Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm

Abstract

Abstract Emergency Medical Services (EMS) are vital for providing timely out‐of‐hospital care during medical emergencies. This research aims to optimize ambulance services by strategically allocating resources to minimize response time. A modified Whale Optimization Algorithm (mWOA) is introduced to achieve this goal, focusing on providing 24 × 7 services to every patient in need. The, conducted in Southern Delhi, India, considers the uncertain and stochastic nature of demand and traffic. The results demonstrate a 14.6% improvement in average EMS‐based response time, highlighting the effectiveness of the mWOA algorithm in enhancing ambulance allocation strategies. The results obtained using different algorithms are compared with those obtained using mWOA. The experiment outcomes demonstrate that the mWOA has higher efficiency and superiority than alternative algorithms regarding convergence rate and stability.

Keywords

• accident analysis
• accident prevention
• artificial intelligence
• automated driving and intelligent vehicles
• data communication
• intelligent transportation systems