Green wave for cyclists: Users' perception and preferences.

Several innovative measures in traffic control applied in Europe have successfully improved the comfort and safety of cycling, among which is the green waves for cyclists. Consecutive traffic lights are synchronised to create a green wave, increasing comfort and decreasing waiting times and related deliberate red-light running. This study focused on exploring the user acceptance of green wave systems and the user evaluation of six distinct interface designs (i.e. numeric-based countdown, dot-based vertical countdown, dot-based clockwise countdown, LED line, LED road surface, on-bike speed indicator). Results indicate a preference for three systems: numeric-based countdown, LED line and LED road surface. Results also show a significant influence of nationality on the evaluation of the interfaces. Based on our findings, we argue that the numeric-based countdown represents the most promising option for future adaptive green wave implementations. The outcomes of the present study represent a useful evidence and guidance for researchers, designers and decision makers in the field of green waves, mobility and traffic safety.

Cardiovascular state changes in simulated work environments.

The usefulness of cardiovascular measures as indicators of changes in cognitive workload has been addressed in several studies. In this paper the question is explored whether cardiovascular patterns in heart rate, blood pressure, baroreflex sensitivity and HRV that are found are consistent within and between two simulated working environments. Two studies, were performed, both with 21 participants: one in an ambulance dispatch simulation and one in a driving simulator. In the ambulance dispatcher task an initial strong increase in blood pressure is followed by a moderate on-going increase in blood pressure during the next hour of task performance. This pattern is accompanied by a strong increase in baroreflex sensitivity while heart rate decreases. In the driving simulator study, blood pressure initially increases but decreases almost to baseline level in the next hour. This pattern is accompanied by a decrease in baroreflex sensitivity, while heart rate decreases. Results of both studies are interpreted in terms of autonomic control (related to both sympathetic and para-sympathetic effects), using a simplified simulation of a baroreflex regulation model. Interpretation of the results leads to the conclusion that the cardiovascular response patterns in both tasks are a combination of an initial defensive reaction, in combination with compensatory blood pressure control. The level of compensatory blood pressure control, however, is quite different for the two tasks. This helps to understand the differences in response patterns between the two studies in this paper and may be helpful as well for understanding differences in cardiovascular response patterns in general. A substantial part of the effects observed during task performance are regulatory effects and are not always directly related to workload manipulations. Making this distinction may also contribute to the understanding of differences in cardiovascular response patterns during cognitive workload.

Short-term cardiovascular measures for driver support: Increasing sensitivity for detecting changes in mental workload.

With on-going increases in traffic density and the availability of more and more in-vehicle technology, driver overload is a growing concern. To reduce the burden of workload on the driver, it is essential that support systems that become available are able to use estimations of drivers' workload. In this paper a short-term cardiovascular approach to assess drivers' mental workload is described using data collected in a driving simulator study. The effects of short lasting increases in task demand (40s) on heart rate and blood pressure and derived variability measures are applied as indicators of mental effort. Fifteen drivers participated in 6 sessions of 1.5h in a driving simulator study. Two traffic density levels (7.5minute segments) were compared in which short-segments (40s) of fog were used to induce additional workload demands. Higher traffic density was reflected in increased systolic blood pressure and decreased blood pressure variability. Heart rate variability and blood pressure variability measures decreased during driving in fog in the low traffic condition, indicating increased effort investment during fog in this condition. The results show that the described short-term measures can be applied to give an indication of cardiovascular reactivity as a function workload.

An adaptive driver support system: user experiences and driving performance in a simulator.

OBJECTIVE: The aim of this study was to test the implementation of an adaptive driver support system. BACKGROUND: Providing support might not always be desirable from a safety perspective, as support may lead to problems related to a human operator being out of the loop. In contrast, adaptive support systems are designed to keep the operator in the loop as much as possible by providing support only when necessary. METHOD: A total of 31 experienced drivers were exposed to three modes of lane-keeping support nonadaptive, adaptive, and no support. Support involved continuously updated lateral position feedback shown on a head-up display. When adaptive, support was triggered by performance-based indications of effort investment. Narrowing lane width and increasing density of oncoming traffic served to increase steering demand, and speed was fixed in all conditions to prevent any compensatory speed reactions. RESULTS: Participants preferred the adaptive support mode mainly as a warning signal and tended to ignore nonadaptive feedback. Furthermore, driving behavior was improved by adaptive support in that participants drove more centrally, displayed less lateral variation and drove less outside the lane's delineation when support was in the adaptive mode compared with both the no-support mode and the nonadaptive support mode. CONCLUSION: A human operator is likely to use machine-triggered adaptations as an indication that thresholds have been passed, regardless of the support that is initiated. Therefore supporting only the sensory processing stage of the human information processing system with adaptive automation may not feasible. APPLICATION: These conclusions are relevant for designing adaptive driver support systems.