• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.115-120
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• 2006

A Korean Road Roughness Classification(KRC) method is proposed. Using a dynamic road profiling device equipped with the Accelerometer Established Inertial Profiling Reference(AEIPR) method, road profile measurement is performed on various types of public paved roads in Korea. The road profiling data are processed to classify the characteristics of Korean road roughness. The resultant Korean road roughness classification(KRC) is shown different characteristics compared to the road classification proposed by ISO, MIRA, and Wong. The proposed KRC is composed of 8 classes(A-H, very good-poor) based on the power spectral density and is in good agreements with the characteristics of Korean paved road roughness and can be used well in vehicle ride comfort simulation using domestic road profile.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.48-56
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• 2014

Even though vehicle types, gradient, pavement conditions and types of pavement should be considered for estimating fuel consumption, existing models were developed as a function of vehicle types and vehicle speed. Therefore in this study, the model of fuel consumption was developed using field test data in order that effect analysis on the passenger vehicle fuel consumption by road gradient. At first, fuel consumption was measured in second-based, using GPS device and fuel consumption measurement device for development of fuel consumption model considered road gradient. The road gradient was classified as flatland, up-hill and down-hill. Development of model was using by regression model which vehicle speed(km/h) and fuel consumption(${\ell}/km$). The on-road test proved that fuel consumption of passenger vehicle is affected by road gradient.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.239-245
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• 2017

For privacy protection, we propose a vehicle license plate region detection method in road view image served from portal site. Because vehicle license plate regions in road view images have different feature depending on distance, long distance vehicle license plate regions are not detected by feature of low resolution. Therefore, we suggest a method to detect short distance vehicle license plate regions by edge feature and long distance vehicle license plate regions using MSER feature. And then, we select candidate region of vehicle license plate region from detected region of each method, because the number of the vehicle license plate has a structural feature, we used it to detect the final vehicle license plate region. As the experiment result, we got a recall rate of 93%, precision rate of 75%, and F-Score rate of 80% in various road view images.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.10
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• pp.773-778
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• 2012

A road energy harvester was designed and fabricated to convert mechanical energy from the vehicle load to electrical energy. The road energy harvester is composed of 16 piezoelectric cantilevers. We fabricated prototypes using a vehicle load transfer mechanism. Applying a vehicle load transfer mechanism rather than directly installing energy harvesters under roads decreases the area of road construction and allows more energy harvesters to be installed on the side of the road. The power generation amount with respect to the vehicular velocity change was assessed by installing the vehicle load transfer mechanism form and underground form. The energy harvester installed in the underground form generated power of 4.52 mJ at the vehicular velocity of 50 km/h. Also, power generation of the energy harvester installed in the vehicle load transfer mechanism form was 48.65 mJ at the vehicular velocity of 50 km/h.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.3
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• pp.561-573
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• 2018

In order to design the ventilation in the road tunnel, it is necessary to know the ratio of average annual daily traffic by vehicle type. In general, the road tunnels are onedirectional tunnel, so the traffic of each vehicle type does not change along the tunnel. On the other hand, in the case of network road tunnels, since the connections in the tunnels are complex, the traffic of vehicle-type varies depending on the network composition of tunnels. In the studying the easy method for calculating the ratio of vehicle type for the network road tunnel are proposed with using incidence matrix.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.735-741
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• 2011

In the early phase of vehicle development, CAE is conducted as tool for vehicle performance assessment. To maintain acceptable road noise performance, solution for reduced vehicle sensitivity is required. Chassis interface dynamic stiffness characteristics are key component to isolating vibration and noise of road from the vehicle interior. This research provide how to set up the optimized dynamic characteristics under noise effect through DFSS study. CAE-based DOE is performed to build prediction math model, CMS process involves DOE to achieve very fast run times while giving results very comparable. Minimized $95^{th}$ percentile of performance distribution is applied to minimize vehicle sensitivity and road noise levels variation during the optimization process. Finally, the results of optimization were reviewed for performance and robustness.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.227-235
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• 2006

In this paper a robust image processing method with modified Otsu algorithm to recognize the road lane for a real-time controlled autonomous vehicle is presented. The main objective of a proposed method is to drive an autonomous vehicle safely irrespective of road image qualities. For the steering of real-time controlled autonomous vehicle, a detection area is predefined by lane segment, with previously obtained frame data, and the edges are detected on the basis of a lane width. For stable as well as psudo-robust autonomous driving with "good", "shady" or even "bad" road profiles, the variable threshold with modified Otsu algorithm in the image histogram, is utilized to obtain a binary image from each frame. Also Hough transform is utilized to extract the lane segment. Whether the image is "good", "shady" or "bad", always robust and reliable edges are obtained from the algorithms applied in this paper in a real-time basis. For verifying the adaptability of the proposed algorithm, a miniature vehicle with a camera is constructed and tested with various road conditions. Also, various highway road images are analyzed with proposed algorithm to prove its usefulness.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.17-21
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• 2011

This paper presents a real- time detection of on-road succeeding vehicles based on low level edge features and a boosted cascade of Haar-like features. At first, the candidate vehicle location in an image is found by low level horizontal edge and symmetry characteristic of vehicle. Then a boosted cascade of the Haar-like features is applied to the initial hypothesized vehicle location to extract the refined vehicle location. The initial hypothesis generation using simple edge features speeds up the whole detection process and the application of a trained cascade on the hypothesized location increases the accuracy of the detection process. Experimental results on real world road scenario with processing speed of up to 27 frames per second for $720{\times}480$ pixel images are presented.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.351-357
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• 2005

Development of a real-time simulation model for high-speed and multibody tracked vehicles is difficult because they involve hundreds of highly nonlinear equations. In the development of a reliable tracked vehicle model for real-time simulation, it is helpful to use an off-line tracked vehicle model developed by considering all the degrees of freedom of each element. This paper presents a step-by-step procedure for the development of a real-time simulation model based on the off-line tracked vehicle model. The road input data, Profile IV, is used for the real time simulation and simulation results are compared with vehicle test results obtained in the military test field. It is noted that the simulation results are quite close to the test results.

• International Journal of Automotive Technology
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• v.5 no.4
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• pp.257-268
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• 2004

The wavelet analysis method is introduced in this paper to study the nonstationary vibration of vehicles. A new road model, a so-called time domain correlated four-wheel road roughness, which considers the coherence relationships between the four wheels of a vehicle, has been newly developed. Based on a vehicle model with eight degrees of freedom, the analysis of nonstationary random vibration responses was carried out in a time domain on a computer. Verification of the simulation results show that the proposed road model is more accurate than previous ones and that the simulated responses are credible enough when compared with some references. Furthermore, by taking wavelet analysis on simulated signals, some substantial rules of vehicle nonstationary vibration, such as the relationship between each vibration level, and how the vibration energy flows on a time-frequency map, beyond those from conventional spectral analysis, were revealed, and these will be of much benefit to vehicle design.