• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.4
• /
• pp.71-82
• /
• 2020

Traffic accidents due to excessive speed frequently occur in places where traffic signal controllers are installed, places where sharp curves exist, or places where the traffic signal cycle does not match the current time. These traffic accidents cause economic loss due to the destruction of road facilities and structures, and cause a big problem of increasing the number of traffic accident deaths. When a traffic accident occurs, leaving a tire mark before or after a car crash, pre-collision speed of the car is calculated using the law of conservation of momentum or the skid mark formula. In the skip skid mark generated in ABS brake vehicles and the combshaped yaw mark generated by tire trace caused by lateral sliding, there is a difference of 30-40% in the reliability of the vehicle speed calculated by the smite mark. In this paper, we propose an algorithm that can improve the calculation reliability in vehicle speed by using skid marks in order to compensate for this problem. In addition, we present an intelligent speed calculation algorithm for traffic safety and a computer simulation in order to prevent traffic accidents by estimating the speed of a vehicle, using Skid marks, Yaw marks, and ABS brake characteristics and fuzzy rules.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.1
• /
• pp.125-132
• /
• 2012

In this paper, We proposes FE-SM/SONN for recognizing blurred and smeared skid mark image caused by sudden braking of a vehicle. In a blurred and smeared skid marks, tread pattern image is ambiguous. To improve recognition of such image, FE-SM/SONN reads skid marks utilizing Fuzzy Logic and distinguishing tread pattern SONN(Self Organization Neural Networks) recognizer. In order to substantiate this finding, 48 tire models and 144 skid marks were compared and overall recognition ratio was 89%. This study showed 13.51% improved recognition compared to existing back propagation recognizer, and 8.78% improvement than FE-MCBP. The expected effect of this research is achieving recognition of ambiguous images by extracting distinguishing features, and the finding concludes that even when tread pattern image is in grey scale, Fuzzy Logic enables the tread pattern recognizable.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.12
• /
• pp.55-63
• /
• 2003

The traffic accident is the prerequisite of the traffic accident reconstruction. In this study, the traffic accident (forward collision) and traffic accident reconstruction (inverse collision) simulations are conducted to improve the quality and accuracy of the traffic accident reconstruction. The vehicle and tire models are used to simulate the trajectories for the post-impact motion of the vehicles after collision. The impact dynamic model applicable to the forward and inverse collision simulations is also provided. The accuracy of impact analysis for the vehicular collision depends on the accuracy of the coefficients of restitution and friction. The neural network is used to estimate these coefficients. The forward and inverse collision simulations for the multi-collisions are conducted. The new method fur the accident reconstruction is proposed to calculate the pre-impact velocities of the vehicles without using the trial and error process which requires the repeated calculations of the initial velocities until the forward collision simulation satisfies with the accident evidences. This method estimates the pre-impact velocities of the vehicles by analyzing the trajectories of the vehicles. The vehicle slides on a road surface not only under the skidding during an emergency braking but also under the steering. A vehicle over steering or cornering with excessive speed loses the traction and leaves tile yaw marks on the road surface. The new critical speed formula based on the vehicle dynamics is proposed to analyze the yaw marks and shows smaller errors than ones of the existing critical speed formula.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.15 no.2
• /
• pp.109-114
• /
• 2007

Skid mark and coefficient of friction are usually utilized to calculate the velocity and behavior of vehicles. For a critical case such as traffic accident reconstruction, however, the initial velocity of the car should be calculated precisely. In this study, the skid marks on dry asphalt pavement were measured, and the velocity at brake onset was precisely recovered. A passenger car with new tires and non-contact optical speedometer were set up for the tests. A new methodology to determine the more precise velocity for Non-ABS vehicle at braking onset were suggested.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2004.11a
• /
• pp.561-564
• /
• 2004

Crack sealing automation machines' have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). It is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose a crack network mapping and modeling algorithm using neural network for improving the accuracy of the algorithm used in the APCS. It is anticipated that the effective use of the proposed algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Korean Journal of Construction Engineering and Management
• /
• v.5 no.2 s.18
• /
• pp.90-105
• /
• 2004

Machines for crack sealing automation have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). Moreover, it is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose machine vision algorithms (digital image processing algorithm and path planning algorithm) for fully automated pavement crack sealing. It is anticipated that the effective use of the proposed machine vision algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Journal of Korean Society of Transportation
• /
• v.28 no.1
• /
• pp.87-96
• /
• 2010

The impact speed estimation practice used in the car-bicycle accident analysis practice in Korea was mainly dependent on foreign study results which were tested with limited speed ranges and vehicle types, but the characteristics of roadway, human body, and vehicle performance were quite different. This study developed an impact speed estimation model using the car-bicycle accident field data. For this, a regression analysis was performed using the impact speed and bicycle throw distance collected from 23 real accident data, and statistical test was also conducted. For the verification of the induced model, the impact speeds derived from the model were compared with the true impact speeds estimated from skid marks of two accident cases. The result showed that the two speeds were very close to each other. It is believed that the model could be included in the car-bicycle accident analysis practice.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.6D
• /
• pp.587-597
• /
• 2010

When a car accident occurs, people who had an accident are not free from civil and criminal issues so that the accident investigator should reenact and analyze the accident situation accurately. In addition, the obtained documents through the analysis of such car accident occurrence and related factors have to be used to carry out the improvement of the areas that has numerous car accidents and complementary actions. The vehicle speed, accelerating force, braking power are currently known as the most affecting factors in accordance with many car accidents, traffic facilities, road design, etc. The vehicle's performance and rode friction coefficient road surface friction coefficient are affecting the most closely in this field. Especially, once the estimate of the speed of the accident moment relating to main eleven articles of Traffic Accident Exemption Law is very important and accuracy is required. However, currently the researches of these matters have not made exclusively yet in Korea. In this study by reflecting this current situation, until the sudden braking history is found from the car's sudden braking, it estimates accurately the transient brake time and rode friction coefficient by measuring a time of transient brake time through the precision speed detector (Vericom VC2000PC). The analysis of the experimental results calculated the transient brake time and friction coefficient to fit into the purpose of this study in the basis of different kind of various special purpose asphalt pavement and slip-prevention pavement and provided the fundamental data.