Age-Related Differences in Vehicle Control and Eye Movement Patterns at Intersections: Older and Middle-Aged Drivers

Intersection challenges for older drivers: The impact of aging on visual cognition and driving efficiency at crossroads

OBJECTIVE

To examine the effects of aging on drivers' visual cognition and driving performance under different conditions, and to explore the associations between visual cognition and driving performance in older drivers.

METHODS

A driving simulator experiment was conducted, featuring critical scenarios with varying driving tasks and traffic complexities. Different scenarios with diverse levels of traffic complexity and driving tasks were set up. Participants from two age groups were invited: 15 individuals aged 24-47 and 15 individuals over 60. Experimental data on driving behavior and visual characteristics were collected. Based on visual features, a "Perception and Cognition" evaluation system was established, and a "Vehicle Operation" evaluation system was constructed using driving behavior data. By integrating these two dimensions, the correlation between visual cognition and driving performance in older drivers was thoroughly discussed.

RESULTS

Complex traffic flow did not significantly affect cognitive load and driving performance, possibly due to drivers waiting for oncoming traffic. Left-turning drivers exhibited lower speeds, longer times, higher speed variability, and greater acceleration. Age significantly impacted visual perception and driving performance, with older drivers finding information processing more challenging but using compensatory measures like slower intersection approach speeds. However, older drivers were weaker in speed control.

CONCLUSION

The result shows a clear link between visual cognition and driving performance. It is possible to consider how to utilize these psychological abilities to identify and potentially help drivers improve driving safety.

Evaluation of assistance systems allowing older drivers to intercept moving inter-vehicular space

Introduction

The objective of the present study was to test two Advanced Driving Assistance Systems (ADAS) designed to help older drivers to intercept a moving inter-vehicular space.

Method

Older and younger drivers were asked to intercept a moving inter-vehicular space within a train of vehicles in a driving simulator. Three ADAS conditions (No-ADAS, Head Down, Head Up) as well as five distinct speed regulation conditions were tested. Vehicle trajectory, gaze behavior and acceptance were analyzed.

Results

Our results reveal that the ADAS tested make it possible to perform the interception task but also to reduce the variability of the behavior produced. They also indicate that the location of the augmented information provided by the ADAS directly impacts the information-gathering strategy implemented. Finally, whereas younger divers reported mixed levels of ADAS acceptance, older drivers reported a good level of acceptance.

Discussion

All these results could be particularly useful with a view of designing ADAS for older drivers.

Exploring the stop sign running at all-way stop-controlled intersections with the SHRP2 naturalistic driving data

INTRODUCTION

All-way stop control (AWSC) has been widely used at unsignalized intersections in the United States for its safety effects. However, many drivers do not make a complete stop before stop signs in practice (i.e., stop sign running), which presents safety concerns.

METHOD

This study explores driver behaviors at AWSC intersections with the SHRP2 naturalistic driving data.

RESULTS

First, it is found that the full-stop rate is only 20.2% at AWSC intersections. Then, the study quantitatively analyzes what factors might influence the stop sign running decisions at AWSC intersections, where driver, vehicle, intersection geometry, maneuver, and environmental features are taken into account. In addition, considering the possible unobserved heterogeneities across drivers and intersections, a logistic regression model with both driver and intersection random effects is adopted. The results show that young and older drivers are less likely to fully stop, but there is no gender difference found. SUVs and vans are less likely to fully stop, drivers are less likely to fully stop at 3-leg intersections, and drivers are more likely to fully stop in daytime and weekdays. In terms of maneuvers, left-turn traversals are more likely to make a complete stop. In addition, both the driver and intersection random effects are found to be significant, vary greatly by individuals, and can be used to identify the few but critical high-risk drivers/intersections.

PRACTICAL APPLICATIONS

The findings are expected to provide new insights for transportation agencies to formulate effective measures to deter stop sign running.

Does longevity impact the severity of traffic crashes? A comparative study of young-older and old-older drivers

INTRODUCTION

This article analyzes the effect of driver's age in crash severity with a particular focus on those over the age of 65. The greater frequency and longevity of older drivers around the world suggests the need to introduce a possible segmentation within this group at risk, thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector.

METHOD

We investigate differences in the severity of traffic crashes among two subgroups of older drivers -young-older (65-75) and old-older (75+), and findings are compared with the age interval of drivers under 65. Here, we draw on data for 2016 provided by Spanish Traffic Authority. Parametric and semi-parametric regression models are applied.

RESULTS

We identified the factors related to the crash, vehicle, and driver that have a significant impact on the probability of the crash being slight, serious, or fatal for the different age groups.

CONCLUSIONS

We found that crash severity and the expected costs of crashes significantly increase when the driver is over the age of 75. Practical Applications: Our results have obvious implications for regulators responsible for road safety policies - most specifically as they consider there should be specific driver licensing requirements and driving training for elderly - and for the automobile insurance industry, which to date has not examined the impact that the longevity of drivers is likely to have on their balance sheets.

Drivers' visual scanning behavior at signalized and unsignalized intersections: A naturalistic driving study in China

INTRODUCTION

Intersections are the most dangerous locations in urban traffic. The present study aims to investigate drivers' visual scanning behavior at signalized and unsignalized intersections.

METHOD

Naturalistic driving data at 318 green phase signalized intersections and 300 unsignalized ones were collected. Drivers' glance allocations were manually categorized into 10 areas of interest (AOIs), based on which three feature subsets were extracted including glance allocation frequencies, durations and AOI transition probabilities. The extracted features at signalized and unsignalized intersections were compared. Features with statistical significances were integrated to characterize drivers' scanning patterns using the hierarchical clustering method. Andrews Curve was adopted to visually illustrate the clustering results of high-dimensional data.

RESULTS

Results showed that drivers going straight across signalized intersections had more often glances at the left view mirror and longer fixation on the near left area. When turning left, drivers near signalized intersections had more frequent glances at the left view mirror, fixated much longer on the forward and rearview mirror area, and had higher transition probabilities from near left to far left. Compared with drivers' scanning patterns in left turning maneuver at signalized intersections, drivers with higher situation awareness levels would divide more attention to the forward and right areas than at unsignalized intersections.

CONCLUSIONS

This study revealed that intersection types made differences on drivers' scanning behavior. Practical applications: These findings suggest that future applications in advanced driver assistance systems and driver training programs should recommend different scanning strategies to drivers at different types of intersections.

Road traffic accidents involving elderly people: an integrative review

Abstract Objective: To identify the epidemiological and socio-demographic profile of elderly victims of traffic accidents reported in articles published in scientific literature from 2013 to 2018. Method: The Literatura Latino Americana em Ciências da Saúde (Latin American Literature in Health Sciences), Base de Dados de Enfermagem (Database in Nursing), Scientific Electronic Library Online, and Medical Literature Analysis and Retrieval System Online databases were used, with the guiding question being: What is the scientific production on traffic accidents involving elderly people? A total of 355 articles were found. After the application of the selection criteria, 16 were evaluated, and nine remained for final analysis. Results: The age range was 60 to 69 years and the majority of the sample were men, who were married and had low schooling. Being run over was the most frequent accident. The width of the traffic lanes and the time of the accident influenced the frequency and risk of accidents and the severity of the injuries. Conclusion: Younger elderly persons were the most affected, and being run over was the most frequent type of accident.

The role of driver age in performance and attention allocation effects of roadway sign count, format and familiarity

White-on-blue logo signs are used to inform drivers of food, gas, lodging, and attraction businesses at highway interchanges. In this study, 60 drivers were asked to look for food and attraction targets on logo signs while driving in a realistic freeway simulation. The objective of the study was to quantify effects of the number of sign panels (six vs. nine), logo familiarity (familiar vs. unfamiliar), logo format (text vs. pictorial), and driver age (young, middle, and elderly) on performance, attention allocation and target identification accuracy. Results revealed elderly drivers to exhibit worse performance in comparison to middle-age and young groups even though they adopted a more conservative driving strategy. There was no significant effect of the number of panels, logo familiarity, and logo format on driver performance or attention allocation. In target identification, drivers were more accurate with familiar or text-based panels appearing in six-panel signs.