Development of a Prototype Safety Advisory System to Aid Senior Citizens in Gap Selection

Yi, Ping · 2023 · ROSA P / University of Michigan. Center for Connected and Automated Transportation

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Summary

This research addresses the safety challenges faced by older drivers (aged 60 and above) at unsignalized intersections, where age-related declines in vision, hearing, reaction time, and cognitive function impair gap selection. Older drivers are disproportionately involved in intersection crashes, often rejecting usable gaps or selecting unsafe ones, which compromises both their safety and the efficiency of mainline traffic. The study aims to develop and evaluate a prototype in-vehicle safety advisory system utilizing connected vehicle technologies to assist these drivers in identifying safe gaps for turning maneuvers. The methodology involved a mixed-methods approach comprising field data collection, hardware development, simulation, and field testing. Field data was gathered at two unsignalized T-intersections in Stow and Tallmadge, Ohio, to determine site-specific critical gaps. The advisory system was designed to provide warnings via red flashing lights, audible beeps, and text messages on an LCD screen when an upcoming gap was deemed unsafe. The system operated in two scenarios: a "controlled" situation with fully connected vehicles and an "uncontrolled" mixed-traffic situation. A field test was conducted with 79 older drivers (75.9% male) using the prototype hardware, which included GPS units, Zigbee modules, and data acquisition units. Additionally, traffic simulation models were built using field data to assess the system's impact on traffic flow metrics, such as average delay, queue length, and waiting time, under various traffic volumes. The findings revealed that the empirically derived safe gap of 7.4 seconds at the Stow location was more appropriate than the 6.5 seconds recommended by the Highway Capacity Manual, as it prevented speed impedance to oncoming vehicles. Simulation results indicated that the advisory system effectively reduced negative impacts on mainline traffic when older drivers adhered to the recommended safe gaps. In the field test, 96% of participants accepted the system and agreed it improved safety. Participants preferred a combination of visual (red flashing) and auditory (beeping) warnings over single-mode alerts. Statistical analysis showed no significant difference in safety perception based on gender, but confirmed that the warning type influenced user preference. The system successfully alerted drivers to unsafe gaps, allowing them to wait for safer opportunities without causing excessive delays. The significance of this work lies in demonstrating the viability of connected vehicle technologies as assistive tools for aging populations, promoting mobility and independence while enhancing intersection safety. The study provides empirical evidence that tailored advisory systems can mitigate the risks associated with older drivers' gap acceptance behavior. By establishing site-specific safe gap thresholds and validating user acceptance, the research offers a framework for integrating such systems into future connected vehicle infrastructure. The results suggest that combining multiple warning modalities improves user engagement and safety outcomes, offering a practical solution to reduce intersection crashes among older drivers without significantly disrupting overall traffic flow.

Key finding

A prototype in-vehicle safety advisory system using connected vehicle technology was accepted by 96% of older driver participants, who reported that it improved safety during gap selection at unsignalized intersections.

Methodology

mixed_methods

Sample size: 79

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• gap acceptance