Data sharing framework for naturalistic driving data

This paper describes the content of a proposed Data Sharing Framework for data collected in Field Operational Tests and in Naturalistic Driving Studies. These projects gather data regarding the driver behaviour in relation to the vehicle, ITS and traffic environment during normal driving. Huge amounts of data are stored from these tests and could be re-used in many different fields of research, i.e. safety, automated driving or mobility, to understand the human behaviour in different traffic environments. The framework includes topics such as data description, data protection and storage, research support services and topics to address in agreements to make data re-use possible. The purpose of the framework is to facilitate global data sharing and re-use and thereby enhance the availability of data for future research in ITS

A Platform for sharing data from field operational tests

In this paper we will describe how a platform is being developed for sharing data collected in Field Operational Tests (FOTs). In these tests often a huge amount of data is gathered about driver behaviour and the interaction between drivers, vehicles, ITS, infrastructure and the traffic environment. These datasets are often only partly analysed, because of targeted research goals and lack of resources. They may be of great value for other organisations and researchers in order to answer further research questions and to determine the impact of widescale use of ITS. The paper will describe a how a European platform for enabling data sharing and data re-use is being developed

Business ethics : practical proposals

While most people agree that the inculcation of ethical awareness is desirable, the means of stimulating this awareness vary among companies, industries and cultures. The fundamental question surrounding the difference between social responsibility and ethics is addressed. Guidelines for establishing ethical priorities from both the individual, group and organisational perspectives are provided. <br /

The Current State of Performance Appraisal Research and Practice: Concerns, Directions, and Implications

On the surface, it is not readily apparent how some performance appraisal research issues inform performance appraisal practice. Because performance appraisal is an applied topic, it is useful to periodically consider the current state of performance research and its relation to performance appraisal practice. This review examines the performance appraisal literature published in both academic and practitioner outlets between 1985 and 1990, briefly discusses the current state of performance appraisal practice, highlights the juxtaposition of research and practice, and suggests directions for further research

Data sharing of transport research data

With the rapid progress of the development of intelligent transport systems over the last 15 years, the need for testing them in the real world and collecting data about their impact became more and more important. We have seen a fast growth in the number of Field Operational Tests (FOT) and Naturalistic Driving Studies (NDS) performed worldwide. The need to better understand the benefits of safety systems and the factors behind the occurrence of incidents and accidents have been a main driving force and the data has therefore been collected through naturalistic driving by volunteer drivers. As the number of different datasets has increased and so also the awareness of the substantial effort and funding needed to run these FOT/NDS, the interest in data sharing has increased worldwide. The availability of a common Data Sharing Framework (DSF) could highly facilitate a larger use of the collected FOT/NDS data. The FOT-Net Data project has developed such a framework, in collaboration with a variety of stakeholders from Europe, the US, Japan and other countries. The seven topics addressed by the DSF are (1) project agreements, (2) data and metadata descriptions, (3) data protection, (4) training, (5) support and research services, (6) financial models and (7) applications procedures. Many of the topics are general and can be used for other types of transport research data as well. There remain challenges to make data sharing possible on a global scale. Some of these are: the project funding schemes, leading to multiple schemas of ownerships of data, and the legal settings in different countries. On a technical level, the documentation of datasets and of the metadata describing the test is not always sufficient. Furthermore, new projects need to be made aware of the importance of inserting the pre-requisites for data sharing into the different project agreements right from the start. This paper describes the content of the DSF with its hands-on recommendations on how to prepare for and perform data sharing of transport research data. It also presents the status of a use case, implementing the DSF into the European project UDRIVE

Anonymization of Data from Field Operational Tests

Data anonymization is a rising topic and is included in the EU's ITS directive. It brings new requirements for products and projects. Plans to arrange Field Operational Tests on connected ITS systems and automated driving are part of the European H2020 research and innovation programme. Data sharing will be an important part of those projects, aiming at widely studying the test data. Without anonymization and other data post-processing techniques to strip the logs of personal and confidential information, data sharing cannot happen or at least will require extensive non-disclosure agreements between several organisations. This paper discusses the state of the art on data sharing and anonymization techniques for FOT data sets, concentrating especially on video and GPS data