Vehicle Technology Choice

Vehicle Technology Choice#

The vehicle technology choice model in POLARIS determines the level of automation technology assigned to each household vehicle. This model captures the adoption of Connected and Autonomous Vehicle (CAV) technology based on individuals’ willingness to pay, socio-demographic characteristics, and attitudinal factors. The model uses a random-parameters ordered probit formulation with two stages (Shabanpour et al., 2017):

  1. Partial automation adoption: An ordered probit model predicting willingness to adopt partial automation, with explanatory variables including:

    • Job type (administrative, has vehicle, long-distance trips),

    • Crash history and telecommuting behavior,

    • Fuel efficiency and stress reduction expectations,

    • Concerns about imperfect performance and high price,

    • Transit accessibility and log of VMT,

    • Attitudinal factors: advanced mobility interest, driving enjoyment, public transit affinity, environmental concern.

  2. Full automation adoption: A separate ordered probit model for full automation is estimated, with additional variables for education, household size, AV interest, and privacy concerns. Both models use threshold parameters with standard deviations to capture population heterogeneity. Population-level averages for attitudinal factors (e.g., advanced mobility interest, driving enjoyment) are provided as inputs to center the random parameter distributions.

Application in Simulation#

Vehicle technology is determined at the household level. Each vehicle in a household is assigned to a specific household member, and the model estimates that individual’s willingness to pay for both partial and full automation. Using user-specified cost parameters for partial and full automation, the final vehicle technology choice is then selected based on these estimated willingness-to-pay values.

References#

  • Shabanpour, R., Golshani, N., Auld, J., & Mohammadian, A. (2017, March). Willingness-to-pay for automated vehicles: A random parameters and random thresholds HOPIT model. In International Choice Modelling Conference 2017.