A learning-based vehicle-trajectory generation method for vehicular networking

L Zhao, Y Liu, A Al-Dubai, Z Tan… - 2019 IEEE 21st …, 2019 - ieeexplore.ieee.org
With the rapid development of mobile applications, networking technologies have been
constantly evolved to offer a more convenient way of sharing information and online …

En route: Towards vehicular mobility scenario generation at scale

R Ketabi, B Alipour, A Helmy - 2017 ieee conference on …, 2017 - ieeexplore.ieee.org
Vehicular mobility scenarios are utilized to study vehicular networks and transportation
systems. However, the generation of vehicular simulation scenarios at scale poses several …

Synthesizing town-scale vehicle mobility from traffic surveillance cameras: A case study

K Hayashi, A Hiromori, H Yamaguchi… - … and other Affiliated …, 2022 - ieeexplore.ieee.org
This paper presents a case study on synthesizing realistic vehicle mobility using link traffic
information extracted from surveillance videos. Our trial has been conducted in a town of …

Data-driven traffic flow analysis for vehicular communications

Y Wang, L Huang, T Gu, H Wei, K Xing… - IEEE INFOCOM 2014 …, 2014 - ieeexplore.ieee.org
Due to high mobility and frequent disconnections in a vehicular network, reliable and
efficient vehicular communication is very challenging. Previous studies focus on predicting …

On the temporal analysis of vehicular networks

C Celes, A Boukerche… - 2018 IEEE Symposium on …, 2018 - ieeexplore.ieee.org
Vehicular networks are seen as the key communication solution for intelligent transportation
systems. An essential task for the development of solutions for vehicular networks is to …

Deep Learning based Urban Vehicle Trajectory Analytics

S Choi - arXiv preprint arXiv:2111.07489, 2021 - arxiv.org
Atrajectory'refers to a trace generated by a moving object in geographical spaces, usually
represented by of a series of chronologically ordered points, where each point consists of a …

Generation and analysis of a large-scale urban vehicular mobility dataset

S Uppoor, O Trullols-Cruces, M Fiore… - IEEE Transactions …, 2013 - ieeexplore.ieee.org
The surge in vehicular network research has led, over the last few years, to the proposal of
countless network solutions specifically designed for vehicular environments. A vast majority …

Space and time matter: An analysis about route selection in mobility traces

ACSA Domingues, FA Silva… - 2018 ieee symposium …, 2018 - ieeexplore.ieee.org
The feasibility of vehicular networks is directly related to the understanding of mobility
patterns, which is a necessary knowledge for the elaboration and application of novel …

Applying deep recurrent neural network to predict vehicle mobility

W Liu, Y Shoji - 2018 IEEE Vehicular Networking Conference …, 2018 - ieeexplore.ieee.org
Sensing data gathering and dissemination is one of the most challenging tasks in smart city
construction, and vehicles moving around a city have been widely considered as a good …

Vemo: Enabling transparent vehicular mobility modeling at individual levels with full penetration

Y Yang, X Xie, Z Fang, F Zhang, Y Wang… - The 25th Annual …, 2019 - dl.acm.org
Understanding and predicting real-time vehicle mobility patterns on highways are essential
to address traffic congestion and respond to the emergency. However, almost all existing …