Deep learning on traffic prediction: Methods, analysis, and future directions
X Yin, G Wu, J Wei, Y Shen, H Qi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
Travel time prediction system based on data clustering for waste collection vehicles
In recent years, intelligent transportation system (ITS) techniques have been widely
exploited to enhance the quality of public services. As one of the worldwide leaders in …
exploited to enhance the quality of public services. As one of the worldwide leaders in …
Multi-attention graph neural networks for city-wide bus travel time estimation using limited data
An important factor that discourages patrons from using bus systems is the long and
uncertain waiting times. Therefore, accurate bus travel time prediction is important to …
uncertain waiting times. Therefore, accurate bus travel time prediction is important to …
MLPST: MLP is All You Need for Spatio-Temporal Prediction
Traffic prediction is a typical spatio-temporal data mining task and has great significance to
the public transportation system. Considering the demand for its grand application, we …
the public transportation system. Considering the demand for its grand application, we …
Improving deep-learning methods for area-based traffic demand prediction via hierarchical reconciliation
Mobility services require accurate demand prediction in both space and time to effectively
manage fleet rebalancing, provide quick on-demand responses, and enable advanced ride …
manage fleet rebalancing, provide quick on-demand responses, and enable advanced ride …
Learning heterogeneous traffic patterns for travel time prediction of bus journeys
In this paper, we address the problem of travel time prediction of bus journeys which consist
of bus riding times (may involve multiple bus services) and also the waiting times at transfer …
of bus riding times (may involve multiple bus services) and also the waiting times at transfer …
Relational fusion networks: Graph convolutional networks for road networks
The application of machine learning techniques in the setting of road networks holds the
potential to facilitate many important intelligent transportation applications. Graph …
potential to facilitate many important intelligent transportation applications. Graph …
[HTML][HTML] Quantifying variable contributions to bus operation delays considering causal relationships
Bus services often face operational delays due to dynamic conditions such as traffic
congestion, which can propagate through bus routes, affecting overall system performance …
congestion, which can propagate through bus routes, affecting overall system performance …
Real-time bus arrival delays analysis using seemingly unrelated regression model
To effectively manage and control public transport operations, understanding the various
factors that impact bus arrival delays is crucial. However, limited research has focused on a …
factors that impact bus arrival delays is crucial. However, limited research has focused on a …
[HTML][HTML] A review of research on public transport priority based on CiteSpace
G Cheng, X Liu, Y Pei - Journal of traffic and transportation engineering …, 2023 - Elsevier
The prioritization of public transit as an essential means of promoting sustainable urban
development has a significant role in improving the quality of public transportation services …
development has a significant role in improving the quality of public transportation services …