# Early Gapping and Platoon Merging Strategies for Autonomous Vehicles using Local Controllers
## 1 Introduction  
Merging lanes are common conditions in traffic flow when an obstacle is incorporated along the way or when a ramp road merges into the main lane. Due to the possible impact of merging lanes on the total traffic flow, the topic of traffic flow merging has been studied extensively for manually driven vehicles, using experimental observations [1] and by using simulations or mathematical models such as game theory [2], agent-based simulations [3] and simulations of cooperative lane changing [4].  
An intuitive solution for autonomous vehicle (AV) merging requires the establishment of communication between vehicles [5], i.e., the ability of a vehicle to connect with network services, other vehicles and infrastructure [6]. Such technology may also provide real-time information about ongoing traffic conditions [7]. However, obtaining a vehicular communication network requires defined protocols [8] and may be challenging due to network load and loss rate. Vehicular ad hoc networks have failed in their scalability issues and their required resultant communication overhead. They do not address the time required for a vehicle to verify all message signatures sent by neighboring vehicles, especially when traffic is dense (where packet length increases due to signatures and public-key certificates). This problem is further increased when considering inter-vehicle communication [9]. Further complications in the physical layer include obstacles, reflections and non-conventional problems emerging as the vehicles change their positions. Therefore, alternative control methods that do not rely solely on vehicle-to-vehicle communication should also be considered.  
An alternative approach that does not assume vehicle-to-vehicle communication is based on assignments of predetermined speed profiles to the vehicles. It has been suggested to improve road traffic flow and avoid conflicts in urban driving scenarios [10, 11]. Speed profiles are generated using temporal optimization of the timestamps for all waypointsalong the given path. These schemes are suited for a small number of vehicle scenarios, as the configuration space grows exponentially with the number of vehicles. In a previous paper [12], we proposed a control scheme in which each vehicle controls its speed according to signals received from roadside units (RSU) and gap measurements to the vehicle ahead. The RSUs convey a predetermined speed profile along the road to optimize the traffic flow of a line of vehicles in the sense of road capacity, energy consumption or vehicle travel duration. No further information is conveyed from the RSU to the vehicles or vice versa.  
In this paper, we suggest controlling lane merging control using _gap profiles_ assigned to all the vehicles, based on their position along the road. This is inspired by measurements of _speed profiles_ of human drivers close to intersections [1]. Such measurements reveal different populations of vehicles following different speed patterns, with consistent behavior along the road. For example, under free-flow conditions, for a certain road portion at approximately 200 m away from a forked-road intersection, vehicles start to slow down to 40 km/h, and vehicles heading straight keep their speed at 60 km/h. This implies that there can be an optimal behavioral profile that can be enforced upon AVs during lane merging. The present study aims to explore such location-dependent gap profiles.