Access and Response to Advanced Traveler Information Systems

1. Access and Response to Advanced Traveler Information Systems Asad J. Khattak & Felipe Targa Department of City and Regional Planning University of North Carolina-Chapel Hill

2. Background: Choices Demand Supply Consequence: Changes Risk:Uncertainty Gather information Trip Frequency Network: Surveillance, processing & dissemination Perfect information assumption Trip Destinations Mode Choice Perfect information assumption Route & time Choice

3. Decision Processes Separate out decisions related to: • Purchasing products • In-vehicle systems, PDAs, computers • Purchasing services • Cellphone & Internet • Product & services use—car, tel & Internet use • Travel knowledge acquisition • Static: Travel network, modes, routes • Dynamic: Network state, travel times • Travel choices & changes • Trips, destinations, modes, times, routes

4. Decision-making Decisions influenced by: Context, perceptions, attitudes, preferences, socio-economics, learning & info Complex vs. simple decisions: • Car buying, purchasing services, route choice • One-to-one more possible—info customization • Limitations: Access, acquisition & processing info Attributes of alternatives differ: • Transit cost is perceived differently from auto • Medium, content & quality of info • Time savings, anxiety reduction, “intrinsic value” • Product “personality” or extensions of self

5. Objectives Understand decision-making processes: • Information device access/ownership • Acquisition/use of dynamic travel info • Behavioral change in travel routine Examine fresh empirical evidence • Survey of travelers

6. Structural Equations Model

7. Methodology Behavioral survey • San Francisco Bay Area, 1999, N=1000 • Random digit dialing—fairly representative Statistical analysis: • Device access/ownership: Poisson • Dynamic info acquisition/use: Ordered logit • Behavioral change/adjustment: Binary logit Structural equations: 3 endogenous & 15 exogenous variables Two model specifications using structural equations: • Recursive—no reciprocal causal effects • Non-recursive—reciprocal causal effects

8. Structural Equations Model Recursive Non Recursive

9. Results: Bay-Area Survey • Info device access/ownership—# of devices: • 4 devices owned/accessed, on average—100% coverage • Increased with higher income and certain professions • Freq of info device use for acquiring travel info: • Acquisition limited—66% • Increased with higher access/ownership, longer tenure in study area, highway/freeway use, more exposure to unexpected congestion & longer travel times • Readjust routine travel: • Changing behavior based on info = 33% • Increased with more frequent use of dynamic travel information

10. Conclusions • Planning for ATIS involves consideration of new travel-related decisions • Info device access/ownership and acquisition • Changes in habitual patterns • New info sources not used to their full capacity • Dynamic info Readjustment • More research on: • How people access, use & respond to dynamic travel information • Causal relationships among travel and information decision-making processes

11. Thank You Asad J. Khattak, Felipe Targa Department of City and Regional Planning University of North Carolina-Chapel Hill