6 research outputs found
A Rule Based Control Algorithm for On-Ramp Merge with Connected and Automated Vehicles
One of the designs for future highways with mixed flow of connected automated vehicles (CAVs) and manual cars will be a dedicated lane for the CAVs to form platoons and travel with higher speeds and lower headways. Connectivity between vehicles and the infrastructure will enable control strategies to become more advanced. The connectivity will enable the formation of platoons of CAVs which will travel beside non-platoon lanes. Every connected vehicle joining the highway from an onramp will have the challenge of when and where - while traveling on the acceleration lane - to join the adjacent mainline of the highway. In this research, the aim is developing a model for investigating the effects of different merge actions yielding a more efficient and systematic method for the vehicles joining the mainlines comprised of platoon and non-platoon lanes. The actions tested for assisting the merge process include deceleration in the mainlines, joining a platoon, etc. The model targets to direct every CAV entering a multi-lane highway segment from an on-ramp, to the rightmost lane of the highway based on the appropriate action which is selected according to the traffic conditions on the mainline. To account for car following behavior, the platoon lanes are assumed to have a simplified CACC (cooperative adaptive cruise control) and the non-platoon lanes the IDM+ car-following model. Numerous simulation experiments proved the efficiency of the model in increasing the throughput in the merge area. The results of this research will help in the design and development of advances systems for controlling on-ramp merge sections in the future with CAVs