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Advances in Dynamic Network Modeling in Complex Transportation Systems pp 193–224Cite as

Information Impacts on Traveler Behavior and Network Performance: State of Knowledge and Future Directions

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Part of the book series: Complex Networks and Dynamic Systems ((CNDS,volume 2))

Abstract

Advanced Traveler Information Systems (ATIS) have the potential to maximize the operating efficiency of existing transportation infrastructure. Such systems rely on the generation and dissemination of guidance in order to allow drivers to make informed choices about travel mode, route and departure time, etc. The evaluation of the effectiveness of ATIS requires multidimensional study encompassing the analysis of various choice situations arising in the real world, constructing models that explain driver response to information in different contexts, and developing algorithms that can generate traveler information. Since driver confidence in the ATIS is directly related to the accuracy, relevance, and usefulness of the information, a key aspect is the collection of relevant field data that can instruct model development and ATIS evaluation before real-world deployment. This chapter aims to provide a synthesis of both the state of the art and the state of the practice of ATIS modeling and evaluation. We review the literature related to data collection and driver response model development, and classify the same according to the specific choice situations they address. We provide a conceptual discussion of the general framework within which traveler information may be generated, including key ATIS design parameters that may impact the performance of (and consequently, driver confidence in) the system. We also present brief empirical results from past simulation-based evaluations of ATIS, and conclude with recommendations for future research directions in order to further real-world ATIS deployment.

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Authors and Affiliations

  1. Caliper Corporation, Newton, Massachusetts, USA

    Ramachandran Balakrishna

  2. Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Moshe Ben-Akiva

  3. Steer Davies & Gleave Inc., Boston, Massachusetts, USA

    Jon Bottom

  4. University of Massachusetts at Amherst, Amherst, USA

    Song Gao

Authors
  1. Ramachandran Balakrishna
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  2. Moshe Ben-Akiva
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  3. Jon Bottom
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  4. Song Gao
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Correspondence to Ramachandran Balakrishna .

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Editors and Affiliations

  1. , School of Civil Engineering, Purdue University, Stadium Mall Drive 550, West Lafayette, 47907, USA

    Satish V. Ukkusuri

  2. , Department of Civil & Environmental Engi, Rutgers University, Browser Road 623, Piscataway, 08854, New Jersey, USA

    Kaan Ozbay

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Balakrishna, R., Ben-Akiva, M., Bottom, J., Gao, S. (2013). Information Impacts on Traveler Behavior and Network Performance: State of Knowledge and Future Directions. In: Ukkusuri, S., Ozbay, K. (eds) Advances in Dynamic Network Modeling in Complex Transportation Systems. Complex Networks and Dynamic Systems, vol 2. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6243-9_8

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