Agent-based Transportation Demand Management - Demand Effects of Reserved Parking Space and Priority Lanes in Comparison and Combination

Markus C. Beutel, Sebastian Addicks, Barbara S. Zaunbrecher, Simon Himmel, Karl-Heinz Krempels, Martina Ziefle

2015

Abstract

Fostering the usage of alternative mobility modes, e.g., carsharing or carpooling becomes more and more urgent in modern urban planning. Politicians and city planners have already recognized that putting targeted incentives can influence people’s mobility behavior in an effective way. Agent-based simulations of transportation demand can be a valuable tool to support these planning processes. This work is based on a state-of-the-art transportation demand simulation and shows modeling and simulation modifications related with agents under the influence of incentives. These agents have been assessed in qualitative and quantitative studies prior to the simulation. Results show that agent-based simulation of transportation demand is suitable to evaluate impacts of transportation demand management measures. More specifically, all investigated measures show certain impacts on mobility mode choice, at which an incentive combination is most effective.

References

  1. Axelrod, R. (2006). Agent-Based Modeling as a Bridge between Disciplines. In Tesfastian, L. and Judd, K. L., editors, Handbook of Computational Economics, pages 1565-1638. Elsevier, Amsterdam.
  2. Ben-Akiva, M. and Atherton, T. J. (1977). Methodology for short-range travel demand predictions: analysis of carpooling incentives. Journal of Transport Economics and Policy, pages 224-261.
  3. Dubernet, T. and Axhausen, K. W. (2012). Including joint trips in a multi-agent transport simulation. 12th Swiss Transport Research Conference.
  4. Ferguson, E. (1990). Transportation Demand Management. Planning, Development and Implementation. Journal of American Planning Association, 56(4):442-456.
  5. Freudenstein, J. (2003). Agentenbasierte Simulation individueller Tagesabläufe (Agent Based Simulation of Individual Daily Routines). Master's thesis, RWTH Aachen.
  6. Hensher, D. A. and Pucket, S. M. (2007). Congestion and variable user charging as an effective travel demand management instrument. Transportation Research Part A: Policy and Practice, 41(7):615-626.
  7. Horni, A., Axhausen, K. W., and Nagel, K. (2011). HighResolution Destination Choice in Agent-Based Demand Models High-Resolution Destination Choice in Agent-Based Demand Models. Technical report, Eidgenössische Technische Hochschule Zürich, IVT, Institut für Verkehrsplanung und Transportsysteme.
  8. Ison, S. and Rye, T. (2008). TDM Measures and their Implementation. In Ison, S. and Rye, T., editors, The Implementation and Effectiveness of Transport Demand Management Measures, pages 1-12. Ashgate Publishing Limited, Hampshire, England.
  9. Jacobs, H. E., Fairbanks, D., Poche, C. E., and Bailey, J. S. (1982). Multiple Incentives in Encouraging Car Pool Formation on a University Campus. Journal of Applied Behavior Analysis, 15(1):141-149.
  10. Kickhöfer, B. (2009). Die Methodik der ökonomischen Bewertung von Verkehrsmanahmen in Multiagentensimulationen (Methods of Economic Evaluation for Traffic Measures in Multi Agent Simulations). Master's thesis, TU Berlin.
  11. Macal, C. and North, M. (2013). Introductory tutorial: Agent-based modeling and simulation. In Winter Simulation Conference (WSC), pages 362-376.
  12. Macal, C. and North, M. J. (2009). Agent-based modeling and simulation. In Winter Simulation Conference (WSC), pages 86-98.
  13. Magg, C. (2012). Agentenbasierte Verkehrsnachfragemodellierung für die Region Stuttgart (Agent Based Modelling of Traffic Demand for the Region of Stuttgart). Master's thesis, Uni Stuttgart.
  14. Rennekamp, R. A. and Nall, M. A. (2006). Using Focus Groups in Program Development and Evaluation. Technical report, University of Kentucky.
  15. Rodriguez, J. and Murtha, C.-a. T. (2009). Travel Demand Management.
  16. Schlag, B. and Schade, J. (2004). Public acceptability of travel demand management. In Huguenin, D. and Rothengatter, T., editors, Traffic and Transport Psychology. Theory and Application, volume 41, pages 493-500. Elsevier Science Publ., Oxford.
  17. Seik, F. T. (2000). An advanced demand management instrument in urban transport Electronic road pricing in Singapore. Cities, 17(1):33-45.
  18. Smith, R. a. (2008). Enabling technologies for demand management: Transport. Energy Policy, 36(12):4444- 4448.
  19. Sonnenberger, M. and Ruddat, M. (2013). Was tun? Strategien zur Förderung des kollektiven Individualverkehrs. (What to do? Strategies to Foster Collective Individual Transport.). In Sonnenberger, M., Gallego Carrera, D., and Ruddat, M., editors, Teilen satt Besitzen, pages 165-191. Europäischer Hochschuldverlag, Bremen, Germany, 1 edition.
  20. Teal, R. F. (1987). Carpooling: Who, how and why. Transportation Research Part A: General, 21(3):203-214.
  21. Tesfatsion, L. (2006). Agent-Based Computational Economics: A Constructive Approach to Economic Theory. In Tesfatsion, L. and Judd, K. L., editors, Handbook of Computational Economics, chapter 16, pages 831-878. Elsevier, Amsterdam.
  22. Zutshi, A., Grilo, A., and Jardim-Concalves (2013). DYNAMOD: A Modelling Framework for Digital Businesses based on Agent Based Modeling. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pages 1372-1376.
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Paper Citation


in Harvard Style

Beutel M., Addicks S., Zaunbrecher B., Himmel S., Krempels K. and Ziefle M. (2015). Agent-based Transportation Demand Management - Demand Effects of Reserved Parking Space and Priority Lanes in Comparison and Combination . In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-105-2, pages 317-323. DOI: 10.5220/0005411503170323


in Bibtex Style

@conference{smartgreens15,
author={Markus C. Beutel and Sebastian Addicks and Barbara S. Zaunbrecher and Simon Himmel and Karl-Heinz Krempels and Martina Ziefle},
title={Agent-based Transportation Demand Management - Demand Effects of Reserved Parking Space and Priority Lanes in Comparison and Combination},
booktitle={Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2015},
pages={317-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005411503170323},
isbn={978-989-758-105-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Agent-based Transportation Demand Management - Demand Effects of Reserved Parking Space and Priority Lanes in Comparison and Combination
SN - 978-989-758-105-2
AU - Beutel M.
AU - Addicks S.
AU - Zaunbrecher B.
AU - Himmel S.
AU - Krempels K.
AU - Ziefle M.
PY - 2015
SP - 317
EP - 323
DO - 10.5220/0005411503170323