Travel Demand Model of Automated Vehicles on a California Highway Network Predicts Nearly 74 Percent Annual CO2 Reductions Per Capita.

Microsimulation Model Reveals Health Benefits of Various Connected and Automated Vehicle Scenarios Applied to San Francisco Bay Area.

Date Posted
03/21/2022
Identifier
2022-B01637
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Active Transportation and Community Health Impacts of Automated Vehicle Scenarios: An Integration of the San Francisco Bay Area Activity Based Travel Demand Model and the Integrated Transport and Health Impacts Model (ITHIM)

Summary Information

Connected and Automated Vehicles (CAVs) are an important new development in the transportation system, and their impacts are not yet fully understood. There is a need to assess the health impacts of any transportation development, such as CAVs, and to develop long term transportation plans and policies conducive to a sustainable, and equitable system. This study investigated the potential human health impacts of CAVs concentrating on changes in travel demand, safety, and emissions with full penetration of CAVs in the San Francisco Bay Area.

METHODOLOGY

Integrated Transport and Health Impacts Model (ITHIM), developed in 2010, is an open‐source tool that incorporates the peer‐reviewed science with a web‐accessible engine capable of inputting calibration and scenario data to generate quantitative health impact estimates. The activity‐based ITHIM estimates potential impacts of CAVs on human health by considering changes in travel demand and levels of physical activity, with features that enable users to specify different calibration data sources such as survey or travel models.  ITHIM measures the burden of disease in the unit of Disability‐Adjusted Life Years (DALYs), which is a sum of Years of Life Lost due to premature death and Years of Living with Disability (YLD).

For the baseline scenario, the DALYs were obtained from the Global Burden of Disease database for the United States in 2010 and scaled to the Bay Area population. To estimate vehicular carbon emissions, ITHIM takes emission rates from California Emissions Rates database and multiplies by per capita car Vehicle Miles Traveled (VMT) and the scenario population. In this study, the years 2010 and 2040 were considered as the base and Automated Vehicle (AV) scenario years, respectively.

To simulate the effects of active transport (AT) policies (e.g. pedestrian and bicycle facility improvement), short Single Occupancy Vehicle (SOV) trips that could be made by walking (under 1.5 miles), and biking (between 1.5 and 5 miles) were identified, and 10 and 50 percent of those trips were replaced by active modes (non-motorized travel and public transit) and reassigned to the network in the travel model to update VMT and Vehicle Hours Traveled (VHT) parameters.

 

FINDINGS

  • The results showed that daily physical activity time for walking and bicycling decreased from the median of 8.2 and 0.4 minutes respectively in the baseline to 7.2 and 0.3 minutes in the AV scenario. On the other hand, daily travel time for the car driver and passenger individuals increased from 28.4 and 9.1 minutes to 32.2 and 9.5 minutes, respectively.
  • The results showed reductions in CO2 emissions brought by CAV technology; annual aggregate million metric tons (MMT) of CO2 emissions decreased by 76.4 percent when the AV scenario is compared to the baseline scenario (decrease from 16.1 to 3.8 MMT per year). Similarly, annual per capita million metric tons of CO2 emissions decreased by 74 percent when the AV scenario is compared to the baseline scenario (decrease from 2.3 to 0.6 MMT per year).
  • Compared with the baseline scenario, the burden of diseases resulting from road traffic injuries decreased in the AV scenario, avoiding 270-320 premature deaths and gaining more than 12-14 thousand DALY per year, primarily due to the decrease in car-car and car-pedestrian crashes on local roads.
  • The “AV+10 percent AT” scenario estimated annual per capita MMT of CO2 emissions to reduce by 74 percent when compared to the baseline (decrease from 2.3 to 0.6 MMT per year). Similarly, the “AV+50 percent AT” scenario estimated annual per capita MMT of CO2 emissions to reduce by 70 percent when compared to the baseline (decrease from 2.3 to 0.7 MMT per year).
  • An increase in AT mode by a 50 percent rate saved DALYs and premature deaths, which compensated for the generated burden of diseases caused by AV presence. For example, increased physical activity in the “AV+50 percent AT” scenario could result in a change of premature deaths from 37 to -70 and a change of DALY from 773  to -2,064 . “AV+50 percent AT” scenario could also reduce disease burden from road traffic injuries.
  • However, there is only a slight decrease in PM2.5-caused burden of diseases because of walkers and bikers’ higher respiration rate, which can offset the benefits from eliminated car trips.

Active Transportation and Community Health Impacts of Automated Vehicle Scenarios: An Integration of the San Francisco Bay Area Activity Based Travel Demand Model and the Integrated Transport and Health Impacts Model (ITHIM)

Active Transportation and Community Health Impacts of Automated Vehicle Scenarios: An Integration of the San Francisco Bay Area Activity Based Travel Demand Model and the Integrated Transport and Health Impacts Model (ITHIM)
Source Publication Date
06/15/2020
Author
Jaller, Miguel; Elham Pourrahmani; Caroline Rodier; Neil Maizlish; and Michael Zhang
Publisher
Prepared by University of California, Davis for USDOT
Results Type