Age-related changes in driving performance under driver assistance systems during curve negotiation

Age-related changes in driving performance have long been a critical issue in traffic safety. However, it remains unclear whether such differences occur during curve negotiation, particularly in the approach phase preceding curve entry. This study examined age-related changes that emerge in this context and investigated whether driver assistance systems can mitigate these differences. Thirty-six participants (mean age = 44.3 years, SD = 17.1) completed a 30-min simulated drive under three conditions: Manual, Lane Centering (LC), and Adaptive Cruise Control (ACC). In the Manual condition, participants maintained a speed of 60 km/h and kept the vehicle centered in the lane. In the LC condition, lateral support was provided, ACC controlled speed, and participants managed the remaining operations. Results showed that, under the Manual condition, increasing age was associated with initiating curve preparation closer to the entry point and with greater variability and magnitude of steering. Under ACC, curve preparation began earlier, as indicated by an earlier Start Point of Steering Wheel Angle (SPSWA), although age-related steering patterns remained unchanged. No significant age-related differences were found in accelerator pedal use under the Manual condition, and neither performance differences nor age-related patterns were observed in the LC condition. These findings indicate that age-related changes are evident in steering. ACC promotes earlier curve entry preparation but does not compensate for age-related steering differences. LC showed limited effectiveness across age groups. Trial-level analyses confirmed that automation did not differentially affect age-related patterns in driver control behavior. Overall, the findings underscore the need for driver assistance systems that more effectively support age-related changes in lateral control during curve negotiation. • Age-related differences are evident in steering in manual driving during curve negotiation. • ACC prompted earlier steering preparation, but age-related differences remained. • No age-related differences in accelerator pedal use were found under LC. • Age-related tendencies did not differ between manual and assisted driving (LC, ACC). • Results highlight the need for systems that support steering when approaching a curve, considering age-related changes.

Authors

Institutions

Publication Details

Journal
Transportation Research Part F Traffic Psychology and Behaviour
Published
2025-12-27
DOI
https://doi.org/10.1016/j.trf.2025.103499
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Age-related changes in driving performance under driver assistance systems during curve negotiation

Yanbin Wu, Ken Kihara, Takatsune Kumada, Byungju Kim et al.
Transportation Research Part F Traffic Psychology and Behaviour
Traffic and Road Safety
article

Age-related changes in driving performance under driver assistance systems during curve negotiation

Yanbin Wu, Ken Kihara, Takatsune Kumada, Byungju Kim, Yuji Takeda
article en

Abstract

Age-related changes in driving performance have long been a critical issue in traffic safety. However, it remains unclear whether such differences occur during curve negotiation, particularly in the approach phase preceding curve entry. This study examined age-related changes that emerge in this context and investigated whether driver assistance systems can mitigate these differences. Thirty-six participants (mean age = 44.3 years, SD = 17.1) completed a 30-min simulated drive under three conditions: Manual, Lane Centering (LC), and Adaptive Cruise Control (ACC). In the Manual condition, participants maintained a speed of 60 km/h and kept the vehicle centered in the lane. In the LC condition, lateral support was provided, ACC controlled speed, and participants managed the remaining operations. Results showed that, under the Manual condition, increasing age was associated with initiating curve preparation closer to the entry point and with greater variability and magnitude of steering. Under ACC, curve preparation began earlier, as indicated by an earlier Start Point of Steering Wheel Angle (SPSWA), although age-related steering patterns remained unchanged. No significant age-related differences were found in accelerator pedal use under the Manual condition, and neither performance differences nor age-related patterns were observed in the LC condition. These findings indicate that age-related changes are evident in steering. ACC promotes earlier curve entry preparation but does not compensate for age-related steering differences. LC showed limited effectiveness across age groups. Trial-level analyses confirmed that automation did not differentially affect age-related patterns in driver control behavior. Overall, the findings underscore the need for driver assistance systems that more effectively support age-related changes in lateral control during curve negotiation. • Age-related differences are evident in steering in manual driving during curve negotiation. • ACC prompted earlier steering preparation, but age-related differences remained. • No age-related differences in accelerator pedal use were found under LC. • Age-related tendencies did not differ between manual and assisted driving (LC, ACC). • Results highlight the need for systems that support steering when approaching a curve, considering age-related changes.

Transportation Research Part F Traffic Psychology and BehaviourVol. 118
Kyoto University (JP), Kyoto College of Graduate Studies for Informatics (JP), National Institute of Advanced Industrial Science and Technology (JP)
Openalex Percentile: Top 36%
Traffic and Road Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.