Hybrid Honey Badger and Cuttlefish Optimization Algorithm(HHBCOA) for On-Road Vehicle Breakdown Assistance in VANETs

Efficient path planning for on-road vehicle breakdown assistance in Vehicular Ad Hoc Networks (VANETs) is crucial for ensuring timely and effective response to incidents. This paper proposes a novel approach that harnesses the adaptive and resilient characteristics of the Honey Badger optimization algorithm along with the deceptive and adaptive behaviors of the Cuttlefish optimization algorithm to optimize path planning in VANETs. The hybridization of these two distinct optimization techniques offers a unique synergy, allowing for robust and agile response strategies in dynamic vehicular environments. Through a comprehensive methodology, we formulate the breakdown assistance problem as an optimization task and integrate the Honey Badger and Cuttlefish algorithms to generate and update paths in real-time. We implement the proposed algorithm in a VANET simulation environment and evaluate its performance using various metrics, including path length, time to reach the stranded vehicle, and resource utilization. Experimental results demonstrate the effectiveness of the hybrid algorithm, outperforming traditional approaches and showcasing its potential for enhancing vehicle breakdown assistance in VANETs.