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Recent Advancements and Research Challenges in Design and Implementation of Autonomous Vehicles
Autonomous Intelligent Vehicles
GSA‐ELM: A hybrid learning model for short‐term traffic flow forecasting
Machine‐learning methodology for energy efficient routing
PLSAV: Parallel loop searching and verifying for loop closure detection
Detecting and interpreting non‐recurrent congestion from traffic and social media data
Automatic classification of traffic incident's severity using machine learning approaches
Lane detection method based on lane structural analysis and CNNs
Understanding drivers' route choice behaviours in the urban network with machine learning models
Prediction of energy consumption for new electric vehicle models by machine learning
Use of learning classifier systems in microscopic toll plaza simulation models
Deep learning methods in transportation domain: a review
Hybrid model for predicting anomalous large passenger flow in urban metros
Comparative analysis of implicit models for real‐time short‐term traffic predictions
Unsupervised hybrid anomaly detection model for logistics fleet management systems
Advanced accident prediction models and impacts assessment
Hybrid machine learning and optimisation method to solve a tri‐level road network protection problem
Smartphone‐based fatigue detection system using progressive locating method
Driver identification in intelligent vehicle systems using machine learning algorithms
Value‐based deep reinforcement learning for adaptive isolated intersection signal control