Abstract—Congestion, environmental impact, and public transit inefficiency are all key concerns for urban mobility. This study investigates deploying a Bus Signal Priority (BSP) system in Semarang, Indonesia, as part of a larger smart city project aimed at improving urban mobility and encouraging the transition from private vehicles to public transportation. The major goal of this project is to create and implement BSP technology that enhances bus travel efficiency by reducing delays at traffic signals. The project combines a combination of traffic data gathering, simulation-based analysis with VISSIM software, and real-world implementation of RFID-based BSP systems at major crossings across Semarang. The process comprises field surveys that analyze traffic volume, queue lengths, and vehicle speeds, followed by the deployment of Radio Frequency Identification (RFID) sensors and IoT-enabled devices for real-time traffic signal modifications. The BSP system can reduce bus travel time by up to 30% during peak hours, resulting in lower CO₂ emissions and increased public transit reliability. The implementation also encourages more public transportation use, which aligns with the city’s sustainable transportation goals. Artificial Intelligence (AI) has been used in Verkehr In Städten – SIMulationsmodell (VISSIM) simulations to improve signal timing and traffic flow This work advances intelligent transportation systems and serves as an example for other cities seeking to implement BSP for sustainable urban mobility.

Cite: Mudjiastuti Handajani, Ari E. Jayati, Elfira N. Ardina, Eko S. Hasrito, and Siti V. Octaviany, “Bus Signal Priority: Enhancing Urban Mobility and Communication Efficiency in Smart Cities in Semarang, Indonesia," Journal of Communications, vol. 20, no. 4, pp. 491-500, 2025.