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Furthermore, traffic decision‐making systems predicts the probability of traffic accident occurrence using big data algorithms [37]. This requires to have smart healthcare systems, which is nominated as one of smart cities features discussed in ssss1, to help emergency centers to facilitate the process of emergency rescue.

Researchers in [5] leveraged DL algorithms and advanced communication technologies to link vehicles, roads, and drivers to facilitate and enhance various traffic‐related tasks and improve air pollution [6]. The scientists focused on different initiatives with the goal of creating a safe and smart environment and transportation. Further, Zhu et al. [37] developed an approach to use two algorithms: Bayesian inference and Random forest to execute in real time to predict the probability of crash occurrence to decrease crash risks in smart cities. Moreover, researchers [38] have established a combination of supervised and regression algorithms such as multivariate adaptive regression splines, classification and regression trees, and logistic regression to study the dataset of motor vehicle accident injury.