Temporal Optimization of Dynamic Message Signs: A Survival Analysis of Driver Comprehension Factors
Dynamic Message Signs (DMSs) play a critical role in conveying real-time traffic information to drivers; however, their effectiveness heavily relies on how messages are structured and displayed, particularly regarding phasing duration and content length. This study examines the influence of these two factors on driver readability, comprehension, and gaze behavior using an advanced virtual reality (VR) driving simulator. Controlled experiments simulated four DMS scenarios, combining two phasing intervals (2.5 and 4 s) with short and long message formats, adhering to Michigan Department of Transportation (MDOT) guidelines. The experiment integrated eye-tracking technology to measure fixation duration and frequency, while statistical methods, including survival analysis and LASSO regression, were employed to identify significant predictors of message readability. Results revealed that shorter messages with shorter phasing intervals led to the highest comprehension rates and reduced cognitive strain. Furthermore, individual characteristics such as gender, driving speed, and highway driving experience significantly affected how drivers engaged with DMS messages. These findings contribute to the development of more effective DMS deployment strategies and provide practical design recommendations to enhance traffic safety and information delivery on high-speed roadways.
Authors
- Ahmed Jaber (ORCID: https://orcid.org/0000-0001-5493-2530)
- Mohammad Nour Al-Marafi (ORCID: https://orcid.org/0000-0001-5083-9398)
- Fadi Alhomaidat (ORCID: https://orcid.org/0000-0001-6876-4945)
- Mousa Abushattal (ORCID: https://orcid.org/0009-0009-6933-183X)
- Rasha Al-Shamaseen
- Layan Alkodary
Institutions
- Al-Hussein Bin Talal University (JO)
- Tafila Technical University (JO)
- University of Jordan (JO)
- An-Najah National University (PS)
- Palestinian Hydrology Group (PS)
Publication Details
- Journal
- Vehicles
- Published
- 2026-03-08
- DOI
- https://doi.org/10.3390/vehicles8030050
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00