents. With the recent development of autonomous vehicle (AV), it has become important to prepare the new EDR for AV. Therefore, the purpose of this study is to propose the direction of EDR-AV recording. First of all, the recent EDR data elements and the data elements of AV under discussion at UNECE WP29 EDR/DSSAD (Data Storage System for Automated Driving) were analyzed. The consumer complaint database in Motor Vehicle Recall Center in Korea was analyzed in order to utilize cases of domestic traffic accidents related to advanced driver assistance systems (ADAS). Consequently, problems with existing EDR were identified through unclear accident cases related to ADAS. In the future, it was proposed to record images in which the ADAS perception systems recognize the surroundings of the accident site as an EDR-AV recording item.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.173-188
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• 2024

With the advancement of autonomous vehicle (AV) technology, autonomous driving on real roads has become feasible. However, there are challenges in achieving complete autonomy due to perceptual blind areas, which occur when the AV's sensory range or capabilities are limited or impaired by surrounding objects or environmental factors. This study aims to analyze AV accident patterns and safety issues of perceptual blind area that may occur in urban areas, with the goal of developing test scenarios for Level 4+ autonomous driving. It utilized AV accident data from the California Department of Motor Vehicles (DMV) to compare accident patterns and characteristics between AVs and conventional vehicles based on activation status of autonomous mode. It also categorized AV disengagement data to identify types and real-world cases of disengagements caused by perceptual blind areas. The analysis revealed that AVs exhibit different accident types due to their safe driving maneuvers, and three types of perceptual blind area scenarios were identified. The findings of this study serve as crucial foundational data for developing Level 4+ autonomous driving test scenarios, enabling the design of efficient strategies to mitigate perceptual blind areas in various scenarios. This, in turn, is expected to contribute to the effective evaluation and enhancement of AV driving safety on real roads.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.75-82
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• 2022

Automated vehicles (AVs) are coming to our roadways. In practice, there are still several challenges that can impede the AV sensors are polluted on various road conditions. In this paper, we propose a strategy for V2E performance assurance technology using Kano model. We are developing the vehicle sensor cleaning system about the three types of commonly used sensors: camera, radar, and LiDAR. Surveys were carried out in 30 AV's experts on quality characteristics about V2E performance assurance technology. As a result, the Kano model developed to verify a major requirement of autonomous vehicle's sensor cleaning system. It is expected that the Kano model will be actively used to verify the importance of V2E development strategy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.55-72
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• 2017

Autonomous Vehicles(AV) are considered as an alternative to solve various social problems. Many researches which are related to developing technologies and AV operations have been conducted vastly and on-going. However, there seem to be little studies on various influences of AI algorithm on driving installed in AV. This study aims to examine the impacts of the ethical decisions made by Utilitarianism-based AI in AV when the oncoming car crossed over the central line. It establishes scenarios about situation of encroaching a central line and analyzes traffic impacts of ethical decision made by AV. According to the results of the analyses, as th accident occurs, overall speed of traffic decrease. There is a negative impact on the traffic flow when AV made an Utilitarian-based ethical decision by changing the lane. However, when AV choose to collide head-on, there is a positive effect to relieve traffic flow with an assistance of CACC, equipped.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.33-44
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• 1999

This paper describes the Autonomous Vehicles (AV) which are operated for their own tasks. There are chances of conflict resolution such as sharing the same path which can lead to the risk of a collision. This research represents some ways of negotiating the conflict resolution by generating cooperative actions. Negotiation while traveling the path is accomplished by using priority and by announcing the start time of the task. When there is a risk of collision, the AV tries to dissolve the situation of conflict resolution by concurrently adjusting mutual speed and by performing the algorithm of passing. If the speed of the AV cannot be adjusted, it measures the distance between the counterpart of the AV and an obstacle along the path. Then it judges either to proceed by passing the counterpart of the AV or to turn back after observing the current circumstances. The performance of the algorithm described above was proven by a simulator.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.81-90
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• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.4
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• pp.531-544
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• 2024

The purpose of this study is to analyze traffic flow characteristics according to the market penetration rate (MPR) of autonomous vehicles (AV) on road sections where bus rapid transit (BRT) is actually operating. Furthermore, the maximum traffic volume was set through estimation of future traffic demand, and traffic flow characteristics were analyzed through traffic simulation for each scenario considering of a combination of BRT introduction and AV's MPR. To test statistical significance, Kruskal-Willis test and Jonckheere-Terpstra test were used to examine the impact of the market penetration rate of Autonomous vehicles on travel time and delay time etc. At the same time, the existence of the order relationship among travel time data according to the market penetration rate of autonomous vehicle was examined. As a result of the analysis, it was founded that the travel time significantly decreased as the MPR of AV increases in both intermittent flow and continuous flow environments. In particular, in the case of continuous flow, the law of increasing returns was satisfied in the effect of increasing travel speed and reducing travel time as the MPR of AV increases. The results of this study are expected to be used as a basic information for design plans for road reconstruction and space utilization after the commercialization of AV in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.80-96
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• 2024

This study conducted over two rounds Delphi survey targeting experts in the fields of roads, transportation, automobiles, intelligent transport systems(ITS), and communications to analyze the direction of change in road design, operation, and systems in the Lv.4/4+ autonomous driving era. To construct the Delphi survey items, a basic survey was conducted. The first and second Delphi surveys targeted experts in fields closely related to autonomous driving. The results of the survey revealed an expectation that in the future, transportation operations would change focus to shared autonomous vehicle(AV) and public transportation transfers, and there would be corresponding changes in the cross-sectional configuration. Exclusive lanes for AV are expected to be introduced commencing from highways and general national roads, and there was a consensus that they should be installed in the center of the road rather than on the sides and would use the same lane width as that of the existing road. In terms of facilities for AVs, it was found that it would be necessary to expand pedestrian-vehicle separation facilities, insert communication chips into facilities for location recognition, advance precision maps, and expand roadside communication facilities.

• Asia Marketing Journal
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• v.20 no.2
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• pp.65-83
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• 2018

Technological advances are bringing autonomous vehicles to the ever-evolving transportation system. Anticipating adoption of these technologies by users is essential to vehicle manufacturers for making more precise production and marketing strategies. The research investigates regulatory focus and consumer innovativeness with consumers' adoption of autonomous vehicles (AVs) and to consumers' subsequent willingness to pay for AVs. An online questionnaire was fielded to confirm predictions, and regression analysis was conducted to verify the model's validity. The results show that a promotion focus does not have a significantly positive effect on the automation level at which consumers will adopt AVs, but a prevention focus has a significantly positive effect on conditional AV adoption. Consumer innovativeness, consumers' novelty-seeking have a significantly positive relationship with high and full AV adoption, and consumers' independent decision-making has a significantly positive effect on full AV adoption. The higher the level of automation at which a consumer adopts AVs, the higher the willingness to pay for them. Finally, using a neural network and decision tree analyses, we show methods with which to describe three categories for potential adopters of AVs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.13-27
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• 2021

In this study, the impact of traffic flow on the market penetration rate of autonomous vehicles(AV) was analyzed using the data for the year 2020 of the Yongin IC~Yangji IC section of Yeongdong Expressway. For this analysis, a microscopic traffic simulation model VISSIM was utilized. To construct the longitudinal control of the AV, the Intelligent Driver Model(IDM) was built and applied, and the driving behavior was verified by comparison with a normal vehicle. An examination of the study results of mobility and safety according to the market penetration rate of the AV, showed that the network's mobility improves as the market penetration rate increases. However, from the point of view of safety, the network becomes unstable when normal vehicles and AVs are mixed, so there should be a focus on traffic management for ensuring safety in mixed traffic situations.