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In California in 2022, according to CARB, passenger car VMT produced 27.6% of overall human-caused GHG emissions. USDOT BTS has California commuting to work in 2017 at about 17% of automobile travel, and single occupant travel is predominant in cars at 65% of commuting trips as of 2022. An important, feasible alternative mode for reducing transportation’s impact on climate change is HOV commuting in private vehicles, that is, carpooling and vanpooling. According to USDOT BTS, this mode already has a 2022 work travel market share in California of 9.8% (including drivers) notably exceeding the 2.7% share for public transit. Pooling is a point of attack on carbon. It is an available mode where there is no public transit service in operation. Ten SOV commuters to a suburban office park deciding to cooperatively travel pairwise in five cars would represent a 50% reduction in commuting VMT for them. The policy challenge is how to motivate cooperative commuting that generates HOV travel and reduces VMT. This proposal is about motivating more pooling. However, it’s also important to note that if ten regular bus passengers decided because of a new incentive scheme to switch to carpooling in five personal ICE automobiles, more carbon would be the result, and the revenue stream of the bus agency would take a hit as well. The project team will take this scenario seriously.
There is growing interest in using financial incentives (generally, cash payments but sometimes gift payments), to reward a shift from single occupant (SOV) driving to passenger travel, by carpool, vanpool, or transit. A 2018 project, Congestion-Clearing Payments for Passengers, (CCPTP) tested for the first time the idea of using incentives at a congestion-clearing level. The CCPTP project established a methodology for defining and evaluating a “build nothing – pay passengers” option as a potential alternative to highway expansion.
In the CCPTP project report, a reward curve was estimated showing the amount of reward needed per day per passenger to encourage a given proportion of commuters to shift to passenger travel on the case study route. The basis for the reward curve estimation was a survey of residents of Half Moon Bay and nearby communities that make up the catchment of travelers that might use Highway 92 to travel to work or play in Silicon Valley. This was the first time such a reward curve had been estimated in this way. The survey showed significant potential for financial incentives to reduce congestion. The estimated benefit-to-cost ratio was 4.5, and estimated value creation of half a billion dollars over a 20-year period.
The CCPTP researchers cautioned that the reward curve might not be generalizable to other catchments or congested routes, work should be done to improve the quality of the estimation, and survey results (stated preference) should be calibrated to actual results (revealed preference). The CCPTP survey was completed prior to the COVID-19 pandemic, and the impact of the pandemic on the estimated reward curve should also be investigated. However, the team will make an assessment of this impact based on published research in the 2020s.
The reward curve has subsequently been used to support proposals for the use of incentives to reduce traffic. The Minett, Niles, et al. CCPTP project reached worldwide visibility in a peer-reviewed article that has been cited subsequently by several researchers. Since 2020, Patrick DeCorla Souza, outside of his professional duties in the U.S. DOT Federal Highway Administration, has been designing an innovative plan to incorporate carpooling incentives into new configurations of managed lanes on urban expressways, as documented in several publications. Minett, Niles, et al. (2020) has also been cited by researchers in China exploring the effectiveness of different types of non-cash gift incentives, by Greek researchers seeking linkages of carpooling to “smart city” projects, and by Florida researchers exploring randomized controlled trial methodologies for validating a particular MaaS smartphone app.
The CCPTP reward curve has been used in an evaluation of a concept referred to as HOTTER (High Occupancy, Transit, or Toll in Existing lanes for Rewards) lanes, in which a subset of existing lanes on a major highway would be converted to High Occupancy or Toll (HOT) lanes, and the toll revenues would be used to pay incentives to those who shifted to passenger travel.
The HOTTER lanes evaluation found that there would be a significant surplus of toll revenue after paying incentives and other operating costs and that HOTTER lanes would improve person throughput while reducing vehicle throughput. HOTTER lanes have been discussed as a potential solution for application in California. This present proposal for improving the reward curves is supported by the previously mentioned HOTTER researcher, by Caltrans managers, and by transportation thought leader Michael Replogle.
USDOT Priorities:
The project supports two central USDOT priorities: Equity, and Climate and Sustainability. The project supports the equity goal by investigating a policy avenue that promotes an additional cost-effective way of commuting for disadvantaged commuters (besides public transit). Payments to passengers are likely to be more appealing to income-disadvantaged consumers. The project supports climate and sustainability priorities by investigating a promising policy avenue that promotes multi-passenger vehicle travel, which would lead to lower VMT and lower emissions of GHGs.
San Jose State University
$99,956 (federal)
The project will generate new data, combine new data with existing data in ways not previously done, and will employ existing data in ways not previously done to assess the impact of payments to passengers on shifting the mode from SOVs to multi-passenger vehicles. The new data will be generated by new surveys of commuters and potential commuters, the existing data consists of PUMS and ACS data that have not previously been used in this area of transportation research, and involves methods, such as multi-level, Poisson, and negative binomial regression, not previously used in this area of transportation research.
The research will produce datasets, methodologies represented by statistical computer code, and assessments and recommendations that will inform policy decisions about the levels of and impacts of payments to passengers as a means of reducing SOV commuting.
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SJSU Research Foundation 210 N. 4th Street, 4th Floor, San Jose, CA 95112 Phone: 408-924-7560 Email: mineta-institute@sjsu.edu