Understanding the role of self-identity in habitual risky behaviours: pedestrian road-crossing decisions across the lifespan

Self-identity as a careful pedestrian has not been fully considered in previous work on predicting intention to cross the road, or actual crossing behaviour, in non-optimal situations. Evidence suggests that self-identity may be a better predictor than attitudes in situations where decision-making styles have become habitual ways to respond. This study compared contributions of self-identity and attitudes to the prediction of intentions in two situations differing in level of habitual crossing expectation, and to crossing behaviour. Three hundred and sixty-two adults (17–92 years) completed a questionnaire measuring self-identity, attitudes, intentions, experience, social identity variables (e.g. age, gender) and personal limitations (mobility). Two hundred and five participants also completed a road-crossing simulation. Self-identity and attitude were both shown as significant independent predictors of intention in both situations. However, self-identity was less effective as a predictor in the higher risk scenario, where intention to perform the behaviour was lower, and for participants aged >75 years who had lower intention across scenarios. Self-identity strongly predicted intention to cross, which in turn predicted behaviour, but self-identity did not directly predict behaviour. Self-identity was strongly predicted by age. Implications for theories of compensation in older age and for design and targeting of pedestrian safety education are discussed.

Low level feature detection in human vision

Influential models of edge detection have generally supposed that an edge is detected at peaks in the 1st derivative of the luminance profile, or at zero-crossings in the 2nd derivative. However, when presented with blurred triangle-wave images, observers consistently marked edges not at these locations, but at peaks in the 3rd derivative. This new phenomenon, termed ‘Mach edges’ persisted when a luminance ramp was added to the blurred triangle-wave. Modelling of these Mach edge detection data required the addition of a physiologically plausible filter, prior to the 3rd derivative computation. A viable alternative model was examined, on the basis of data obtained with short-duration, high spatial-frequency stimuli. Detection and feature-making methods were used to examine the perception of Mach bands in an image set that spanned a range of Mach band detectabilities. A scale-space model that computed edge and bar features in parallel provided a better fit to the data than 4 competing models that combined information across scale in a different manner, or computed edge or bar features at a single scale. The perception of luminance bars was examined in 2 experiments. Data for one image-set suggested a simple rule for perception of a small Gaussian bar on a larger inverted Gaussian bar background. In previous research, discriminability (d’) has typically been reported to be a power function of contrast, where the exponent (p) is 2 to 3. However, using bar, grating, and Gaussian edge stimuli, with several methodologies, values of p were obtained that ranged from 1 to 1.7 across 6 experiments. This novel finding was explained by appealing to low stimulus uncertainty, or a near-linear transducer.