Driving Mode Advisory for Emergency Maneuvering in TransVerse Enabled Connected Vehicular Network

The future intelligent transport systems (ITSs) promise to improve traffic safety and security along with reducing the driver workload. In this article, we consider a pre-emptive emergency situation, wherein we design a safe-driving maneuver problem for transportation Metaverse (TransVerse) to compensate for driver reaction delay. The proposed scheme balances the risk of collision, and the spectral and computation resources required by the network. This combination of the spectral and computation resources required is also known as utility of the vehicular network. Further, an emergency maneuver is proposed to suggest a lane-changing maneuver based on the safe lane quality index for vehicles in vicinity of the emergency vehicle, also known as collision risk vehicles (CRVs). Moreover, based on the current position of the vehicles and the proposed safe maneuver, we propose a driving mode advisory to the drivers to provide a speed profile and a real-time high-level driving modes advice on acceleration, cruise, and engine brake. We evaluate the performance of the proposed safe-maneuver planning for CRVs in terms of collision probability, velocity, driving mode, and end-to-end lane changing delay. It can be observed that with the use of the proposed scheme, there is no effect on the performance of the high-CRV (HCRV). However, for the second following vehicle (HCRV2), the probability of collision decreases by 34.78%, and the velocity of the vehicle increases by 61.70% with the use of TransVerse. Moreover, a tradeoff between resource allocation and end-to-end delay of the network is also analyzed with and without TransVerse scenario.