How Does a Rearview Camera Influence Driver Performance and Confidence in Parking?

Urban parking challenges continue to intensify as vehicle density increases and parking spaces become scarce, making efficient reverse maneuvering a critical driver skill. While reverse camera technology promises to enhance parking performance by eliminating blind spots and providing real-time visual feedback, limited empirical evidence exists regarding its actual behavioral impact across diverse driver populations. This controlled field study addresses this gap by systematically examining how camera technology transforms driver behavior during reverse parking maneuvers in realistic urban conditions. A comprehensive 2×2 factorial experiment was conducted using 18 participants (9 males, 9 females) who completed four standardized parking tasks: parallel and perpendicular maneuvers under both no-technology and camera-assisted conditions. The study was conducted in a controlled outdoor environment using a sport utility vehicle equipped with standard reverse camera technology. Results reveal significant behavioral adaptations and performance variations across technology conditions, gender, and experience levels. All experienced drivers demonstrated consistent visual scanning behavior during unassisted parking, indicating well-developed situational awareness strategies. Conversely, inexperienced drivers exhibited longer completion times when using camera technology, suggesting a cognitive adaptation period as they integrated multiple information sources such as dashboard display, side mirrors, and rearview mirror into their maneuvering strategy. Gender-based performance differences emerged across all experimental conditions, with female participants requiring longer completion times regardless of technology assistance or maneuver type. These findings provide critical insights for automotive manufacturers, urban planners, and driver education programs, highlighting the need for differentiated technology design and training approaches. The study contributes to the growing body of research on human-machine interaction in automotive contexts and offers evidence-based recommendations for optimizing camera-assisted parking systems.