We tested the prototype willingness model (PWM). The participants (N=198) completed online questionnaire measures of PWM constructs (time 1) and subsequent speeding behaviour (time 2). Path analyses showed that the PWM accounted for 89% of the variance in subsequent (self-reported) speeding behaviour. This significantly exceeded the variance accounted for by the theory of planned behaviour. In line with the PWM, both behavioural intention and behavioural willingness had direct effects on behaviour. Behavioural willingness had a significantly larger effect. Attitude and subjective norm both had indirect effects on behaviour through both behavioural intention and behavioural willingness. Prototype (similarity) perceptions had indirect effects on behaviour through behavioural willingness only. The findings support the notion that driving is governed by reactive decision-making (willingness), underpinned by prototype perceptions, attitudes and subjective norms, to a greater extent than it is deliberative decision-making (intentions), underpinned by attitudes and subjective norms. The implications for safety interventions are discussed

Implementation intentions (if-then plans) exert conditional effects on behavior, meaning that their ability to change behavior is conditional upon encountering the critical situation specified in the if component of the plan. In the present study, we tested whether implementation intentions can exert unconditional effects on behavior. Consistent with the process of operant generalization, we hypothesized that implementation intentions would change behavior, not only in situations that are contextually identical to those specified in the if component but also in contextually similar situations. Implementation intentions were not expected to generate behavior-change in contextually different situations to those specified. Participants (N = 139) completed questionnaires measuring speeding behavior and motivation to speed. Experimental participants then specified implementation intentions to avoid speeding in critical situations that were contextually identical, similar, or different to those subsequently encountered on a driving simulator. Control participants received educational information about the risks of speeding. All participants then drove on a driving simulator. Consistent with the hypotheses participants in both the contextually identical and similar conditions exceeded the speed limit less frequently than did controls. There was no difference in speeding behavior between the contextually different and control conditions. Implications of the findings for behavior-change are discussed.

The widespread day-to-day carrying of powerful smartphones gives opportunities for crowd-sourcing information about the users' activities to gain insight into patterns of use of a large population in cities. Here we report the design and initial investigations into a crowdsourcing approach for sudden decelerations to identify dangerous road sections. Sudden brakes and near misses are much more common than police reportable accidents but under exploited and have the potential for more responsive reaction than waiting for accidents. We also discuss different multimodal feedback conditions to warn drivers approaching a dangerous zone. We believe this crowdsourcing approach gives cost and coverage benefits over infrastructural smart-city approaches but that users need incentivized for use

Bidimensional attitudes have been shown to independently predict behaviour, with the positive dimension of attitude being a stronger predictor of behaviour than the negative dimension (e.g., Elliott, Brewster, et al., 2015, Br. J. Psychol, 106, 656). However, this positivity bias has been demonstrated with explicit attitude measures only and explicit attitude measures tap deliberative processes rather than automatic processes, which are known to be important in the execution of many behaviours. The aim of this study was to test whether implicit bidimensional attitudes can account for variance in speeding behaviour over and above explicit bidimensional attitudes and whether the positivity bias that is typically found with explicit attitudes generalizes to implicit attitudes. A total of 131 drivers completed a questionnaire measuring their explicit bidimensional attitudes towards speeding. They also completed Implicit Association Tests measuring their implicit bidimensional attitudes. Two weeks later, speeding behaviour was measured using a driving simulator. Explicit attitudes accounted for a significant proportion of the variance in subsequent speeding behaviour. Implicit attitudes accounted for a statistically significant increment to explained variance. The positive dimension of both explicit and implicit attitudes predicted speeding behaviour but the negative dimensions did not. Theoretical implications for understanding the potential attitudinal causes of behaviour and practical implications for behaviour‐change interventions are discussed.

Positive and negative attitude dimensions (i.e., bi-dimensional attitudes) asymmetrically predict behaviour, with the positive dimension being the better predictor than the negative dimension. These findings have been demonstrated using self-reported behaviour measures. In this study, we aimed to test the bi-dimensional attitude-behaviour relationship using objectively measured speeding behaviour derived from a driving simulator and test if the asymmetrical prediction of behaviour from the positive and negative attitude dimensions could be explained by attitude accessibility (how available an attitude is in memory and therefore how readily it is able to guide behaviour). One hundred and six drivers completed online measures of the positive and negative dimensions of their attitudes towards exceeding the speed limit. Response latency measures of the accessibilities of both dimensions were also taken. A driving simulator was used to measure speeding behaviour. Both attitude dimensions independently predicted speeding, with the positive dimension being the stronger predictor. The positive attitude dimension was also more accessible than was the negative dimension. The difference in the accessibilities of the positive and negative attitude dimensions significantly mediated the difference in their predictive validities. The results demonstrate that the positive attitude dimension is the principle predictor of speeding and a reason for this is that it is more accessible in memory than is the negative attitude dimension. Road safety interventions (e.g., education) that aim to reduce speeding and associated traffic crashes might usefully decrease the valence or accessibility of the positive attitude dimension. There would also appear to be scope to reduce speeding by increasing the valence or accessibility of the negative attitude dimension.