U.S. vehicle occupancy trends relevant to future automated vehicles and mobility services.

OBJECTIVE

Identifying current occupant travel patterns can inform decision making regarding the design, regulation, and occupant protection systems helpful for automated vehicle systems and mobility services.

METHODS

Two travel data sets were analyzed to quantify travel patterns: the 2017 National Household Travel Survey (NHTS), which provides data on household trips logged for a 24-h period, and the 2011-2015 National Automotive Sampling System-General Estimates System (NASS-GES), which contains data sampled from police-reported crashes. Analysis identified trends with driver age and gender, occupant age and gender, time of day, day of week, trip purpose, trip duration, vehicle type, as well as occupant role as solo driver, driver of others, single passenger, or multiple passengers.

RESULTS

In NHTS, the median trip duration is 15 min; only 10% of trips last longer than 40 min. Trip duration does not vary with occupant role or vehicle type. Variations with trip time of day and day of week show a unimodal pattern for weekends, as well as weekday trips for those aged 55 years and older and non-solo occupants aged 18 to 29 years. Other occupant groups have a bimodal weekday travel pattern with peak trips corresponding to morning and evening rush hours.In GES, approximately half of occupants are solo drivers. Female drivers aged 55 and older travel alone 60% of the time, and drivers under age 18 and female drivers aged 30 to 54 drive alone on less than 45% of trips. Approximately 13% of occupants are single passengers, and 16% travel with a driver and at least 1 other passenger. About 16% of occupants are front seat passengers.

CONCLUSIONS

This analysis of vehicle occupancy provides insights on what ridership of future automated vehicles and expanded ride-hailing services may look like. Because half of occupants are solo drivers, only 16% are multiple passengers, and median trip length is just 15 min, proposed alternative seating arrangements intended to promote comfort and passenger interaction may not represent the typical future vehicle use case in the United States. Knowledge of current occupancy patterns can help automated vehicle designers and regulators develop safe seating scenarios that meet customer needs.