Enhancing Public Transportation Through Advanced Technologies: A Comprehensive Review

Abstract

Public transport is crucial for the sustained development of the region. Modernising it with technologies like Intelligent Transportation Systems (ITS) is vital to tackle climate change by reducing the transport sector’s carbon footprint, especially because the model share of public transport is steadily declining. This work provides a concise overview of the pivotal considerations associated with public transit planning such as vehicle capacity and types, dynamic demand patterns, required headway, variability in headway, vehicle bunching, and fare evasion. The work also explores the use of cutting-edge technologies in the domain of ITS encompassing Machine Learning, cloud computing, fog and edge computing, Internet of Things (IoT) and big data analytics; these technologies are employed to address the issues encountered in this sector. Furthermore, the work investigates the utilization of the travelling salesman problem (TSP) and its variations as a tactic for path planning, along with the implementation of contemporary optimization techniques. An ITS based transit monitoring system can predict demand, monitor transit vehicles, rectify deficiencies, and enhance scheduling, route optimisation through vehicle planning algorithms, thereby increasing service reliability, reducing travel time, and improving customer experience. Finally, some of the challenges in implementation of the ITS in transit planning as well as challenges in considerations in transit planning are recognized.