Data-Driven Mobility System for Vehicular Communication: A Step Towards Transport Resilience in Intelligent Transport Systems

Intelligent Transport Systems (ITS) collect a dynamic and versatile range of data from vehicles and infrastructure to analyze and regulate the traffic and network flow. The collected data optimizes ITS functional capacity and efficiency to build smart infrastructure or smart cities. The issue arises when huge data volumes from rapidly transitioning vehicles result in missing data points, poor analytical capabilities, replication, higher cost, big volumes, increased time, and congestion followed by frequent network disruptions and disoriented communication.Ensuring transport resilience is crucial to maintaining stable and adaptive mobility systems that can withstand such disruptions and optimize real-time decision-making. To practically design solutions for previously mentioned challenges, an optimized Intelligent Information System (IDT) is proposed that is a self-maturing data information system set to independently train data streams coming from real-time traffic to facilitate data communication. Data is set to be processed and stored through designated smart interchangeable logs established using Apache Spark. Live data streams are integrated into the information system to induce independent learning within vehicles for smooth ITS operation. IDT’s functionalities are enhanced through dynamic segmentation switching which is a smart feature of calculated division and time-dependent interoperability of segments to avoid replicated data and network bottlenecks. IDT’s features and modules are real-time implemented on Ireland’s largest road network M50. Its operations, functionalities, and features are set to perform model training based on collected data for transparent communication in a cost-effective way. The validated results have shown that the given data information system is accomplishing higher performance with optimal resource utilization with rich and time-efficient data communication ranging from 70% to 94% based on architectural complexities and traffic ratios.