Chunjiao Dong

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To address the dilemma between the need for truck transportation and the costs related to truck-involved crashes, the key is to identify the risk factors that significantly affect truck-involved crashes. The objective of this research is to estimate the effects of the characteristics of traffic, driver, geometry, and environment on severity of(More)
Scavenger receptor class A, member 5 (SCARA5) is a member of the scavenger receptor family, and is involved in several types of human malignancy; however, its roles in osteosarcoma (OS) remain to be fully elucidated. Therefore, in the present study, the biological functions of SCARA5 in OS, and the potential underlying mechanisms were investigated. SCARA5(More)
Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up(More)
OBJECTIVE Crash injury results from complex interaction among factors related to at-fault driver's behavior, vehicle characteristics, and road conditions. Identifying the significance of these factors which affect crash injury severity is critical for improving traffic safety. A method was developed to explore the relationship based on crash data collected(More)
Applying image processing technologies to pedestrian detection has been a hot research topic in Intelligent Transportation Systems (ITS). However, the existing video-based algorithms to extract background image may suffer their inefficiency in detecting slow or static pedestrians. To fill the gap, an improved Gaussian Mixture Model (GMM) for pedestrian(More)
In crash frequency studies, correlated multivariate data are often obtained for each roadway entity longitudinally. The multivariate models would be a potential useful method for analysis, since they can account for the correlation among the specific crash types. However, one issue that arises with this correlated multivariate data is the number of zero(More)
Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is(More)
The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle(More)
This paper has presented a novel approach designed to realize multi-section short-term traffic flow synchronization forecasting in terms of road network. First, the road network is split into sub networks in accordance with traffic flow spatial-temporal characteristics. Second, chaos analysis method is proposed to forecast short-term traffic flow.(More)