A novel signal processing technique for vehicle detection radar

Park, Soo‐Jin; Kim, Tae Yong; Kang, Sung Min; Koo, Kyung Heon

doi:10.1109/mwsym.2003.1211012

Cited by 43 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This scheme showed good simulation results, but its practical demonstration was not provided. Another study [167] developed a radar-based driver safety system for an actual multi-lane system using discrete time signal processing. With 200 classification tests, a high accuracy of 90% was achieved for vehicle speed detection.…”

Section: Driving Environment-focused Studies and Systemsmentioning

confidence: 99%

A Comprehensive Survey of Driving Monitoring and Assistance Systems

Khan

Lee

2019

Sensors

156

View full text Add to dashboard Cite

Improving a vehicle driver’s performance decreases the damage caused by, and chances of, road accidents. In recent decades, engineers and researchers have proposed several strategies to model and improve driving monitoring and assistance systems (DMAS). This work presents a comprehensive survey of the literature related to driving processes, the main reasons for road accidents, the methods of their early detection, and state-of-the-art strategies developed to assist drivers for a safe and comfortable driving experience. The studies focused on the three main elements of the driving process, viz. driver, vehicle, and driving environment are analytically reviewed in this work, and a comprehensive framework of DMAS, major research areas, and their interaction is explored. A well-designed DMAS improves the driving experience by continuously monitoring the critical parameters associated with the driver, vehicle, and surroundings by acquiring and processing the data obtained from multiple sensors. A discussion on the challenges associated with the current and future DMAS and their potential solutions is also presented.

show abstract

Section: Driving Environment-focused Studies and Systemsmentioning

confidence: 99%

A Comprehensive Survey of Driving Monitoring and Assistance Systems

Khan

Lee

2019

Sensors

156

View full text Add to dashboard Cite

show abstract

“…For intelligent traffic management, accurate and efficient detection of traffic flow is crucial. The five primary categories that classify traffic detection technologies are radar [ 3 , 4 ], infrared [ 5 , 6 ], magnetic [ 7 , 8 ], video [ 9 , 10 ], and wireless sensor network detection technology [ 11 , 12 ]. However, conventional detection methods possess particular limitations.…”

Section: Introductionmentioning

confidence: 99%

Traffic Vibration Signal Analysis of DAS Fiber Optic Cables with Different Coupling Based on an Improved Wavelet Thresholding Method

et al. 2023

Sensors

View full text Add to dashboard Cite

Distributed Acoustic Sensing (DAS) is a novel technology that uses fiber optics to sense and monitor vibrations. It has demonstrated immense potential for various applications, including seismology research, traffic vibration detection, structural health inspection, and lifeline engineering. DAS technology transforms long sections of fiber optic cables into a high−density array of vibration sensors, providing exceptional spatial and temporal resolution for real−time monitoring of vibrations. Obtaining high−quality vibration data using DAS requires a robust coupling between the fiber optic cable and the ground layer. The study utilized the DAS system to detect vibration signals generated by vehicles operating on the campus road of Beijing Jiaotong University. Three distinct deployment methods were employed: the uncoupled fiber on the road, the underground communication fiber optic cable ducts, and the cement−bonded fixed fiber optic cable on the road shoulder, and compared for their outcomes. Vehicle vibration signals under the three deployment methods were analyzed using an improved wavelet threshold algorithm, which was verified to be effective. The results indicate that for practical applications, the most effective deployment method is the cement−bonded fixed fiber optic cable on the road shoulder, followed by the uncoupled fiber on the road, and the underground communication fiber optic cable ducts are the least effective. This has important implications for the future development of DAS as a tool for various fields.

show abstract

“…Hence, in order to guarantee a greater safety-level with respect to environmental conditions [3,4,16,17], it is necessary to account for their effect since from the very beginning of the ADAS design phase, introducing advanced control strategies that could leverage both real-time measurements, coming from different in-vehicles sensors (camera, radar, lidar and combinations of those via sensor-based fusion techniques [18][19][20][21]), and on-board environmental estimation modules. Indeed, the use of only sensors' measurements could be not enough to perceive properly the external environment, since the vehicle control system has also to predict and discern how heavy rain, snow, ice condition or road singularities (e.g., oil stains, puddles, holes, or disconnected cobblestone) could impact on safety, so that the driving policy is to be tuned according to the actual environmental adversities.…”

Section: Introductionmentioning

confidence: 99%

On-Board Road Friction Estimation Technique for Autonomous Driving Vehicle-Following Maneuvers

et al. 2021

View full text Add to dashboard Cite

In recent years, autonomous vehicles and advanced driver assistance systems have drawn a great deal of attention from both research and industry, because of their demonstrated benefit in reducing the rate of accidents or, at least, their severity. The main flaw of this system is related to the poor performances in adverse environmental conditions, due to the reduction of friction, which is mainly related to the state of the road. In this paper, a new model-based technique is proposed for real-time road friction estimation in different environmental conditions. The proposed technique is based on both bicycle model to evaluate the state of the vehicle and a tire Magic Formula model based on a slip-slope approach to evaluate the potential friction. The results, in terms of the maximum achievable grip value, have been involved in autonomous driving vehicle-following maneuvers, as well as the operating condition of the vehicle at which such grip value can be reached. The effectiveness of the proposed approach is disclosed via an extensive numerical analysis covering a wide range of environmental, traffic, and vehicle kinematic conditions. Results confirm the ability of the approach to properly automatically adapting the inter-vehicle space gap and to avoiding collisions also in adverse road conditions (e.g., ice, heavy rain).

show abstract

A novel signal processing technique for vehicle detection radar

Cited by 43 publications

References 4 publications

A Comprehensive Survey of Driving Monitoring and Assistance Systems

A Comprehensive Survey of Driving Monitoring and Assistance Systems

Traffic Vibration Signal Analysis of DAS Fiber Optic Cables with Different Coupling Based on an Improved Wavelet Thresholding Method

On-Board Road Friction Estimation Technique for Autonomous Driving Vehicle-Following Maneuvers

Contact Info

Product

Resources

About