Road Traffic Prediction and Optimal Alternate Path Selection Using HBI-LSTM and HV-ABC

Objectives: The objective of this work is to monitor and manage the traffic flow, so an Intelligent Transportation System (ITS) developed that comprises fundamental information real-time flow. Methods: For reducing road Traffic Congestion (TC), paper proffers efficient prediction framework optimal alternate route selection. conversion videos (from surveillance camera) into frames done, then pre-processing occurs. Then, for recognizing on roadways, background elimination utilizing Gaussian Mixture Model (GMM) performed. Next, identifying vehicle motion, Motion Estimation (ME) Virtual loop-based Lucas-Kanade (VLK) technique Utilizing You Only Look Once (YOLO) technique, are segmented centered estimated motion type objects road. classifying number in frames, H-detach optimized Bidirectional Long Short Term Memory (HBI-LSTM) utilized. classified by classifier as heavy traffic, medium low traffic. Findings: Horizontal Vertical cross-search appended Artificial Bee Colony (HV-ABC) optimization algorithm, paths chosen from different other routes if or medium. Novelty: experimental outcomes demonstrate top-notch models outperformed proposed framework. Keywords: Congestion, Surveillance Videos, Noise Removal, Estimation, Path Selection, (ABC) Optimization