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Perez Lazaro, Cristino (author)
Flooding events not only cause physical damage to the road infrastructure and roadside systems, yet they potentially lead to significant traffic disruptions over the network which have a large impact on the sustainability of urban cities. According to several climate change scenarios, flooding events as a result of intense precipitation are...
master thesis 2020
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Bhoraskar, Akshay (author)
This study aims at a possible solution to predict the fuel consumption of heavy duty diesel trucks, particularly, the tractor semitrailer for their long haul operations using various machine learning techniques. It intends to provide a possible alternative to simulation or physics based models, which often are very complicated. The stringent...
master thesis 2019
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Wu, Ting Wei (author)
Congestion in the landside air cargo supply chain occurs for different concurring reasons. Lack of coordination between freight forwarders, as example, might create truck congestion on the ground handler side. Horizontal collaboration between forwarders can be introduced and modeled via mathematical programming to mitigate congestion. Resulting...
master thesis 2019
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Echaniz Soldevila, Ignasi (author)
This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine...
master thesis 2017
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Sparnaaij, Martijn (author)
This research investigates the question how the choice of scenarios and metrics influences the calibration of pedestrian simulation models. By calibrating a pedestrian model using different combinations of scenarios and metrics and comparing the results it was concluded that it matters what scenarios and metrics are included during the...
master thesis 2017
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