How navigation centric traffic management is rapidly changing traffic management already today

Despite large suspicion from road authorities in the beginning of the large-scale use of navigation systems, independent research has shown that the use of navigation systems leads to safer, more comfortable and less pollutant traffic. And there's more to come. The positive role of navigation systems in traffic management will even be even bigger now a new generation of connected navigation systems starts connecting drivers with each other. This paper will highlight the current and future potential of navigation technology for efficient and effective traffic management, based on research and the results of recent Field Operational Trials. Connected navigation technology is already starting to show the huge potential of ITS in everyday life and the added value for smarter mobility is expected to grow exponentially. The shift from a traffic center being in the lead of managing traffic, towards well-informed individuals taking the lead will have big implications on the future of traffic management. But it will for sure change for the better

How navigation centric traffic management is rapidly changing traffic management already today

Despite large suspicion from road authorities in the beginning of the large-scale use of navigation systems, independent research has shown that the use of navigation systems leads to safer, more comfortable and less pollutant traffic. And there's more to come. The positive role of navigation systems in traffic management will even be even bigger now a new generation of connected navigation systems starts connecting drivers with each other. This paper will highlight the current and future potential of navigation technology for efficient and effective traffic management, based on research and the results of recent Field Operational Trials. Connected navigation technology is already starting to show the huge potential of ITS in everyday life and the added value for smarter mobility is expected to grow exponentially. The shift from a traffic center being in the lead of managing traffic, towards well-informed individuals taking the lead will have big implications on the future of traffic management. But it will for sure change for the better.</p

Semantic Pyramids for Gender and Action Recognition

Person description is a challenging problem in computer vision. We investigated two major aspects of person description: 1) gender and 2) action recognition in still images. Most state-of-the-art approaches for gender and action recognition rely on the description of a single body part, such as face or full-body. However, relying on a single body part is suboptimal due to significant variations in scale, viewpoint, and pose in real-world images. This paper proposes a semantic pyramid approach for pose normalization. Our approach is fully automatic and based on combining information from full-body, upper-body, and face regions for gender and action recognition in still images. The proposed approach does not require any annotations for upper-body and face of a person. Instead, we rely on pretrained state-of-the-art upper-body and face detectors to automatically extract semantic information of a person. Given multiple bounding boxes from each body part detector, we then propose a simple method to select the best candidate bounding box, which is used for feature extraction. Finally, the extracted features from the full-body, upper-body, and face regions are combined into a single representation for classification. To validate the proposed approach for gender recognition, experiments are performed on three large data sets namely: 1) human attribute; 2) head-shoulder; and 3) proxemics. For action recognition, we perform experiments on four data sets most used for benchmarking action recognition in still images: 1) Sports; 2) Willow; 3) PASCAL VOC 2010; and 4) Stanford-40. Our experiments clearly demonstrate that the proposed approach, despite its simplicity, outperforms state-of-the-art methods for gender and action recognition.Funding Agencies|Swedish Foundation for Strategic Research through the Collaborative Unmanned Aircraft Systems Project; Swedish Research Council through the ETT Project; Strategic Area for Information and Communication Technology research ELLIIT; CADICS; Academy of Finland, through the Finnish Centre of Excellence in Computational Inference Research [251170]; Ministerio de Ciencia e Innovacion through the Ramon y Cajal Fellowship</p

Essaybundel RWS Imagine!: hoe kan die nieuwe wereld van big data, veranderde mobiliteit, transformatie van netwerken en duurzame leefomgeving er fysiek uitzien?

In juni 2014 heeft het Bestuur van Rijkswaterstaat aan het Programma Strategische Verkenningen gevraagd een designsessie te organiseren voor de Groepsraad van Rijkswaterstaat. De designsessie moet antwoord geven op de vraag: ‘hoe kan die nieuwe wereld van big data, veranderende mobiliteit, transformatie van de netwerken en een duurzame leefomgeving er fysiek uit zien? En hoe werken we samen in die nieuwe wereld?’ Ter voorbereiding van deze sessie is aan 10 personen, met verschillende expertises, gevraagd een essay te schrijven. Martijn de Waal (onderzoeker Citizen Empowerment aan de HvA) leverde een bijdrage