How Human Alike Connected Autonomous Vehicles Affect Traffic Conditions in Urban Environment?

Different methodologies are being used to study the effects of autonomous vehicle (AV) in the mixed traffic indicating the interaction among autonomous and human-driven vehicles. Micro-scopic simulation tools are popular in such assessment as it offers scope to experiment in eco-nomical, robust, and optimistic way. Lack of reliable real-world data to calibrate and evaluate the connected autonomous vehicles (CAV) simulation model is a major challenge. One interesting methodology could be dealing the CAVs as conventional human driven vehicles and predict its possible characteristics based on the simulation inputs. The conventional human driven vehicles from real world, in this methodology, come to aid as benchmark to offer the measure of effective-ness (MoE) for the calibration and validation. For the three most common driving modules, a sensitivity analysis of the driving behaviors of AVs and an effect assessment of CAVs in a mixed traffic environment were done to explore the human alike autonomous technology. The findings show that, up to a point, which is directly re-lated to the quantity of interacting vehicles, the impact of CAVs is typically favorable. This study validates the approach and supports past studies by showing that CAVs perform better in traffic than AVs for traffic performance and safety aspects. On top of that, the sensitivity analysis has shown that enhancements in technology are required for obtaining the maximum advantages.