• Broadcasting and Media Magazine
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• v.24 no.1
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• pp.13-22
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• 2019

전통적인 자동차는 운전자의 판단과 조작에 의해서만 움직여야 하나 최근 자율주행자동차가 선을 보이고 있으며, 미래에는 운전자의 조작 없이 자동차가 스스로 목적지를 찾아가는 완전자율주행자동차 시대가 올 것으로 예견된다. 본 고에서는 자율주행자동차의 출현에 따른 지상파 방송의 역할을 제시한다.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.101-113
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• 2008

VMS are installed in many Korean highways in oder to give drivers informations such as travel time to destination, congestion and Incident situation. However, some guidelines for install VMS are restricted in only geometric factors although human factors considering driver behavior are very important to affect the VMS installation. Therefore, this paper are focusing on developing and verifying the discriminant model for VMS installation considering human factors. As a result, following outputs are obtained ; (1) developing the discriminant model using human factors of driving simulation experiments in oder to predict driver reading VMS messages safely detour highway. (2) proving that driving experiences in highway, personal driving history, vehicle speed orderly affects VMS installation (3) verifying predictability of developed model by comparing the real values with predicted values. (4) suggesting that VMS should be installed off 3.2Km from the I.C. of rural highway.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.103-120
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• 2020

Using driving simulation, this study investigated the effects of driver's trust in the adaptive cruise control (ACC) system and road density on driver's workload and situation awareness. The drivers were allocated into one of four experimental conditions manipulated by ACC system trust level (trust-increased vs. trust-decreased) and road congestion (high vs. low). The workload and situational awareness of the participants were measured as dependent variables. The results showed followings. First, trust-decreased group for the ACC system had significantly lower trust scores for the system in all of the measurement items, including reducing the driving load and securing safe driving due to the use of this system, than the trust-increased group. Second, the trust-decreased group showed a slower reaction time in the secondary tasks and higher subjective workload than trust-increased group. Third, in contrast, the situational awareness for the driving situation was significantly higher in the trust-decreased group than trust-increased group. The results of this study showed that the driver's trust in the ACC system can affect the various information processing performed while driving. Also, these results suggest that trust in the user's system should be considered as an important variable in the design of an automated driving assistance system.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.65-79
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• 2006

The ATIS(Advance Traveler Information System), as one part of ITS, is a system aiming to disperse traffic volume on transportation networks by providing traffic information to transportation users on pre-trip and en-route trips. One of tools in ATIS is usage of VMS(Variable Message Signs). It provides to the drivers with direct information about state of processing direction. which is considered as the most effective method in ATIS. The purposes of providing VMS information are classified two categories. One is to provide simple information to drivers for their convenience. The other is to manage traffic demand to improve transportation network performance. However, for more effective and reliable VMS information, several strategies should be taken into account. The main VMS management strategy is "Traffic Diversion Strategy for minimum delay" when traffic congestion or incident are occurred. For effective operation. firstly. reasonable diversion traffic volume is determined by network traffic condition Secondly, it is necessary to make providing information strategy which reflects driver response behavior for controling diversion traffic volume. This paper focuses on the providing real-time route guidance information by VMS when congestion is occurred by the incidents. This sturdy estimates time-dependent system optimal diversion rate that inflects travel time and queue lengths using traffic flow simulation model on base Cellular Automata. In addition, route choice behavior models are developed using binary logit model for traffic information variable by traffic system controller. Finally, this study provides time-dependent VMS massage contents and degree of providing information in order to optimize the traffic flow.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.49-59
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• 2006

DAS(Driver Assistance Systems) support the driver's decision making to increase safety and comfort by issuing the naming signals or even exert the active control in case of dangerous conditions. Most previous research and products intend to offer only a single warning service like the lane departure warning, collision warning, lane change assistance, etc. Although these functions elevate the driving safety and convenience to a certain degree, New type of DAS will be developed to integrate all the important functions with an efficient HMI (Human-Machine Interface) framework for various driving conditions. We propose an all-around sensing based on the integrated DAS that can also remove the blind spots using 2 cameras and 8 sonars, recognize the driving environment by lane and vehicle detection, construct a novel birds-eye HMI for easy comprehension. it can give proper warning in case of imminent danger.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.112-123
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• 2012

Different from general roads, intersections are the points where roads having different geometric structure and traffic operation system are met, and thereby they have complicated road structure and environmental factors. Various changes in driving patterns such as collision between vehicles approaching from roads adjacent to intersections, sudden stop of vehicles upon stop sign, quick start upon green lights kept increasing traffic accidents. It is known that traffic accidents are mainly derived from human factors. This study, in order to find out factors affecting drivers' behaviors within intersections, measured physiological responses such as brain wave, sight, driving speed, and so on by using state-of-the-art measuring device. As to concentration brain wave at individual intersections, it was found out that brain wave of testes was higher at main Arterial and accident-prone intersections compared with that of subsidiary Arterial. In addition, it was detected that drivers' visual activity was widely distributed at accident-prone intersections, meaning that it enhanced cautious driving from nearby vehicles. As to major factors causing drivers' workloads, factors from nearby vehicles such as deceleration, acceleration, lane change of nearby vehicles appeared as direct factors causing drivers' workloads, clarifying that these factors were closely related to causes of traffic accidents at intersections. Results of this study are expected to be used as basic data for evaluation of safety at intersections in consideration of physiological response of drivers.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.23-32
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• 2007

Variable message sign (VMS), which is used for providing real-time information on traffic conditions and incidents, is one of the important components of intelligent transportation systems. VMS messages need to meet the requirements with the consideration of human factors that messages should be readable and understandable while driving. This study developed a legibility distance model for VMS messages using in-vehicle differential global positioning data (DGPS). Traffic conditions, highway geometric conditions, and VMS message characteristics were investigated for establishing the legibility model based on multiple linear regression analysis. The height of VMS characters, speed, and the number of lanes were identified as dominant factors affecting the variation of legibility distances. It is expected that the proposed model would play a significant role in designing VMS messages for providing more effective real-time traffic information.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.17-25
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• 2009

This research analyzed the changes of drivers' visual workload with beta wave of bionic signals from brain's occipital lobe from entrance to exit section of the Yuksimnyeong tunnel which is 3.1km long in Daejeon-Tongyeong section of Jungbu expressway. There are 10 subjects who Participate our experiments and the results are as follows. First. the drivers' visual workload is higher about 41% in entrance section of the tunnel than 200m in advance of the section of the tunnel. Second, it is higher than 200m in advance of the section of the tunnel by 34.5% that the value of the drivers' visual workload who is driving in the tunnel. Third, as a result of analyzing the tunnel into 200m unit section, it is statistically different from other sections' at the 1.0km and 2.4km section from the entrance of the tunnel. If drivers sustain average visual workload for safe driving in very long tunnel, it's not desirable environment that drivers' visual workload goes under the average workload. Therefore, it would be the section where drivers who is driving in tunnel could cause a traffic accident.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.36-43
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• 2011

The forward collision of vehicles in high speed can cause a chain collisions and high fatality rate. Most of the forward collisions are caused by insufficient braking distance due to detection time of driver and safe distance. Also, accumulated detection time of driver is cause of chain collisions after the forward collision. The FVCWS prevents the forward collision by maintaining the safety distance inter-vehicle and reducing detection time of driver. However the FVCWS can cause chain collisions because the system that interacts only forward vehicle has accumulated detection time of driver. In this paper, we analyze forward and chain collisions of normal vehicles and FVCWS vehicles on static traveling scenario. And then, we analyze and compare V2V based FVCWS with them after explaining the system. The V2V FVCWS reduces detection time of driver alike FVCWS as well as remove accumulated detection time of driver by broadcasting emergence message to backward vehicles at the same time. Therefore, the system decrease possibility of forward and chain collisions. All backward normal vehicles and 3~4 backward FVCWS vehicles have possibility of forward and chain collisions in result of analysis. However V2V FVCWS vehicles almost do not chain collisions in the result.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.