## 2 Research Methodology
### Car-Following Models with Platoons  
There are many tools that utilize Sumo to create platoons, such as Simpla, Veins, and Plexe. Veins and Plexe combine wireless networking and a realistic vehicle environment based on the Sumo traffic simulator to implement platooning. However, the connection between them and Sumo is complicated because they require additional software for simulation. Simpla is a configurable platooning plugin for the TraCI Python client to create basic platooning logic and provide additional parameters.  
Figure 1: Research architecture.  
To simulate our traffic model, we used Simpla and adjusted the current parameters to match the simulation conditions. Features of the platoon configuration in our model are as follows:  
* When CVs are within the defined platoon range on the same lane, they can switch to 4 modes (platoon leader, platoon follower, catch-up, and catch-up follower mode), as shown in Figure 2. Platooning vehicles are considered as a platoon if the gap is smaller than 15 m (yellow and green vehicles). CVs switch their type to catch-up mode when the front platoon is closer to a given value of 50 m (red and blue vehicles). If the connection conditions are not met, CVs' movement is similar to that of RVs (cyan vehicle).
* Changing lanes to join the platoon is not yet supported in Simpla. If the platoon leader changes lanes, other vehicles will try to change lanes.
* In the combined operation mode, when joining the platoon, CVs in the follower and catch-up modes can move at a speed greater than the maximum speed (speed_Factor equals 1.2). Other modes default to 1.
* A platoon leader has the ability to accelerate and switch to the follower mode if it is within range of another platoon in front.
* A platooning vehicle can switch to the manual mode if it is outside of the platooning range. It can accelerate and connect to form a platoon in a catch-up area.
* At the intersection area, due to the influence of traffic lights, CVs can be split from the platoon. The reforming of the platooning operation is shown in Figure 3.  
We assumed that the platoon configuration was perfect, meaning that there was no damage, data package loss, or time delay during platooning operations. Vehicles in platoons try to maintain a safe distance from their preceding vehicles. Simulation experiments were  
Figure 3: Platooning operation.  
Figure 2: Platoon configuration with Simpla.  
performed with platoons of different sizes (the number of vehicles in the platoons varied from 1 to 2 and 3 vehicles). A safe distance between vehicles was an important factor in controlling the movement and characteristics of platoons [25]. To reduce the intra-platoon gap, we used a tau factor (minimum time headway) of 0.3 s for CVs. Our designed platoon protocol is presented in Table 1 below.  
The movement of the leader vehicle in platoons is affected by the inter-platoon gap. If the distance is smaller than the safe distance, the platoon will decelerate according to the car-following model until this distance increases to a safe distance. The following vehicles in the platoon adjust their acceleration and speed according to the leader. Thus, the platoon's formation is dynamic when it moves through the intersection.