Susan Handy et al.
A comparison of mitigation measures under these two metrics raises a fundamental question about what type of built environments communities want, and how they use the CEQA process to achieve them.
Does Davis want more traffic signals and turn lanes? Will replacing LOS with VMT in CEQA facilitate – or make it more challenging – for communities to finance and construct the built environment they desire?
General plans tell us the aspirations of the community, and the City of Davis has visions for its built environment that include (City of Davis, 2007):
- Foster a safe, sustainable, healthy, diverse, and stimulating environment for all in the community.
- Become a community where the impacts of traffic, noise, pollution, crime, and litter are minimized.
- Maintain Davis as a cohesive, compact, university-oriented city surrounded by and containing farmland, greenbelts, natural habitats, and natural resources.
- Reflect Davis’ small town character in urban design that contributes to and enhances livability and social interaction.
- Maintain a strong, vital, pedestrian-oriented and dynamic downtown area
- Encourage carefully-planned, sensitively-designed infill and new development to a scale in keeping with the existing city character.
- Encourage a clean, quiet, safe, and attractive transportation system that harmonizes with the city’s neighborhoods and enhances quality of life.
- Promote alternative transportation modes such as bicycling, walking, public transit, and telecommuting.
In the longer-term, researchers and planners should watch for changes in the types and locations of developments that are proposed. This shift in performance metric changes the incentives and disincentives to develop certain types of projects in certain areas. Where LOS analysis has favored projects and locations that can maintain “driver comfort and convenience” per the Highway Capacity Manual, VMT analysis incentivizes projects and locations that generate less driving.
We will presumably see dense urban areas with well-mixed land uses and high-quality transit – areas with inherently high vehicle delay but often low VMT – become more attractive to developers as they prompt fewer transportation impacts and requisite mitigations.
Analysis of impacts and thresholds is important for understanding the short- and long-run incentives for different types and location of development. As SB 743 is implemented across California, and the concept is perhaps adopted elsewhere, longitudinal research will show how the use of VMT as a performance metric influences long-term planning and development decisions, how it incentivizes certain types of development decisions, and ultimately the types of communities that are built.
In the shorter term, we show the short-term influence that each metric has on communities via impact mitigations. Our analysis of LOS mitigation shows how the CEQA process per se impacts the built environment, often in ways that increase vehicle capacity and thus VMT (see Figs. 2 & 3). Over time, the VMT induced by mitigating LOS with capacity increases will cause further vehicle delay and trigger more LOS impacts. Breaking the congestion-capacity-congestion cycle requires addressing the demand for travel, which is inextricably linked with the accessibility provided by land development patterns (Fig. 3).
We further show that under its current framework of SB 743, expensive capacity-increasing mitigation measures aimed at easing automobile congestion may be supplanted by streamlining for projects that reduce travel demand by locating near transit or in low-VMT areas. Projects sited in urban cores near transit will enjoy an expeditious transportation impact analysis, as well as fewer mitigations to finance. Finally, we show that the vehicle capacity constructed to mitigate LOS may contravene the goals and aspirations of many communities in California, as well as the state’s goals for GHG reductions. Further investigation of LOS mitigation across a larger sample of projects and jurisdictions would shed light on the extent of vehicle capacity that has been built in the name of CEQA.
References
California Air Pollution Control Officers Association (CAPCOA) (2013). California
Emissions Estimator Model (CalEEMod). http://www.caleemod.com.
California Air Resources Board (2017). Senate Bill 375 – research on impacts of transportation
and land use-related policies. arb.ca.gov/cc/sb375/policies/policies.htm.
California Code of Regulations Title 14 Natural Resources, Division 6 Resources Agency,
Chapter 3 Guidelines for Implementation of the California Environmental Quality Act
(§ 15000–§15387). https://govt.westlaw.com/calregs/Browse/Home/California/
CaliforniaCodeofRegulations?guid=I95DAAA70D48811DEBC02831C6D6C108E&
originationContext=documenttoc&transitionType=Default&contextData=(sc.
Default).
California Department of Transportation (Caltrans) Office of Multi-Modal Planning
(2014). California Statewide Travel Demand Model 2.0. dot.ca.gov/hq/tpp/offices/
omsp/VMT_Analysis_2015_11_19.xlsx.
California Public Resources Code Division 13: Environmental Quality (§ 21000 –
§21189.57). https://leginfo.legislature.ca.gov/faces/codes_displayexpandedbranch.
xhtml?tocCode=PRC&division=13.&title=&part=&chapter=&article.
Castiglione, J., Freedman, J., & Bradley, M. (2003). Systematic investigation of variability
due to random simulation error in an activity-based microsimulation forecasting
model. Transportation Research Record: Journal of the Transportation Research Board,
1831, 76–88.
Cervero, R. (2003). Road expansion, urban growth, and induce travel: A path analysis.
Journal of the American Planning Association, 69(2), 145–163.
Cervero, R. (2006). Alternative approaches to modeling the travel-demand impacts of
smart growth. Journal of the American Planning Association, 72(3), 285–295.
Cervero, R., & Arrington, G. B. (2008). Vehicle trip reduction impacts of transit-oriented
housing. Journal of Public Transportation, 11(3).
City of Davis (2006). Draft environmental impact report – Second street crossing (target
store) project. community-development.cityofdavis.org/Media/Default/Documents/
PDF/CDD/Planning/Special-Projects/Target-Store/Environmental-Review/
Environmental-Impact-Report/04d-Transportation-and-Circulation.pdf.
City of Davis (2007). City of Davis general plan – Amended 2007. cityofdavis.org/cityhall/
community-development-and-sustainability/planning-and-zoning/general-plan.
City of Davis (2013). Draft environmental impact report – Cannery Park. cityofdavis.org/
city-hall/community-development-and-sustainability/development-projects/thecannery/
environmental-review.
City of Davis (2015). Nishi gateway project – Draft environmental impact report. http://
cityofdavis.org/city-hall/community-development-and-sustainability/developmentprojects/
nishi-and-downtown-university-gateway-district/environmental-review.
City of Oakland Planning Commission (2016). Modification of CEQA thresholds of significance
guidelines. Staff report for September 21, 2016 hearingwww2.oaklandnet.
com/government/o/PBN/OurOrganization/PlanningZoning/o/Commissions/
OAK062917.
City of Orange v. Valenti (1974). 37 Cal. App. 3rd 240.
City of Pasadena Department of Transportation (2015). Transportation impact analysis
current practice & guidelines. ww5.cityofpasadena.net/transportation/wp-content/
uploads/sites/6/2015/12/Current-Practice-and-Guidelines.pdf.
Clifton, K., Currans, K., & Muhs, C. (2013). Evolving ITE trip generation handbook:
Proposal for collecting multimodal, multicontext, establishment-level data.
Transportation Research Record: Journal of the Transportation Research Board, 2344,
107–117.
Clifton, K. K., Currans, K. M., & Muhs, C. (2015). Adjusting ITE’s trip generation handbook
for urban context. Journal of Transport and Land Use, 8(1), 5–29.
Currans, K. M., & Clifton, K. (2015). Using household travel surveys to adjust ITE trip
generation rates. Journal of Transport and Land Use, 8(1), 85–119.
Downs, A. (1962). The law of peak-hour expressway congestion. Traffic Quarterly, 16(3).
Downs, A. (1992). Stuck in traffic. Washington, DC: The Brookings Institution.
Downs, A. (2004). Why traffic congestion is here to stay … and will get worse. Access
Magazine, 25, 19–25.
Duranton, G., & Turner, M. (2011). The fundamental law of road congestion: Evidence
from US cities. American Economic Review, 101, 2616–2652.
Ewing, R., & Cervero, R. (2010). Travel and the built environment. Journal of the American
Planning Association, 76(3), 265–294.
Fang, K., & Volker, J. (2017). Cutting greenhouse gas emissions is only the beginning: A literature
review of the co-benefits of reducing vehicle miles traveled. National Center for
Sustainable Transportationncst.ucdavis.edu/wp-content/uploads/2017/03/NCSTWhite-
Paper-VMT-CoBenefits-White-Paper-LP_EB.pdf.
Federal Highway Administration (1987). Technical advisory 6640.8A: Guidance for
preparing and processing environmental and section 4(f) documents. environment.
fhwa.dot.gov/projdev/impTA6640.asp#back.
A.E. Lee, S.L. Handy Research in Transportation Business & Management xxx (xxxx) xxx–xxx
11
Fulton, W., & Shigley, P. (2012). Guide to California planning (4th Edition). Point Arena:
Solano Press Books179.
Governor’s Office of Planning and Research (2016). Revised proposal on updates to the
CEQA guidelines on evaluating transportation impacts in CEQA: Implementing senate
bill 743 (Steinberg, 2013). opr.ca.gov/docs/Revised_VMT_CEQA_Guidelines_
Proposal_January_20_2016.pdf.
Handy, S. (2005). Smart growth and the transportation-land use connection: What does
the research tell us? International Regional Science Review, 28(2), 146–167.
Handy, S., & Clifton, K. (2001). Local shopping as a strategy for reducing automobile
travel. Transportation, 28(4), 317–346.
Handy, S., Shafizadeh, K., & Schneider, R. (2013). Final report: California smart-growth
trip estimation study. University of California. Davis for the California Department of
Transportationdownloads.ice.ucdavis.edu/ultrans/smartgrowthtripgen/Final_
Report.pdf.
Highway Research Board of the Division of Engineering and Industrial Research (1965).
Highway capacity manual 1965. Washington, DC: National Academy of Sciences –
National Research Council.
Institution of Transportation Engineers (ITE) (2012). Trip generation handbook (9th
Edition). Institute of Transportation Engineers.
ITE (2004, June). Trip Generation Handbook (2nd ed.). 15.
Lee, A., Fang, K., & Handy, S. (2017). Evaluation of sketch-level vehicle miles traveled
quantification tools. National Center for Sustainable Transportationncst.ucdavis.edu/
wp-content/uploads/2017/06/NCST-SGC_Handy-VMT-Quant_Final-Report-
AUGUST-2017.pdf.
Lovejoy, K., Sciara, G. C., Salon, D., Handy, S., & Mokhtarian, P. (2013). Measuring the
impacts of local land-use policies on vehicles miles of travel: The case of the first bigbox
store in Davis, California. The Journal of Transport and Land Use, 6(1), 25–39.
Newmark, G., Haas, P., Pappas, J., Schwartz, M., Kenyon, A., & Unit, M. O. (2015).
Income, location efficiency, and VMT: Affordable housing as a climate strategy.
Center for neighborhood technology working paper, produced for the california housing
partnership.
Newmark, G. L., & Haas, P. M. (2016). Does the vehicle-miles traveled associated with
location efficiency vary by income group? Transportation Research Board 95th Annual
Meeting (No. 16-4242).
Roess, R. P. (1984). Level of service concepts: Development, philosophies, and implications.
Transportation Research Record: Journal of the Transportation Research Board,
971, 1–6.
Rothman, L. D. (2011). CEQA turns forty: The more things change, the more they remain
the same. Environmental Law News, 20(1) (Winter 2011).
San Francisco Planning Department (2016). Executive summary: Resolution modifying
transportation impact analysis. commissions.sfplanning.org/cpcpackets/Align-
CPC%20exec%20summary_20160303_Final.pdf.
Schneider, R. J., Shafizadeh, K., & Handy, S. L. (2015). Method to adjust Institute of
Transportation Engineers vehicle trip-generation estimates in smart-growth areas.
Journal of Transport and Land Use, 8(1), 69–83.
Senate bill no. 743. California State Senatehttps://leginfo.legislature.ca.gov/faces/
billNavClient.xhtml?bill_id=201320140SB743.
Shafizadeh, K., Lee, R., Niemeier, D., Parker, T., & Handy, S. (2012). Evaluation of operation
and accuracy of available smart growth trip generation methodologies for use
in California. Transportation Research Record: Journal of the Transportation Research
Board, 2307, 120–131.
Virginia Department of Transportation (VDOT) (2015). HB2 implementation policy
guide. vasmartscale.org/documents/hb2policyguide_8-1-2015.pdf.
Walters, J., Bochner, B., & Ewing, R. (2013). Getting trip generation right: Eliminating the
bias against mixed-use development. American Planning Associationasap.fehrandpeers.
com/wp-content/uploads/2016/03/APA_PAS_May2013_GettingTripGenRight-2.pdf.
Zhao, Y., & Kockelman, K. M. (2002). The propagation of uncertainty through travel
demand models: An exploratory analysis. The Annals of Regional Science, 36(1),
145–163.
A.E. Lee, S.L. Handy Research in Transportation Business & Management xxx (xxxx) xxx–xxx
12
