Driver feedback has emerged as a promising tool for improving road safety by influencing driver behavior, propelled by technological advancements. After implementing a PRISMA framework and locating 597 candidate studies, this systematic review selects and examines 34 studies in real-world driving conditions that investigate the role of driver feedback towards improving driving behavior. The review explores the various types of feedback systems used, including smartphone applications, in-vehicle systems, and web-based platforms, and evaluates their effectiveness in reducing risky driving behaviors such as speeding, harsh braking, and mobile phone use. The studies are analyzed in terms of their experimental frameworks, including sample sizes, feedback delivery methods, and feedback phases, along with statistical models employed to assess the impact of feedback on driving behavior and road safety. Additionally, this review highlights research gaps, such as the need to account for traffic conditions and vulnerable road users, while also discussing the potential of emerging technologies like Internet of Things (IoT) and machine learning to enhance the customization and real-time applicability of feedback systems. The findings suggest that driver feedback can significantly reduce crash risks and improve driving behavior, but further research is required to explore its long-term effects and broader applicability.
| ID | pj273 |
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