Developing CircuitGo: A Game-Based Driving Simulator for Driver Education under Kurikulum Pendidikan Pemandu 02

Abstract

Kurikulum Pendidikan Pemandu 02 (KPP 02) has been the basic module for driving education that focuses on skill based practical training in preparation for Jabatan Pengangkutan Jalan (JPJ)driving test in Malaysia. Yet, the traditional training method relies largely on a few physical practice sessions at driving institutes that potentially increase learner anxiety while also reducing exposure to multiple attempts at skill rehearsal and limiting familiarization of learners with the assessment examination circuit pre-assessment. However, the application of GBL frameworks in driving simulators is limited and does not align with the Malaysian KPP 02 curriculum as structured GBL approaches. In this work, we present CircuitGo that is a game-based driving simulator as a complement to the KPP 02 circuit module providing safe and interactive digital training environment. In terms of methodology, the study uses an adapted Agile development framework, mixed with principles of GBL instructional design to allow for iterative prototyping and user-centered refinement of the simulator. The system features a 3D environment to model the Shahbandar training circuit, embedding five key KPP 02 modules: Hill Start, S-Course, Z-Course, Side Parking and Three-Point Turn. Interactive tutorials, performance feedback, scoring systems, and tracking were also part of the GBL features. Evaluation of the system involved functionality and usability testing with 10 participants. Metrics were based on accuracy in completing tasks, the responsiveness of the controls, the ease of understanding the interface, and the perceived usefulness of the system for educational purposes. Evaluation results showed that all the modules worked as per the operational standards of JPJ, and the usability of the simulator is high. The results show that CircuitGo has the potential to improve the preparedness of learners, decrease their anxiety, and close the knowledge-skill gap. Future works include the mobile version, VR, and AI-based dynamic simulation of traffic.