Optimal route search using the hamiltonian circuit algorithm for assessing vehicular pollution and public health impacts in urban corridors

Rapid population expansion, inadequate infrastructure, and a significant reliance on private automobiles are the main causes of traffic congestion in Indian cities, which causes delays and has a negative influence on the environment. Vehicle emissions pose a particularly serious problem for Chennai, a rapidly expanding metropolitan area with a population of around 10 million. Many metropolitan corridors are already functioning at saturation $$(V/C \approx 1)$$, with about 15% of families possessing vehicles and 50% owning motorbikes. The Hamiltonian circuit with a branch-and-bound approach is used in this study’s intelligent agent-based model for public transportation route optimization. When compared to the current linear routes, the optimal circular route between Poonamallee and Ambattur cuts average travel time by 18.6% and congestion by 21.4% out of the three possible options. A structured survey of 420 respondents along the Poonamallee High Road corridor was conducted to evaluate perceptions of transport choices and health impacts of vehicular pollution. According to the results, 31.8% of respondents named motor vehicles as the main cause of pollution, while 28.9% cited industrial activity. The frequency of respiratory problems was highest among younger individuals (25–35 years old) (52.7%), and women reported being more susceptible to asthma (45.7%) than men (24.5%). The choice for private vehicles was still driven by convenience, but notably, 42% of respondents with higher incomes thought that stronger regulations could lower pollution. All things considered, the findings show that route optimization can enhance urban mobility in Chennai’s transport system while lowering emissions and reducing hazards to public health. Identified the most efficient route for urban commuters using congestion metrics and graph theory. Quantified the health impacts of vehicular congestion through statistical validation. Demonstrated that optimizing traffic routes can reduce exposure to air pollution and related illnesses.