Forecasting Delivery Pattern through Floating Car Data: Empirical Evidence

Offloading Floating Car Data through V2V Communication

During a century of existence, vehicles transformed from mechanical master pieces into consumer products with more and more computing power and sensing capabilities. Current vehicles include tens or even hundreds of Electronic Control Units (ECUs) that gather important amounts of information from the embedded sensors, and use this information to control different parts of the vehicles or to pro...

Supporting augmented floating car data through smartphone-based crowd-sensing

Traffic Condition Forecasting System by Floating Car Data with Data Mining Method

A traffic condition forecasting system using floating car data in conjunction with a data mining method is proposed. A register network is used to describe the congestion model. The register network denotes the dual graph of the actual road link connections. In this forecasting system, estimation and learning agents alternately calculate the results to improve the forecasting accuracy. To forec...

Intelligent extended floating car data collection

The elaboration of data collected by vehicles moving on road network is relevant for traffic management and for private service providers, which can bundle updated traffic information with navigation services. Floating data, in its extended acceptation, contains not only time and location provided by a positioning system, but also information coming from various vehicle sensors. In this paper w...

Traffic State Estimation Using Floating Car Data

There is an increasing availability of floating car data both historic, in the form of trajectory datasets and real-time, in the form of continuous data streams. This paves the way for several advanced traffic management services such as current traffic state estimation, congestion and incident detection and prediction of the short-term evolution of traffic flow. In this paper, we present an an...