The current study aims to obtain knowledge about the nature of the processes involved in Hazard Perception, using measurement techniques to separate and independently quantify these suspected subprocesses: Sensation, Situation Awareness (recognition, location and projection) and Decision-Making. It applies Signal Detection Theory analysis to Hazard Perception and Prediction Tasks. To enable the calculation of Signal Detection Theory parameters, video-recorded hazardous vs. quasi-hazardous situations were presented to the participants. In the hazardous situations it is necessary to perform an evasive action, for instance, braking or swerving abruptly, while the quasi-hazardous situations do not require the driver to make any evasive manoeuvre, merely to carry on driving at the same speed and following the same trajectory. A first Multiple Choice Hazard Perception and Prediction test was created to measure participants' performance in a What Happens Next? Task. The sample comprised 143 participants, 47 females and 94 males. Groups of non-offender drivers (learner, novice and experienced) and offender drivers (novice and experienced) were recruited. The Multiple Choice Hazard Perception and Prediction test succeeded in finding differences between drivers according to their driving experience.In fact, differences exist with regard to the level of hazard discrimination (d' prime) by drivers with different experience (learner, novice and experienced drivers) and profile (offenders and non-offenders) and these differences emerge from Signal Detection Theory analysis. In addition, it was found that experienced drivers show higher Situation Awareness than learner or novice drivers. On the other hand, although offenders do worse than non-offenders on the hazard identification question, they do just as well when their Situation Awareness is probed (in fact, they are as aware as non-offenders of what the obstacles on the road are, where they are and what will happen next). Nevertheless, when considering the answers participants provided about their degree of cautiousness, experienced drivers were more cautious than novice drivers, and non-offender drivers were more cautious than offender drivers. That is, a greater number of experienced and non-offender drivers chose the answer "I would make an evasive manoeuvre such as braking gradually".2

Hazard perception (HP) is the ability to spot on-road hazards in time to avoid a collision. This skill is traditionally measured by recording response times to hazards in video clips of driving, with safer, experienced drivers often out-performing inexperienced drivers. This study assessed whether HP test performance is culturally specific by comparing Chinese, Spanish and UK drivers who watched clips filmed in all three countries. Two test-variants were created: a traditional HP test (requiring timed hazard responses), and a hazard prediction test, where the film is occluded at hazard-onset and participants predict what happens next. More than 300 participants, across the 3 countries, were divided into experienced and inexperienced-driver groups. The traditional HP test did not discriminate between experienced and inexperienced drivers, though participant nationality influenced the results with UK drivers reporting more hazards than Chinese drivers. The hazard prediction test, however, found experienced drivers to out-perform inexperienced drivers. No differences were found for nationality, with all nationalities being equally skilled at predicting hazards. The results suggest that drivers' criterion level for responding to hazards is culturally sensitive, though their ability to predict hazards is not. We argue that the more robust, culturally-agnostic, hazard prediction test appears better suited for global export.

The aim of this work was to explore the effect of Proactive Listening to a Training Commentary, using the recently developed version of the Spanish Hazard Perception test. Firstly, 16 videos were used in the pre-test session in its short version, cut to black just before the hazard appearance. The What Happens Next Assessment (at the pre-test stage) generates expectations about the outcome of the traffic situation. Then, the training (8 minutes in length) uses the complete version of the same 16 videos, revealing the hazards unfolding. It involves listening to a voice with relevant information about where to allocate attention in the complex driving scene in order to recognise and anticipate the hazard successfully. A total of 121 participants were included in this study The sample consisted of learner, novice and experienced drivers, including re-offender and non-offender drivers. The participants were divided into 2 groups: a trained and an untrained group. Two assessment times were used: pre-test (16 videos) and post-test sessions (another 16 videos). The test presented a high internal consistency (Alpha = 0.875). This training shows significant positive effects for all types and groups of participants. No significant differences were found between the non-offender and the offender groups. Performance in gradual-onset hazard events can be improved after training but also by practice; however this training is essential and especially beneficial for training the ability to detect hazards that appear abruptly (which seems to be difficult to improve just by practice).

Detecting danger in the driving environment is an indispensable task to guarantee safety which depends on the driver's ability to predict upcoming hazards. But does correct prediction lead to an appropriate response? This study advances hazard perception research by investigating the link between successful prediction and response selection. Three groups of drivers (learners, novices and experienced drivers) were recruited, with novice and experienced drivers further split into offender and non-offender groups. Specifically, this works aims to develop an improved Spanish Hazard Prediction Test and to explore the differences in Situation Awareness, (SA: perception, comprehension and prediction) and Decision-Making ("DM") among learners, younger inexperienced and experienced drivers and between driving offenders and non-offenders. The contribution of the current work is not only theoretical; the Hazard Prediction Test is also a valid way to test Hazard Perception. The test, as well as being useful as part of the test for a driving license, could also serve a purpose in the renewal of licenses after a ban or as a way of training drivers. A sample of 121 participants watched a series of driving video clips that ended with a sudden occlusion prior to a hazard. They then answered questions to assess their SA ("What is the hazard?" "Where is it located?" "What happens next?") and "DM" ("What would you do in this situation?"). This alternative to the Hazard Perception Test demonstrates a satisfactory internal consistency (Alpha=0.750), with eleven videos achieving discrimination indices above 0.30. Learners performed significantly worse than experienced drivers when required to identify and locate the hazard. Interestingly, drivers were more accurate in answering the "DM" question than questions regarding SA, suggesting that drivers can choose an appropriate response manoeuvre without a totally conscious knowledge of the exact hazard. AcknowledgmentsWe are grateful to the Spanish participants who volunteered for the tests as well as to the two anonymous reviewers whose comments enabled us to improve the manuscript and to our English editor Barbara Lamplugh for revising and improving the English. We are also indebted to the Junta de Andalucía (Proyecto Motriz P11-SEJ-7404), the BS-14-164 I+D+I Research project from the CEI-Biotic, University of Granada and the Spanish Government, MICINN (PSI2013-42729-P), all of whom gave us financial support. This research was supported by the Spanish Dirección General de Tráfico -DGT (0100DGT21263 and SPIP2015-01782) and the three driving schools in Granada (Autoescuelas la Victoria, Luna and Genil) from whom we obtained our sample of participants. We much appreciate their contribution to the study. We gratefully acknowledge financial support from the computational resources supplied by the Centro de Servicios de Informática y Redes de Comunicaciones (CSIRCUniversidad de Granada). Its design, data collection, analysis and interpretation were carried out independently of the f...

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