Disaggregating Traffic Demand Data for Agent-Based Traffic Simulations
| Thesis type |
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| Status | Running |
| Proposal on | 24. Mar 2020 00:00 |
| Proposal room | Seminarraum I5 |
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Traditional Traffic Demand Analysis as implemented in most commercial tools operate given variations of the so called four-step model. During this four-stepped modelling process origin-destination matrices are generated as output. With a rising amount of computation power, so called agent-based simulation tools are emerging. Here the traffic demand is not generated using a statistical model, but the decisions of each agent is evaluated in a simulation framework. In agent-based simulation frameworks more information is necessary, for example, complete activity chains for each agent. In this thesis a novel method for generating activity chains from origin-desination matrices is explored and compared with traditional demand forecasting methods.
Best Paper Award at ICWL‘20 