TRB 2016 Blue Ribbon Committee
16th National Transportation Planning Applications Conference

Quantifying the Potential Mobility Impacts of AV/CV Technology on Older Drivers

Corresponding Author: Kevin Hall, Texas A&M Transportation Institute

Presented By: Byron Chigoy, Texas A&M Transportation Institute


One of the potentially transformative outcomes of realizing a completely autonomous and connected vehicle environment is the mobility implications for older and non-driver age populations. With respect to pre-drivers—those teens or children that are younger than age 15—a number of legal questions may arise that prevent higher participation, especially in vehicle trips that lack adult supervision. For aging older drivers, access to mobility either through on-demand services or a self-driving car might encourage greater trip making. Consequently, fully autonomous vehicles, at least initially, may have a greater impact on the older population versus the pre-driving age population.

In the State of Texas, drivers that are 70 and older represent 8.83 percent of the total driving population using the latest figures from FHWA. In Austin, Texas, people aged 70 and older increases from 5.41 percent of the population in 2010 to more than 13 percent of the population in the year 2040, which is consistent with the general trends in the entire state, where 13.74 percent of the total population will exceed the age of 70 by 2040. Given that traditional trip-based approaches hold trip generation rates constant and by default ignore household life-cycle transformations, the impacts of current driving characteristics on future year conditions is not recognized in existing models, much less, changing mobility options.

The 2008 Austin-area household travel survey was reprocessed using the 2015 household age and gender stratifications and 2040 household age and gender stratifications from the Texas State Data Center (TSDC) to determine if the magnitude of overall change in travel could be measured using a different household stratification (with currently observed travel behavior). Researchers performed four separate analyses using the previous household travel survey data that were collected to support the 2010 travel demand models. This presentation will present the findings from this analysis, which could illuminate potential system-wide implications of aging population on system VMT. This is especially germane when discussing the potential implications of automated and connected vehicle technology. These findings are a part of a larger demand estimation research project on the potential impacts of AC/CV technology on travel demand.


Discuss This Abstract