India, one of the world’s fastest-developing countries, is also experiencing a significant surge in population. The initial steps of planning and meeting the future demand for smart and sustainable cities are underway, coinciding with their rapid expansion. Consequently, there is a growing demand for enhanced mobility. When transportation is well managed, it has the potential to increase workforce efficiency, improve quality of life, and promote environmental sustainability, therefore making a significant contribution to economic growth within society. Traffic congestion is a significant problem that comes with an increase in the number of vehicles. Indian cities, with their existing infrastructure, necessitate improved, efficient, and intelligent resource management strategies to accommodate the increasing demand. Implementing an effective traffic management system has a higher probability of helping alleviate the issues at hand, thereby decreasing instances of traffic jams. In this chapter, the existing techniques and methods for traffic congestion detection using different geomatics techniques have been studied and compared against each other to draw appropriate conclusions and complement the preceding chapters. This chapter presents a comprehensive framework for the management of traffic flow through the utilization of artificial intelligence techniques, traffic detection technologies, and centralized supervision. The use of various measures, such as dynamic traffic signal regulations, dynamic speed restrictions, and accident detection, can effectively mitigate a range of traffic-related concerns. The concepts endeavor to transform the traffic management and monitoring methods in the present scenario, thereby making a valuable contribution to the field of intelligent and sustainable transportation planning.
Geomatics Approaches for Traffic Congestion Study
Sustainable Development and Geospatial Technology ; Chapter : 11 ; 197-212
2024-09-21
16 pages
Article/Chapter (Book)
Electronic Resource
English
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