Behavioural effects of Advanced Cruise Control Use

 In this study, a meta-analytic approach was used to analyse effects of Advanced Cruise Control (ACC) on driving behaviour reported in seven driving simulator studies. The effects of ACC on three consistent outcome measures, namely, driving speed, headway and driver workload have been analysed. The indicators of speed, headway and workload have been chosen because they are assumed to be directly affected by the ACC support, their relationship with road safety is reasonably established and they are the most frequently used outcome measures in the sample of analysed studies. The results suggest that different operational settings of ACC that are important for the level of support provided by the system, are significant for the effects ACC have on various aspects of driving behaviour, i.e. on mean driving speed and mean time headway. The obtained effect sizes clustered in two groups, with more intervening ACCs having the effects of an increased driving speed and decreased mean time headway. These results are further discussed in the context of road safety, especially in the context of behavioural adaptation

The Adaption Test: The Development of a Method to Measure Speed Adaption to Traffic Complexity

To monitor novice driver performance in the first years of solo driving, a test aimed at assessing speed adaptation to the traffic situation was developed and evaluated. The Adaptation Test consisted of 18 traffic scenes presented in two (almost) identical photographs, which differed in one single detail, increasing the situation’s complexity. The difference in reported speed between the two pictures was used as an indication of drivers’ adaptation of speed to the complexity of the traffic situation. A previous study showed that novice, unsafe and overconfident drivers, as identified in an on-road driving assessment, performed worse on the Adaptation Test (i.e. less often reported a lower speed in the more complex situation). The analysis of new data in this paper shows no correlation between performance on the Adaptation Test and self-reported crashes, and that after two years, experienced drivers had improved their performance on the Adaptation Test just as much as novice drivers

Overestimation of Skills Affects Drivers’ Adaptation to Task Demands

Inadequate self-assessment, and specifically, overestimation of skill, results in insufficient adaptation to task demands, which can manifest itself on different levels of the driving task. A total of 130 drivers (83 novice and 47 experienced drivers) participated in an on-road driving assessment. Their performance in this assessment (i.e., fail or pass) was compared to the participants’ reported confidence in their driving skills (i.e., high or low confidence), resulting in three calibration groups: a) well-calibrated drivers (reported confidence matched performance on assessment), b) overconfident drivers (high confidence but failed assessment) and c) insecure drivers (low confidence but passed assessment). Furthermore, participants completed a questionnaire which focused on choices made on the strategic and manoeuvring level of the driving task. No significant difference was found between the calibration groups for the strategic level. Overconfident drivers reported significantly more violating behaviour than the well-calibrated and the insecure drivers. At the manoeuvring level, overconfident drivers showed significantly less instances of adaptation to traffic complexity. In conclusion, the current study suggests that overconfidence is related to inadequate adaptation to task demands

Enforcement or incentives? Promoting safety belt use among military personnel in the Netherlands

During a nationwide campaign to promote safety belt use among military personnel, a field study was conducted at 12 different military bases in the Netherlands. Amount of enforcement, type of publicity, and incentive strategies were varied among military bases. Observations of safety belt use among servicemen in their personal vehicles were conducted before the campaign, immediately following the campaign, and 3 months later. Safety belt use increased from 65% during baseline to 73% directly after the campaign and to 76% 3 months later. An overall 28.6% increase in safety belt use (from 63% to 81%) was observed at seven bases, whereas no changes were found at five bases (68% on all occasions). To a large degree the effects were due to a 37.7% increase among young drivers. These results confirmed that enforcement, as well as incentives, can be effective in promoting safety belt use. However, treatment effects were not systematic, thereby complicating the interpretation of the results. Implications of these varied outcomes are discussed

Effects of incentive programs to stimulate safety belt use: A meta-analysis

The effects of campaigns using tangible incentives (rewards) to promote safety belt usage have been evaluated by means of a meta-analytic approach. Two coders extracted a total number of 136 short-term and 114 long-term effect sizes and coded many other variables from 34 journal articles and research reports. The results show a mean short-term increase in use rates of 20.6 percentage points; the mean long-term effect was 13.7 percentage points. Large scale studies report smaller effect sizes than small scale studies; when studies were weighted by the (estimated) number of observations, the weighted mean effect sizes were 12.0 and 9.6 percentage points for the short and long term, respectively. The main factors that influence the magnitude of the reported short-term effect of the programs were the initial baseline rate (which was highly correlated with the presence or absence of a safety belt usage law), the type of population involved, whether incentives were delivered immediately or delayed, and whether incentives were based on group or individual behaviour. Together these four variables accounted for 64% of the variance. Other variables, such as the duration of the intervention, the probability of receiving a reward, and the value of the reward were not related to the short-term effect sizes. The relationship between moderating variables and long-term effects was less clear

Frequency, determinants, and consequences of different drivers' emotions:An on-the-road study using self-reports, (observed) behaviour, and physiology

In the present study, the frequency, determinants and consequences of three relevant emotions in traffic were investigated. Based on appraisal theory, it was predicted that the combination of three appraisal components (goal congruence, blame and threat) affects the occurrence of anger, anxiety and happiness. Participants (n = 44) filled in a questionnaire containing background and personality variables, and performed a test drive in an instrumented car. During the drive, speed and heart rate were registered and the traffic environment was recorded on video. Participants verbally reported scores for emotions and perceived risk. The most frequently occurring emotion was anxiety, followed by anger and happiness. Emotions while driving were related to emotional traits. Emotions while driving were also related to traffic events: anger and anxiety were both associated with goal incongruent events, and happiness with goal congruent events. Anger was mostly associated with other-blame and anxiety with situation-blame. Anger was mostly associated with events affecting impeded progress, and anxiety with events affecting safety. Anxiety, but not anger or happiness, was associated with increased perceived risk and with increased heart rate. Participants who reported anger drove faster and exceeded the speed limit more often on a 100 km/road section than participants who did not report anger. These and other results are discussed in terms of appraisal theory and state-trait differences in emotion. (C) 2007 Elsevier Ltd. All rights reserved

Cyclists’ Crossing Intentions When Interacting with Automated Vehicles: A Virtual Reality Study

Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This study aims to determine the main factors influencing cyclists’ crossing intentions when interacting with an automated vehicle as compared to a conventional vehicle (CV) using a 360° video-based virtual reality (VR) method. The considered factors in this study included vehicle type, gap size between cyclist and vehicle, vehicle speed, and right of way. Each factor had two levels. In addition, cyclist’s self-reported behavior and trust in automated vehicles were also measured. Forty-seven participants experienced 16 different crossing scenarios in a repeated measures study using VR. These scenarios are the result of combinations of the studied factors at different levels. In total, the experiment lasted 60 min. The results show that the gap size and the right of way were the primary factors affecting the crossing intentions of the individuals. The vehicle type and vehicle speed did not have a significant effect on the crossing intentions. Finally, the 360° video-based VR method scored relatively high as a research method and comparable with the results of a previous study investigating pedestrians’ crossing intentions confirming its suitability as a research methodology to study cyclists’ crossing intentions

Cyclists' predictions of what a car driver will do next at intersections

This article is part of the Proceedings of the 6th Annual International Cycling Safety Conference held in Davis, California, USA on September 20th through 23rd in the year 2017.<br><br>Paper ID: 7