Parking prediction in smart cities: A survey

X **ao, Z Peng, Y Lin, Z **, W Shao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
With the growing number of cars in cities, smart parking is gradually becoming a strategic
issue in building a smart city. As the precondition in smart parking, accurate parking …

Parking occupancy prediction method based on multi factors and stacked GRU-LSTM

C Zeng, C Ma, K Wang, Z Cui - Ieee Access, 2022 - ieeexplore.ieee.org
With the development of society and the continuous advancement of urbanization, motor
vehicles have increased rapidly, which exacerbates the imbalance between parking supply …

Parking availability prediction for sensor-enabled car parks in smart cities

Y Zheng, S Rajasegarar… - 2015 IEEE tenth …, 2015 - ieeexplore.ieee.org
The growth in low-cost, low-power sensing and communication technologies is creating a
pervasive network infrastructure called the Internet of Things (IoT), which enables a wide …

Parking demand forecasting based on improved complete ensemble empirical mode decomposition and GRU model

G Li, X Zhong - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Parking demand forecasting plays an important role in relieving traffic congestion and
reducing greenhouse gas emissions. However, most previous studies model based on …

A survey of parking solutions for smart cities

M Aljohani, S Olariu, A Alali… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Existing surveys look at parking solutions from the perspective of sensors, communication
protocols, and the hardware-software interface. While this is a worthwhile approach, it …

[HTML][HTML] Predicting parking occupancy via machine learning in the web of things

JC Provoost, A Kamilaris, LJJ Wismans… - Internet of Things, 2020 - Elsevier
Abstract The Web of Things (WoT) enables information gathered by sensors deployed in
urban environments to be easily shared utilizing open Web standards and semantic …

Predicting electric vehicle charging station availability using ensemble machine learning

C Hecht, J Figgener, DU Sauer - Energies, 2021 - mdpi.com
Electric vehicles may reduce greenhouse gas emissions from individual mobility. Due to the
long charging times, accurate planning is necessary, for which the availability of charging …

A user behavior and reinforcement learning based dynamic pricing method for idle connection time reduction at charging stations

X Zhou, Y Cai, Q Meng, Y Ji - Transportation Research Part A: Policy and …, 2025 - Elsevier
Reducing idle connection time is crucial for improving the operational efficiency of charging
stations and enhancing the satisfaction of electric vehicle (EV) users. During idle connection …

Analysis of user charging behavior at public charging stations

A Almaghrebi, S Shom, F Al Juheshi… - … and Expo (ITEC), 2019 - ieeexplore.ieee.org
Plug-in electric vehicles (PEVs) play significant role in the development of green cities, since
they have less impact on the environment compared to conventional vehicles. To promote …

Prediction of Vacant Parking Spaces in Multiple Parking Lots: A DWT-ConvGRU-BRC Model

L Gao, W Fan, Z Hu, W Jian - Applied Sciences, 2023 - mdpi.com
For cities, the problem of “difficult parking and chaotic parking” increases carbon emissions
and reduces quality of life. Accurately and efficiently predicting the availability of vacant …