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Improving Non Driver Mobility

DEFINITION OF “NON-DRIVER”

The HRTPO uses the term “Non-driver” to refer to a person who does not consider themselves to be a driver. The usage of this term comes from the National Household Travel Survey in which persons are simply asked “Are you a driver?”. It is assumed that non-drivers—for whatever reason: physical, financial, legal—do not have a driver’s license and therefore cannot currently drive. In HRTPO reports, non-drivers are at least 18 years of age and live in households.

OVERVIEW OF MULTI-YEAR STUDY

In order to improve the mobility of non-drivers, the HRTPO began a series of analyses in 2003. The first non-driver document Improving Elderly Transportation using the NHTS (June 2005) examined improvements to the mobility of elderly non-drivers using the National Household Travel Survey (NHTS). It revealed that:

  • elderly non-drivers travel half as much as elderly drivers, but
  • elderly non-drivers living in denser areas have higher mobility due to walking and bus usage.

The second document Improving the Mobility of Non-Drivers Age 18-64 Using the NHTS (November 2006) examined non-drivers age 18-64 again using the NHTS. It revealed that:

  • 18-64 non-drivers also make half as many trips as their driving counterparts,
  • the mobility of 18-64 non-drivers living in central areas is significantly higher than those living in other areas, and
  • walking and use of public transit give non-drivers in central areas this higher mobility.

It was concluded in these first two documents that living near destinations and having access to public transit causes the higher non-driver mobility observed in dense areas and central areas. But due to the structure of the NHTS survey, neither study was able to directly measure the mobility impact of living near transit and living within walking distance of destinations. Therefore, a local survey was designed, implemented, and analyzed to measure these factors. A third document Snapshot of Non-Drivers in Hampton Roads (June 2007) presented a statistical snapshot of local non-drivers based on data from the survey.

A fourth document Improving the Mobility of Non-Drivers Using Proximity to Destinations and Bus Routes (June 2007) presented a model—developed from the local survey—which indicated numerically the factors which determine non-driver mobility. That mobility model revealed that:

  • better-walking non-drivers living in the high activity locations in urban and suburban areas of Hampton Roads have odds of leaving home five (5) times higher than the odds of those living away from activities, and
  • better-walking non-drivers living near a bus stop have odds of leaving home two (2) times higher than the odds of those living away from bus stops.

The fourth document presented recommendations to local governments, developed from these findings, for improving the mobility of local non-drivers, including:

1) furthering the location of mobility-enhancing infrastructure near non-drivers:

  • locating bus routes near concentrations of residences
  • locating government facilities near concentrations of residences
  • using zoning authority to ensure that adequate numbers of activity locations (businesses, institutions, etc.) are allowed to be built near concentrations of residences

2) furthering the location of housing near mobility-enhancing activity areas:

  • using zoning authority to ensure that adequate numbers of residences are allowed to be built in High Business Activity Locations

A fifth document Improving the Mobility of Non-Drivers: Neighborhood Gaps Analysis (June 2007) applied the findings of the fourth document to three specific neighborhoods in Hampton Roads. In addition to recommendations concerning deficiencies in neighborhood pedestrian and bus networks, recommendations were made based on the neighborhoods’ proximity to activity locations. Additional residential units were recommended for areas proximate to activity locations; additional businesses were recommended for areas away from activity locations.

In the sixth document Non-Driver Opportunity Analysis (June 2009), the HRTPO developed a performance measure based on mobility odds—using the model from the fourth document—to measure the success of Hampton Roads localities’ co-positioning of activity locations, bus routes/stops, and residences favored by non-drivers. A method of locating non-drivers at the block level (but not by vehicle availability) was developed and applied. Using this detailed location data, specific successes and prospects in the proximity of these three were identified. In addition, this report visually examined the proximity of non-drivers and bike/ped facilities, pointing out successes and prospects in that arena as well. Local government can use the findings of this report to identify prospects for modifying land use and investing in bus, bicycle, and pedestrian infrastructure to improve non-driver mobility.

In 2011, the Transportation Research Board (TRB) published this HRTPO performance measure method as Performance Measures for Coordination of Transportation and Land Use to Improve Nondriver Accessibility in its peer-reviewed Transportation Research Record (No. 2242) enabling it to become a model for metro areas around the U.S.

In the seventh document Non-Driver Residential Locations at the Census Block Level by Vehicle Availability (November 2009), non-driver data not being available from the Census, the HRTPO developed location data for use in planning for emergency evacuation and improving daily non-driver mobility. Given that non-drivers in zero-vehicle households are vulnerable during evacuation events and have a greater need for the mobility improvement provided by a nearby bus stop and nearby activity locations, locating non-drivers by vehicle availability is valuable. The Virginia Department of Emergency Management (VDEM) can use this data to plan evacuation aid in its current Regional Catastrophic Preparedness project. Local government and transit agencies can use this data when deciding where to promote the development of activity locations and where to invest in transit, two factors which improve non-driver mobility as measured by previous HRTPO studies. Because the data includes a break-out of non-drivers in zero-vehicle households, particular emphasis can be placed on these persons. 

Non-Drivers Residential Locations 2000 at the Census Block Level (GIS data) (ZIP File, click HERE)

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