Travel behavior understanding is a long-standing and critically important topic in the area of
smart cities. Big volumes of various GPS-based travel data can be easily collected, among …

Destination prediction is known as an important problem for many location based services
(LBSs). Existing solutions generally apply probabilistic models or neural network models to …

Two-thirds of the people who buy a new car prefer to use a substitute instead of the built-in
navigation system. However, for many applications, knowledge about a user's intended …

Proposed work uses big data analysis and machine learning approach to accurately predict
the taxi travel time for a trip based on its partial trajectory. To achieve the target, ensemble …

Ultra-dense networking (UDN) is a promising technology to improve the network capacity in
the next-generation mobile communication system. The virtualization paradigm is tightly …

The prediction of the destination location at the time of pickup is an important problem with
potential for substantial impact on the efficiency of a GPS-enabled taxi service. While this …

Taxi waiting times is an important criterion for taxi passengers to choose appropriate pick-up
locations in urban environments. How to predict the taxi waiting time accurately at a certain …

This study aimed to evaluate the driving behavior of taxi drivers in Isfahan, Iran, and assess
the probability of a driver being among the high‐risk taxi drivers. To identify risky driving …

Trajectory prediction aims to estimate an entity's future path using its current position and
historical movement data, benefiting fields like autonomous navigation, robotics, and human …

Vehicle trajectory modelling is an essential foundation for urban intelligent services. In this
paper, a novel method, Distant Neighbouring Dependencies (DND) model, has been …