Using SHRP2 NDS data to examine infrastructure and other factors contributing to older driver crashes during left turns at signalized intersections

Modeling temporal correlation and heterogeneity in real-time conflict rates using Bayesian Tobit models for signalized intersections

The use of real-time traffic conflicts for safety studies provide more insight into how important dynamic signal cycle-related characteristics can affect intersection safety. However, such short-time window for data collection raises a critical issue that the observed conflicts are temporally correlated. As well, there is likely unobserved heterogeneity across different sites that exist in conflict data. The objective of this study is to develop real-time traffic conflict rates models simultaneously accommodating temporal correlation and unobserved heterogeneity across observations. Signal cycle level traffic data, including traffic conflicts, traffic and shock wave characteristics, collected from six signalized intersections were used. Three types of Tobit models: conventional Tobit model, temporal Tobit (T-Tobit) model, and temporal grouped random parameters (TGRP-Tobit) model were developed under full Bayesian framework. The results show that significant temporal correlations are found in T-Tobit models and TGRP-Tobit models, and the inclusion of temporal correlation considerably improves the goodness-of-fit of these Tobit models. The TGRP-Tobit models perform best with the lowest Deviance Information Criteria (DIC), indicating that accounting for the unobserved heterogeneity can further improve the model fit. The parameter estimates show that real-time traffic conflict rates are significantly associated with traffic volume, shock wave area, shock wave speed, queue length, and platoon ratio.

Rethinking infrastructure design: evaluating pedestrians and VRUs' psychophysiological and behavioral responses to different roadway designs

The integration of human-centric approaches has gained more attention recently due to more automated systems being introduced into our built environments (buildings, roads, vehicles, etc.), which requires a correct understanding of how humans perceive such systems and respond to them. This paper introduces an Immersive Virtual Environment-based method to evaluate the infrastructure design with psycho-physiological and behavioral responses from the vulnerable road users, especially for pedestrians. A case study of pedestrian mid-block crossings with three crossing infrastructure designs (painted crosswalk, crosswalk with flashing beacons, and a smartphone app for connected vehicles) are tested. Results from 51 participants indicate there are differences between the subjective and objective measurement. A higher subjective safety rating is reported for the flashing beacon design, while the psychophysiological and behavioral data indicate that the flashing beacon and smartphone app are similar in terms of crossing behaviors, eye tracking measurements, and heart rate. In addition, the smartphone app scenario appears to have a lower stress level as indicated by eye tracking data, although many participants do not have prior experience with it. Suggestions are made for the implementation of new technologies, which can increase public acceptance of new technologies and pedestrian safety in the future.

A Longitudinal Study Examining Self-Regulation Practices in Older Drivers with and without Suspected Mild Cognitive Impairment

Purpose

Mild cognitive impairment can impact driving performance and self-regulation practices. However, there is little evidence on how cognitive impairment may impact these self-regulation practices over a period of time. Therefore, the aim of this study was to examine changes in the number and type of situations in which older drivers with and without suspected mild cognitive impairment (MCI) self-regulate their driving over a one-year period, after accounting for relevant confounders.

Participants and Methods

A longitudinal cohort study involving older drivers (65+ years) from metropolitan Western Australia was interviewed by a telephone interview at baseline and one-year follow-up. The Telephone Cognitive Screen (T-CogS) was also administered to determine changes in their cognitive status. The outcome of interest was the number and type of situations older drivers self-regulated their driving.

Results

A total of 670 drivers were interviewed at baseline (suspected MCI: n = 227; no cognitive impairment: n = 443) and one-year follow-up (suspected MCI: n = 251; no cognitive impairment: n = 419), which provided 1340 observations. Drivers with suspected MCI increased the number of driving situations in which they self-regulated by 13% over a period of one-year compared with drivers without cognitive impairment (IRR = 1.13, 95% CI = 1.02–1.27, p = 0.025). Specifically, drivers with suspected MCI had 60% increased odds of self-regulating when “making turns across oncoming traffic” compared with drivers without cognitive impairment (unadjusted OR = 1.60, 95% CI = 1.02–2.53, p = 0.041). Other significant factors included being female (IRR = 1.87, 95% = 1.52–2.32, p = 0.001), aged 75+ years (IRR = 1.33, 95% CI = 1.10–1.60, p = 0.003), higher number of comorbidities (1–3 comorbidities: IRR = 1.26, 95% CI = 1.01–1.58, p = 0.040; 4+ comorbidities: IRR = 1.39, 95% CI = 1.08–1.78, p = 0.011), “decreased driving confidence” (IRR = 1.32, 95% CI = 1.10–1.58, p-value = 0.003) and “preference of having someone else drive” (IRR = 1.38, 95% CI = 1.12–1.70, p = 0.003). Having one or more traffic infringements was also associated with a decrease in the number of self-regulated driving situations (IRR = 0.80, 95% CI = 0.67–0.95, p = 0.011).

Conclusion

Over a one-year period, drivers with suspected MCI increased the number of situations in which they self-regulated their driving compared with drivers without cognitive impairment, particularly when “making turns across oncoming traffic”. Future studies should examine whether this increase in the types and number of self-regulated driving situations is enough to compensate for declines in cognition.

Older Driver Safety: A Renewed Perspective in a Survey Study in Illinois, U.S

Older adults (aged 65 or older) are at higher risk of involvement in motor vehicle crashes. Many studies have been conducted on older road users’ safety, but how older people’s driving behavior and demographic characteristics, and warnings of side effects of prescription medication, are associated with their crash risk has not been fully investigated. Aimed to address this knowledge gap, a mail survey of older drivers in Illinois, U.S. was conducted. Information on respondents’ driving behaviors, demographic characteristics, physical conditions, medication use, crash experience, etc. was gathered. Response distributions, odds ratios, and logistic regression models were employed to analyze the survey data. The results showed that most respondents kept a high level of mobility despite driving difficulty and medication use. Older drivers’ crash risk is mainly affected by external factors (driving exposure, alcohol consumption, and medication use) rather than their demographic characteristics and driving difficulty. Warnings from physicians on the side effects of prescription drugs had no significant effects on older drivers’ crash risk. Given the importance of mobility to older adults, the focus needs to be placed on providing a safe roadway system and safe driving advice for older drivers, particularly those who are on medication.

Left Turns by Older Drivers With Vision Impairment: A Naturalistic Driving Study

BACKGROUND AND OBJECTIVES

Older drivers are overrepresented in collisions at intersections while making left turns across oncoming traffic. Using naturalistic driving methods, we evaluated the association between vision impairment and their left-turn characteristics.

RESEARCH DESIGN AND METHODS

In this prospective, observational study, vision impairment as defined by visual acuity, contrast sensitivity, visual processing speed, visual field sensitivity, and motion perception was assessed in drivers ≥70 years old. Data acquisition systems were installed in their personal vehicles recording video and vehicle kinematics. Driving during everyday life was recorded for 6 months. Data analysts evaluated a temporal data window surrounding randomly selected left turns at 4-way intersections. Left-turn traversals and turning behavior were evaluated in terms of age-adjusted associations with vision impairment.

RESULTS

The sample consisted of 151 older drivers. The number of turns studied was 473; 265 turns were rated as unsafe traversals, and 201 as problematic turning behavior. Drivers with slowed visual processing speed and visual field impairment were less likely to exhibit unsafe traversals (p < .05); those with worse contrast sensitivity, slowed visual processing speed, and visual field impairment were less likely to exhibit problematic turning behavior (p < .05).

DISCUSSION AND IMPLICATIONS

Using naturalistic driving, our study suggests older drivers with vision impairment exhibit better performance in making left turns than those without deficits, which contradicts older driver studies on left turns using driving simulators and on-road driving evaluations. Our findings suggest more cautious and self-regulatory behavior, which are consistent with older visually impaired drivers' commonly expressed concerns about their driving difficulties.