The EU project X-TEAM D2D focuses on future seamless door-to-door mobility, considering the experiences from Air Traffic Management and the currently available and possible future transport modalities in overall multimodal traffic until 2050. This paper deals with developing a Concept of Operations of an intermodal transport system with special consideration of the pabengers' satisfaction with up to 4-hour journeys. For this purpose, the influences of quality management systems and other organizational facilities on the quality of pabenger travel in the transport system were examined. In the study, integration of various management systems, like resources, traffic information, energy, fleet emergency calls, security and infrastructure, and applications such as weather information platforms and tracking systems, is expected.
In the city of Amsterdam commercial transport is responsible for 15% of vehicles, 34% of traffic’s CO2 emissions and 62% of NOx emissions. The City of Amsterdam plans to improve traffic flows using real time traffic data and data about loading and unloading zones. In this paper, we present, reflect, and discuss the results of two projects from the Amsterdam University of Applied Sciences with research partners from 2016 till 2018. The ITSLOG and Sailor projects aim to analyze and test the benefits and challenges of connecting ITS and traffic management to urban freight transport, by using real-time data about loading and unloading zone availability for rerouting trucks. New technologies were developed and tested in collaboration with local authorities, transport companies and a food retailer. This paper presents and discusses the opportunities and challenges faced in developing and implementing this new technology, as well as the role played by different stakeholders. In both projects, the human factor was critical for the implementation of new technologies in practice.
MULTIFILE
We present a novel anomaly-based detection approach capable of detecting botnet Command and Control traffic in an enterprise network by estimating the trustworthiness of the traffic destinations. A traffic flow is classified as anomalous if its destination identifier does not origin from: human input, prior traffic from a trusted destination, or a defined set of legitimate applications. This allows for real-time detection of diverse types of Command and Control traffic. The detection approach and its accuracy are evaluated by experiments in a controlled environment.
The Netherlands is one of the most densely populated countries in Europe. Despite the excellent road network, The Netherlands is confronted with this density on a daily basis: the negative impact of traffic jams and incidents on travel times is growing by 38% the next 5 years. VIA NOVA will lay the necessary foundation for the next step of technological developments to overcome these negative impacts of congestion in future. This next step in technological developments is called Talking Traffic. Vehicles will communicate directly with the infrastructure and other road users and vice versa. The potential with respect to congestion reduction is big, because traffic can be managed more directly. To reach this potential, Talking Traffic relies to a large extent on (big)data already available in modern cars: data of sensors, navigation, etc. However, the problem is data usage in terms of quality and variety among car-brands. The partners stressed the fact that besides technical requirements: data deployment quality, code of practice and a guideline, research should also address business requirements. Without a clear view on quality variations and demands with respect to quality, the data cannot be used effectively. VIA NOVA researches the following issues, o quality and quantity of data from cars o needed quality and quantity of data from cars in Talking Traffic use cases o big data analysis tools to interpret large quantities of data o business models, privacy and security of data from cars The outcome enables users to judge whether data from cars can be useful to solve specific traffic related problems, which data is than to be used, which quality of data is needed and finally the quantity of the needed data. With this measure Talking Traffic can be deployed more effectively resulting in more reduction of congestion.
