Road User Interactions: Patterns of Road Use and Perception of Driving Risk

The goal of the Road User Interactions research programme is a better understanding of the human factors of our road transport system: road user demographics, risk perceptions of road users, and the driving attitudes of various road user groups. Our analysis of the 1989 and 1999 New Zealand Household Travel Surveys identified several fundamental road user differences and consistent demographic trends over the past 10 years. The driver characteristics of gender, age, and area of residence (urban, secondary urban, and rural) are the demographic factors which most clearly differentiate New Zealand road user groups. Analysis of the patterns of road use suggests that, although these road user groups do drive at distinctly different times, there are periods of conflict which are also associated with the greatest crash risk for these drivers. Our analysis of a sample of road user groups in Hamilton, Auckland, Gisborne, New Plymouth, and Palmerston North found significant differences in their perceptions of risk and driving behaviours. Rural drivers and women drivers rated a range of driving situations as having greater risk than did the other road user groups, and they rated the high risk scenarios as being much riskier. Men indicated the greatest willingness to accept the risk in driving situations and rated their own driving skill as higher. Older drivers also rated driving situations as having higher risk, and young drivers generally rated low risk situations much lower than other drivers. In the survey of driving behaviour, young men in our sample reported very high levels of violations and aggressive violations. The male drivers’ rates of violations and aggressive violations were significantly higher than the women drivers’ and the number of both decreased significantly with age. Finally, inspection of crash data show that young drivers’ and older drivers’ crashes have some characteristics in common; both groups have a disproportionate number of crossing, turning, and manoeuvring crashes at intersections in the mid-afternoon

Influencing driver behaviour through road marking

This paper will describe how road marking can be used to influence driver behaviour in order to improve road safety and traffic flows. Extensive use will be made of examples from recent research undertaken by the authors on overtaking lane design, speed change management, managing speed around curves and improving the safety of high risk sections of roads. This research included both on-road and driving simulator-based measurements. The concept of self explaining roads and what is required to implement it will also be described

The effectiveness of delineation treatments

A literature review undertaken for Transit NZ has found that delineation has a significant effect on driver behaviour with, for example, shoulder rumble strips reducing run-off-theroad crashes by between 22% and 80% (average of 32% for all crashes and 44% for fatal run-of-the-road crashes). The concern that enhancing roadway delineation may sometimes be accompanied by an unwanted increase in drivers’ speeds (known as behavioural adaptation) is not borne out by the research and appears to be a phenomenon associated with a few restricted situations (e.g. where a centre line is added to an otherwise unmarked road). The preponderance of the evidence supports the conclusion that profiled edge lines and centre lines provide drivers with positive guidance and produce significant reductions in crashes as a result of improving drivers’ lateral position. Further, unlike other safety measures that show decreased effectiveness over time due to a novelty effect, profiled lane delineation continues to work regardless of driver familiarity. There is no published research to suggest that profiled edge lines will decrease the effectiveness of a profiled centre line or will result in an increase in crash rates or an increase in the severity of crashes. However it has also been noted that local conditions have a major influence on the level of benefits that can be achieved through improved delineation

Research-based Student Selected Components (SSCs)

A presentation on research-based Student Selected Components (SSCs), given at the University of Cambridge on 6-Sept-2023

Does haste make waste? The human factors of overtaking land design

The aim of this research was to improve overtaking safety and efficiency through improvements in road signage, markings, geometry and speed control associated with the placement and layout of passing lanes. The approach of the research was to explore the effects of several types of overtaking lane treatments in the safety and controlled environment of a state-of-the-art driving simulator. It was found that under the most benign conditions there were no differential effects of the three treatments. With poorer visibility or more taxing road geometry, the drivers relied more heavily on the road markings and signage and the effects of the treatments become more pronounced. The sensitivity to the more "challenging" situations was borne out by the greater speed differential between merge area sections at these sites

Robust peak detection for photoplethysmography signal analysis

Efficient and accurate evaluation of long-term photoplethysmography (PPG) recordings is essential for both clinical assessments and consumer products. In 2021, the top opensource peak detectors were benchmarked on the Multi-Ethnic Study of Atherosclerosis (MESA) database consisting of polysomnography (PSG) recordings and continuous sleep PPG data, where the Automatic Beat Detector (Aboy) had the best accuracy. This work presents Aboy++, an improved version of the original Aboy beat detector. The algorithm was evaluated on 100 adult PPG recordings from the MESA database, which contains more than 4.25 million reference beats. Aboy++ achieved an F1-score of 85.5%, compared to 80.99% for the original Aboy peak detector. On average, Aboy++ processed a 1 hour-long recording in less than 2 seconds. This is compared to 115 seconds (i.e., over 57-times longer) for the open-source implementation of the original Aboy peak detector. This study demonstrated the importance of developing robust algorithms like Aboy++ to improve PPG data analysis and clinical outcomes. Overall, Aboy++ is a reliable tool for evaluating long-term wearable PPG measurements in clinical and consumer contexts.Comment: 4 pages, 1 figure, 50th Computing in Cardiology conference in Atlanta, Georgia, USA on 1st - 4th October 202

Influence of photoplethysmogram signal quality on pulse arrival time during polysomnography

Intervals of low-quality photoplethysmogram (PPG) signals might lead to significant inaccuracies in estimation of pulse arrival time (PAT) during polysomnography (PSG) studies. While PSG is considered to be a “gold standard” test for diagnosing obstructive sleep apnea (OSA), it also enables tracking apnea-related nocturnal blood pressure fluctuations correlated with PAT. Since the electrocardiogram (ECG) is recorded synchronously with the PPG during PSG, it makes sense to use the ECG signal for PPG signal-quality assessment. (1) Objective: to develop a PPG signal-quality assessment algorithm for robust PAT estimation, and investigate the influence of signal quality on PAT during various sleep stages and events such as OSA. (2) Approach: the proposed algorithm uses R and T waves from the ECG to determine approximate locations of PPG pulse onsets. The MESA database of 2055 PSG recordings was used for this study. (3) Results: the proportions of high-quality PPG were significantly lower in apnea-related oxygen desaturation (matched-pairs rc = 0.88 and rc = 0.97, compared to OSA and hypopnea, respectively, when p < 0.001) and arousal (rc = 0.93 and rc = 0.98, when p < 0.001) than in apnea events. The significantly large effect size of interquartile ranges of PAT distributions was between low- and high-quality PPG (p < 0.001, rc = 0.98), and regular and irregular pulse waves (p < 0.001, rc = 0.74), whereas a lower quality of the PPG signal was found to be associated with a higher interquartile range of PAT across all subjects. Suggested PPG signal quality-based PAT evaluation reduced deviations (e.g., rc = 0.97, rc = 0.97, rc = 0.99 in hypopnea, oxygen desaturation, and arousal stages, respectively, when p < 0.001) and allowed obtaining statistically larger differences between different sleep stages and events. (4) Significance: the implemented algorithm has the potential to increase the robustness of PAT estimation in PSG studies related to nocturnal blood pressure monitoring

pyPPG: A Python toolbox for comprehensive photoplethysmography signal analysis

Photoplethysmography is a non-invasive optical technique that measures changes in blood volume within tissues. It is commonly and increasingly used for in a variety of research and clinical application to assess vascular dynamics and physiological parameters. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and open tools exist for continuous photoplethysmogram (PPG) analysis. Consequently, the primary objective of this research was to identify, standardize, implement and validate key digital PPG biomarkers. This work describes the creation of a standard Python toolbox, denoted pyPPG, for long-term continuous PPG time series analysis recorded using a standard finger-based transmission pulse oximeter. The improved PPG peak detector had an F1-score of 88.19% for the state-of-the-art benchmark when evaluated on 2,054 adult polysomnography recordings totaling over 91 million reference beats. This algorithm outperformed the open-source original Matlab implementation by ~5% when benchmarked on a subset of 100 randomly selected MESA recordings. More than 3,000 fiducial points were manually annotated by two annotators in order to validate the fiducial points detector. The detector consistently demonstrated high performance, with a mean absolute error of less than 10 ms for all fiducial points. Based on these fiducial points, pyPPG engineers a set of 74 PPG biomarkers. Studying the PPG time series variability using pyPPG can enhance our understanding of the manifestations and etiology of diseases. This toolbox can also be used for biomarker engineering in training data-driven models. pyPPG is available on physiozoo.orgComment: The manuscript was submitted to "Physiological Measurement" on September 5, 202

Acquiring Wearable Photoplethysmography Data in Daily Life:The PPG Diary Pilot Study

The photoplethysmogram (PPG) signal is widely measured by smart watches and fitness bands for heart rate monitoring. New applications of the PPG are also emerging, such as to detect irregular heart rhythms, track infectious diseases, and monitor blood pressure. Consequently, datasets of PPG signals acquired in daily life are valuable for algorithm development. The aim of this pilot study was to assess the feasibility of acquiring PPG data in daily life. A single subject was asked to wear a wrist-worn PPG sensor six days a week for four weeks, and to keep a diary of daily activities. The sensor was worn for 75.0% of the time, signals were acquired for 60.6% of the time, and signal quality was high for 30.5% of the time. This small pilot study demonstrated the feasibility of acquiring PPG data during daily living. Key lessons were learnt for future studies: (i) devices which are waterproof and require charging less frequently may provide signals for a greater proportion of the time; (ii) data should either be stored on the device or streamed via a reliable connection to a second device for storage; (iii) it may be beneficial to acquire signals during the night or during periods of low activity to achieve high signal quality; and (iv) there are several promising areas for PPG algorithm development including the design of pulse wave analysis techniques to track changes in cardiovascular properties in daily life.</p

Comment on 'Numerical assessment and comparison of pulse wave velocity methods aiming at measuring aortic stiffness'

A recent numerical study investigated the potential utility of peripheral PWV measurements for assessing aortic stiffness by simulating pulse wave propagation through the arterial tree. In this Comment we provide additional analysis of the simulations in which arterial compliances were changed. The analysis indicates that relationships between aortic and peripheral pulse transit times (PTTs) may not be constant when compliances change. Consequently, peripheral PWV measurements may have greatest utility in particular clinical settings in which either: an assumption can be made about possible changes in compliance, allowing aortic PTT to be estimated from peripheral PTT; or, one wishes to assess changes in peripheral PWV over time