Traffic delays are not wholly new and are a well-known problem that impacts many of the world’s populations through disruptions and pollution. The rising urbanization and quantity of powered road vehicles necessitate a greater traffic control demand to maintain flow and avoid jams. In order to understand the notion of sustainable transportation, this study first examined sustainable transportation systems. This research then assessed Pakistan’s present transportation infrastructure and urban transportation to find the most reasonable and sustainable alternative to reduce congestion. The Taxila intersection was utilized as a pilot study area because of its vicinity to Pakistan’s leading economic hubs (i.e., industrial estates and the twin cities of Islamabad and Rawalpindi). The study used multi-criteria decision making (MCDM) techniques, including the fuzzy AHP, TOPSIS, VIKOR, and traffic simulation software, to determine the optimal solution for a more sustainable transportation system, and reducing traffic congestion. A pairwise comparison of the criteria and alternatives was made using a survey. This survey was used to look into the perspectives of various stakeholders and experts. The outcomes of the fuzzy AHP-TOPSIS and fuzzy AHP-VIKOR revealed that a flyover is the best alternative. In contrast, the best alternative, according to the software was a parking area. Ultimately, we assessed our results using the literature, and site observation, and concluded that a parking area would be the most sustainable alternative in the Taxila intersection.

The construction industry is characterized by its complex and dynamic nature, where risk assessment and safety management play pivotal roles in ensuring project success and worker well-being. Integrating Artificial Intelligence (AI) technologies has introduced transformative possibilities for enhancing risk assessment methodologies and safety management practices in construction projects. This chapter explores the synergistic relationship between AI and construction safety, shedding light on the innovative applications, benefits, and challenges that emerge when AI is harnessed to improve risk analysis and safety protocols. Furthermore, the ethical and social considerations associated with adopting AI in construction safety are explored, underlining the importance of striking a balance between technological advancement and the human element. The potential challenges related to data privacy, algorithm transparency, and workforce upskilling are addressed, offering insights into the responsible deployment of AI-enabled safety solutions. This chapter underscores the transformative potential of AI-enabled risk assessment and safety management in construction. By leveraging cutting-edge AI technologies, construction stakeholders can revolutionize traditional safety practices, leading to enhanced project outcomes, reduced incidents, and improved overall industry sustainability. <!----> <!----> <!----> <!---->

In recent years, traffic congestion has become one of many cities’ most significant financial and ecological concerns worldwide. It also costs citizens a substantial amount of time and fuel. Many experts believe that identifying traffic congestion characteristics is the first step in reducing traffic congestion. This study aimed to determine the extent of traffic congestion and fuel consumption at Taxila Chowk. The research’s primary methodological tools were a traffic volume survey and peak hour volume study using Aimsun software. According to this study, auto-rickshaws, bicycles, motorcycles, and trucks were the most common modes of transportation. Traffic flow is particularly heavy in the morning, noon, and evening hours. It was revealed that the H.M.C. road is the most congestion-prone route compared to the other four routes. Also, the distinctive design of rickshaws and bus stands and the misplacement of fruit and vegetable markets play a considerable role in Congestion. The level of service of the four routes is almost intolerable, and the sole P.O.F. road that offered comparable better services to city commuters is an acceptable illustration. The study has also identified the amount of fuel consumption on each route, focused on the environmental impact of Congestion due to emissions of green gasses, and provided feasible solutions in the form of alternatives.