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From this pool of trips, realistic road usage data are obtained in an agent-based process.
"Results" section presents the obtained results, primarily focusing on the question whether realistic road usage data could be obtained.
The aim of the model presented here is to generate realistic road usage data and resulting congestion information using a network approach utilizing statistical data about mobility behavior.
The starting point of this study is the idea presented in [15], but goes beyond this by investigating traffic jam avoidance behavior and developing a technique to quantitatively evaluate the validity of the road usage data produced in a network-based traffic model.
Similar(56)
In this work we validate for the first time a methodology, which employs comprehensive mobile phone data to detect patterns of road usage and the origins of the drivers.
Data sources Total population operational registration and usage data for the London cycle hire scheme (collected April 2011-March 2012), surveys of cycle hire users (collected 2011), and London data on travel, physical activity, road traffic collisions, and particulate air pollution (PM2.5, (collected 2005-12).
Accurately depicting the correct road usage of a given system without relying on actual origin destination data is the basis of future investigations.
However, these data do not contain any specific origin or destination points, so, to calculate actual traffic data, we use a multi-agent approach, presented in "Calculating road usage" section.
The second is usage data.
Indeed, directly charging for road usage seems to be just what the doctor ordered.
This work studies the impact of the in- creasing penetration of routing apps on road usage.
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