Geospatial Intelligence and Predictive Analytics for Autonomous Mobility

The evolution of autonomous mobility systems depends on the effective integration of using geospatial intelligence and predictive analytics to inform and realise real-time decisions in a highly complex dynamic environment. This type of integrated system is introduced in the paper and benefits safety and efficiency by ensuring complete autonomous control of cars, which can be obtained by integrating processing of data with geospatial data, predictive models operated through machine learning, and adaptive mobility algorithms. The literature review is undertaken to give a concise history of the methodologies that are offered in the field of geospatial intelligence, predictive modeling and autonomous navigation. The proposed technical model will reduce the real-time spatial stream of information, high definition mapping, sensor fusion and predictive analytics to the framework of cloud-edge hybrids. Further testing of the system is done in simulated conditions (traffic prediction, obstacle avoidance, route optimization).

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