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Experimental Studies for Traffic Incident Management with Pricing, Private Information, and Diverse Subject

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  • Brownstone, David
  • McBride, Michael
  • Kong, Si-Yuan
  • Mahmassani, Amine

Abstract

The effective management of traffic incidents and other irregular disruptions on roadways is key to minimizing travel delay and improving the quality of life for urban residents and businesses. We are currently using economic experiments involving human subjects and a networked, realistic driving simulation to study driver behavior in response to information displayed by variable message systems and to dynamic road pricing schemes. Based on our existing results, we propose four new extensions to our study: the addition of more realistic driving mechanics to test driver responses to our treatments under increased cognitive load, the recruitment of subjects outside the UCI student body to confirm the validity of our results with different demographic groups, the implementation of treatments to study the impact of private information messaging systems (e.g. Waze, Google Maps, etc.), and the implementation of treatments to study a novel value-of-time based auction system for toll lane pricing and allocation. Improvements to the driving realism and the representativeness of our experimental subject pool will strengthen the robustness and validity of our study’s results, while the investigation of private information messaging and value-of-time auction scenarios will shed light on their potential for improving transportation management.

Suggested Citation

  • Brownstone, David & McBride, Michael & Kong, Si-Yuan & Mahmassani, Amine, 2018. "Experimental Studies for Traffic Incident Management with Pricing, Private Information, and Diverse Subject," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8nj034g7, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt8nj034g7
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    1. Gonchar V., 2016. "Forecasting as a method of metals marketing research," Економічний вісник Донбасу Экономический вестник Донбасса, CyberLeninka;Институт экономики промышленности НАН Украины, issue 4 (46), pages 104-108.
    2. Jou, Rong-Chang & Lam, Soi-Hoi & Liu, Yu-Hsin & Chen, Ke-Hong, 2005. "Route switching behavior on freeways with the provision of different types of real-time traffic information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(5), pages 445-461, June.
    3. Ishuan Li & Robert Simonson, 2016. "Capstone senior research course in economics," The Journal of Economic Education, Taylor & Francis Journals, vol. 47(2), pages 161-167, April.
    4. Peter Ping Li & Tomoki Sekiguchi & Kevin Zhou, 2016. "The emerging research on indigenous management in Asia," Asia Pacific Journal of Management, Springer, vol. 33(3), pages 583-594, September.
    5. Stephan B Bruns & John P A Ioannidis, 2016. "p-Curve and p-Hacking in Observational Research," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-13, February.
    6. Small, Kenneth A. & Yan, Jia, 2001. "The Value of "Value Pricing" of Roads: Second-Best Pricing and Product Differentiation," Journal of Urban Economics, Elsevier, vol. 49(2), pages 310-336, March.
    7. Graham Kendall & Ruibin Bai & Jacek Błazewicz & Patrick De Causmaecker & Michel Gendreau & Robert John & Jiawei Li & Barry McCollum & Erwin Pesch & Rong Qu & Nasser Sabar & Greet Vanden Berghe , 2016. "Good Laboratory Practice for optimization research," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(4), pages 676-689, April.
    8. Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability," Econometrica, Econometric Society, vol. 73(4), pages 1367-1382, July.
    9. Wardman, Mark, 2004. "Public transport values of time," Transport Policy, Elsevier, vol. 11(4), pages 363-377, October.
    10. Richard H. M. Emmerink & Peter Nijkamp & Piet Rietveld & Jos N. Van Ommeren & Richard H. M. Emmerink & Peter Nijkamp & Piet Rietveld & Jos N. Van Ommeren, 2004. "Variable Message Signs and Radio Traffic Information: An Integrated Empirical Analysis of Drivers’ Route Choice Behaviour," Chapters, in: Location, Travel and Information Technology, chapter 16, pages 343-361, Edward Elgar Publishing.
    11. Edward C. F. Wilson & Miranda Mugford & Garry Barton & Lee Shepstone, 2016. "Efficient Research Design," Medical Decision Making, , vol. 36(3), pages 335-348, April.
    12. Valeria Lo Iacono & Paul Symonds & David H.K. Brown, 2016. "Skype as a Tool for Qualitative Research Interviews," Sociological Research Online, , vol. 21(2), pages 103-117, May.
    13. Liina Lepp & Marvi Remmik & Äli Leijen & Djuddah A. J. Leijen, 2016. "Doctoral Students’ Research Stall," SAGE Open, , vol. 6(3), pages 21582440166, July.
    14. Christoph Schmidt, 2016. "Research Methodology," Progress in IS, in: Agile Software Development Teams, chapter 0, pages 65-86, Springer.
    15. Hong Huo & David Levinson, 2003. "Effectiveness of Variable Message Signs Using Empirical Loop Detector Data," Working Papers 000033, University of Minnesota: Nexus Research Group.
    16. Iida, Yasunori & Akiyama, Takamasa & Uchida, Takashi, 1992. "Experimental analysis of dynamic route choice behavior," Transportation Research Part B: Methodological, Elsevier, vol. 26(1), pages 17-32, February.
    17. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    18. Agnieszka Żur & Maria Urbaniec, 2016. "Editorial: Advancing Research in Entrepreneurship," Entrepreneurial Business and Economics Review, Centre for Strategic and International Entrepreneurship at the Cracow University of Economics., vol. 4(3), pages 7-9.
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