Destination and mode choice in an agent-based simulation of long-distance travel demand
Axhausen, Kay W.
- Other Conference Item
Rights / licenseIn Copyright - Non-Commercial Use Permitted
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 to the complex task of destination choice modelling, there are just few agent-based simulations available. This paper presents a continuous target-based simulation that simulates long-distance travel behavior for a long period of time. It is shown how destination choice and mode choice is modelled in this agent-based simulation. Destination and mode are chosen simultaneously along with activity type and activity duration. The presented approach uses a heuristic to reduce the choice set since the underlying multi-dimensional optimization problem is too hard to be solved directly with acceptable computational effort. Afterwards the best combination of destination, mode and activity is determined based on the agents’ projected discomfort Show more
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SubjectLong-distance travel demand; Destination choice; Agent-based simulation; C-Tap
Organisational unit03521 - Axhausen, Kay W.
02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
NotesConference lecture held 18 May 2017
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