Predicting the spatiotemporal legality of on-street parking using open data and machine learning

S Gao, M Li, Y Liang, J Marks, Y Kang, M Li - Annals of GIS, 2019 - Taylor & Francis
Searching for a parking spot in metropolitan areas is a great challenge, especially in highly
populated areas such as downtown districts and job centres. On-street parking is often a …

[HTML][HTML] The illegal parking score–Understanding and predicting the risk of parking illegalities in Lisbon based on spatiotemporal features

B Jardim, N Alpalhão, P Sarmento… - Case Studies on …, 2022 - Elsevier
Illegal parking represents a costly problem for most cities as it leads to an increase in traffic
congestion and emission of air pollutants, and decreases pedestrian, biking, and driving …

Short-term prediction of available parking space based on machine learning approaches

X Ye, J Wang, T Wang, X Yan, Q Ye, J Chen - IEEE Access, 2020 - ieeexplore.ieee.org
Reliable short-term prediction of available parking space (APS) is the basic theory of parking
guidance information system (PGIS). Based on the Intelligent parking system at the Eastern …

Predicting safe parking spaces: A machine learning approach to geospatial urban and crime data

I Matijosaitiene, A McDowald, V Juneja - Sustainability, 2019 - mdpi.com
This research aims to identify spatial and time patterns of theft in Manhattan, NY, to reveal
urban factors that contribute to thefts from motor vehicles and to build a prediction model for …

Multisource data integration and comparative analysis of machine learning models for on-street parking prediction

S Inam, A Mahmood, S Khatoon, M Alshamari… - Sustainability, 2022 - mdpi.com
Searching for a free parking space can lead to traffic congestion, increasing fuel
consumption, and greenhouse gas pollution in urban areas. With an efficient parking …

Predicting on-street parking violation rate using deep residual neural networks

N Karantaglis, N Passalis, A Tefas - Pattern Recognition Letters, 2022 - Elsevier
The lack of available parking spaces can be among the most significant issues that can
affect the quality of life of citizens in large cities. This has led to the development of on-street …

A machine learning approach for modelling parking duration in urban land-use

J Parmar, P Das, SM Dave - Physica A: Statistical Mechanics and its …, 2021 - Elsevier
Parking is an inevitable issue in the fast-growing developing countries. Increasing number of
vehicles require more and more urban land to be allocated for parking. However, a little …

Contextual prediction of parking spot availability: A step towards sustainable parking

G Jelen, V Podobnik, J Babic - Journal of cleaner production, 2021 - Elsevier
One of the challenges of living in today's cities is parking availability. Searching for available
parking spots can be a time-consuming task that simultaneously increases traffic congestion …

A smart eco-system for parking detection using deep learning and big data analytics

SNR Mettupally, V Menon - 2019 SoutheastCon, 2019 - ieeexplore.ieee.org
This work aims to conduct a comprehensive study on existing parking infrastructures and
proposes intelligent parking solutions using novel Big Data Analytics with Deep Learning …

Parking occupancy prediction under COVID-19 anti-pandemic policies: A model based on a policy-aware temporal convolutional network

Z Niu, X Hu, M Fatmi, S Qi, S Wang, H Yang… - … Research Part A: Policy …, 2023 - Elsevier
Real-time and reliable parking occupancy prediction is critical for managing transportation
infrastructure and services. However, the COVID-19 pandemic and its corresponding …