Effects of Connectivity and Automation on Saturation Headway and Capacity at Signalized Intersections

This paper analyzes the potential effects of connected and automated vehicles on saturation headway capacity at signalized intersections. A intersection is created in Vissim as a testbed, where four vehicle types are modeled tested: (I) human-driven (HVs), (II) (CVs), (III) (AVs), (IV) (CAVs). Various scenarios defined based different market-penetration rates these types. AVs assumed to move more cautiously than HVs. CVs CAVs supposed receive information about future state traffic lights adjust their speeds avoid stopping intersection. As result, movements expected be smoother with lower number stops. The mixed investigated relation headway, capacity, travel time, delay, queue length lane groups an Python script code developed by used provide communication between signal controller accordingly. results show that increasing CV CAV rate reduces consequently increases On other hand, AV deteriorates operations. Results also indicate highest increase (80%) decrease (20%) lane-group observed respectively stream 100% AVs.