Experienced travel time prediction for congested freeways
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For several decades - and still today - mobility policies in industrialised countries have sought to reduce travel time to meet the expectations of infrastructure users for speed. However, despite major investments to achieve this objective of improving ac ...
Ensuring good access is a key element of land-use planning, allowing people to move around and access different services. This project focuses on the perception of access, as people base their transport mode choice on it. The context of lockdown due to COV ...
Management of road traffic in urban settings remains a challenging problem. Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume noise-free measurements of the traffic state, which is problematic since mea ...
As traffic congestion becomes a huge problem for most developing and developed countries across the world, intelligent transportation systems (ITS) are becoming a hot topic that is attracting attention of researchers and the general public alike. In this p ...
Moving walkways are pedestrian dedicated hardware which generally decrease pedestrian travel time. We propose the utilization of these devices to dynamically control pedestrian flows in order to improve pedestrian dynamics. Three variations of a control st ...
Urbanization intensifies as a global trend, exposing transportation networks to ever increasing levels of congestion. As network usage increases with available infrastructure, building new roads is not a solution. Design of intelligent transportation syste ...
Complex network theory describes network performance mostly based on topological characteristics, like betweenness centrality. This work integrates concepts from complex networks and traffic engineering. We propose a new measure for spatial networks and, i ...
Accurate traffic density estimations is essential for numerous purposes like the developing successful transit policies or to forecast future traffic conditions for navigation. Current developments in the machine learning and computer systems bring the tra ...
Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction a challenging task. Here we propose to use dynamic linear models (DLMs) to a ...
This paper proposes an integrated methodological framework to design a spatially heterogeneous bus route network and time-dependent service headways to serve travel demand that varies over time and space. Travelers choose to use either the transit mode or ...
