Agent-Based Dynamic Traffic Assignment with Information Mixing
This study develops an approach for network assignment convergence using individualized agent-based routing and agent-specific link cost information as well as historical travel times. Each traveler is routed individually from their starting and ending network link at a specific departure time. The approach is gap-based in two ways. First, as in previous approaches, the re-assignment decision during the convergence process is based on the gap between the routed and experienced travel time from the previous iteration. Secondly, the historical time-dependent and prevailing traffic conditions are averaged into a single expected value for each agent using a weight calculated by a modified two-parameter Weibull survival function. This weight is individualized based on the relative gap of the traveler from the previous iteration, as well as the iteration number; a novel aspect of this work. The methodology is tested on a medium-scale network of Bloomington, IL. The algorithm converges after only two iterations, which is promising as computational time of a single iteration can be high for large-scale networks.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Office of Vehicle Technologies (VTO)
- DOE Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1528926
- Resource Relation:
- Conference: 8th International Workshop on Agent-based Mobility, Traffic and Transportation Models, Methodologies and Applications, 04/29/19 - 05/02/19, Leuven, BE
- Country of Publication:
- United States
- Language:
- English
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