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The Application of Visual Information into Freeway Operating Speed Prediction Modeling
Operating speed is one of the most important branches in field of Road Safety. Many operating speed prediction models have been presented in the research community, while few take visual information into consideration. It is common sense that the driver's visual information would influence the speed, but it is difficult to be quantified. Based on the features of human vision, this paper proposes a novel concept— Spatial Sight-Distance (SCSD) to quantify the visual information of drivers. An algorithm is presented to compute the SCSD value abstracted from the visual information of drivers on any location of the road. The algorithm mainly takes into account three factors including the horizontal deviation angle limits, vertical deviation angle limits and terrain undulation. Based on the experimental data, the nonlinear relationship between the expecting speed and SCSD is obtained through regression procedure, and finally the operating speed prediction model is established by the point-by-point grade calibration of nonlinear relationship through TWOPAS model. The experiment results show that the operating speed prediction model based on the visual information matches the reality pretty well in the case of free flow. This operating speed prediction model based on visual information will be very useful to the research work on road safety, road safety audit, alignment assessment, accident black-pot discrimination and accident cause analysis etc.
The Application of Visual Information into Freeway Operating Speed Prediction Modeling
Operating speed is one of the most important branches in field of Road Safety. Many operating speed prediction models have been presented in the research community, while few take visual information into consideration. It is common sense that the driver's visual information would influence the speed, but it is difficult to be quantified. Based on the features of human vision, this paper proposes a novel concept— Spatial Sight-Distance (SCSD) to quantify the visual information of drivers. An algorithm is presented to compute the SCSD value abstracted from the visual information of drivers on any location of the road. The algorithm mainly takes into account three factors including the horizontal deviation angle limits, vertical deviation angle limits and terrain undulation. Based on the experimental data, the nonlinear relationship between the expecting speed and SCSD is obtained through regression procedure, and finally the operating speed prediction model is established by the point-by-point grade calibration of nonlinear relationship through TWOPAS model. The experiment results show that the operating speed prediction model based on the visual information matches the reality pretty well in the case of free flow. This operating speed prediction model based on visual information will be very useful to the research work on road safety, road safety audit, alignment assessment, accident black-pot discrimination and accident cause analysis etc.
The Application of Visual Information into Freeway Operating Speed Prediction Modeling
Yang, Zhiqing (author) / Du, Xiaoli (author) / Guo, Zhongyin (author)
Seventh International Conference of Chinese Transportation Professionals Congress (ICCTP) ; 2007 ; Shanghai, China
2008-03-21
Conference paper
Electronic Resource
English
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