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Destination and mode choice in an agent-based simulation of long-distance travel demand
(2017)Analysis of long-distance travel demand has become more relevant in recent times. The reason is the growing share of traffic induced by journeys related to remote activities, which are not part of daily life. In today’s mobile world, these journeys are responsible for almost 50 percent of the overall traffic. Consequently, there is a need of reliable long-distance travel forecasting tools. A potential tool is agent-based simulation. Due ...Other Conference Item -
Population synthesis for long-distance travel demand simulations using mobile phone data
(2017)Other Conference Item -
A direct demand modeling framework for traffic volume and speed prediction
(2017)Other Conference Item -
Context-dependent models comparisons
(2017)When facing alternatives, people are often assumed to choose the alternative which maximizes their utilities. This concept is widely known as random utility maximization (RUM). In transportation research, one of the most famous modeling techniques based on this idea, e.g. for modeling mode choice, is the multinomial logit (MNL) approach. Recently there is a growing interest in an alternative modeling approach, random regret minimization ...Other Conference Item -
Spatial modelling of traffic volumes and mean speed values
(2017)hEART 2017: List of AbstractsOther Conference Item -
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«Heute»: Herausforderungen - Welches sind die drängendsten Herausforderungen und wie lösen wir diese?
(2017)Other Conference Item -
More thinking about autonomous vehicles: Business models and demand growth
(2017)Other Conference Item -