Vehicle merging on highways has always been an important aspect, which directly affects the capacity of the highway. Under critical traffic conditions, the merging of main road traffic and on-ramp traffic is known to trigger speed breakdown and congestion. Additionally, merging is one of the most stressful tasks for the driver, since it requires a synchronized set of observations and actions. Consequently, drivers often perform merging maneuvers with low efficiency. Emerging vehicle technologies, such as cooperative adaptive cruise control and/or merging-assistance systems, are expected to enable the so-called “cooperative merging”. The purpose of this work is to propose a cooperative merging system and evaluate its performance and its impact on highway capacity. The modeling and simulation of the proposed methodology is performed within the framework of a microscopic traffic simulator. The proposed model allows for the vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication, which enables the effective handling of the available gaps between vehicles. Different cases are examined through simulations, in order to assess the impact of the system on traffic flow, under various traffic conditions. Useful conclusions are derived from the simulation results, which can form the basis for more complex merging algorithms and/or strategies that adapt to traffic conditions.
Lidar Data Analysis for Time to Headway Determination in the DriveSafe Project Field Tests
