A survey of traffic prediction: from spatio-temporal data to intelligent transportation

H Yuan, G Li - Data Science and Engineering, 2021 - Springer
Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

A survey of localization methods for autonomous vehicles in highway scenarios

J Laconte, A Kasmi, R Aufrère, M Vaidis, R Chapuis - Sensors, 2021 - mdpi.com
In the context of autonomous vehicles on highways, one of the first and most important tasks
is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take …

Transformer-based map-matching model with limited labeled data using transfer-learning approach

Z **, J Kim, H Yeo, S Choi - Transportation Research Part C: Emerging …, 2022 - Elsevier
In many spatial trajectory-based applications, it is necessary to map raw trajectory data
points onto road networks in digital maps, which is commonly referred to as a map-matching …

Fl-amm: Federated learning augmented map matching with heterogeneous cellular moving trajectories

H Lu, F Lyu, H Wu, J Zhang, J Ren… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Map matching is a fundamental component for location-based services (LBSs), such as
vehicle mobility analysis, navigation services, traffic scheduling, etc. In this paper, we …

Rntrajrec: Road network enhanced trajectory recovery with spatial-temporal transformer

Y Chen, H Zhang, W Sun… - 2023 IEEE 39th …, 2023 - ieeexplore.ieee.org
GPS trajectories are the essential foundations for many trajectory-based applications. Most
applications require a large number of high sample rate trajectories to achieve a good …

Deep spatial-temporal travel time prediction model based on trajectory feature

Z Sheng, Z Lv, J Li, Z Xu - Computers and Electrical Engineering, 2023 - Elsevier
Research on travel time prediction shows its importance in the rational planning of travel
arrangements and traffic congestion mitigation. The scale of taxi and online ride-hailing …

DMM: Fast map matching for cellular data

Z Shen, W Du, X Zhao, J Zou - Proceedings of the 26th annual …, 2020 - dl.acm.org
Map matching for cellular data is to transform a sequence of cell tower locations to a
trajectory on a road map. It is an essential processing step for many applications, such as …

Analytical review of map matching algorithms: analyzing the performance and efficiency using road dataset of the indian subcontinent

S Singh, J Singh, SB Goyal, M El Barachi… - … Methods in Engineering, 2023 - Springer
Precise position information of moving entities on digital road networks is a vital requirement
of location-based applications. Location information received from Global Positioning …

L2mm: learning to map matching with deep models for low-quality gps trajectory data

L Jiang, CX Chen, C Chen - ACM Transactions on Knowledge Discovery …, 2023 - dl.acm.org
Map matching is a fundamental research topic with the objective of aligning GPS trajectories
to paths on the road network. However, existing models fail to achieve satisfactory …

Deep learning for trajectory data management and mining: A survey and beyond

W Chen, Y Liang, Y Zhu, Y Chang, K Luo… - arxiv preprint arxiv …, 2024 - arxiv.org
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …