Scenario-Based Visualization for Traffic Congestion Mitigation

Traffic congestion is a major problem in most sustainable smart cities in current days, causing delays, increased emissions, and decreased quality of life. This research proposes a new approach for visualizing traffic congestion using scenario-based visualization. This method uses real-time traffic data to create interactive visualizations of different traffic scenarios, allowing decision-makers and stakeholders to explore the potential impact of different congestion mitigation strategies. It demonstrates the effectiveness of this approach by applying it to a real-world case study of traffic congestion in a major city. The results show that scenario-based visualization can provide valuable insights into the causes and potential solutions for traffic congestion and support evidence-based decision-making in traffic management. When analysing several causes of traffic congestion, it becomes easier to get the solution to mitigate such problems. Here by taking the help of urban mobility tools like SUMO, it is possible to create a scenario for any futuristic event by taking past real-time information. And based on the scenario, it can be possible to define alternate routes for transportation for that particular event so that the overall traffic congestion can be reduced with proper visualization to understand the whole process.