Intelligent Transportation Systems Projects for M.E, M.Tech, Masters, MS abroad, and PhD students. These Intelligent Transportation Systems ieee projects are implemented with future work and extension for final year project submission with research paper publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Intelligent Transportation Systems Projects
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Advanced Learning Technologies for Intelligent Transportation Systems: Prospects and Challenges
This project studies how smart transportation systems can be improved using deep learning. It looks at how traffic, vehicles, roads, and weather affect transportation. The study explains modern AI methods for predicting traffic, recognizing vehicles, and monitoring road conditions. It also highlights challenges and future ideas to make transportation safer and more efficient. -
Sustainable Mobility in B5G/6G: V2X Technology Trends and Use Cases
This project studies how mobile communication technologies can make transportation more sustainable. It looks at smart city vehicles that communicate with each other and with infrastructure. The research explores trends like climate-friendly systems, cloud and edge computing, and AI to improve vehicle networks. It also estimates how these technologies can reduce fuel use and greenhouse gas emissions. -
A C-ITS Architecture for MEC and Cloud Native Back-End Services
This project builds a smart system that helps vehicles communicate quickly and safely using cloud and edge computing. It connects cars, nearby servers, and cloud systems to share traffic and road data in real time. The design reduces delays and supports many connected vehicles at once. It was tested to ensure smooth and scalable communication between all parts. -
2CAP A Novel Curve Crash Avoidance Protocol to Handle Curve Crashes in Vehicular Ad-Hoc Network
This project focuses on preventing accidents on curved roads. It uses smart sensors in vehicles to detect dangerous curves and warn drivers in advance. The system collects road and vehicle data and processes it using a machine learning model to predict risky turns. This helps reduce crashes and saves lives by improving road safety.
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