# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 3 Applications
### Safety Applications
#### 3.1.4 Platooning  
Cooperative vehicle/truck platooning is considered one of the most promising applications that has received significant attention from both automotive industries (e.g., Volvo, Daimler, and Scania) and academia. Vehicles/trucks in platoons are expected to maintain safe inter-vehicle distance and synced speed, routes, and braking through sensors/radar technology utilization, which is enabled by V2V communication when closely following a leader vehicle/truck. Platoons will benefit from significant reduction in fuel consumption, congestion, harmful gas emission, and aerodynamic drag. Reduction and improvements in aerodynamics drag will specifically have a remarkable impact on trucks, which are susceptible to higher wind resistance in comparison to other vehicles. Trucks in platoons are expected to save up to 15% of fuel consumption when auto-following their leader truck. Even with the aforementioned benefits, inter-platoon communication interference may arise among adjacent/opposite platoons, especially in intersections or crossings, where a number of platoons may coexist. Remote leader truck hacking, out-of-the loop drivers in tailgated trucks, abrupt software/hardware failures, real-world heterogeneous platoons, and platoon stability are all among the challenges of platooning application. One of the proposed solutions to tackle out-of-the-loop drivers is the deployment of a level 1/level 4 platooning system, where the lead truck will be operated by a human driver to combat any unexpected road conditions or adverse weather situations followed by tailgated level 4 automated trucks [90; 91].  
Furthermore, research studies have been dedicated to enhance both centralized (followers communicate with platoon leader) and decentralized (peer-to-peer platoon communication) platooning systems [92]. The authors in [93] propose platooning as a service framework that adopts a centralized mobile edge computing (MEC)-based approach to control the speed/acceleration of follower vehicles in the platoon. Uplink/downlink transmissions' latency/packet loss probability impacts and electromechanical actuation lags of vehicles/trucks were investigated in the SUMO simulator. The proposed platooning system was tested on highways; however, other traffic flow scenarios, such as intersections should be considered. Other studies adopted a decentralized approach such as [94], where the authors proposed a distributed resource allocation (channel assignment/power allocation) algorithm, which was developed for C-V2X-based platoons. Optimization decisions based on a deep reinforcement learning algorithm are taken by the leader vehicle to allocate the optimized sub-band and power of transmitted signals to the auto-following vehicles. Reduction in signal overheads and near-centralized V2I sum-rate performance were achieved and validated using the simulation. Another interesting aspect is the communication latency within platoons of vehicles, which has been tackled in several research studies. For instance, the authors in [95] proposed an adjusted cooperative adaptive cruise control (CACC) framework for longitudinal safety and sensitivity analysis of the communication latency for vehicles' platoons.