2013 Session: 550

• Synthesis of State of the Art in Visibility Detection Systems Applications and Research
  Abstract: Visibility is a critical component to the task of driving on all types of roads. The visibility detection and warning systems provide real-time, automated detection as well as appropriate responses to counteract reduced visibility conditions due to fog, heavy rain, snow, smoke, dust or haze by informing drivers of present conditions and lowering the speed limits to match the reduced visibility condition. The objective of this research is to provide a synthesis of visibility detection systems and traffic control techniques that are developed and/or implemented in the US and around the world. This paper provides an overview of the best practices of fixed visibility systems at areas of recurrent dense fog and mobile systems for seasonal visibility reduction for areas of predicted seasonal fog or smoke from wildfires. Ongoing research efforts of developing new camera-based visibility detection systems are also discussed.
  Authors: Ahmed, Mohamed M.; Abdel-Aty, Mohamed A.; Shi, Qi; Abuzwidah, Muamer
  Authors: Ahmed, Mohamed M.; Abdel-Aty, Mohamed A.; Shi, Qi; Abuzwidah, Muamer
  Year: 2013
  Document Type: Paper
  Subject: Design; Operations and Traffic Management; Safety and Human Factors
  Session: 550
  Paper Number: 13-0832
• Measuring and Analyzing Driver's Perception-Reaction Time to Green Phase Based on Digital Image Processing
  Abstract: A method based on digital image processing for measuring drivers¡¯ perception-reaction time (PRT) to the green phase is proposed. The detection of the onset of a green signal is based on the RGB color model. The detection of the start of the vehicle is based on the frame difference. The driver¡¯s perception-reaction time (PRT) is equal to the difference between the frame of the onset of the green signal and the frame of the start of the vehicle divided by the video frame rate. Normal, Lognormal, Gamma and Weibull distributions are used to fit the PRT data. The Chi-Square goodness-of-fit test is conducted to determine how well the distributions fit to the sample data. The results show the Weibull distribution appears to best fit the PRT to the green phase. The fuzzy c-means clustering is utilized for PRTs classification. The PRTs are classified into five classes: ¡°Very fast¡±, ¡°Fast¡±, ¡°Moderate¡±, ¡°Slow¡± and ¡°Very slow¡±. The five clustering centers, which are the typical value of ¡°Very fast¡±, ¡°Fast¡±, ¡°Moderate¡±, ¡°Slow¡± and ¡°Very slow¡±, can be regarded as reference values of drivers¡¯ starting response for microscopic traffic simulation software. The results also show the PRT to the green phase is higher than the brake PRT because of the different urge for the response, limb motion and operation.
  Authors: Li, Zhenlong; Rong, Jian
  Authors: Li, Zhenlong; Rong, Jian
  Year: 2013
  Document Type: Paper
  Subject: Design; Operations and Traffic Management; Safety and Human Factors
  Session: 550
  Paper Number: 13-1624
• Comparison of LED Luminaires for Roadway Lighting Using Object Detection and Color Recognition Distances
  Abstract: This study compared two LED luminaires and their abilities to provide detection distance and color recognition distance of potential roadway hazards. Detection distance is regarded as a metric of visibility. Color recognition distance is a metric for comparing the impact of the CCT (Correlated Color Temperature) of each luminaire and their color contrast impact. Mesopic vision, the mode of vision most commonly used for night driving, was considered in this study. The impacts of luminance and color contrast were addressed in this study. The experiment was performed on the Virginia Smart Road where small wooden targets of different colors and pedestrians wearing different colors were detected by drivers of a moving vehicle in a controlled environment. The key difference between the two luminaires was their color temperatures (3500K versus 6000K). The results indicated that neither light source provided a significant benefit over the other although significant interactions were found among object color, age, and lighting level. The results indicate that the luminaires provide similar luminance contrast but their color contrasts depend heavily on the color temperature, the object, and the observer.
  Authors: Terry, Travis Neal; Gibbons, Ronald B.
  Authors: Terry, Travis Neal; Gibbons, Ronald B.
  Year: 2013
  Document Type: Paper
  Subject: Design; Operations and Traffic Management; Safety and Human Factors
  Session: 550
  Paper Number: 13-2929
• Assessment of Background Complexity of Overhead Guide Signs from Nighttime Digital Images of Roadway Scenes by Image Processing
  Abstract: Researchers have developed a systematic method to assess the background complexity of overhead guide and street name signs under nighttime driving conditions using image processing techniques. These techniques are used to extract image properties such as entropy, contrast, energy, homogeneity, number of saturation pixels, edge ratio, and number of objects, all of which are considered as potential factors for evaluating the background complexity. The researchers combined these factors with image survey ratings by human participants to develop a multivariate linear regression model that could be used by practitioners to evaluate background complexity of overhead guide and street name signs under nighttime conditions. Bootstrapping, a resampling method, was employed to improve the performance of proposed model due to the small samples of the data sets. The empirical results demonstrate that the proposed model has a good performance in the analysis of background complexity of traffic signs with high consistency with ratings from survey participants. It is believed that this model could be used by practitioners to identify potential overhead guide and street name signs that have highly complex backgrounds and may require sign lighting, supplemental signs, and/or relocation to minimize driver difficulty in detecting and obtaining information from the signs.
  Authors: Ge, Hancheng; Zhang, Yunlong; Miles, Jeffrey David; Carlson, Paul J.
  Authors: Ge, Hancheng; Zhang, Yunlong; Miles, Jeffrey David; Carlson, Paul J.
  Year: 2013
  Document Type: Paper
  Subject: Design; Operations and Traffic Management; Safety and Human Factors
  Session: 550
  Paper Number: 13-4305
• Synthesis of State of the Art in Visibility Detection Systems Applications and Research
  Authors: Ahmed, Mohamed
  Authors: Ahmed, Mohamed
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Design; Operations and Traffic Management; Safety and Human Factors
  Session: 550
  Paper Number: 13-0832