Spatio-temporal accident analysis for accident prevention in relation to behavioral factors in driving: The case of South Anatolian Motorway

Analyzing the pattern of traffic accidents on road segments can highlight the hazardous locations where the accidents occur frequently and help to determine problematic parts of the roads. The objective of this paper is to utilize accident hotspots to analyze the effect of different measures on the behavioral factors in driving. Every change in the road and its environment affects the choices of the driver and therefore the safety of the road itself. A spatio-temporal analysis of hotspots therefore can highlight the road segments where measures had positive or negative effects on the behavioral factors in driving. In this paper 2175 accidents resulted in injury or death on the South Anatolian Motorway in Turkey for the years between 2006 and 2009 are considered. The network-based kernel density estimation is used as the hotspot detection method and the K-function and the nearest neighbor distance methods are taken into account to check the significance of the hotspots. A chi-square test is performed to find out whether temporal changes on hotspots are significant or not. A comparison of characteristics related driver attributes like age, experience, etc. for accidents in hotspots vs. accidents outside of hotspots is performed to see if the temporal change of hotspots is caused by structural changes on the road. For a better understanding of the effects on the driver characteristics, the accidents are analyzed in five groups based on three different grouping schemes. In the first grouping approach, all accident data are considered. Then the accident data is grouped according to direction of the traffic flow. Lastly, the accident data is classified in terms of the vehicle type. The resultant spatial and temporal changes in the accident patterns are evaluated and changes on the road structure related to behavioral factors in driving are suggested.     

The conscious experience of color constancy and neural responses to subliminal deviations – A behavioral and EEG/ERP oddball study

IntroductionColor constancy, a property of conscious color experience, maintains object color appearance across illuminant changes. We investigated the neural correlates of subliminal vs. conscious stimulus deviations of color constancy manipulations.MethodsBehavioral and Oddball EEG/ERP experiments were conducted (n = 20). Psychophysical illuminant variation discrimination thresholds were first estimated, to establish individual perceptual awareness ranges, allowing for simulation of natural daylight spectral and spatial variations on colored surfaces, at different ambiguity levels.ResultsBehavioral results validated illuminant choice. ERPs showed a significant modulation of posterior P1 component specifically for the subliminal global uniform deviation condition, respecting color constancy. Neural correlates of conscious percepts were identified at posterior N2-P3 latencies, parietal (P3b) and frontal regions.ConclusionsWe identified an early subliminal correlate of low-level illuminant change, which reflects automatic unconscious detection of global color constancy deviations. Its suppression under conscious perception is probably due to top-down suppression according to prediction error models.