Traffic Pattern

Traffic pattern analysis aims to understand and predict the movement of vehicles and pedestrians, informing improved transportation infrastructure and management. Current research focuses on developing accurate predictive models using diverse data sources (e.g., sensor networks, video, GPS traces) and advanced machine learning techniques, including recurrent neural networks (RNNs), graph convolutional networks (GCNs), and transformer architectures, often incorporating transfer learning and data augmentation to address data limitations. These advancements have significant implications for optimizing traffic flow, enhancing urban planning, improving autonomous vehicle navigation, and bolstering network security through improved intrusion detection.

Papers

September 14, 2023

TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection
Dania Herzalla, Willian T. Lunardi, Martin Andreoni Lopez
MAESTRO Dataset Unsupervised Anomaly Detection Intrusion Detection Detection Model Network Intrusion Detection Traffic Pattern Typological Exploration

August 20, 2023

Enhancing Spatiotemporal Traffic Prediction through Urban Human Activity Analysis
Sumin Han, Youngjun Park, Minji Lee, Jisun An, Dongman Lee
Graph Convolution Traffic Prediction Traffic Pattern Spatiotemporal Traffic

August 11, 2023

July 10, 2023

Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey
Pranav Singh Chib, Pravendra Singh
Deep Learning Timely Survey Autonomous Driving Recent Advance Traffic Pattern End to End Autonomous Driving End to End Driving Driving Task

June 21, 2023

Understanding human mobility patterns in Chicago: an analysis of taxi data using clustering techniques
Harish Chauhan, Nikunj Gupta, Zoe Haskell-Craig
General Analysis Human Mobility Clustering Method Traffic Pattern Ride Hailing Data

June 2, 2023

Improving the generalizability and robustness of large-scale traffic signal control
Tianyu Shi, Francois-Xavier Devailly, Denis Larocque, Laurent Charlin
Native Robustness Multi Agent Reinforcement Learning Stronger Generalizability Distributional Reinforcement Learning Traffic Signal Control Traffic Pattern

May 2, 2023

FlowMap: Path Generation for Automated Vehicles in Open Space Using Traffic Flow
Wenchao Ding, Jieru Zhao, Yubin Chu, Haihui Huang, Tong Qin, Chunjing Xu, Yuxiang Guan, Zhongxue Gan
Automated Driving Traffic Flow Traffic Pattern Path Generation Flow Map Like Path

May 1, 2023

Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction
Weiheng Zhong, Hadi Meidani, Jane Macfarlane
Neural ODE Graph Attention Traffic Forecasting Traffic Datasets Traffic Pattern Attention Graph

April 14, 2023

Smart Metro: Deep Learning Approaches to Forecasting the MRT Line 3 Ridership
Jayrald Empino, Jean Allyson Junsay, Mary Grace Verzon, Mideth Abisado, Shekinah Lor Huyo-a, Gabriel Avelino Sampedro
Deep Learning Traffic Pattern Passenger Flow Historical Ridership Data

March 17, 2023

Urban Regional Function Guided Traffic Flow Prediction
Kuo Wang, Lingbo Liu, Yang Liu, Guanbin Li, Fan Zhou, Liang Lin
Traffic Flow Prediction Traffic Pattern Flow Prediction

March 14, 2023

Traffic4cast at NeurIPS 2022 -- Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors
Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David Kreil, Sepp Hochreiter
Sparse Data Traffic Pattern Urban Traffic Dynamic Prediction Traffic4cast Competition Future Traffic Graph Edge Road Network Data

January 19, 2023

Causal conditional hidden Markov model for multimodal traffic prediction
Yu Zhao, Pan Deng, Junting Liu, Xiaofeng Jia, Mulan Wang
Temporal Correlation Causal Event Traffic Flow Traffic Pattern

December 21, 2022

5G Long-Term and Large-Scale Mobile Traffic Forecasting
Ufuk Uyan, M. Tugberk Isyapar, Mahiye Uluyagmur Ozturk
Large Scale Long Term Traffic Pattern Cellular Traffic

December 15, 2022

Anomaly Detection in Driving by Cluster Analysis Twice
Chung-Hao Lee, Yen-Fu Chen
Anomaly Detection Sensor Data Traffic Pattern Cluster Analysis Driving Context

December 6, 2022

Trajectory Flow Map: Graph-based Approach to Analysing Temporal Evolution of Aggregated Traffic Flows in Large-scale Urban Networks
Jiwon Kim, Kai Zheng, Jonathan Corcoran, Sanghyung Ahn, Marty Papamanolis
Trajectory Data Network Traffic Traffic Pattern Graph Based Approach Temporal Evolution Urban Network

October 30, 2022

Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting
Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou
Graph Attention Network Traffic Forecasting Traffic Pattern Traffic4cast Competition Intrinsic Feature Transposed Convolution

July 4, 2022

NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction
Xueyan Yin, Feifan Li, Yanming Shen, Heng Qi, Baocai Yin
Transfer Learning Traffic Prediction Traffic Network Traffic Pattern Temporal Traffic Graph Transfer Learning

February 21, 2022

Data-Driven Traffic Assignment: A Novel Approach for Learning Traffic Flow Patterns Using a Graph Convolutional Neural Network
Rezaur Rahman, Samiul Hasan
Novel Approach Graph Convolutional Neural Network Traffic Pattern Transportation Network Traffic Assignment Driven Network

January 15, 2022

Network Level Spatial Temporal Traffic State Forecasting with Hierarchical Attention LSTM (HierAttnLSTM)
Tianya Terry Zhang
Big Data Traffic Pattern Travel Time Hierarchical Recurrent

Traffic Pattern

Papers

TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection

Enhancing Spatiotemporal Traffic Prediction through Urban Human Activity Analysis

Uncertainty Quantification for Image-based Traffic Prediction across Cities

Automated Construction of Time-Space Diagrams for Traffic Analysis Using Street-View Video Sequence

Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey

Understanding human mobility patterns in Chicago: an analysis of taxi data using clustering techniques

Improving the generalizability and robustness of large-scale traffic signal control

FlowMap: Path Generation for Automated Vehicles in Open Space Using Traffic Flow

Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction

Smart Metro: Deep Learning Approaches to Forecasting the MRT Line 3 Ridership

Urban Regional Function Guided Traffic Flow Prediction

Traffic4cast at NeurIPS 2022 -- Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors

Causal conditional hidden Markov model for multimodal traffic prediction

5G Long-Term and Large-Scale Mobile Traffic Forecasting

Anomaly Detection in Driving by Cluster Analysis Twice

Trajectory Flow Map: Graph-based Approach to Analysing Temporal Evolution of Aggregated Traffic Flows in Large-scale Urban Networks

Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting

NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction

Data-Driven Traffic Assignment: A Novel Approach for Learning Traffic Flow Patterns Using a Graph Convolutional Neural Network

Network Level Spatial Temporal Traffic State Forecasting with Hierarchical Attention LSTM (HierAttnLSTM)