• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.180-189
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• 2013

The SMART Highway project combines road construction with advanced technology and vehicle telecommunications. Its expected outcome is a world-leading intelligent road that is green, fast, and comfortable. A vehicular ad-hoc network(VANET) is the core technology of the SMART Highway, whose transport operation is based on road vehicles. The VANET is a next-generation networking technology that enables wireless communication between vehicles or between vehicles and a road side unit(RSU). In the VANET system, a vehicle accident is likely to cause a serious disaster. Therefore, some information on safety is essential to serve as the key exchange protocol for communication between vehicles. However, the key exchange scheme of the general network proposed for a fast-moving communication environment is unsuitable for vehicles. In this paper, communication between multiple vehicles more efficient and secure key exchange at the vehicle certification by signcryption is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1853-1856
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• 2003

This paper considers the problem of longitudinal control of a platoon of automotive vehicles on a straight lane of a highway and proposes control laws in the event of loss of communication between the lead vehicle and the other vehicles in the platoon. Since safety plays a key role in the development of an Automated Highway System, fault-tolerant control is vital. In this paper, we develop a control algorithm in vehicle platooning and prove that this control algorithm is stable for certain class of faults such as parameter uncertainties. The performance of the controller is demonstrated through a series of simulations incorporating various vehicles and AHS faults. Results of simulation shows that the vehicles have good performance in spite of simple automotive and AHS failure, such as actuator failure,that is to say, engine input failure, communication failure between lead vehicle and the another vehicles.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.581-588
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• 2002

Precise highway traffic noise simulation and reduction require the accurate data for sound power levels omitted by vehicles, varied to road surface, traffic speed, vehicle types and makers, different from countries to countries. In this study, we have elaboratively measured Korea highway traffic noise and parameters affecting noise levels at the nearside carriageway edge. From numerical simulation using the measured results for highway traffic noise, we propose not only two correction factors to enhance the accuracy of Korea highway traffic sound power estimation using ASJ Model-1998 but also its typical power spectrum according to road surface type. The measured and predicted highway traffic noise levels using the proposed sound power show little difference within 1 dB.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.8-14
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• 1997

The dynamic responses of highway bridges are varying depending on the features of either traveling vehicles or bridges. In this study, the probabilistic characteristics of dynamic amplification factors of highway bridges due to traveling heavy vehicles have been examined through analytical simulation processes. The truck with tandem axle and tractor with semitrailer are selected as the representative heavy vehicles, which are modeled with three dimensional 7-DOF and 12-DOF models, respectively. The analytical results have been compared with the experimental results of dynamic loading tests and the validity of the analytical models has been examined. Parametric studies on the means and extreme values of amplification factors have been performed with various traffic conditions such as vehicle types, vehicle weights, surface profiles, vehicle velocity, etc.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.13-20
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• 2023

In connected vehicles, drivers are exposed to attacks when they communicate with unauthenticated peers. This occurs when a vehicle relies on outdated information resulting in interactions with vehicles that have expired or revoked certificates claiming to be legitimate nodes. Vehicles must frequently receive or query an updated revoked certificate list to avoid communicating with suspicious vehicles to protect themselves. In this paper, we propose a scheme that works on a highway divided into clusters and managed by roadside units (RSUs) to ensure authenticity and preserve hidden identities of vehicles. The proposed scheme includes four main components each of which plays a major role. In the top hierarchy, we have the authority that is responsible for issuing long-term certificates and managing and controlling all descending intermediate authorities, which cover specific regions (e.g., RSUs) and provide vehicles with short-term pseudonyms certificates to hide their identity and avoid traceability. Every certificate-related operation is recorded in a blockchain storage to ensure integrity and transparency. To regulate communication among nodes, security managers were introduced to enable authorization and access right during communications. Together, these components provide vehicles with an immediately revoked certificate list through RSUs, which are provided with publish/subscribe brokers that enable a controlled messaging infrastructure. We validate our work in a simulated smart highway environment comprising interconnected RSUs to demonstrate our technique's effectiveness.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.116-128
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• 2017

Traffic accidents can be defined as a physical collision event of vehicles occurred instantaneously when drivers do not perceive the surrounding vehicles and roadway environments properly. Therefore, detecting the high potential events that cause traffic accidents with monitoring the interactions among the surroundings continuously by driver is the prerequisite for prevention the traffic accidents. For the analysis, basic data were collected to analyze interactions using a test vehicle which is equipped the GPS(Global Positioning System)-IMU(Inertial Measurement Unit), camera, radar and RiDAR. From the collected data, highway geometric information and the surrounding traffic situation were analyzed and then safety evaluation algorithm for driving vehicle was developed. In order to detect a dangerous event of interaction with surrounding vehicles, locations and speed data of surrounding vehicles acquired from the radar sensor were used. Using the collected data, the tangent and curve section were divided and the driving safety evaluation algorithm which is considered the highway geometric characteristic were developed. This study also proposed an algorithm that can assess the possibility of collision against surrounding vehicles considering the characteristics of geometric road structure. The methodology proposed in this study is expected to be utilized in the fields of autonomous vehicles in the future since this methodology can assess the driving safety using collectible data from vehicle's sensors.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.1
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• pp.47-54
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• 2012

This study analyzed influence factors and the correlation among pollutants which affect occurrence of leaked pollution based on the long-term runoff flow and water quality investigation results to understand the characteristics of highway rainfall runoff pollution load. According to the result of correlation analysis on TSS (Total Suspended Solid) concentration, anteceded dry days, rainfall intensity, traffic volume and etc. as major influence factors of highway rainfall runoff pollution loads, the correlations were weak or scarce in most items. These results might be attributed that runoff pollutant concentration changes vary severely on changes of rainfall intensity and rainfall duration within rainfall and it is affected by disturbances of vehicles and street cleaning and etc. as characteristics of the highway. While Cu, Fe and Zn which are discharged with high concentrations out of heavy metals showed high correlation with particulate matter, organic matter(COD), nutrient(TN, TP), Ni and Pb showed relatively low correlation in a correlation evaluation by pollutant. Significant correlation with traffic volumes was not shown and TSS concentration even decreased in accordance with increase of the traffic volume. In the comparison with precedent studies, it was considered necessary additional analysis of the effects of rainfall section analysis, road type, disturbances of surface contaminants by vehicles, rainfall and climate conditions, surrounding terrains etc.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.183-195
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• 2016

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no non-automotive vehicles or pedestrians, as these would interfere with the results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2228-2234
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• 2000

Steering of the vehicles on a slippery highway is a difficult task for most passenger car drivers. The steering vehicles on slippery roads tend to slide outward with less lateral forces than on nor mal roads. When the drivers notice that their vehicles on a slippery highway start to depart from the cornering lane, most of them make a sudden steering and/or braking, which in turn may induce spin-out and instability on their vehicles. In this paper, an active steering control method is proposed such that the vehicles in slippery roads are steered as if they are driven on the normal roads. In the proposed method, the estimated lateral forces acting on the steering tires are compared with the reference values and the difference is compensated by the active steering method. A fuzzy logic controller is designed for this purpose and evaluated on a steering Hardware-In-the-Loop Simulation (HILS) system. Steering performance results on the slippery curved and sinus roads demonstrate the effectiveness of the proposed controller. This method can be realized with the steer-by-wire concept and is promising as an active safety technology.