# Coordinated Multi-Platooning Planning for Resolving Sudden Congestion on Multi-Lane Freeways
## 2 Background and Related Work
Table 2 summarizes related works on effective platoon management, maneuver protocol, and trajectory simulation [23, 24, 25, 26, 27, 28, 29, 30, 31]. We classify the related work into two categories based on their solution architecture: a centralized [23, 24, 25, 26, 27] and decentralized [28, 29, 30, 31, 32, 33] approach. As shown in Table 2, many previous works adopted the centralized architecture [23, 24, 25, 26, 27], which usually requires a central system to collect a large amount of information and high-performance hardware. On the contrary, the decentralized architecture [28, 29, 30, 31, 32, 33] utilizes V2V communication to manage platoon maneuvers, such as velocity and distance, which can more effectively deal with temporary emergency road conditions. However, most previous works only focused on collision avoidance between platoon members and did not consider the conditions of surrounding vehicles. For example, the works in [23, 25, 29, 31] just considered the scenario of how a vehicle could change lanes to join a platoon rather than the lane-changing of the entire platoon. In addition, most of the proposed protocols focused on platoon management rather than resolving traffic congestion and driving safety due to emergencies. Unlike previous works, we propose a heuristic decentralized traffic method for forming multiple platoons on multiple lanes, where the vehicle members can cooperate with their leaders to quickly exit the congestion spot in order. In order to realize the autonomous operation decision of the vehicle, we propose to control the vehicles through the CACC [19] mode. Furthermore, compared to the literature, we further consider the effect of different platoon sizes on resolving traffic congestion and several platoon lane-changing maneuver strategies on multi-lane freeways. For centralized approaches, [PERSON] et al. [23] proposed a multi-lane architecture for the autonomous driving of a platoon, which consists of an offline motion planner system and an online hierarchical controller system. In order to avoid collisions between vehicles in their platoon, the authors use an optimization-based scheme to plan smooth trajectories, and the operations can also be reconfigured to deal with temporary road conditions based on real-time traffic information. [PERSON] et al. [24] developed a longitudinal control Model Predictive Control (MPC) method to handle external vehicles joining or leaving the platoon. The authors proposed a centralized control algorithm to obtain detailed information from the platoon followers. According to the received information, the platoon leader regulates the acceleration and deceleration of the vehicle in the platoon to minimize squared deviations in position, velocity, and tractive force. [PERSON] et al. [25] simulated three different merge operations: front merge, middle merge, and tail merge. In order to minimize the merge completion time and total travel distance or maximize the merge success rate or average traffic velocity, the authors analyzed the efficiency of these operations, showing the merge completion time, total distance traveled, average traffic velocity, and merge success rate to verify the efficiency and correctness of the model. [PERSON] et al. [26] developed a CACC platoon management protocol, based on a Vehicular Ad Hoc Network (VANET), using a Finite State Machine (FSM) for the description of vehicle-joining, leaving, and lane-changing maneuvers. When vehicle communication is lost, the controller and platoon management protocol can enable an individual follower in the platoon to downgrade to the Adaptive Cruise Control (ACC) mode. [PERSON] et al. [27] also studied the platoon formation solution. Based on a cost function, a rear vehicle searches and selects a platoon to join among many platoon candidates. If there is no platoon available to join, the vehicle forms a new platoon by itself. Their goal is to optimize the travel time and reduce fuel consumption based on each platoon's expected velocity and location.