Grenoble traffic lab: An experimental platform for advanced traffic monitoring and forecasting [applications of control]

CC De Wit, F Morbidi, LL Ojeda… - IEEE Control …, 2015 - ieeexplore.ieee.org
The start from the Ocean House was something marvelous to see. The drivers stormed and
scolded, the women shrieked and cried, wheels locked at intervals of perhaps ten minutes …

A Survey of Traffic Flow Prediction Methods Based on Long Short-Term Memory Networks

BL Ye, M Zhang, L Li, C Liu… - IEEE Intelligent …, 2024 - ieeexplore.ieee.org
It is generally recognized that accurate and timely prediction of future traffic flow information
is one of the important conditions for improving the utilization rate of road networks and …

Real-time traffic prediction and probing strategy for Lagrangian traffic data

KC Chu, R Saigal, K Saitou - IEEE Transactions on Intelligent …, 2018 - ieeexplore.ieee.org
The objective of this paper is to present a new analytical tool that predicts highway
congestion in real time by utilizing a macroscopic traffic flow model, and to investigate a data …

Unifying Uber and taxi data via deep models for taxi passenger demand prediction

J Zhao, C Chen, H Huang, C Xiang - Personal and Ubiquitous Computing, 2023 - Springer
Taxi passenger demand prediction is of great significance to perceive citywide human
mobility and make a lot of urban sensing applications more convenient. There are two major …

Efficient deep learning based method for multi‐lane speed forecasting: a case study in Beijing

W Lu, Z Yi, W Liu, Y Gu, Y Rui… - IET Intelligent Transport …, 2020 - Wiley Online Library
Real‐time and accurate multi‐lane traffic condition forecasting is of great importance to the
connected and automated vehicle highway system. However, the majority of existing deep …

Network-wide traffic state estimation and rolling horizon-based signal control optimization in a connected vehicle environment

A Emami, M Sarvi, SA Bagloee - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper presents an innovative method to adaptively optimize traffic signal plans based
on the estimation of traffic situation achieved from the information of various penetration …

A Transfer Learning–Based LSTM for Traffic Flow Prediction with Missing Data

Z Zhang, H Yang, X Yang - Journal of transportation engineering …, 2023 - ascelibrary.org
Traffic flow prediction plays an important role in intelligent transportation systems (ITS) on
freeways. However, incomplete traffic information tends to be collected by traffic detectors …

Origin-destination flow prediction with vehicle trajectory data and semi-supervised recurrent neural network

T Huang, Y Ma, ZT Qin, J Zheng, HX Liu… - … Conference on Big …, 2019 - ieeexplore.ieee.org
Origin-Destination (OD) flow data is an important instrument for traffic study and
management. So far traditional ways like surveys or detectors are costly and only give …

[PDF][PDF] Regression based forecast of electricity demand of New Delhi

A Goel, A Goel - International Journal of Scientific and Research …, 2014 - Citeseer
The forecast of electricity demand in India is of considerable interest since the electricity
sector has been the prime focus of past as well as present Governments. This study presents …

Precise stop control and experimental validation for metro train overcoming delays and nonlinearities

J Kim, J Park, Y Eun - IEEE Transactions on Vehicular …, 2022 - ieeexplore.ieee.org
Automatic Train Operator (ATO) is a system equipped on metro trains and controls train
operation. One of the main functions of ATO is precise stop control, which aims to ensure …