With the increasing vehicles on the road, it is becoming more and more important to sense
citywide traffic, which is of great benefit to the government's policy-making and people's …

Many research works deal with big data platforms looking forward to data science and
analytics. These are complex and usually distributed environments, composed of several …

Traffic sensing has been revolutionized with the commoditization of GPS technology.
Smartphone navigation applications ubiquitously track vehicles as samples of the overall …

Accurate and efficient urban traffic flow prediction can help drivers identify road traffic
conditions in real-time, consequently helping them avoid congestion and accidents to a …

The goal of smart cities and sustainable transport is to ensure the efficient movement of
people while minimizing a negative impact on the environment. Many cities around the …

In this paper, we propose a new data-driven traffic state estimation model that estimates
traffic flow based on average speed data only. The model is devised to implement a cost …

With the great development of urban transportation systems, immediate urban traffic
information has become an essential resource for the public. Traffic estimation is to predict …

This study develops an optimal mobile-communication-based National Highway traffic
volume estimation model using an ensemble-based machine learning algorithm. Based on …

Human activities in cities, such as eating foods in restaurants and attending special events,
are traditionally measured using surveys, questionnaires, and interviews. While such …

Location data is vital for traffic management and for transportation and urban planning, but
also benefits people in daily life, helping on decisions related to route planing and on the …