Automobile Export Automation through Connected and Autonomous Vehicles: Simulation from manufacturing plants to the RORO Ports

Purpose - In general, the transport of vehicles from manufacturing plants to roll-on/roll-off (RO- RO) ports has been a complex, labor-intensive operation. The integration of autonomous vehicles (AVs) and connected and autonomous vehicles (CAVs) into this chain promises a transformative change. This study investigates the transformative impact of CAVs in the automotive logistics and transportation sectors, particularly in the transport of vehicles from manufacturing plants to RORO ports. Design/Methodology - This study employs the Simulation of Urban MObility (SUMO) simulation tool to model and analyze traffic and logistics scenarios from manufacturing plants to RORO ports, inf luenced by intelligent vehicles. Specifically, the study examines the effects of CAVs with cooperative adaptive cruise control, AVs with the intelligent driving model, and human-driven vehicles using the Krauss model. Findings - Our main findings can be summarized as follows: human-driven vehicles (HDVs) demonstrated the longest step times and the highest mean waiting times, indicating lower operational efficiency. On the other hand, CAVs and AVs enhance traffic efficiency in urban traffic systems. In particular, AVs reduces CO2 emissions. Originality/value - This study integrates three specific car-following models: cooperative adaptive cruise control (CACC), intelligent driving model (IDM), and the Krauss model, to assess urban traffic dynamics more comprehensively. This research marks a significant step toward understanding the transformative impact of AV technology in the logistics and transportation sectors of the automotive industry.