Web and MATLAB-Based Platform for UAV Flight Management and Multispectral Image Processing.

The deployment of any UAV application in precision agriculture involves the development of several tasks, such as path planning and route optimization, images acquisition, handling emergencies, and mission validation, to cite a few. UAVs applications are also subject to common constraints, such as weather conditions, zonal restrictions, and so forth. The development of such applications requires the advanced software integration of different utilities, and this situation may frighten and dissuade undertaking projects in the field of precision agriculture.

Dataset Construction from Naturalistic Driving in Roundabouts.

A proper driver characterization in complex environments using computational techniques depends on the richness and variety of data obtained from naturalistic driving. The present article proposes the construction of a dataset from naturalistic driving specific to maneuvers in roundabouts and makes it open and available to the scientific community for performing their own studies. The dataset is a combination of data gathered from on-board instrumentation and data obtained from the post-processing of maps as well as recorded videos.

Think Aloud Protocol Applied in Naturalistic Driving for Driving Rules Generation.

Understanding naturalistic driving in complex scenarios is an important step towards autonomous driving, and several approaches have been adopted for modeling driver's behaviors. This paper presents the methodology known as "Think Aloud Protocol" to model driving. This methodology is a data-gathering technique in which drivers are asked to verbalize their thoughts as they are driving which are then recorded, and the ensuing analysis of the audios and videos permits to derive driving rules.

Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving.

This article presents a machine learning-based technique to build a predictive model and generate rules of action to allow autonomous vehicles to perform roundabout maneuvers. The approach consists of building a predictive model of vehicle speeds and steering angles based on collected data related to driver-vehicle interactions and other aggregated data intrinsic to the traffic environment, such as roundabout geometry and the number of lanes obtained from Open-Street-Maps and offline video processing. The study systematically generates rules of action regarding the vehicle speed and steering angle required for autonomous vehicles to achieve complete roundabout maneuvers.

A system for traffic violation detection.

This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations.

Data acquisition and real-time control using spreadsheets: interfacing Excel with external hardware.

Spreadsheets have become a popular computational tool and a powerful platform for performing engineering calculations. Moreover, spreadsheets include a macro language, which permits the inclusion of standard computer code in worksheets, and thereby enable developers to greatly extend spreadsheets' capabilities by designing specific add-ins. This paper describes how to use Excel spreadsheets in conjunction to Visual Basic for Application programming language to perform data acquisition and real-time control.