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This research was commissioned by the province of Groningen. The province of Groningen asked the question how the quality her bus stop data could be improved.The province of Groningen is ultimately responsible for public transport. The public transport bureau is set up in 2005 to arrange bus transportation. The management of the bus stops, however, is in the hands of the regional and local authorities. The province manages the bus stops along the provincial highways The municipalities are responsible for the other bus stops in the province. The staff who manage the bus stops are called road authorities. Also on this domain the County has to do with laws and policies. The province of Groningen states in its strategic Information plan that it will focus on the quality of its information in the coming years. The different activities within the bus stop management provide different, complex information flows. The complexity has to do with the province that distributes the tasks through several departments and works together with several external partners in the chain.Research, commissioned by the province of Groningen. The province of Groningen asked the question how the quality her bus stop data could be improved.
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ABSTRACT: Local homebuyers in the Groningen earthquake regionIr. Hieke T. van der KloetHanze University of Applied Sciences GroningenResearch Centre for Built Environment NoorderRuimteh.t.van.der.kloet@pl.hanze.nl0031-50-595-2015The earthquakes after the natural gas extraction in the Groningen region of the Netherlands have a significant impact on the housing market and sustainability of the communities in this region. Since the strongest earthquake around the community of Huizinge in August 2012, with an magnitude of 3.6 on the Richter scale, it became clear there is a relation between natural gas extraction and earthquakes due to soil subsidence. As a consequence houses in the region get damaged and after research it gets obvious housing prices decline and the region will become unattractive to potential buyers of houses, damaged or not. Therefore the Dutch Petroleum Company (NAM) since April 29th 2014 offers a compensation for the loss of the housing price before and after the earthquake of Huizinge to property owners who want to sell their home. They only get the compensation after a sales deal and only if they agree with the proposed compensation. Since the compensation for the decrease in house prices has been introduced, the number of participants of the regulation is lacking behind the actual sales of houses. Our study aims to contribute to the research on the consequences of earthquakes by natural gas mining on the real estate market in the northern part of the Netherlands, especially the Groningen region. First of all we want to declare why relatively a large part of the property owners (about 60% until 2015) don’t request for the compensation regulation. Our second question concerns the buyers of the (damaged) houses in the earthquake area. Why would they buy a home in a region full of risks? Who are these buyers? We use a mixed-method approach for data collection which leads to an analysis of a unique dataset on notarial deeds of house sales in nine municipalities in the Groningen earthquake region according to The Land Registry of the Netherlands during the period 2013 until the end of 2015 as well as discovering common patterns of interview results with residents and experts. First results show that the majority of the homebuyers originate from the local earthquake area in the Province of Groningen. Reasons why property sellers after the house sale don’t opt for the compensation regulation concerns the complexity of the regulation, the used valuation model and the expected long control time afterwards.From the first results we conclude that the Groningen earthquake region still has its attractiveness for local residents and buyers. Otherwise the regulation for compensation doesn’t reach enough property sellers in the nine municipalities of the Groningen earthquake region. Advise to the Dutch government should be to generously compensate the residents of the Groningen earthquake regions for the loss of value of their dwellings, damaged or not. This will help to improve the regional development and attractiveness of areas that are effected by earthquakes.
Using technology to improve the adolescents' journey to school by bike in province of Drenthe and Groningen.All unsafe area that children spotted on the map, are because the lack of traffic safety ( lack of visibility, high speed, etc). In general children do not have a positive perception of cycling to school, and their favourite mode of traveling to school is car. What technology based intervention can make adolescents’ cycling to and from school safer and more attractive for them? Also does it help to encourage those who live far from the school (>10 km) to cycle to and from school more often?
Automated driving nowadays has become reality with the help of in-vehicle (ADAS) systems. More and more of such systems are being developed by OEMs and service providers. These (partly) automated systems are intended to enhance road and traffic safety (among other benefits) by addressing human limitations such as fatigue, low vigilance/distraction, reaction time, low behavioral adaptation, etc. In other words, (partly) automated driving should relieve the driver from his/her one or more preliminary driving tasks, making the ride enjoyable, safer and more relaxing. The present in-vehicle systems, on the contrary, requires continuous vigilance/alertness and behavioral adaptation from human drivers, and may also subject them to frequent in-and-out-of-the-loop situations and warnings. The tip of the iceberg is the robotic behavior of these in-vehicle systems, contrary to human driving behavior, viz. adaptive according to road, traffic, users, laws, weather, etc. Furthermore, no two human drivers are the same, and thus, do not possess the same driving styles and preferences. So how can one design of robotic behavior of an in-vehicle system be suitable for all human drivers? To emphasize the need for HUBRIS, this project proposes quantifying the behavioral difference between human driver and two in-vehicle systems through naturalistic driving in highway conditions, and subsequently, formulating preliminary design guidelines using the quantified behavioral difference matrix. Partners are V-tron, a service provider and potential developer of in-vehicle systems, Smits Opleidingen, a driving school keen on providing state-of-the-art education and training, Dutch Autonomous Mobility (DAM) B.V., a company active in operations, testing and assessment of self-driving vehicles in the Groningen province, Goudappel Coffeng, consultants in mobility and experts in traffic psychology, and Siemens Industry Software and Services B.V. (Siemens), developers of traffic simulation environments for testing in-vehicle systems.
Post-earthquake structural damage shows that wall collapse is one of the most common failure mechanisms in unreinforced masonry buildings. It is expected to be a critical issue also in Groningen, located in the northern part of the Netherlands, where human-induced seismicity has become an uprising problem in recent years. The majority of the existing buildings in that area are composed of unreinforced masonry; they were not designed to withstand earthquakes since the area has never been affected by tectonic earthquakes. They are characterised by vulnerable structural elements such as slender walls, large openings and cavity walls. Hence, the assessment of unreinforced masonry buildings in the Groningen province has become of high relevance. The abovementioned issue motivates engineering companies in the region to research seismic assessments of the existing structures. One of the biggest challenges is to be able to monitor structures during events in order to provide a quick post-earthquake assessment hence to obtain progressive damage on structures. The research published in the literature shows that crack detection can be a very powerful tool as an assessment technique. In order to ensure an adequate measurement, state-of-art technologies can be used for crack detection, such as special sensors or deep learning techniques for pixel-level crack segmentation on masonry surfaces. In this project, a new experiment will be run on an in-plane test setup to systematically propagate cracks to be able to detect cracks by new crack detection tools, namely digital crack sensor and vision-based crack detection. The validated product of the experiment will be tested on the monument of Fraeylemaborg.