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Hybrid attention-RNN and HMM framework for reliable high-speed arterial vs. urban road classification under degraded GPS conditions

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By R. Karthikeyan, V. Balaji, Praveen Kumar Balachandran, Sangeetha Kannan, V. Allwyn, S. Faizal Mukthar Hussain, S. Ramamoorthi
| Nature Verified
Abstract Classifying vehicles as travelling on a high-speed arterial road or a low-speed urban road is important for Intelligent Transportation System (ITS), especially for applications like GNSS-based tolling. However, this task still poses a significant challenge. The traditional algorithms like Geometric, Hidden Markov Models (HMMs), and Kalman Filters fail in urban areas where GPS signals are poor, signal reflection which creates errors that confuse these algorithms.
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