Name
Abstract | ||
|---|---|---|
The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is desirable to have a means of simulating commuting in order to allow organisations to predict the effects of changes to working patterns and locations and inform decision making. In this paper we outline an agent-based software framework that combines real-world data from multiple sources to simulate the actions of commuters. We demonstrate the framework using data supplied by an employer based in the City of Edinburgh UK. We demonstrate that the BDI-inspired decision making framework used is capable of forecasting the transportation modes to be used. Finally we present a case study, demonstrating the use of the framework to predict the impact of moving staff within the organisation to a new work site. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.18564/jasss.4007 | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION |
Keywords | Field | DocType |
Transport Mode Choice,Transport Network,BDI Agent | Computer science,Operations research,Multi-agent system,Software framework,Transport network,Management science | Journal |
Volume | Issue | ISSN |
22 | 2 | 1460-7425 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| neil b urquhart | 1 | 83 | 14.70 |
| Simon T. Powers | 2 | 73 | 13.02 |
| Zoe Wall | 3 | 0 | 0.34 |
| Achille Fonzone | 4 | 5 | 1.47 |
| Jiaqi Ge | 5 | 5 | 3.79 |
| J. Gary Polhill | 6 | 93 | 13.08 |