Capturing delays in response of emergency services in Delhi

Abstract

Response time of an ambulance plays a significant role in pre-hospital care. The absence of response standards in India has made it challenging for emergency services to provide efficient and timely pre-hospital services. Also, traffic congestion in a city like Delhi may prove detrimental to a patient who needs urgent transport. Since travel times fluctuate throughout the day, solving an ambulance location problem with average travel times would not suffice. Therefore, the Gaussian Mixture Model (GMM) has been used to capture the variability in travel time between each origin-destination pair for Delhi's vast transportation network. This variation in travel times and delays in the dispatch of an ambulance (pre-trip delay) has been incorporated into the traditional double standard model as a chance constraint. The study thus builds three different variations of model, one being deterministic and the other two stochastic with probabilistic response times. These models are referred to as the Chance Constrained Double Standard Model (cc-DSM), Chance Constrained Double Standard Stochastic Model (cc-DSSM) and Double Standard Stochastic Model (DSSM). This study shows the similarity of previously used relocation approaches with the current approach and highlights the difference between vehicle busyness concept from the concept of multiple coverage.