A review of machine learning and IoT in smart transportation

F Zantalis, G Koulouras, S Karabetsos, D Kandris - Future Internet, 2019 - mdpi.com
With the rise of the Internet of Things (IoT), applications have become smarter and
connected devices give rise to their exploitation in all aspects of a modern city. As the …

Road traffic forecasting: Recent advances and new challenges

I Lana, J Del Ser, M Velez… - IEEE Intelligent …, 2018 - ieeexplore.ieee.org
Due to its paramount relevance in transport planning and logistics, road traffic forecasting
has been a subject of active research within the engineering community for more than 40 …

Deep learning methods in transportation domain: a review

H Nguyen, LM Kieu, T Wen… - IET Intelligent Transport …, 2018 - Wiley Online Library
Recent years have seen a significant amount of transportation data collected from multiple
sources including road sensors, probe, GPS, CCTV and incident reports. Similar to many …

Big data processing and analysis in internet of vehicles: architecture, taxonomy, and open research challenges

A Arooj, MS Farooq, A Akram, R Iqbal… - … Methods in Engineering, 2022 - Springer
The extensive progression in the Internet of Vehicles (IoV) and the exponential upsurge in
data consumption reflect the importance of big data in IoV. In general, big data has gained a …

Short-term speed predictions exploiting big data on large urban road networks

G Fusco, C Colombaroni, N Isaenko - Transportation Research Part C …, 2016 - Elsevier
Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the
road network and provide great opportunities for enhanced short-term traffic predictions …

Short-term traffic volume prediction using GA-BP based on wavelet denoising and phase space reconstruction

Y Peng, W Xiang - Physica A: Statistical Mechanics and its Applications, 2020 - Elsevier
Accurate traffic volume prediction can help traffic managers to control traffic well, and can
also provide convenient travel routes for passengers. In order to better describe the non …

Optimization of real-time traffic network assignment based on IoT data using DBN and clustering model in smart city

J Yang, Y Han, Y Wang, B Jiang, Z Lv… - Future Generation …, 2020 - Elsevier
With the rapid development of the information age, smart city has gradually become the
mainstream of urban construction. Dynamic transportation assignment has attracted more …

Data-driven short-term forecasting for urban road network traffic based on data processing and LSTM-RNN

W Xiangxue, X Lunhui, C Kaixun - Arabian Journal for Science and …, 2019 - Springer
A short-term traffic flow prediction framework is proposed for urban road networks based on
data-driven methods that mainly include two modules. The first module contains a set of …

Shaping future low-carbon energy and transportation systems: Digital technologies and applications

J Song, G He, J Wang, P Zhang - IEnergy, 2022 - ieeexplore.ieee.org
Digitalization and decarbonization are projected to be two major trends in the coming
decades. As the already widespread process of digitalization continues to progress …

A double auction mechanism for resource allocation in coded vehicular edge computing

JS Ng, WYB Lim, Z Xiong, D Niyato… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The development of smart vehicles and rich cloud services have led to the emergence of
vehicular edge computing. To perform the distributed computation tasks efficiently, Coded …