• 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 the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.1-9
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• 2012

In this paper, we propose a vision-based robust vehicle detection and inter-vehicle distance estimation algorithm for driving assistance system. We use the haar-like features of car rear-shadows, as well as the edge features for detecting of vehicles. The use of additional vehicle edge features greatly reduces the false-positive errors in the vehicle detection. And, after analyzing the conventional two inter-vehicle distance estimation methods: the location-based and the vehicle width-based, an improved inter-vehicle distance estimation algorithm which has the advantage of both method is proposed. Several experimental results show the effectiveness of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.157-163
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• 2020

Recently, fine dust has been known to cause cardiovascular diseases here, raising interest in ways to reduce emissions by efficiently using fuel from cars that cause air pollution. Accordingly, a driving assistance system was developed to save fuel by eco-driving and improve the driver's bad driving habits. The system was developed using raspberry pi, arduino and Android. Using RPM, speed, fuel injection information obtained from OBD-II, and gyro-sensor values, Fuel-Cut is induced to create an optimal inertial driving environment. It also provides various information system such as weather, driving environment, and preventing drowsy driving through GUI and voice recognition functions. It is possible to check driving records and vehicle fault information using Android application and has low overhead for message transmission using MQTT protocol optimized for IoT environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.182-196
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• 2024

This study introduces driving pattern analysis and change detection methods using smartphone sensors, based on contrastive learning. These methods characterize driving patterns without labeled data, allowing accurate classification with minimal labeling. In addition, they are robust to domain changes, such as different vehicle types. The study also examined the applicability of these methods to smartphones by comparing them with six lightweight deep-learning models. This comparison supported the development of smartphone-based driving pattern analysis and assistance systems, utilizing smartphone sensors and contrastive learning to enhance driving safety and efficiency while reducing the need for extensive labeled data. This research offers a promising avenue for addressing contemporary transportation challenges and advancing intelligent transportation systems.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.252-263
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• 2016

Road sign is an important street furniture that gives some information such as road conditions, driving direction and condition for a driver. Thus, road sign is a major target of image recognition for self-driving car, ADAS(autonomous vehicle and intelligent driver assistance systems), and ITS(intelligent transport systems). In this paper, an enhanced road sign recognition system is proposed for MMS(Mobile Mapping System) using the single camera and GPS. For the proposed system, first, a road sign recognition scheme is proposed. this scheme is composed of detection and classification step. In the detection step, object candidate regions are extracted in image frames using hybrid road sign detection scheme that is based on color and shape features of road signs. And, in the classification step, the area of candidate regions and road sign template are compared. Second, a Geo-marking scheme for geo-content that is consist of road sign image and coordinate value is proposed. If the serious situation such as car accident is happened, this scheme can protect geographical information of road sign against illegal users. By experiments with test video set, in the three parts that are road sign recognition, coordinate value estimation and geo-marking, it is confirmed that proposed schemes can be used for MMS in commercial area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.347-350
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• 2012

The researches on driver assistance systems that can prevent an accident have been actively performed due to social issues of traffic accidents with development of vehicle industry in recent. It is required for researchers to develope systems which assist driver's perception and judgment when considering that over 70% of traffic accidents occur by drivers' carelessness and 75% of the total accidents occur at the speed of less 29km per hour. In this paper, we implemented a front and rear vehicle monitoring system that monitors distance in real-time from a vehicle to obstacles at the low-speed or back-ward driving. The implemented system consists of a high angle ultrasonic sensor with distance detection of 10m and 10-degree angle, a wide angle ultrasonic sensor with the detection distance of 3m and a 180-degree, and a ATmega128 chip of ATmel company.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.126-136
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• 2014

In the Advanced Driver Assistance Systems (ADAS) of smart vehicle and Intelligent Transportation System (ITS) for to detect the boundary of lane is being studied a lot of Hough Transform. This method detects correctly recognition the lane. But recognition rate can fall due to detecting straight lines outside of the lane. In order to solve this problems, this paper proposed an algorithm to recognize the lane boundaries and the accumulator cells in Hough space. Based on proposed algorithm, we develop application for Android was developed by H/W verification. Users of smart phone devices could use lane detection and lane departure warning systems for driver's safety whenever and wherever. Software verification using the OpenCV showed efficiency recognition correct rate of 93.8% and hardware real-time verification for an application development in the Android phone showed recognition correct rate of 70%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.65-72
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• 2006

The traffic lights detection and recognition system is an essential module of the driver warning and assistance system. A method which is a color vision-based real time detection and recognition of traffic lights is presented in this paper This method has four main modules : traffic signals lights detection module, traffic lights boundary candidate determination module, boundary detection module and recognition module. In traffic signals lights detection module and boundary detection module, the color thresholding and the subtraction value of saturation and intensity in HSI color space and detection probability mask for lights detection are used to segment the image. In traffic lights boundary candidate determination module, the detection mask of traffic lights boundary is proposed. For the recognition module, the AND operator is applied to the results of two detection modules. The input data for this method is the color image sequence taken from a moving vehicle by a color video camera. The recorded image data was transformed by zooming function of the camera. And traffic lights detection and recognition experimental results was presented in this zoomed image sequence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2532-2537
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• 2012

In recent, the researches on driver assistance systems have been actively performed with development of vehicle industry. AVM(Around View Monitoring) Systems, a part of these systems, have been researching and developing. Existing AVM systems have been developed in the forms of embedded systems or a SoC (System on Chip) to provide view around vehicle in real time. However, if Car PC is equipped with in vehicle, AVM can be developed using only software without additional cost. In this study, we implemented AVM system which provides location information by adding the informations such as latitude, longitude and speed to functions of "Car PC" based AVM system. If storing function is added to the AVM system implemented in this study which provides location information, the system with storing function can be used as AVM black box system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.457-467
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• 2020

Increasing environmental concerns have prompted countries around the world to tighten regulations on greenhouse gases and fuel efficiency. Research is being done using advanced driver assistance systems to improve fuel economy and for the convenience of drivers. Research on systems such as adaptive cruise control (ACC), LKAS, and AEB is active. The purpose of ACC is to control the longitudinal speed and distance of the vehicle and minimize the driver's load, which is considered useful for accident prevention. From this point of view, research has used a mathematical method of safety evaluation as a function of distances and scenarios while considering domestic road environments. A vehicle is tested with a simulation in a proposed scenario. The purpose of the analysis is to verify the functional safety of ACC by comparing the theoretical calculations using theoretical equations, the relative distances in the simulation, and an actual vehicle test. These methods are expected to enable many companies to use scenarios, formulas, and simulations as safety verification methods in the development of ACC.