Autonomous Shuttle Service in Sub-Urban Mixed Traffic Conditions: Microscopic Simulation-Based Impact Assessment

Highlights: What are the main findings? Developed a framework to calibrate autonomous shuttle movement in a simulation environment with real-world trajectory data. Assessed the impact of autonomous shuttle movements in mixed traffic conditions. What is the implication of the main finding? The calibration framework enables realistic simulation of autonomous shuttle operations, providing critical insights before large-scale implementation/commercial deployment. The findings can help shuttle operators to optimize shuttle frequency or speed without interrupting the regular traffic, or local authorities to accommodate additional infrastructures for shuttle operation. Autonomous shuttle services are currently introduced in different urban conditions throughout the world. As a result, studies are needed to assess the safety and mobility performance of such autonomous shuttle services. However, calibrating the movement of autonomous shuttles in a simulation environment has been a difficult task due to the absence of any real-world data. This study aims to assess the impact of the shuttle service on suburban road capacity through a calibrated simulation prototype of an operational shuttle system at Lake Nona, Orlando, Florida. The movements of autonomous vehicles are calibrated using real-world trajectory data, which helps replicate the driving behavior of the shuttle in the simulation. The analysis reveals that with increasing frequency of the shuttle service, the delay time percentage of the shared road sections increases and traveling speed decreases. A moving bottleneck phenomenon is also observed with the shuttle movement. The findings also demonstrate that increasing the speed of shuttles up to 10 mph can improve traffic conditions, which are constrained by the operational safety aspects. The findings from this study provide insights for policymakers and transportation agencies towards deploying autonomous shuttles and for planning road infrastructures for shared road-use of autonomous and human-driven vehicles.