Eriq Muhammad Adams Jonemaro, Buce Trias Hanggara, Aryo Pinandito, Hadziq Fabroyir, Darlis Herumurti
The imbalance between difficulty levels and player skill levels in racing games can lead to frustration or boredom that reduces the quality of the gaming experience. This study proposed a race progress-based Dynamic Difficulty Adjustment (DDA) method for racing games that provides more representative performance measurement than conventional rubber banding approaches which rely on distance-based measurement. A between-subjects factorial design compared novice and expert player performance under static and adaptive difficulty conditions. A controlled experiment with simulated players measured win rate, overtaking frequency, and race time gap. The findings demonstrated that the proposed method achieved optimal performance balance with a 50% win rate for both player categories, increased overtaking frequency by 18-fold for novice and 11-fold for expert players, and reduced race time gap by 95% for novice and 90% for expert players. The race progress-based DDA approach significantly enhanced overtaking activities and reduced disparities in race completion times. © 2025 IEEE.
Institut Teknologi Sepuluh Nopember, Department of Informatics, Surabaya, Indonesia; Universitas Brawijaya, Department of Informatics Engineering, Malang, Indonesia; Universitas Brawijaya, Department of Information Systems, Malang, Indonesia
