A multimodal transport network model for advanced traveler information systems

Past research has established that human factors guidelines following traditional formats for presenting information are not useful and are often ignored by designers. Within the human factors community, there is considerable uncertainty and concern regarding the nature and utility of human factors handbooks and guidelines materials. Indeed, many existing human factors reference materials have been criticized by designers for being “too wordy”, “too general,” and “too hard to understand.” The development of clear, relevant, and useful human factors guidelines requires a judicious mix of science and art to overcome such criticisms. This paper describes an on going effort to develop clear, relevant, and easy-to-use guidelines for the design of Advanced Traveler Information Systems (ATIS) and Commercial Vehicle Operations (CVO). It focuses on the methods and results of a user requirements analysis conducted to identify the appropriate content, organization, and format of the ATIS/CVO guidelines.

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Congestion Detection in Large-Scale Advanced Traveler Information Systems

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)51558-x ◽

1995 ◽

Vol 28 (10) ◽

pp. 441-446

Author(s):

Andrzej P. Tarko ◽

Nagui M. Rouphail

Keyword(s):

Information Systems ◽

Large Scale ◽

Advanced Traveler Information Systems ◽

Traveler Information ◽

Traveler Information Systems ◽

Congestion Detection

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Modeling Revealed and Stated Pretrip Travel Response to Advanced Traveler Information Systems

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198196153700107 ◽

1996 ◽

Vol 1537 (1) ◽

pp. 46-54 ◽

Cited By ~ 15

Author(s):

Asad Khattak ◽

Amalia Polydoropoulou ◽

Moshe Ben-Akiva

Keyword(s):

Information Systems ◽

Stated Preference ◽

Mode Selection ◽

Management Strategies ◽

Strong Relationship ◽

Stated Preferences ◽

Advanced Traveler Information Systems ◽

Traveler Information ◽

Traveler Information Systems ◽

Travel Decisions

Advanced traveler information systems (ATISs) offer benefits to travelers and may improve transportation system performance in congested areas. An understanding of how information affects travelers' decisions can help in evaluating benefits and designing demand management strategies. The objective of the present study was to explore how people deal with unexpected congestion during the pretrip stage and how they might respond to ATISs. Travelers' routes, departure times, and mode selection decisions were investigated through a survey of Bay Area automobile commuters. The effects of various factors such as sources of congestion information (radio traffic reports versus observation), trip characteristics, and route attributes on travelers' responses to unexpected congestion were examined. The pretrip response to future ATIS technologies was explored through stated preferences (hypothetical scenarios). A combined reported preference and stated preference model of traveler response was developed by using the multinomial logit formulation. The estimations indicate that travel time and information are important determinants of changes in travel decisions in response to unexpected delays. The model indicates a strong relationship between reported and stated preferences. The results indicate that ATISs overcome behavioral inertia and that individuals are more likely to change their travel patterns in response to prescriptive information. More specific findings and their implications for ATIS design are also discussed.

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