WP 2 “Automobile”

1. COST action 355 WATCH WP 2 “Automobile” The relationship between the specific (dis)utility and the frequency of driving a car Marco Diana Politecnico di Torino, ITALY FUNDP, Namur, 2nd December 2004

2. Transport planning models • Trip-based models: trips and traffic flows are at the core of the modelling effort (4 steps…) • Activity-based models: transport demand is derived from underlying activity patterns however… • A too rigid interpretation of the “activity-based paradigm” seems not appropriate: • (Individual) travel time budgets • “Irrational” travel behaviours and choices • Telework-commute trips complementarity • Research work by Mokhtarian et al. (2001)

3. Mohktarian (2001b) Mohktarian (2001a) Gaia (2003): Teleportation test Some results from previous researches

4. Research objective Primary utility = portion of the total utility not dependent on the fact of leaving a place to reach another place • Final goal: the assessment of the influence of the primary utility of travel (if any) on travel behaviour, against the influence of the derived utility • Milestones of our research: • Endogenous variable: car driving frequency • Data source: NTAUS (2002) • Considering mode-related primary utility

5. Methodological challenges • We face a serious measurement problem: primary and derived utility are often confounded by respondents • Idea: to focus on the presence of reported difficulties and limiting behaviours while driving • Assumption: the above affects the primary more than the derived utility of travel • Limitation: the method works only in presence of difficulties and limiting behaviours

6. Case study: the NTAUS dataset • In 2002, the National Transportation Availability and Use Survey (NTAUS) has been carried out in the U.S. • 5019 completed surveys (about half with persons with disabilities) • Not a classical mobility survey. Covered topics: • Trip frequencies per mode • Household vehicles ownership and use • Experiences, opinions and difficulties related to the use of different transport modes

7. Exploratory factorial analyses Literature search Statistical confir-mation Methodological steps • Define a suitable measurement model for the “primary utility” construct • Define causal interrelationships between: • Socioeconomic variables • Primary utility • Driving frequency Simultaneous estimation of the measurement and of the structural models through a structural equation modelling technique

8. EFA for the measurement model (1/2) Driving-related fitness: “The following is worse/same/better than 5 years ago:” • ……………………….…….. 0.504 • ……………………………………….. 0.655 • ……………………………………………….. 0.573 • …………………………………………. 0.755 • ………………… 0.750 • ……………………………………. 0.685 Driving-related fitness: “The following is worse/same/better than 5 years ago:” • Eyesight or night vision • Attention span • Hearing • Coordination • Reaction time to brake or swerve • Depth perception

9. EFA for the measurement model (2/2) Driving self-limitations: “Do you usually…” • ……………………………….……. 0.533 • ……………………………………………. 0.673 • ………………………………..….….. 0.616 • ……………………….. 0.696 • …………………………… 0.650 • ……………………. 0.371 • ……………………………………………. 0.371 • ………………………………… 0.615 • …… 0.690 • ……………………. 0.679 Driving self-limitations: “Do you usually…” • Drive less than you used to • Avoid driving at night • Drive less in bad weather • Avoid high-speed roads and highways • Avoid busy roads and intersections • Drive slower than the posted speed limits • Avoid left-hand turns • Avoid driving during rush hour • Avoid driving on unfamiliar roads or to unfamiliar places • Avoid driving distances of over 100 miles

10. Rationale of the structural model • General model structure: research on the relationships between socioeconomic characteristics, attitudes, perceptions and choice • Socioeconomic variables influence primary utility and driving frequency; primary utility also influences driving frequency • No feedback loops are modeled at this stage (hierarchical and recursive model)

11. Gender Age Number of household vehicles Income: • Less than $15,000 • $15,000 – $50,000 • Over $50,000 Presence of modified vehicles Household kind: • Lives alone • Lives with spouse • Lives with kids • Lives with parents • Lives with others Driving-related fitness Physical impairments: • None • Mild • Moderate • Severe Driving self-limitations Needs help to travel Unavailable transport Structural model path diagram Driving frequency

12. Estimation results: direct effects

13. Total effects on driving frequency

14. Gender Age Number of household vehicles Income: • Less than $15,000 • $15,000 – $50,000 • Over $50,000 Presence of modified vehicles Household kind: • Lives alone • Lives with spouse • Lives with kids • Lives with parents • Lives with others Overfitting model Physical impairments: • None • Mild • Moderate • Severe Needs help to travel Unavailable transport Not considering the primary utility Driving frequency

15. Conclusions and future work • The importance of the primary utility of travel seems confirmed within the selected framework • Case study: to combine specific information on primary utility with a classical mobility survey dataset • Measurement model: to define constructs for people that do not report difficulties or limiting behaviors • Structural model: to have a better representation of cognitive processes (feedback from driving frequency)

16. Thank you The relationship between the specific (dis)utility and the frequency of driving a car Research carried out in collaboration with INRETS – DEST To be presented at: 84th TRB Annual Meeting Washington, D.C., 9-13 January 2005 Marco Diana marco.diana@polito.it