Subject: DOE's interagency comments on EPA/DOT CAFE/GHG emissions NPRM for MY 2017-2025 

Sent: 11/03/2011 08:36 AM AST

From: "White, Thomas" [Thomas.White@hq.doe.gov]

To: "james.tamm@dot.gov" <james.tamm@dot.gov>; William Charmley; "rebecca.yoon@dot.gov" 

<rebecca.yoon@dot.gov>

 

Hi Jim, Bill, and Rebecca, 

 

I just wanted to make sure you had DOE’s interagency comments on the NPRM. Let us know if you 

have any questions. 

 

Thank you, 

Tom 

 

 

 

Thomas White 

U.S. Department of Energy 

Office of Policy and International Affairs 

202-586-1393 

thomas.white@hq.doe.gov

From: Kohl, Elizabeth 

Sent: Wednesday, November 02, 2011 7:36 PM

To: White, Thomas

Cc: Difiglio, Carmine

Subject: FW: for your review: EPA/DOT CAFE/GHG emissions NPRM for MY 2017-2025 

 

Tom – Per your request, here are the comments provided to OMB. Thank you, 

 

Betsy 

 

DOE comments on EPA-NHTSA 2017-2025 GHG CAFE NPRM.DOCX 

DOE Comments on II G Safety Considerations in Establishing CAFE.DOCX 
DOE’s General Comments on the NPRM Preamble: 

Page 39 – “EPA is proposing that EVs and FCVs start with a multiplier value of 2.0 in MY 2017, phasing

down to a value of 1.5 in MY 2021. PHEVs would start at a multiplier value of 1.6 in MY 2017 and phase 

down to a value of 1.3 in MY 2021.1 The multiplier would be 1.0 for MYs 2022-2025.” The multipliers 

appear to be related to the hybridization degree of the powertrain (I.e., BEVs have a higher multiplier 

than PHEVs). If so, perhaps the multiplier should be proportional to the hybridization degree. This would 

allow differentiating PHEVs with different EV ranges. Otherwise, a PHEV with a small battery (i.e., 

4kWh) gets the same credit as a PHEV with a larger one (i.e., 16kWh). 

Page 40 – “EPA is proposing that mild HEV pickup trucks would be eligible for a per vehicle credit of 10 

g/mi2

 during MYs 2017-2021 if the technology is used on a minimum percentage of a company’s full size 

pickups...” Is there a credit for other technologies, such as PHEVs? 

Page 61, Table I-21: The 7% discount rate Car Sum of Present Values is incorrect. 

Page 84, Table II-2: The term “MAV (Multi-Activity Vehicle)” is introduced without a definition; the 

NPRM would benefit from a definition of this term, as it is not one that has been used before. 

Page 100 – “The agencies excluded diesels and dedicated AFVs because the agencies anticipate that 

advanced gasoline-fueled vehicles are likely to be dominant through MY2025.” However likely this 

outcome is, we would like to understand more how this conclusion was reached. 

Page 112 – “Shift optimization is a strategy whereby the engine and/or transmission controller(s) 

emulates a CVT by continuously evaluating all possible gear options that would provide the necessary 

tractive power and select the best gear ratio that lets the engine run in the most efficient operating

zone.” DOE understands that the trade-off between drive quality and fuel consumption benefits with 

respect to CVT controls has been an issue, and has led many OEMs to scale back development of CVTs. 

(Drive quality suffers when fuel consumption benefits are maximized through CVT operation.) Has 

drive-quality been taken into account, with respect to the shift optimization strategy that emulates a

CVT? 

Page 113 – “Mass Reduction can be achieved in many ways, such as material substitution, design 

optimization, part consolidation, improving manufacturing process, etc. The agencies applied mass 

reduction of up to 20 percent relative to MY 2008 levels in this NPRM compared to only 10 percent in 

2012-2016 final rule.” What does the 20% reduction include? Is this for the entire vehicle, or just the 

glider? 

Page 182 – The table list the incentives for EV/PHEV/FCV multipliers in the same column. This is different 

than the statement on page 39 that mentions that EVs and FCVs start with 2 and PHEVs with 1.6 in 2017.

The same values are also in Table III-14 on page 263 

Page 271 - We find the CNG vehicle utility factor discussion for dual fuel CNG is confusing in the second 

paragraph this page of the preamble. More explanation of how they end up with 95% CNG operation 

would be useful. 

Page 314 – Table III – It seems unusual that GM and Hyundai are shown as having 0% penetration of 

HEVs (and Ford at only 2%) in 2025 while they all have already HEVs in the market. Also, Toyota, the 

 
current market leader, has a lower percentage (12%) than BMW and Tata, who have no HEVs on the 

market. Can the reasoning behind these numbers be explored? 

Page 344 – Table III-50. A table comparing the current technology costs with the values in 2025 along 

with a percentage improvement per year to reach these values would be helpful to evaluate the 

“aggressiveness” of the cost assumptions. – similar comment for Page 673 Table IV.G.4-1A 

Page 324 – Table III-31 - Why are idle-stop systems and mild HEVs not considered in any of the analysis 

of this section? These technologies are being considered in large production by the auto manufacturers. 

Page 407, Table III-66: The “Total” effect on vehicle electrification of the proposed standards is very low 

(<one million kWh, or roughly the amount that could be consumed by 300 Nissan Leafs in one year). 

Page 569 – ‘For this proposal the FEV tear down work was expanded to include an 8-speed DCT, a 

power-split hybrid, which was used to determine a P2 hybrid cost, and a mild hybrid with stop-start 

technology”. Additional explanation of how the power-split hybrid cost was used to determine the P2 

hybrid cost, as the cost of power split and P2 hybrid are different, would be beneficial. 

Page 570 – “NHTSA notes that, in developing technology cost and effectiveness estimates, the agencies 

have made every effort to hold constant aspects of vehicle performance and utility typically valued by

consumers, such as horsepower, carrying capacity, drivability, durability, noise, vibration and harshness 

(NVH) and towing and hauling capacity. More discussion on the criteria used for durability, noise, 

vibration, and harshness would be useful. 

Page 576 – The Volpe model begins with an initial state of the domestic vehicle market, which in this 

case is the market for passenger cars and light trucks to be sold during the period covered by the 

proposed standards. The vehicle market is defined on a year-by-year, model-by-model, engine-byengine, and transmission-by-transmission basis, such that each defined vehicle model refers to a 

separately defined engine and a separately defined transmission. Comparatively, EPA’s OMEGA model 

defines the vehicle market using representative vehicles at the vehicle platform level, which are binned 

into 5 year timeframes instead of year-by-year. It would be beneficial for the agencies to describe the 

necessity to use two separate tools and provide further explanations about how the difference in the 

tool methodologies and assumptions influence the overall results. 

Page 585 – “In past rulemaking analyses, as noted above, both agencies have used a learning curve 

algorithm that applied a learning factor of 20 percent for each doubling of production volume. NHTSA

has used this approach in analyses supporting recent CAFE rules. In its analyses, EPA has simplified the 

approach by using an “every two years” based learning progression rather than a pure production 

volume progression (i.e., after two years of production it was assumed that production volumes would 

have doubled and, therefore, costs would be reduced by 20 percent).3

 More discussion on why the 

simplification was done by EPA, and what effect it has on the overall results would be useful. 

Page 620 – “NHTSA notes that the Volpe model not only has been formally peer-reviewed and tested 

and reviewed through three rulemakings, but also has some features especially important for the 

analysis of CAFE standards under EPCA/EISA. Among these are the ability to perform year-by-year 

analysis, and the ability to account for engineering differences between specific vehicle models.“ More 

 
information elaborating about the impact of these features and how it would affect their results if they 

did not have them would be useful. 

Page 620 – “By combining technologies incrementally and on a model-by-model basis, the CAFE model is 

able to account for important engineering differences between vehicle models and avoid unlikely 

technology combinations.” Additional text elaborating on the impact of addressing technologies 

individually vs. packages would be useful. 

Page 621 – “The model calculates the cost of this electricity, as well as the accompanying upstream 

criteria pollutant and greenhouse gas emissions.” More discussion here whether this calculation takes

into account the regional variability of electric generation around the U.S., and the resulting differences 

in GHG and pollutant emissions, and differences in electricity rates would be beneficial. 

Page 681/682 – Is there an explanation why, if most of the assumptions and methodologies are similar, 

Table IV.G.4-4 shows that almost no HEVs are required (1% SHEV1_2 by 2025) when EPA states that as 

much as 15% would be necessary (Table III-23 page 314)? 

Page 5-71: It is highly unlikely that the g/mi values shown for automobiles for start-stop technology and 

solar roofs would be so close (2.9 vs. 3.0, respectively). We believe that the value of start-stop has got 

to be much larger compared to solar since it is not dependent on the climate (sunny in Dallas vs. rainy in 

Seattle vs. snowy in Vermont) or time of day (daylight vs. night). The same argument applies to solar

control. Is it possible that someone is off by a decimal point for the solar technology? 

DOE Comments on Energy Security Implications pages 420-424: 

Estimating the energy security impacts of reduced U.S. petroleum consumption in the context of a GHG 

emissions rule making has presented the EPA with a novel issue. The apparent dilemma is how to value 

clear-cut energy-security economic benefits to the U.S. that are offset by economic losses to another 

country. The OMB has taken the position that since the benefits of GHG emissions reductions to all 

nations should be counted, the energy security impacts should also be considered on a global scale. As 

a consequence the “monopsony” benefits of reduced U.S. petroleum use (which accrue to all world oil 

consumers) are offset by the reduced revenues of oil producers, and for that stated reason are not 

counted in the EPA’s cost-benefit analysis. This decision is mistaken because it insures that one or the 

other problem cannot be efficiently solved. 

Monopsony benefits arise from the fact that when the U.S. reduces its oil consumption by one barrel, 

there is likely to be a very small reduction in the world price of oil. This very small price reduction 

benefits all remaining barrels of oil consumed and may therefore have substantial value: the estimates

cited based on Leiby (2008) are $10-$11 per barrel. The monopsony benefits to U.S. oil consumers arise 

from losses of monopoly profits to oil producers. The monopoly profits are the result of the use of 

market power by oil producers. The monopoly-monopsony issue is essentially an adversarial zero-sum 

problem. If oil producers can collect monopoly profits they come out ahead but oil consumers lose; if oil 

consumers can reclaim some of the monopoly profit via use of monopsony power, they benefit but oil 

producers lose. In this case, the EPA is arguing that cost-benefit analysis of policies to solve the energy 

security problem should be based on only a fraction of the value to the U.S. economy of solving that 

problem, i.e., just the disruption costs. Inevitably, following this line of reasoning will lead to too little 

investment in solving the nation’s energy security problem. 

On the other hand, GHG mitigation for climate protection is a genuine global concern. The costs of GHG 

emissions and the benefits of mitigation accrue throughout the globe. This is an entirely different 
problem, a problem of the tragedy of the global commons that can only be solved by common global 

action. To count only the GHG mitigation benefits that accrue to a single country would greatly 

underestimate the global benefits and inevitably lead to too little investment in solving the problem of 

global climate change. 

The flaw in this logic is to assume that the two different problems must have the same cost-benefit 

accounting rules, regardless of the nature of the problems. In fact, applying a consistent set of costbenefit rules to both problems inevitably guarantees that one or the other problem cannot be efficiently 

solved. The EPA should recognize that energy security is a problem of national interest while protecting 

the global climate is a problem of global interest. The correct method is to count monopsony energy 

security benefits to the U.S. and GHG mitigation benefits to the entire world. Only this approach can

solve both problems efficiently. 

Inconsistency in Valuation of Global Costs and Benefits of CO2 Energy Security 

Another issue is that when EPA calculates the energy security values using only the disruption 

component of the ORNL energy security premium it is only doing so on a domestic basis. To be 

consistent with evaluating both the social cost of CO2 and energy security on a global basis the energy 

security benefit should be calculated on a global basis. However, if EPA includes both the monopsony 

premium and the global GHG benefits in its rulemaking estimates, this current calculation of the 

disruption component is consistent and need not be changed. 

DOE’s Comments on the EPA Regulation Impact Analysis Document Section 8 

In calculating the vehicle sales impacts starting on page 8-1 EPA used real discounts of 3 and 7 percent 

per OMB Circular A-4. However, annual payments derived from the loan rates were calculated using a 

nominal (current) interest rate, resulting in nominal (current dollars). These payments should be in real 

dollars to be consistent with the OMB discount rates. This could be done using the All Urban Consumer

Price Index found in AEO 2011. Section 8-3 should be revised as follows: 

Pg 8-3, paragraph 1. Annual payment percentage was calculated in nominal dollars, which are 

discounted by the real rate. 

Pg 8-3 paragraph 2. Resale value of the vehicle is in nominal dollars, which is discounted by the 

real rate. Resale value needs to be in real (inflation-adjusted) dollars. 

Pg 8-2 paragraph 3. Insurance costs are assumed to remain constant in nominal dollars over the 

five year period, but are discounted by real interest rates. Insurance rates should probably go up 

in nominal dollars to reflect a constant (real) insurance rate. 

Tables 8.1-1 and 8.1-2 (pgs 8-4 and 8-5) will then be affected. Since this changes the number of 

car and truck sales, Table 8.2-2 (pg 8-27) will also change, as will Table 8.2-6 (pg. 8-32). 

Pg 8-4 paragraph 1. Does the vehicle demand elasticity literature address using total operating cost 

rather than the initial cost of the vehicle? Additional text describing the literature on vehicle demand 

elasticities may be helping in justifying inclusion of operating cost in the net price of technology. 

Inclusion of the car loan calculation in estimating the impact of the rulemaking. 
A broader question involves the how the car loan calculation is incorporated in the economic impact 

calculations. Quoting from pg 8-3 

“Converting the up-front payment to an annual value paid over five years results 

in a consumer paying 23.4 percent of the up-front amount every year. The 

present value of these five payments results in an increase of 7.3 percent of the 

cost, using a 3 percent discount rate; with a 7 percent discount rate, the 

increase is -4.0 percent.” 

Since both the purchaser and the lender are private parties, barring additional information they should 

discount costs and benefits at the same rate. In the above example, if the discount rate is 7 percent and 

the loan agency is lending at 5.5 percent (the fact that this is a nominal rate and should be corrected to 

be consistent with real discount rates provided by OMB has been noted previously) the discounted 

purchase price is 4 percent below the up-front payment. This value has a tangible impact on the 

calculation of the net cost of technology, vehicle sales, and employment. However, if the 7 percent 

discount rate is a proxy for required rate of return, lenders are lending at 5.5 percent but should require 

7 percent. The -4 percent reduction in discounted payments relative to the up-front cost seen by the 

consumer is mirrored in a loss by the auto industry as a whole and lenders in particular, but not 

accounted for anywhere in the rest of the sector analysis. Incorporation of a separate auto loan rate just 

reflects calculation of an arbitrary financial inconsistency between the current loan rate and the 

assumed discount rates presented in the OMB guidance. We suggest that rulemaking assume a 3 

percent or a 7 percent (real) loan rate consistent with the discount rate. 
G. Safety Considerations in Establishing CAFE/GHG Standards 

1. Why do the agencies consider safety?

The primary goals of the proposed CAFE and GHG standards are to reduce fuel 

consumption and GHG emissions from the on-road light-duty vehicle fleet, but in 

addition to these intended effects, the agencies also consider the potential of the standards 

to affect vehicle safety.1 As a safety agency, NHTSA has long considered the potential 

for adverse safety consequences when establishing CAFE standards,2

 and under the 

CAA, EPA considers factors related to public health and human welfare, and safety, in 

regulating emissions of air pollutants from mobile sources.3

 Safety trade-offs associated 

with fuel economy increases may have occurred in the past (particularly before NHTSA 

CAFE standards were attribute-based), and the agencies must be mindful of the 

possibility of future ones. These past safety trade-offs may have occurred because 

manufacturers chose, at the time, to build smaller and lighter vehicles—partly in response 

to CAFE standards—rather than adding more expensive fuel-saving technologies (and 

maintaining vehicle size and safety), and the smaller and lighter vehicles did not fare as 

well in crashes as larger and heavier vehicles. Historically, as shown in FARS data 

analyzed by NHTSA, the safest cars tend to have been heavy and large, while the cars 

with the highest fatal-crash rates have been light and small. The question, then, is 

whether past is necessarily prologue when it comes to potential changes in vehicle size 

(both footprint and “overhang”) and mass in response to these proposed future CAFE and 

GHG standards. Manufacturers have stated that they will reduce vehicle mass as one of 

the cost-effective means of increasing fuel economy and reducing CO2 emissions in order 

to meet the proposed standards, and the agencies have incorporated this expectation into 

our modeling analysis supporting the proposed standards. Because the agencies discern a 

historical relationship between vehicle mass, size, and safety, it is reasonable to assume 

that these relationships will continue in the future. The question of whether vehicle 

design can mitigate the adverse effects of mass reduction is discussed below. 

 

1

 In this rulemaking document, “vehicle safety” is defined as societal fatality rates per vehicle miles 

traveled (VMT), which include fatalities to occupants of all the vehicles involved in the collisions, plus any 

pedestrians. 

2

 This practice is recognized approvingly in case law. As the United States Court of Appeals for the D.C. 

Circuit stated in upholding NHTSA’s exercise of judgment in setting the 1987-1989 passenger car 

standards, “NHTSA has always examined the safety consequences of the CAFE standards in its overall 

consideration of relevant factors since its earliest rulemaking under the CAFE program.” Competitive 

Enterprise Institute v. NHTSA (“CEI I”), 901 F.2d 107, 120 at n. 11 (D.C. Cir. 1990). 

3

 See NRDC v. EPA, 655 F. 2d 318, 332 n. 31 (D.C. Cir. 1981).(EPA may consider safety in developing 

standards under section 202 (a) and did so appropriately in the given instance).

Formatted: Left: 1.25", Right: 1.25"

Deleted: there will also be

Deleted: between vehicle mass and safety

Deleted: , although it may have been in the 

past and possibly the future partially or fully 

mitigated by improvements in vehicle design 

and advances in vehicle safety features
Manufacturers are less likely than they were in the past to reduce vehicle footprint 

in order to reduce mass for increased fuel economy. The primary mechanism in this 

rulemaking for mitigating the potential negative effects on safety is the application of 

footprint-based standards, which create a disincentive for manufacturers to produce 

smaller-footprint vehicles. See section II. C.1, above. This is because, as footprint 

decreases, the corresponding fuel economy/GHG emission target becomes more 

stringent. We also believe that the shape of the footprint curves themselves is 

approximately “footprint-neutral,” that is, that it should neither encourage manufacturers 

to increase the footprint of their fleets, nor to decrease it. Upsizing footprint is also 

discouraged through the curve “cut-off” at larger footprints.4

 However, the footprintbased standards do not discourage downsizing the portions of a vehicle in front of the 

front axle and to the rear of the rear axle, or of other areas of the vehicle outside the 

wheels. The crush space provided by those portions of a vehicle can make important 

contributions to managing crash energy. Additionally, simply because footprint-based 

standards create no incentive to downsize vehicles does not mean that manufacturers will 

not downsize if doing so makes it easier to meet the overall CAFE/GHG standard, as for 

example if the smaller vehicles are so much lighter that they exceed their targets by much 

greater amounts. On balance, however, we believe the target curves and the incentives 

they provide generally will not encourage down-sizing (or up-sizing) in terms of footprint 

reductions (or increases).5

Given that we expect manufacturers to reduce vehicle mass in response to the 

proposed standards, and do not expect manufacturers to reduce vehicle footprint in 

response to the proposed standards, the agencies must attempt to predict the safety 

effects, if any, of the proposed standards based on the best information currently 

available. This section explained why the agencies consider safety; the following section 

discusses how the agencies consider safety. 

 

4

 The agencies recognize that at the other end of the curve, manufacturers who make small cars and trucks 

below 41 square feet (the small footprint cut-off point) have some incentive to downsize their vehicles to 

make it easier to meet the constant target. That cut-off may also create some incentive for manufacturers 

who do not currently offer models that size to do so in the future. However, at the same time, the agencies 

believe that there is a limit to the market for cars and trucks smaller than 41 square feet: most consumers 

likely have some minimum expectation about interior volume, for example, among other things. 

Additionally, vehicles in this segment are the lowest price point for the light-duty automotive market, with 

several models in the $10,000-$15,000 range. Manufacturers who find themselves incentivized by the cutoff will also find themselves adding technology to the lowest price segment vehicles, which could make it 

challenging to retain the price advantage. Because of these two reasons, the agencies believe that the 

incentive to increase the sales of vehicles smaller than 41 square feet due to this rulemaking, if any, is 

small. See Section II.C.1 above and Chapter 1 of the draft Joint TSD for more information on the agencies’ 

choice of “cut-off” points for the footprint-based target curves. 

5

 This statement makes no prediction of how consumer choices of vehicle size will change in the future,

independent of this proposal. 
2. How do the agencies consider safety? 

Assessing the effects of vehicle mass reduction and size on societal safety is a 

complex issue. One part of estimating potential safety effects involves trying to 

understand better the relationship between mass and vehicle design. The extent of mass 

reduction that manufacturers may be considering to meet more stringent fuel economy 

and GHG standards may raise different safety concerns from what the industry has 

previously faced. The principal difference between the heavier vehicles, especially truckbased LTVs, and the lighter vehicles, especially passenger cars, is that mass reduction has 

a different effect in collisions with another car or LTV. When two vehicles of unequal 

mass collide, the change in velocity (delta V) is higher in the lighter vehicle, similar to 

the mass ratio proportion. As a result of the higher change in velocity, the fatality risk 

may also increase. Removing more mass from the heavier vehicle than in the lighter 

vehicle by amounts that bring the mass ratio closer to 1.0 reduces the delta V in the 

lighter vehicle, possibly resulting in a net societal benefit. 

Another complexity is that if a vehicle is made lighter, it may also need to be 

made stiffer to protect its occupants in a crash to manage the total energy of the crash. A 

stiffer vehicle affects the forces on the vehicle’s occupants in a crash – because the 

vehicle manages crash energy differently, the occupants may have to “ride down” greater 

crash forces themselves, putting more burden on the restraint systems to protect the 

occupants. Matching the restraint system to the vehicle stiffness may help mitigate the 

effects of increased vehicle stiffness. Another factor is that a stiffer vehicle also affects 

the forces that the stiffer vehicle exerts on any vehicles it crashes into – stiffer vehicles 

can be more aggressive in crashes due to the crash energy transfer. 

The agencies must attempt to estimate now, based on the best information 

currently before us, how the assumed levels of mass reduction without additional changes 

(i.e. footprint, performance, functionality) might affect the safety of vehicles, and how 

lighter vehicles might affect the safety of drivers and passengers in the entire on-road 

fleet, as we are analyzing potential future CAFE and GHG standards. The agencies seek 

to ensure that the standards are designed to encourage manufacturers to pursue a path 

toward compliance that is both cost-effective and safe. 

To estimate the possible safety effects of the MY 2017-2025 standards, then, the 

agencies have undertaken research that approaches this question from several angles. 

First, we are using a statistical approach to study the effect of vehicle mass reduction on 

safety historically, as discussed in greater detail in section C below. Statistical analysis is 

performed using the most recent historical crash data available, and is considered as the 

agencies’ best estimate of potential mass-safety effects. The agencies recognize that 

negative safety effects estimated based on the historical relationships could be tempered 

with safety technology advances in the future, and may not represent the current or future 

Deleted: to

Deleted: the

Deleted: additionally be potentially
fleet. Second, we are using an engineering approach to investigate what amount of mass 

reduction is affordable and feasible while maintaining vehicle safety and other major 

functionalities such as NVH and acceleration performance. Third, we are also studying 

the new challenges these lighter vehicles might bring to vehicle safety and potential 

countermeasures available to manage those challenges effectively. 

The sections below discuss more specifically the state of the research on the 

mass-safety relationship, and how the agencies integrate that research into our assessment 

of the potential safety effects of the MY 2017-2025 CAFE and GHG standards. 

3. What is the current state of the research on statistical analysis of historical 

crash data? 

a. Background 

Researchers have been using statistical analysis to examine the relationship of 

vehicle mass and safety in historical crash data for many years, and continue to refine 

their techniques over time. In the MY 2012-2016 final rule, the agencies stated that we 

would conduct further study and research into the interaction of mass, size and safety to 

assist future rulemakings, and start to work collaboratively by developing an interagency 

working group between NHTSA, EPA, DOE, and CARB to evaluate all aspects of mass, 

size and safety. The team would seek to coordinate government supported studies and 

independent research, to the greatest extent possible, to help ensure the work is 

complementary to previous and ongoing research and to guide further research in this 

area. 

The agencies also identified three specific areas to direct research in preparation 

for future CAFE/GHG rulemaking in regards to statistical analysis of historical data. 

First, NHTSA would contract with an independent institution to review the 

statistical methods that NHTSA and DRI have used to analyze historical data related to 

mass, size and safety, and to provide recommendation on whether the existing methods or 

other methods should be used for future statistical analysis of historical data. This study 

will include a consideration of potential near multicollinearity in the historical data and 

how best to address it in a regression analysis. The 2010 NHTSA report was also peer 

reviewed by two other experts in the safety field - Charles Farmer (Insurance Institute for 

Highway Safety) and Anders Lie (Swedish Transport Administration).6

 

 

6

 All three of the peer reviews are in docket, NHTSA-2010-0152. You can access the docket at 

http://www.regulations.gov/#!home by typing ‘NHTSA-2010-0152’ where it says “enter keyword or ID” 

and then clicking on “Search.”
Second, NHTSA and EPA, in consultation with DOE, would update the MYs 

1991–1999 database on which the safety analyses in the NPRM and final rule are based 

with newer vehicle data, and create a common database that could be made publicly 

available to help address concerns that differences in data were leading to different 

results in statistical analyses by different researchers. 

And third, in order to assess if the design of recent model year vehicles that 

incorporate various mass reduction methods affect the relationships among vehicle mass, 

size and safety, the agencies sought to identify vehicles that are using material 

substitution and smart design, and to try to assess if there is sufficient crash data 

involving those vehicles for statistical analysis. If sufficient data exists, statistical 

analysis would be conducted to compare the relationship among mass, size and safety of 

these smart design vehicles to vehicles of similar size and mass with more traditional 

designs. 

Significant progress has been made on these tasks since the MY 2012-2016 final 

rule, as follows: The independent review of recent and updated statistical analyses of the 

relationship between vehicle mass, size, and crash fatality rates has been completed. 

NHTSA contracted with the University of Michigan Transportation Research Institute 

(UMTRI) to conduct this review, and the UMTRI team led by Paul Green evaluated over 

20 papers, including studies done by NHTSA’s Charles Kahane, Tom Wenzel of the US 

Department of Energy’s Lawrence Berkeley National Laboratory, Dynamic Research, 

Inc., and others. UMTRI’s basic findings will be discussed below. Some commenters in 

recent CAFE rulemakings, including some vehicle manufacturers, suggested that the 

designs and materials of more recent model year vehicles may have weakened the 

historical statistical relationships between mass, size, and safety. The agencies agree that 

the statistical analysis would be improved by using an updated database that reflects more 

recent safety technologies, vehicle designs and materials, and reflects changes in the 

overall vehicle fleet. The agencies also believe, as UMTRI also found, that different 

statistical analyses may have had different results because they each used slightly 

different datasets for their analyses. In order to try to mitigate this problem and to 

support the current rulemaking, NHTSA has created a common, updated database for 

statistical analysis that consists of crash data of model years 2000-2007 vehicles in 

calendar years 2002-2008, as compared to the database used in prior NHTSA analyses 

which was based on model years 1991–1999 vehicles in calendar years 1995-2000. The 

new database is the most up-to-date possible, given the processing lead time for crash 

data and the need for enough crash cases to permit statistically meaningful analyses. 

NHTSA has made the new databases available to the public,7

 enabling other researchers 

to analyze the same data and hopefully minimizing discrepancies in the results that would 

 

7

 The new databases are available at http://www.nhtsa.gov/fuel-economy (look for “Download Crash 

Databases for Statistical Analysis of Relationships Between Vehicles’ Fatality Risk, Mass, and Footprint.” 

Deleted: Laboratories

Deleted: part of the reason that 

Deleted: past 

Deleted: come up with

Deleted: could be due to the lack of a single 

comprehensive database of crash information.

Deleted: possibility
have been due to inconsistencies across databases.8

 The agencies recognize, however, 

that the updated database may not represent the future fleet, because vehicles have 

continued and will continue to change. 

The agencies are aware that several studies have been initiated using NHTSA’s 

2011 newly established safety database. In addition to a new Kahane study, which is 

discussed in section II.G.4, other on-going studies include two by Wenzel at Lawrence 

Berkeley National Laboratory (LBNL) under contract with the U.S. DOE, and one by

Dynamic Research, Inc. (DRI) contracted by the International Council on Clean 

Transportation (ICCT). These studies may take somewhat different approaches to 

examine the statistical relationship between fatality risk, vehicle mass and size. In

addition to a detailed assessment of the NHTSA 2011 report, Wenzel is expected to 

consider the effect of mass and footprint reduction on casualty risk per crash, using data 

from thirteen states. Casualty risk includes both fatalities and serious or incapacitating 

injuries. DRI is expected to use a two-stage approach to separate the effect of mass 

reduction on the two components of fatality risk, crash avoidance and crashworthiness. 

The LBNL assessment of the NHTSA 2011 report is available in the docket for this 

NPRM.9 The casualty risk effect study was not available in time to inform this NPRM. 

The completed final peer reviewed-report on both assessments will be available prior to 

the final rule. DRI has also indicated that it expects its study to be publicly available 

prior to the final rule. The agencies will consider these studies and any others that 

become available, and the results may influence the safety analysis for the final rule. 

Other researchers are free to download the database from NHTSA’s website, and 

we expect to see additional papers in the coming months and as comments to the 

rulemaking that may also inform our consideration of these issues for the final rule. 

Kahane’s updated study for 2011 is currently undergoing peer-review, and is available in 

the docket for this rulemaking for review by commenters. 

Finally, EPA and NHTSA with DOT’s Volpe Center, part of the Research and 

Innovative Technology Administration (RITA), attempted to investigate the implications 

of “Smart Design,” by identifying and describing the types of “Smart Design” and 

methods for using “Smart Design” to result in vehicle mass reduction, selecting analytical 

pairs of vehicles, and using the appropriate crash database to analyze vehicle crash data. 

The analysis identified several one-vehicle and two-vehicle crash datasets with the 

potential to shed light on the issue, but the available data for specific crash scenarios was 

insufficient to produce consistent results that could be used to support conclusions 

regarding historical performance of “smart designs.” 

 

8

 75 Fed. Reg. 25324 (May 7, 2010); the discussion of planned statistical analyses is on pp. 25395-25396. 

9

 –Wenzel, T.P. (2011b). Assessment of NHTSA’s Report “Relationships between Fatality Risk, Mass, and 

Footprint in Model Year 2000-2007 Passenger Cars and LTVs”, available at...

Deleted: by 

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Deleted: 

Deleted: Wenzel’s dual approach is expected 

to consider the casualty risk effect associated 

with mass reduction, in

Deleted: fatality risk

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mass reduction.

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EPA
Undertaking these tasks has helped the agencies come closer to resolving some of 

the ongoing debates in statistical analysis research of historical crash data. We intend to 

apply these conclusions going forward, and we believe that the public discussion of the 

issues will be facilitated by the research conducted. The following sections discuss the 

findings from these studies and others in greater detail, to present a more nuanced picture 

of the current state of the statistical research. 

b. NHTSA workshop on vehicle mass, size and safety 

On February 25, 2011, NHTSA hosted a workshop on mass reduction, vehicle 

size, and fleet safety at the Headquarters of the U.S. Department of Transportation in 

Washington, DC.10 The purpose of the workshop was to provide the agencies with a 

broad understanding of current research in the field and provide stakeholders and the 

public with an opportunity to weigh in on this issue. NHTSA also created a public 

docket to receive comments from interested parties that were unable to attend. 

The speakers included Charles Kahane of NHTSA, Tom Wenzel of Lawrence 

Berkeley National Laboratory, R. Michael Van Auken of Dynamic Research Inc. (DRI), 

Jeya Padmanaban of JP Research, Inc., Adrian Lund of the Insurance Institute for 

Highway Safety, Paul Green of the University of Michigan Transportation Research 

Institute (UMTRI), Stephen Summers of NHTSA, Gregg Peterson of Lotus Engineering, 

Koichi Kamiji of Honda, John German of the International Council on Clean 

Transportation (ICCT), Scott Schmidt of the Alliance of Automobile Manufacturers, Guy 

Nusholtz of Chrysler, and Frank Field of the Massachusetts Institute of Technology. 

The wide participation of the workshop allowed the agencies to hear from a broad 

range of experts and stakeholders. The contributions were particularly relevant to the 

agencies’ analysis of the effects of weight reduction for this proposed rule. The 

presentations were divided into two sessions that addressed the two expansive sets of 

issues – statistical evidence of the roles of mass and size on safety, and engineering 

realities – structural crashworthiness, occupant injury and advanced vehicle design. 

The first session focused on previous and ongoing statistical studies of crash data 

that attempt to identify the relative effects of vehicle mass and size on fleet safety. There 

was consensus that there is a complicated relationship with many confounding influences 

in the data. Wenzel summarized a recent study he conducted comparing four types of 

risk (fatality or casualty risk, per vehicle registration-years or per crash) using police-

 

10 A video recording, transcript, and the presentations from the NHTSA workshop on mass reduction, 

vehicle size and fleet safety is available at http://www.nhtsa.gov/fuel-economy (look for “NHTSA 

Workshop on Vehicle Mass-Size-Safety on Feb. 25”) 

Deleted: Thomas

Deleted: Library

Deleted: Wenzel identified qualitatively 

similar trends in results
reported crash data from five states.11 He showed that the trends in risk for various 

classes of vehicles (e.g., non-sports car passenger cars, vans, SUVs, crossover SUVs, 

pickups) were similar regardless of what risk was being measured (fatality or casualty) or 

what exposure metric was used (e.g., registration years, police-reported crashes, etc.). In 

general, most trends showed a lower risk for larger or heavier vehicles. However, all of 

the risks shown in the presentation were risk to drivers only, and did not include risk to 

drivers of other vehicles. Including risks to drivers of other vehicles, in order to account 

for societal risk, mutes the trend of decreasing risk with increasing vehicle size or weight, 

and in the case of fatality risk for pickups reverses the trend (with fatality risk increasing 

as pickup size and weight increases). However, there were some differences in the 

various risks analyzed for certain vehicle types. 

Although Wenzel’s analysis was focused on differences in the four types of risk 

on the relative risk by vehicle type, he cautioned that, when analyzing casualty risk per 

crash, analysts should control for driver age and gender, crash location (urban vs. rural), 

and the state in which the crash occurred (to account for crash reporting biases).

Several participants pointed out that analyses must also control for individual 

technologies with significant safety effects (e.g., Electronic Stability Control, airbags).It 

was not always conclusive whether a specialty vehicle group (e.g., sports cars, two-door 

cars, early crossover SUVs) were outliers that confound the trend or unique datasets that 

isolate specific vehicle characteristics. Unfortunately, specialty vehicle groups are usually 

adopted by specific driver groups, often with outlying vehicle usage or driver behavior 

patterns. Green, who conducted an independent review of the previous statistical 

analyses, suggested that evaluating residuals will give an indication of whether or not a 

data subset can be legitimately removed without affecting the analytical results. 

It was recognized that, all else being equal, the physics of a two-vehicle crash 

require that the lighter vehicle experience a greater change in velocity, which often leads 

to disproportionately more injury risk. Lund noted persistent historical trends that, in any 

time period, occupants of the smallest and lightest vehicles had, on average, fatality rates 

approximately twice those of occupants of the largest and heaviest vehicles but predicted 

“the sky will not fall” as the fleet downsizes, we will not see an increase in absolute 

injury risk because smaller cars will become increasingly protective of their occupants. 

Padmanaban also noted in her research of the historical trends that mass ratio and vehicle 

stiffness are significant predictors with mass ratio consistently the dominant parameter 

when correlating harm. Reducing the mass of any vehicle may have competing effects 

on risk: a likely increase in the fatality risk to its own occupants, while a likely decrease 

 

11 Wenzel, T.P. (2011a). Analysis of Casualty Risk per Police-Reported Crash for Model Year 

2000 to 2004 Vehicles, using Crash Data from Five States, March 2011, LBNL-4897E, available at: 

http://eetd.lbl.gov/EA/teepa/pub.html#Vehicle

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databases, results were sometimes off by a 

discernible but consistent factor. 

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injury risk in the lightened vehicle and 

decreases them in the partner vehicle. 
in the fatality risk to occupants of any lighter vehicles it might strike in a crash However, 

the net effect would likely be a benefit in terms of societal risk.

The separation of key parameters was also discussed as a challenge to the 

analyses, as vehicle size has historically been correlated with vehicle mass. Presenters 

had varying approaches for dealing with the potential multicollinearity between these two 

variables. Van Auken of DRI stated that there was latitude in the value of Variance 

Inflation Factor (VIF, a measure of multicollinearity) that would call results into 

question, and suggested that the large value of VIF for curb weight might imply “perhaps 

the effect of weight is too small in comparison to other factors.” Green, of UMTRI, 

stated that highly correlated variables may not be appropriate for use in a predictive 

model and that “match[ing] on footprint” (i.e., conducting multiple analyses for data 

subsets with similar footprint values) may be the most effective way to resolve the issue. 

There was no consensus on the overall effect of the maneuverability of smaller, 

lighter vehicles. German noted that lighter vehicles should have improved handling and 

braking characteristics and “may be more likely to avoid collisions”. Lund presented 

crash involvement data that implied that, among vehicles of similar function and use 

rates, crash risk does not go down for more “nimble” vehicles. Several presenters noted 

the difficulties of projecting past data into the future as new technologies will be used 

that were not available when the data were collected. The advances in technology through 

the decades have dramatically improved safety for all weight and size classes. A video of 

IIHS’s 50th anniversary crash test of a 1959 Chevrolet Bel Air and 2009 Chevrolet 

Malibu graphically demonstrated that stark differences in design and technology that can 

possibly mask the discrete mass effects, while videos of compatibility crash tests between 

smaller, lighter vehicles and contemporary larger, heavier vehicles graphically showed 

the significance of vehicle mass and size. 

Kahane presented results from his 2010 report12 that found that a scenario which 

took some mass out of heavier vehicles but little or no mass out of the lightest vehicles 

did not impact safety in absolute terms. Kahane noted that if the analyses were able to 

consider the mass of both vehicles in a two-vehicle crash, the results may be more 

indicative of future crashes. There is apparent consistency with other presentations (e.g., 

Padmanaban, Nusholtz) that reducing the overall ranges of masses and mass ratios seems 

to reduce overall societal harm. That is, the effect of mass reduction exclusively does not 

appear to be a “zero sum game” in which any increase in harm to occupants of the 

lightened vehicle is precisely offset by a decrease in harm to the occupants of the partner 

vehicle. If the mass of the heavier vehicle is reduced by a larger percentage, the changes 

in velocity from the collision are more nearly equal and the injuries suffered in the lighter 

 

Deleted: is highly

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and 

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Comment [DOE1]: Footnote is missing. 

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vehicle are likely to be reduced more than the injuries in the heavier vehicle are 

increased. Alternatively, a fixed mass reduction (say, 100 lbs) in all vehicles could 

increase societal harm whereas a fixed percentage mass reduction is more likely to be 

neutral. 

Padmanaban described a series of studies conducted in recent years. She included 

numerous vehicle parameters including bumper height and several measures of vehicle 

size and stiffness and also commented on previous analyses that using weight and 

wheelbase together in a logistic model distorts the estimates, resulting in inflated variance 

with wrong signs and magnitudes in the results. Her results consistently showed that 

vehicle mass ratio was a more important parameter than those describing vehicle 

geometry or stiffness. Her ultimate conclusion was that removing mass (e.g., 100 lbs.) 

from all passenger cars would cause an overall increase in fatalities in truck-to-car 

crashes while removing the same amount from light trucks would cause an overall 

decrease in fatalities. 

c. Report by Green et al., UMTRI – “Independent Review: Statistical 

Analyses of Relationship Between Vehicle Curb Weight, Track Width, 

Wheelbase and Fatality Rates,” April 2011. 

As explained above, NHTSA contracted with the University of Michigan 

Transportation Research Institute (UMTRI) to conduct an independent review13 of a set 

of statistical analyses of relationships between vehicle curb weight, the footprint variables 

(track width, wheelbase) and fatality rates from vehicle crashes. The purpose of this 

review was to examine analysis methods, data sources, and assumptions of the statistical 

studies, with the objective of identifying the reasons for any differences in results. 

Another objective was to examine the suitability of the various methods for estimating 

the fatality risks of future vehicles. 

 UMTRI reviewed a set of papers, reports, and manuscripts provided by 

NHTSA (listed in Appendix A of UMTRI’s report, which is available in the docket to 

this rulemaking) that examined the statistical relationships between fatality or casualty

rates and vehicle properties such as curb weight, track width, wheelbase and other 

variables. 

 It is difficult to summarize a study of that length and complexity for purposes 

of this discussion, but fundamentally, the UMTRI team concluded the following: 

• Differences in data may have complicated comparisons of earlier analyses, but if 

the methodology is robust, and the methods were applied in a similar way, small 

 

13 The review is independent in the sense that it was conducted by an outside third party without any 

interest in the reported outcome. 

Deleted: historic analysis

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Deleted: crash or 
changes in data should not lead to different conclusions. The main conclusions 

and findings should be reproducible. The data base created by Kahane appears to 

be an impressive collection of files from appropriate sources and the best ones 

available for answering the research questions considered in this study. 

• In statistical analysis simpler models lead to improved inference, assuming the data 

and model assumptions are appropriate. In that regard, the disaggregate logistic 

regression model used by NHTSA in the 2003 report14 seems to be the most 

appropriate model, and valid for the analysis in the context that it was used:

finding general associations between fatality risk and mass reduction. 

• The two-stage logistic regression model in combination with the two-step aggregate 

regression used by DRI seems to be more complicated than is necessary based on 

the data being analyzed, and summing regression coefficients from two separate 

models to arrive at conclusions about the effects of reductions in weight or size on 

fatality risk seems to add unneeded complexity to the problem. 

• One of the biggest issues regarding this work is the historical correlation between 

curb weight, wheelbase, and track width. Including three variables that are 

correlated in the same model can have adverse effects on the fit of the model, 

especially with respect to the parameter estimates, as discussed by Kahane. 

UMTRI makes no conclusions about multicollinearity, other than to say that 

inferences made in the presence of multicollinearity should be judged with great 

caution. At the NHTSA workshop on size, safety and mass, Paul Green suggested 

that a matched analysis, in which regressions are run on the relationship between 

mass reduction and risk separately for vehicles of similar footprint, could be 

undertaken to address the issue of multicollinearity between vehicle mass and 

footprint. Kahane has combined wheelbase and track width into one variable 

(footprint) to compare with curb weight. NHTSA believes that the 2011 Kahane 

analysis has done all it can to lessen concerns about multicollinearity, but a 

concern still exists. In considering other studies provided by NHTSA for 

evaluation by the UMTRI team: 

o Papers by Wenzel, and Wenzel and Ross, addressing associations between 

fatality risk per vehicle registration-year, weight, and size by vehicle 

model contribute to understanding some of the relationships between risk, 

weight, and size. However, least squares linear regression models, 

without modification, are not exposure-based risk models and inference 

drawn from these models tends to be weak since they do not account for 

additional differences in vehicles, drivers, or crash conditions that could 

explain the variance in risk by vehicle model.

o A 2009 J.P. Research paper focused on the difficulties associated with 

separating out the contributions of weight and size variables when 

analyzing fatality risk properly recognized the problem arising from 

multicollinearity and included a clear explanation of why fatality risk is 

expected to increase with increasing mass ratio. UMTRI concluded that 

the increases in fatality risk associated with a 100-pound reduction in 

 

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reported associations are correct

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UMTRI states that one

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based

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passenger car and light truck model types,

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that are generally in the right direction

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Deleted: positive fatality rate 

Deleted: weight 
weight allowing footprint to vary with weight as estimated by Kahane and 

JP Research, are broadly more convincing than the 6.7 percent reduction 

in fatality risk associated with mass reduction while holding footprint 

constant, as reported by DRI. 

o A paper by Nusholtz et al. focused on the question of whether vehicle size 

can reasonably be the dominant vehicle factor for fatality risk, and finding 

that changing the mean mass of the vehicle population (leaving variability 

unchanged) has a stronger influence on fatality risk than corresponding 

(feasible) changes in mean vehicle dimensions, concluded unequivocally 

that reducing vehicle mass while maintaining constant vehicle dimensions 

will increase fatality risk. UMTRI concluded that if one accepts the 

methodology, this conclusion is robust against realistic changes that may 

be made in the force vs. deflection characteristics of the impacting 

vehicles. 

o Two papers by Robertson, one a commentary paper and the other a peerreviewed journal article, were reviewed. The commentary paper did not 

fit separate models according to crash type, and included passenger cars, 

vans, and SUVs in the same model. UMTRI concluded that some of the 

claims in the commentary paper appear to be overstated, and intermediate 

results and more documentation would help the reader determine if these 

claims are valid. The second paper focused largely on the effects of 

electronic stability control (ESC), but generally followed on from the first 

paper except that curb weight is not fit and fuel economy is used as a 

surrogate. 

 

The UMTRI study provided a number of useful suggestions that Kahane 

considered in updating his 2011 analysis, and that have been incorporated into the safety 

effects estimates for the current rulemaking. 

d. Report by Dr. Charles Kahane, NHTSA – “Relationships Between Fatality 

Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars and 

LTVs,” 2011 

The relationship between a vehicle’s mass, size, and fatality risk is complex, and 

it varies in different types of crashes. NHTSA, along with others, has been examining 

this relationship for over a decade. The safety chapter of NHTSA’s April 2010 final 

regulatory impact analysis (FRIA) of CAFE standards for MY 2012-2016 passenger cars 

and light trucks included a statistical analysis of relationships between fatality risk, mass, 

and footprint in MY 1991-1999 passenger cars and LTVs (light trucks and vans), based 

on calendar year (CY) 1995-2000 crash and vehicle-registration data.15 The 2010 

 

15 Kahane, C. J. (2010). “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 1991-

1999 and Other Passenger Cars and LTVs,” Final Regulatory Impact Analysis: Corporate Average Fuel 

Economy for MY 2012-MY 2016 Passenger Cars and Light Trucks. Washington, DC: National Highway 

Deleted: vehicle

Deleted: of fatalities

Deleted: ,

Deleted: paper
analysis used the same data as the 2003 analysis, but included vehicle mass and footprint 

in the same regression model.

The principal findings of NHTSA’s 2010 analysis were that mass reduction in 

lighter cars, even while holding footprint constant, would significantly increase societal 

fatality risk, whereas mass reduction in the heavier LTVs would significantly reduce net 

societal fatality risk, because it would reduce the fatality risk of occupants in lighter 

vehicles which collide with the heavier LTVs. NHTSA concluded that, as a result, any 

reasonable combination of mass reductions while holding footprint constant in MY 2012-

2016 vehicles – concentrated, at least to some extent, in the heavier LTVs and limited in 

the lighter cars – would likely be approximately safety-neutral; it would not significantly 

increase fatalities and might well decrease them. 

NHTSA’s 2010 report partially agreed with analyses published during 2003-2005 

by Dynamic Research, Inc. (DRI). NHTSA and DRI both found a significant protective 

effect for footprint, and that reducing mass and footprint together (downsizing) on 

smaller vehicles was harmful. DRI’s analyses estimated a significant overall reduction in 

fatalities from mass reduction in all light-duty vehicles if wheelbase and track width were 

maintained, whereas NHTSA’s report showed overall fatality reductions only in the 

heavier LTVs, and benefits only in some types of crashes for other vehicle types. Much 

of NHTSA’s 2010 report, as well as recent work by DRI, involved sensitivity tests on the 

databases and models, which generated a range of estimates somewhere between the 

initial DRI and NHTSA results.16 

Immediately after issuing the final rule for MYs 2012-2016 CAFE and GHG 

standards in May 2010, NHTSA and EPA began work on the next joint rulemaking to 

develop CAFE and GHG standards for MY 2017 to 2025 and beyond. The preamble to 

the 2012-2016 final rule stated that NHTSA, working closely with EPA and the 

Department of Energy (DOE), would perform a new statistical analysis of the 

relationships between fatality rates, mass and footprint, updating the crash and exposure 

databases to the latest available model years, refining the methodology in response to 

 

Traffic Safety Administration, pp. 464-542, available at 

http://www.nhtsa.gov/staticfiles/rulemaking/pdf/cafe/CAFE_2012-2016_FRIA_04012010.pdf. 

16 Van Auken, R. M., and Zellner, J. W. (2003). A Further Assessment of the Effects of Vehicle Weight and 

Size Parameters on Fatality Risk in Model Year 1985-98 Passenger Cars and 1986-97 Light Trucks. 

Report No. DRI-TR-03-01. Torrance, CA: Dynamic Research, Inc.; Van Auken, R. M., and Zellner, J. W. 

(2005a). An Assessment of the Effects of Vehicle Weight and Size on Fatality Risk in 1985 to 1998 Model 

Year Passenger Cars and 1985 to 1997 Model Year Light Trucks and Vans. Paper No. 2005-01-1354. 

Warrendale, PA: Society of Automotive Engineers; Van Auken, R. M., and Zellner, J. W. (2005b). 

Supplemental Results on the Independent Effects of Curb Weight, Wheelbase, and Track on Fatality Risk in 

1985-1998 Model Year Passenger Cars and 1986-97 Model Year LTVs. Report No. DRI-TR-05-01. 

Torrance, CA: Dynamic Research, Inc.; Van Auken, R.M., and Zellner, J. W. (2011). “Updated Analysis 

of the Effects of Passenger Vehicle Size and Weight on Safety,” NHTSA Workshop on Vehicle Mass-SizeSafety, Washington, February 25, 2011, 

http://www.nhtsa.gov/staticfiles/rulemaking/pdf/MSS/MSSworkshop_VanAuken.pdf 

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peer reviews of the 2010 report and taking into account changes in vehicle technologies. 

The previous databases of MY 1991-1999 vehicles in CY 1995-2000 crashes has become 

outdated as new safety technologies, vehicle designs and materials were introduced. The 

new databases comprising MY 2000-2007 vehicles in CY 2002-2008 crashes with the 

most up-to-date possible, given the processing lead time for crash data and the need for 

enough crash cases to permit statistically meaningful analyses. NHTSA has made the 

new databases available to the public17, enabling other researchers to analyze the same 

data and hopefully minimizing discrepancies in the results due to inconsistencies across 

the data used.

18

The basic analytical method used for the 2011 NHTSA report is the same as in 

NHTSA’s 2010 report: cross-sectional analyses of the effect of mass and footprint 

reductions on the societal fatality rate per billion vehicle miles of travel (VMT), while 

controlling for driver age and gender, vehicle type, vehicle safety features, crash times 

and locations, and other factors. Separate logistic regression models are run for three 

types of vehicles and nine types of crashes. Societal fatality rates include occupants of all

vehicles in the crash, as well as non-occupants, such as pedestrians and cyclists. 

NHTSA’s 2011 Report19 analyzes MY 2000-2007 cars and LTVs in CY 2002-2008 

crashes. Fatality rates were derived from FARS data, 13 State crash files, and 

registration and mileage data from R.L. Polk. 

The most noticeable change in MY 2000-2007 vehicles from MY 1991-1999 has 

been the increase in crossover utility vehicles (CUV), which are SUVs of unibody 

construction, often but not always built upon a platform shared with passenger cars. 

CUVs have blurred the distinction between cars and trucks. The new analysis treats 

CUVs and minivans as a separate vehicle class, because they differ in some respects from 

pickup-truck-based LTVs and in other respects from passenger cars. In the 2010 report, 

the many different types of LTVs were combined into a single analysis and NHTSA 

believes that this may have made the analyses too complex and might have contributed to 

some of the uncertainty in the results. 

The new database has accurate VMT estimates, derived from a file of odometer 

readings by make, model, and model year recently developed by R.L. Polk and purchased 

by NHTSA.20 For the 2011 report, the relative distribution of crash types has been 

changed to reflect the projected distribution of crashes during the period from 2017 to 

2025, based on the estimated effectiveness of electronic stability control (ESC) in 

 

17 http://www.nhtsa.gov/fuel-economy

18 75 Fed. Reg. 25324 (May 7, 2010); the discussion of planned statistical analyses is on pp. 25395-25396. 

19 Kahane, C. J. (2011). “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2000-

2007 Passenger Cars and LTVs,”, July 2011. The report is available in the NHTSA docket, NHTSA-2010-

0152. You can access the docket at http://www.regulations.gov/#!home by typing ‘NHTSA-2010-0152’ 

where it says “enter keyword or ID” and then clicking on “Search.” 

20 In the 1991-1999 data base, VMT was estimated only by vehicle class, based on NASS CDS data. 

Deleted: that would have been 

Deleted: databases

Deleted: One way to estimate these effects is 

via statistical analyses of societal fatality rates

per vehicle miles traveled (VMT), by vehicles’ 

mass and footprint, for the current on-road 

vehicle fleet. 

Deleted: ) by mass and footprint,

Deleted: ,

Deleted: , in separate

Deleted: regressions by vehicle class and 

crash type

Deleted: data

Deleted: future crash types 

Deleted: ). For example,
reduction the number of fatalities in rollover crashes and crashes with a stationary object.

The annual target population of fatalities or the annual fatality distribution baseline21 was 

not decreased in the period between 2017 and 2025 for the safety statistics analysis, but is 

taken into account later in the Volpe model analysis, since all vehicles in the future will 

be equipped with ESC22. 

For the 2011 report, vehicles are now grouped into five classes rather than four: 

passenger cars (including both 2-door and 4-door cars) are split in half by median weight; 

CUVs and minivans; and truck-based LTVs, which are also split in half by median 

weight of the model year 2000-2007 vehicles. Table Error! No text of specified style in 

document.-1 presents the estimated percent increase in US societal fatality risk per ten 

billion VMT for each 100-pound reduction in vehicle mass, while holding footprint 

constant, for each of the five classes of vehicles. 

Table Error! No text of specified style in document.-1 Results of 2011 NHTSA 

report Fatality Increase (%) per 100-Pound Mass Reduction While Holding 

Footprint Constant 

MY 2000-2007 

CY 2002-2008 

Fatality Increase (%) Per 100-Pound Mass 

Reduction While Holding Footprint Constant 

Point Estimate 95% Confidence Bounds

Cars < 3,106 pounds 1.44 + .29 to +2.59

Cars > 3,106 pounds .47 - .58 to +1.52

CUVs and minivans - .46 -1.75 to + .83

Truck-based LTVs < 4,594 

pounds 

 .52 - .43 to +1.46

Truck-based LTVs > 4,594 

pounds 

 - .39 -1.06 to + .27

Only the 1.44 percent risk increase in the lighter cars is statistically significant. 

There are non-significant increases in the heavier cars and the lighter truck-based LTVs,

and non-significant societal benefits for mass reduction in CUVs, minivans, and the 

heavier truck-based LTVs. Based on these results, potential combinations of mass 

reductions that maintain footprint and are proportionately somewhat higher for the 

 

21 MY 2004 -2007 vehicles with fatal crashes occurred in CY 2004-2008 are selected as the annual fatality 

distribution baseline in the Kahane analysis. 

22 In the Volpe model, NHTSA assumed that the safety trend would result in 12.6 percent reduction 

between 2007 and 2020 due to the combination of ESC, new safety standard, and behavior changes 

anticipated. 

Deleted: percent

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Deleted: two vehicle 

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Deleted: Table II-12

Deleted: Table Error! No text of specified 

style in document.-1

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Deleted: mass 

Deleted: 12

Deleted: 1

Formatted Table

Deleted: in
heavier vehicles may be safety-neutral or better as point estimates and, in any case, 

unlikely to significantly increase fatalities. The primarily non-significant results are not 

due to a paucity of data, but because the societal effect of mass reduction while 

maintaining footprint, if any, is small. 

MY 2000-2007 vehicles of all types are heavier and larger than their MY 1991-

1999 counterparts. The average mass of passenger cars increased by 5 percent from 2000 

to 2007 and the average mass of pickup trucks increased by 19 percent. Other types of 

vehicles became heavier, on the average, by intermediate amounts. There are several 

reasons for these increases: during this time frame, some of the lighter make-models were 

discontinued; many models were redesigned to be heavier and larger; and consumers 

more often selected stretched versions such as crew cabs in their new-vehicle purchases. 

It is interesting to compare the new results to NHTSA’s 2010 analysis of MY 

1991-1999 vehicles in CY 1995-2000, especially the new point estimate to the “actual 

regression result scenario” in the 2010 report: 

Table Error! No text of specified style in document.-2 2010 Report: MY 1991-

1999, CY 1995-2000 Fatality Increase (%) per 100-Pound Mass Reduction While 

Holding Footprint Constant 

Actual Regression 

Result Scenario 

Upper-Estimate 

Scenario 

Lower-Estimate 

Scenario 

Cars < 2,950 

pounds 2.21 2.21 1.02 

Cars > 2,950 

pounds 0.90 0.90 0.44 

LTVs < 3,870 

pounds 0.17 0.55 0.41 

LTVs > 3,870 

pounds -1.90 -0.62 -0.73 

Table Error! No text of specified style in document.-3 Fatality Increase (%) 

per 100-Pound Mass Reduction While Holding Footprint Constant 

NHTSA (2010) NHTSA (2011) 

Lighter cars 2.21% 1.43% 

Heavier cars 0.89% 0.48% 

Lighter LTVs 0.17%* 0.52% 

Heavier LTVs -1.90%* -0.40% 

CUV/ minivan -0.47% 

*Includes CUV/minivan 

Deleted: 13

Deleted: 2

Formatted Table

Deleted: 14

Deleted: 3
The new results are directionally the same as in 2010: fatality increase in the 

lighter cars, safety benefit in the heavier LTVs, but the effects may have become weaker 

at both ends. (The agencies do not consider this conclusion to be definitive because of 

the relatively wide confidence bounds of the estimates.) The fatality increase in the 

lighter cars tapered off from 2.21 percent to 1.44 percent while the societal benefit of 

mass reduction in the heaviest LTVs diminished from 1.90 percent to 0.39 percent and is 

no longer statistically significant. 

The agencies believe that the changes may be due to a combination of changes in 

the characteristics of newer vehicles and revisions to the analysis. NHTSA believes, 

above all, that several light, small car models with poor safety performance were 

discontinued by 2000 or during 2000-2007. Also, the tendency of light, small vehicles to 

be driven poorly is not as strong as it used to be – perhaps in part because safety 

improvements in lighter and smaller vehicles have made some good drivers more willing 

to buy them. Both agencies believe that at the other end of the weight/size spectrum, 

blocker beams and other voluntary compatibility improvements in LTVs, as well as 

compatibility-related self-protection improvements to cars, have made the heavier LTVs 

less aggressive in collisions with lighter vehicles (although the effect of mass disparity 

remains). This report’s analysis of CUVs and minivans as a separate class of vehicles 

may have relieved some inaccuracies in the 2010 regression results for LTVs. 

Interestingly, the new actual-regression results are quite close to the previous report’s 

“lower-estimate scenario,” which was an attempt to adjust for supposed inaccuracies in 

some regressions and for a seemingly excessive trend toward higher crash rates in smaller 

and lighter cars. 

The principal difference between the heavier vehicles, especially truck-based 

LTVs, and the lighter vehicles, especially passenger cars, is that mass reduction has a 

different effect in collisions with another car or LTV. When two vehicles of unequal 

mass collide, the delta V is higher in the lighter vehicle, in the same proportion as the 

mass ratio. As a result, the fatality risk is also higher. Removing some mass from the 

heavy vehicle reduces delta V in the lighter vehicle, where fatality risk is high, resulting 

in a large benefit, offset by a small penalty because delta V increases in the heavy 

vehicle, where fatality risk is low – adding up to a net societal benefit. Removing some 

mass from the lighter vehicle results in a large penalty offset by a small benefit – adding 

up to net harm. These considerations drive the overall result: fatality increase in the 

lighter cars, reduction in the heavier LTVs, and little effect in the intermediate groups. 

However, in some types of crashes, especially 1st-event rollovers and impacts with fixed 

objects, mass reduction is usually not harmful and often beneficial, because the lighter 

vehicles respond more quickly to braking and steering and are often more stable because 

their center of gravity is lower. Offsetting that benefit is the continuing historical 

Deleted: “real” factors (

Deleted: the 

Deleted: )

Deleted: many cars

Deleted: , which were often light, small cars,

Deleted: The

Deleted: , while still there,

Deleted: somewhat

Deleted: that do not involve collisions 

between cars and LTVs
tendency of lighter and smaller vehicles to be driven less well – although it continues to 

be unknown why that is so, and to what extent, if any, the lightness or smallness of the 

vehicle contributes to people driving it less safely. 

The estimates of the model are formulated for each 100-pound reduction in mass; 

in other words, if risk increases by 1 percent for 100 pounds reduction in mass, it would 

increase by 2 percent for a 200-pound reduction, and 3 percent for a 300-pound reduction

(more exactly, 2.01 percent and 3.03 percent, because the effects work like compound 

interest). Confidence bounds around the point estimates will grow wider by the same 

proportions. 

The regression results are best suited to predict the effect of a small change in 

mass, leaving all other factors, including performance, wheelbase and track width, the 

same. With each additional change from the current environment, the model may 

become somewhat less accurate and it is difficult to assess the sensitivity to additional 

mass reduction greater than 100 pounds. The agencies recognize that the light-duty 

vehicle fleet in the 2017-2025 timeframe will be different than the 2000-2007 fleet 

analyzed for this study. Nevertheless, one consideration provides some basis for 

confidence. This is NHTSA’s fourth evaluation of the effects of mass reduction and/or 

downsizing, comprising databases ranging from MY 1985 to 2007. The results of the 

four studies are not identical, but they have been consistent up to a point. During this 

time period, many makes and models have increased substantially in mass, sometimes as 

much as 30-40 percent.23 If the statistical analysis has, over the past years, been able to 

accommodate mass increases of this magnitude, perhaps it will also succeed in modeling 

the effects of mass reductions on the order of 10-20 percent, if they occur in the future. 

e. Report by Tom Wenzel, LBNL, “An Assessment of NHTSA’s Report 

‘Relationships Between Fatality Risk, Mass, and Footprint in Model Year 

2000-2007 Passenger Cars and LTVs’”, 2011

DOE contracted with Tom Wenzel of Lawrence Berkeley National Laboratory to 

conduct an assessment of NHTSA’s updated 2011 study of the effect of mass and 

footprint reductions on US fatality risk per vehicle miles traveled, and to provide an 

analysis of the effect of mass and footprint reduction on casualty risk per police-reported 

crash, using independent data from thirteen states. The assessment has been completed 

and reviewed by NHTSA and EPA staff, and a draft final version is included in the 

docket of today’s rulemaking; the separate analysis of crash data from thirteen states will 

 

23 For example, one of the most popular models of small 4-door sedans increased in curb weight from 1,939 

pounds in MY 1985 to 2,766 pounds in MY 2007, a 43 percent increase. A high-sales mid-size sedan grew

from 2,385 to 3,354 pounds (41%); a best-selling pickup truck from 3,390 to 4,742 pounds (40%) in the 

basic model with 2-door cab and rear-wheel drive; and a popular minivan from 2,940 to 3,862 pounds 

(31%). 

Deleted: reductions. According to the 

regression results

Deleted: or decreases 

Deleted: or decrease 

Deleted: pounds

Deleted: pounds

Deleted: the same as the model was 

developed (MY 2000-2007 in CY 2002-2008),

Comment [DOE2]: What performance? The 

current study models footprint, not wheelbase 

and track width separately. 

Deleted: 

Comment [DOE3]: We don’t understand 

your point here; has NHTSA done a 

retrospective analysis that indicates that its 

previous studies accurately predicted the future 

effect of mass reduction on risk? The 2003 

analysis did not anticipate the big increase in 

CUVs, which were the same size but roughly 

15% lighter than truck-based SUVs, yet have 

substantially lower risk than SUVs. 
be completed and included in the docket shortly. Both reports will be peer reviewed by 

outside experts. 

The LBNL report replicates Kahane’s analysis for NHTSA, using the same data 

and methods, and in many cases using the same SAS programs. The Wenzel report finds 

that although mass reduction in lighter (less than 3,106 lbs) cars leads to a statistically 

significant 1.44% increase in fatality risk per vehicle miles travelled (VMT), the increase 

is small, is overwhelmed by other factors, and is somewhat sensitive to changes in 

specifications of the regression models and what data are used. In addition Wenzel 

shows that there is a wide range in risk by vehicle model for models that have the same 

mass, even after accounting for differences among models in drivers, safety features 

installed, and crash times and locations. This section summarizes the results of the 

Wenzel assessment of the most recent NHTSA analysis.

The LBNL report highlights the effect of the other driver, vehicle, and crash 

control variables, in addition to the effect of mass and footprint reduction, on risk. It first 

converts the log-odds effects from the SAS output into probabilities; this conversion has

no effect on variables that have small effects, such as mass and footprint reduction, but 

increases the magnitude of variables that have larger effects on risk, such as crash times 

and locations. The other variables NHTSA included in its regression models have much 

larger effects on fatality risk than mass or footprint reduction. For example, the models 

indicate that a 100-lb increase in the mass of a lighter car results in a 1.44% reduction in 

fatality risk; this is the largest estimated effect of changes in vehicle mas, and the only 

one that is statistically significant. For comparison this reduction in fatality risk could 

also be achieved by a 13% increase in 4-door sedans equipped with ESC or a 16% 

increase in 4-door sedans equipped with ABS or torso side airbags.

The 1.44% increase in risk from reducing mass in the lighter cars is somewhat

sensitive to slight changes in the specification of, or the data used in, the regression 

models. For example, using the current distribution of crashes, rather than adjusting the 

distribution to that expected after full adoption of ESC, reduces the effect to 1.18%; 

excluding the calendar year variables from the model, which may be weakening the 

modeled benefits of vehicle safety technologies, reduces the effect to 1.39%; and 

including vehicle make in the model increases the effect to 1.81%. The results also are 

sensitive to the selection of data to include in the analysis: excluding bad drivers 

increases the effect to 2.03, while excluding crashes involving alcohol or drugs increases 

the effect to 1.66, and including sports, police, and all-wheel drive cars increases the 

effect to 1.64. Finally, changing the definition of risk also affects the result for lighter 

cars: using the number of fatalities per induced exposure crash reduces the effect to -0.24 

(that is, a 0.24 reduction in risk), while using the number of fatal crashes (rather than total 

fatalities) per VMT increases the effect to 1.84. These changes in the effect of mass 

reduction for the lighter cars, although not large, suggest that the model results are 
somewhat sensitive to small changes in the model specifications or using different sets of 

data.

Using two or more variables that are strongly correlated in the same regression 

model (referred to as multicollinearity) can lead to inaccurate results. However, the 

correlation between vehicle mass and footprint may not be strong enough to cause serious 

concern. Experts suggest that a correlation of greater than 0.60 (or a variance inflation 

factor of 2.5) raises concern about multicollinearity.24 The correlation between vehicle 

mass and footprint ranges from over 0.80 for four-door sedans, pickups, and SUVs, to 

about 0.65 for two-door cars and CUVs, to only 0.26 for minivans; when pickups and 

SUVs are considered together, the correlation between mass and footprint is only 0.65. 

The 2011 NHTSA report correctly recognizes that the “near” multicollinearity between 

mass and footprint may not be strong enough to invalidate the results from a regression 

model that includes both variables (a point NHTSA argued against DRI using this 

approach in previous studies). Even so, NHTSA has made several attempts to account 

for the near-multicollinearity between mass and footprint. 

First, NHTSA ran a sensitivity model specification, where footprint is not held 

constant, but rather allowed to vary as mass varies (i.e. NHTSA ran a regression model 

which includes mass but not footprint). If the multicollinearity was so great that 

including both variables in the same model gave misleading results, removing footprint 

from the model would give much different results than keeping it in the model. 

NHTSA’s sensitivity indicates that when footprint is allowed to vary with mass, the 

effect of mass reduction on risk increases to 2.64% for lighter cars, and to a statisticallysignificant 1.94% for heaver cars; however, the effect of mass reduction on light trucks is 

unchanged, and is still not statistically significant for CUVs/minivans.

Second, NHTSA conducted a stratification analysis of the effect of mass 

reduction on risk by dividing vehicles into deciles based on their footprint, and running a 

separate regression model for each vehicle and crash type, for each footprint decile (3 

vehicle types times 9 crash types times 10 deciles equals 270 regressions). This analysis 

estimates the effect of mass reduction on risk separately for vehicles with similar 

footprint. The analysis indicates that mass reduction does not consistently increase risk 

across all footprint deciles for any combination of vehicle type and crash type. Mass 

reduction increases risk in a majority of footprint deciles for 13 of the 27 crash and 

vehicle combinations, but few of these increases are statistically significant. On the other 

hand, mass reduction decreases risk in a majority of footprint deciles for 9 of the 27 crash 

and vehicle combinations; in some cases these risk reductions are large and statistically 

significant. If reducing vehicle mass while maintaining footprint inherently leads to an 

 

24 Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy 

Standards; Final Rule, April 1, 2010, Section II.G.3., page 139.
increase in risk, the coefficients on mass reduction should be more consistently positive, 

and with a larger R2, across the 27 vehicle/crash combinations, than shown in the 

analysis.

One limitation to using logistic regression to estimate the effect of mass reduction 

on risk is that a standard statistic to measure the extent to which the variables in the 

model explain the range in risk, equivalent to the R

2

 statistic in a linear regression model, 

does not exist. (SAS does generate a pseudo-R2 value for logistic regression models; in 

almost all of the NHTSA regression models this value is less than 0.10). For this reason 

LBNL conducted an analysis of risk versus mass by vehicle model. LBNL used the 

results of the NHTSA logistic regression model to predict the number of fatalities 

expected after accounting for all vehicle, driver, and crash variables included in the 

NHTSA regression model except for vehicle weight and footprint. LBNL then plotted 

expected fatality risk per VMT by vehicle model against the mass of each model, and 

analyzed the change in risk as mass increases, as well as how much of the change in risk 

was explained by all of the variables included in the model. 

The analysis indicates that, after accounting for all the variables, risk does 

decrease as mass increases; however, risk and mass are not strongly correlated, with the 

R

2

 ranging from 0.33 for CUVs to less than 0.15 for all other vehicle types (as shown in 

Figure x). This means that, on average, risk decreases as mass increases, but for 

individual vehicle models an increase in mass does not inherently result in reduced risk. 

For fullsize (i.e. 3⁄4- and 1-ton) pickups, risk actually increases as mass increases, with an 

R

2

 of 0.43. LBNL also examined the relationship between residual risk, that is the 

remaining unexplained risk after accounting for all vehicle, driver and crash variables, 

and mass, and found similarly poor correlations. This implies that the remaining factors 

not included in the regression model that account for the observed range in risk by 

vehicle model also are not correlated with mass. (LBNL found similar results when the 

analysis compared risk to vehicle footprint.)

Figure x indicates that some vehicles on the road today have the same, or lower, 

risk than models that weigh substantially more, and are substantially larger in terms of 

footprint. After accounting for differences in driver age and gender, safety features 

installed, and crash times and locations, there are numerous examples of models from 

different manufacturers with similar weight and footprint yet widely varying fatality risk. 

Differences in vehicle design can, and already do, mitigate any theoretical safety penalty 

from reduced mass; this is consistent with NHTSA’s opinion that some of the changes in 

its regression results between the 2003 study and the 2011 study are due to the redesign 

or removal of certain smaller and lighter models of poor design.
Figure. Predicted US fatality risk per VMT vs. curb weight by vehicle type, after 

accounting for all driver, crash, and vehicle variables except mass and footprint

Increasing vehicle mass does not inherently increase safety in all kinds of 

crashes. For example, installing a stronger roof and support pillars, which happen to 

weigh an additional 100 lbs, will provide increased protection in rollovers but little 

additional protection in crashes with other vehicles; while adding a stronger bumper, also 

weighing an additional 100 lbs, will improve safety in frontal crashes (and likely reduce 

safety in crash partner vehicles) but not in rollovers. Both of these increases in vehicle 

mass will have larger overall safety benefits than putting 100-lbs of topsoil in your 

vehicle's trunk. So increased mass does not inherently increase vehicle safety; it all 

depends on where and how it is added, in short how it is incorporated into the overall 

design of the vehicle.

Based on this information, what do the agencies consider to be the current state of 

statistical research on vehicle mass and safety? 

The agencies believe that statistical analysis of historical crash data continues to 

be an informative and important tool in assessing the potential safety impacts of the 

proposed standards. The effect of mass reduction while maintaining footprint is a 

complicated topic and there are open questions whether future designs will reduce the 

historical correlation between weight and size. It is important to note that while the 

updated database represents more current vehicles with technologies more representative 

of vehicles on the road today, they still do not fully represent what vehicles will be on the 

road in the 2017-2025 timeframe. The vehicles manufactured in the 2000-2007 

R2 = 0.12 

R2 = 0.04 

R2 = 0.00 

R2 = 0.43 

R2 = 0.05 

R2 = 0.33 

R2 = 0.09 

0 

40 

80 

120 

160 

200 

240 

280 

320 

360 

400 

2000 2400 2800 3200 3600 4000 4400 4800 5200 5600 6000 6400 6800 7200 7600 

Predicted US fatality risk (crash fdatalities per 1010 VMT) 

Curb weight (lbs) 

2-dr cars 

4-dr cars 

Small pickups 

Fullsize pickups 

SUVs 

CUVs 

Minivans 

Formatted: Normal,Normal Preamble Text

Deleted: (

Deleted: )

Deleted: may offset

Deleted: findings of statistical analysis of 

Deleted: data
timeframe were not subject to footprint-based fuel economy standards, or sold in an 

environment of elevated gasoline prices. The agencies expect that the attribute-based 

standards will likely facilitate the design of vehicles such that manufacturers may reduce 

mass while maintaining footprint. Therefore, it is possible that the analysis for 2000-2007 

vehicles may not be fully representative of the vehicles that will be on the road in 2017 

and beyond. 

While we recognize that statistical analysis of historical crash data may not be the 

only way to think about the future relationship between vehicle mass and safety, we also 

recognize that other assessment methods are also subject to uncertainties, which makes 

statistical analysis of historical data an important starting point if employed mindfully 

and recognized for how it can be useful and what its limitations may be. 

NHTSA undertook the independent review of statistical studies and held the 

mass-safety workshop in February 2011 in order to help the agencies sort through the 

ongoing debates over what statistical analysis of historical data is actually telling us. 

Previously, the agencies have assumed that differences in results were due in part to 

inconsistent databases; by creating the updated common database and making it publicly 

available, we are hopeful that that aspect of the problem has been resolved, and 

moreover, the UMTRI review suggested that differences in data were probably less 

significant than the agencies may have thought. The agencies also more recently 

concluded, in the MY 2012-2016 final rule, that multicollinearity was likely a significant 

factor in statistical analysis of historical crash data that could lead to inaccurate results. 

The agencies will continue to monitor issues with multicollinearity in our analyses, and 

hope that outside researchers will do the same. And finally, based on the findings of the 

independent review, the agencies continue to be confident that Kahane’s analysis is one 

of the best for the purpose of analyzing potential safety effects of future CAFE and GHG 

standards. UMTRI concluded that Kahane’s approach is valid, and Kahane has continued 

and refined that approach for the current analysis. The NHTSA 2011 statistical fatality 

report finds directionally similar but less statistically significant relationships between 

vehicle mass, size, and footprint, as discussed above. Based on these findings, the 

agencies believe that in the future, fatalities due to mass reduction will be best reduced if 

mass reduction is concentrated in the heaviest vehicles. NHTSA considers part of the 

reason that more recent historical data shows a dampened effect in the relationship 

between mass reduction and safety is that all vehicles, including traditionally lighter ones, 

grew heavier during that timeframe (2000s). As lighter vehicles become more prevalent 

in the fleet again over the next decade, it is possible that the trend could strengthen again. 

On the other hand, extensive use of new lightweight materials may make vehicles 

simultaneously lighter and safer, while maintaining size. Future updated analyses will be 

necessary to determine how the effect of mass reduction on risk changes over time. 

Deleted: .

Deleted: interact with

Deleted: existing fleet

Deleted: solved

Deleted: risk

Deleted: ,

Deleted: different

Comment [DOE4]: DOE does not believe 

this is correct. NHTSA chose not to include 

mass and size in the same regression model in 

the 1997 and 2003 analyses, mostly because of 

the concern that the two variables were highly 

correlated. If anything, NHTSA is less 

concerned about the multicollinearity now, 

since in the 2010 and 2011 studies it included 

both variables in the same regression model. 

Deleted: the 

Deleted: purposes

Deleted: (although certainly not inevitable) 

Deleted: and that future updates to 

Deleted: common database

Deleted: show that. 
Both agencies agree that there are several identifiable safety trends already in 

place or expected to occur in the foreseeable future that are not accounted for in the 

study, since they were not in effect at the time that the vehicles in question were 

manufactured. For example, there are two important new safety standards that have 

already been issued and will be phasing in after MY 2008. FMVSS No. 126 (49 CFR § 

571.126) requires electronic stability control in all new vehicles by MY 2012, and the 

upgrade to FMVSS No. 214 (Side Impact Protection, 49 CFR § 571.214) will likely 

result in all new vehicles being equipped with head-curtain air bags by MY 2014. 

Additionally, we anticipate continued improvements in driver (and passenger) behavior, 

such as higher safety belt use rates. All of these may tend to reduce the absolute number 

of fatalities. On the other hand, as crash avoidance technology improves, future statistical 

analysis of historical data may be complicated by a lower total number of fatal crashes. 

In summary, the agencies have relied on the coefficients in the Kahane 2011 study for 

estimating the potential safety effects of the proposed CAFE and GHG standards for 

MYs 2017-2025, based on our assumptions regarding the cost-effective amount of mass 

reduction that could be used to meet the standards without adversely affecting safety. 

Section E below discusses the methodology used by the agencies in more detail; while 

the results of the safety effects analysis are less significant than the results in the MY 

2012-2016 final rule, the agencies still believe that any statistically significant results 

warrant careful consideration of the assumptions about appropriate levels of mass 

reduction on which to base future CAFE and GHG standards, and have acted accordingly 

in developing the proposed standards. 

4. How do the agencies think technological solutions might affect the safety 

estimates indicated by the statistical analysis? 

As mass reduction becomes a more important technology option for 

manufacturers in meeting future CAFE and GHG standards, manufacturers will invest 

more and more resources in developing increasingly lightweight vehicle designs that 

meet their needs for manufacturability and the public’s need for vehicles that are also 

safe, useful, affordable, and enjoyable to drive. There are many different ways to reduce 

mass, as discussed in Chapter 3 of this TSD and in Sections II, III, and IV of the 

preamble, and a considerable amount of information is available today on lightweight 

vehicle designs currently in production and that may be able to be put into production in 

the rulemaking timeframe. Discussion of lightweight material designs from NHTSA’s 

workshop is presented below. 

Besides “lightweighting” technologies themselves, though, there are a number of 

considerations when attempting to evaluate how future technological developments might 

affect the safety estimates indicated by the statistical analysis. As discussed in the first 

part of this chapter, for example, careful changes in design and/or materials use may 

Deleted: futures

Deleted: built

Deleted: Federal Motor Vehicle Safety 

Standard

Deleted: will require

Deleted: Federal Motor Vehicle Safety 

Standard

Deleted: (future) 

Deleted: population

Deleted: , and different crash effects that may 

begin to trend as those technologies become 

more widespread in the fleet.

Deleted: in a cost-effective way

Deleted: if reducing
mitigate any potential decrease in safety from mass reduction – through improved 

distribution of crash pulse energy, through making the vehicle stiffer, etc. – but these 

techniques can sometimes cause other problems, such as increased crash forces on 

vehicle occupants that have to be mitigated, or greater aggressivity against other vehicles 

in crashes. Manufacturers may develop new and better restraints – air bags, seat belts, 

etc. – to protect occupants in lighter vehicles in crashes, but NHTSA’s current safety 

standards for restraint systems are designed based on the current fleet, not the yetunknown future fleet. The agency will need to monitor trends in the crash data to see 

whether changes to the safety standards (or new safety standards) become necessary. 

Manufacturers are also increasingly employing a variety of crash avoidance technologies 

– ABS, electronic stability control (ESC), lane departure warnings, vehicle-to-vehicle 

(V2V) communications – that, as they become more prevalent in the fleet, are expected to 

reduce the number of overall, and fatal, crashes. Until these technologies are present in 

the fleet in greater numbers, however, it will be difficult to assess whether they can 

mitigate the observed small relationship between vehicle mass and safety in the historical 

data. 

Along with the California Air Resources Board (CARB), the agencies have 

initiated several projects to estimate the maximum potential for advanced materials and

improved designs to reduce mass in the MY 2017-2021 timeframe, while continuing to 

meeting safety regulations and maintaining functionality of vehicles. Another NHTSAsponsored study will estimate the effects of these design changes on overall fleet safety. 

All of these studies will be peer reviewed and released prior to July 2012, in order for 

them to inform the final rule.

A. NHTSA has awarded a contract to Electricore, with EDAG and George 

Washington University (GWU) as subcontractors, to study the maximum feasible 

amount of mass reduction for a mid-size car – specifically, a Honda Accord. The 

study tore down a MY 2011 Honda Accord, studied each component and subsystem, and then redesigned each component and sub-system trying to maximize 

the amount of mass reduction with technologies that are considered feasible for 

200,000 units per year production volume during the time frame of this 

rulemaking. Electricore and its sub-contractors are consulting industry leaders and 

experts for each component and sub-system when deciding which technologies are 

feasible. Electricore and its sub-contractors are also building detailed 

CAD/CAE/powertrain models to validate vehicle safety, stiffness, NVH, 

durability, drivability and powertrain performance. For OEM-supplied parts, a 

detailed cost model is being built based on a Technical Cost Modeling (TCM) 

approach developed by the Massachusetts Institute of Technology (MIT) Materials 

Systems Laboratory’s research25 to estimate the costs to OEMs for manufacturing 

 

25 Frank Field, Randolph Kirchain and Richard Roth, Process cost modeling: Strategic engineering and 

economic evaluation of materials technologies, JOM Journal of the Minerals, Metals and Materials Society, 

Deleted: makes a vehicle less able to protect 

itself and its occupants in crashes, there are 

ways to redesign the vehicle to help it protect 

itself better

Deleted: (“

Deleted: ”)

Deleted: population of 

Deleted: vehicles

Deleted: these technologies 

Deleted: , or whether for the crashes that 

remain and the relationship also persists

Deleted: The 

Deleted: and independent researchers 

Deleted: vehicle level 

Deleted: determine

Deleted: mass reduction in the MY 2017-

2021 timeframe by using 

Deleted: , and one

Deleted: that 

Deleted: investigate

Deleted: resultant designs

Deleted: :

Deleted: tears

Deleted: studies

Deleted: redesigns

Deleted: for estimating
parts. The cost will be broken down into each of the operations involved in the 

manufacturing; for example, for a sheet metal part, production costs will be 

estimated from the blanking of the steel coil to the final operation to fabricate the 

component. Total costs are then categorized into fixed cost, such as tooling, 

equipment, and facilities; and variable costs such as labor, material, energy, and 

maintenance. These costs will be assessed through an interactive process between 

the product designer, manufacturing engineers, and cost analysts. For OEMpurchased parts, the cost will be estimated by consultation with experienced cost 

analysts and Tier 1 system suppliers. This study will help to inform the agencies 

about the extent to which vehicle mass can be cost-effectively reduced. 

B. EPA has awarded a similar contract to FEV, with EDAG and Monroe & 

Associates, Inc. as subcontractors, to study the maximum feasible amount of mass 

reduction for a mid-size CUV (cross over vehicle) specifically, a Toyota Venza. 

This study builds upon the low development (20% mass reduction) design in the 

2010 Lotus Engineering study “An Assessment of Mass Reduction Opportunities 

for a 2017-2020 Model Year Vehicle Program”. 

C. California Air Resources Board (CARB) has awarded a contract to Lotus 

Engineering, to study the maximum feasible amount mass reduction for a mid-size 

CUV (cross over vehicle) specifically, a Toyota Venza. The study will 

concentrate on the Body-in-White and closures in the high development design 

(40% mass reduction) in the Lotus Engineering study cited above. The study will 

provide an updated design with crash simulation, detailed costing and 

manufacturing feasibility of these two systems for a MY2020 high volume 

production vehicle. 

D. NHTSA has contracted with George Washington University (GWU) to build a 

fleet simulation model to study the impact and relationship of light-weight vehicle 

design and injuries and fatalities. This study will also include an evaluation of 

potential countermeasures to reduce any safety concerns associated with 

lightweight vehicles. NHTSA will include three light-weighted vehicle designs in 

this study: the one from Electricore/EDAG/GWU mentioned above, one from 

Lotus Engineering funded by California Air Resource Board for the second phase 

of the study, evaluating mass reduction levels around 35 percent of total vehicle 

mass, and two funded by EPA and the International Council on Clean 

Transportation (ICCT). This study will help to inform the agencies about the 

possible safety implications for light-weight vehicle designs and the appropriate 

counter-measures,26 if applicable, for these designs, as well as the feasible amounts 

of mass reduction. 

 

Volume 59, Number 10, 21-32. Available at 

http://msl.mit.edu/pubs/docs/Field_KirchainCM_StratEvalMatls.pdf (last accessed Aug. 22, 2011). 

26 Countermeasures could potentially involve improved front end structure, knee bags, seat ramps, buckle

pretensioners, and others. 

Deleted: costs of OEM 

Deleted: , such as

Deleted: by starting

Deleted: , until

Deleted: feasible amount of mass reduction 

and the cost associated with it. NHTSA 

intends to have this study completed and 

peer reviewed before July 2012, in time for 

it to play an integral role in informing the 

final rule

Deleted: The study tears down a MY 2010 

vehicle, studies each component and subsystem, and then redesigns each component 

and sub-system trying to maximize the 

amount of mass reduction with technologies 

that are considered feasible for high volume 

production for a 2017 MY vehicle. FEV in 

coordination with EDAG is building detailed 

CAD/CAE/powertrain models to validate 

vehicle safety, stiffness, NVH, durability, 

drivability and powertrain performance to 

assess the safety of this new design. 

Comment [DOE5]: Move this reference to a 

footnote. 

Deleted: ”. This study will undergo a peer 

review. EPA intends to have this study 

completed and peer reviewed before July 

2012, in time for it to play an integral role in 

informing the final rule.

Deleted: This study will undergo a peer 

review. CARB intends to have this study 

completed and peer reviewed before July 

2012, in time for it to play an integral role in 

informing the final rule.

Deleted: weighted

Deleted: weighted

Deleted: All of these analyses are 

expected to be finished and peer-reviewed 

before July 2012, in time to inform the final 

rule.
a. NHTSA workshop on vehicle mass, size and safety 

As stated above, in section C.2, on February 25, 2011, NHTSA hosted a 

workshop on mass reduction, vehicle size, and fleet safety at the Headquarters of the US 

Department of Transportation in Washington, DC. The purpose of the workshop was to 

provide the agencies with a broad understanding of current research in the field and 

provide stakeholders and the public with an opportunity to weigh in on this issue. The 

agencies also created a public docket to receive comments from interested parties that 

were unable to attend. The presentations were divided into two sessions that addressed 

the two expansive sets of issues. The first session explored statistical evidence of the 

roles of mass and size on safety, and is summarized in section C.2. The second session 

explored the engineering realities of structural crashworthiness, occupant injury and 

advanced vehicle design, and is summarized here. The speakers in the second session 

included Stephen Summers of NHTSA, Gregg Peterson of Lotus Engineering, Koichi 

Kamiji of Honda, John German of the International Council on Clean Transportation 

(ICCT), Scott Schmidt of the Alliance of Automobile Manufacturers, Guy Nusholtz of 

Chrysler, and Frank Field of the Massachusetts Institute of Technology. 

The second session explored what degree of weight reduction and occupant 

protection are feasible from technical, economic, and manufacturing perspectives. Field 

emphasized that technical feasibility alone does not constitute feasibility in the context of 

vehicle mass reduction. Sufficient material production capacity and viable 

manufacturing processes are essential to economic feasibility. Both Kamiji and German 

noted that both good materials and good designs will be necessary to reduce fatalities. 

For example, German cited the examples of hexagonally structured aluminum columns,

such as used in the Honda Insight, that can improve crash absorption at lower mass, and 

of high-strength steel components that can both reduce weight and improve safety. 

Kamiji made the point that widespread mass reduction will reduce the kinetic energy of 

all crashes which should produce some beneficial effect. 

Summers described NHTSA’s plans for a model to estimate fleetwide safety 

effects based on an array of vehicle-to-vehicle computational crash simulations of current 

and anticipated vehicle designs. In particular, three computational models of lightweight 

vehicles are under development. They are based on current vehicles that have been 

modified to substantially reduce mass. The most ambitious was the “high development” 

derivative of a Toyota Venza developed by Lotus Engineering and discussed by Mr. 

Peterson. Its structure currently contains about 75% aluminum, 12% magnesium, 8% 

steel, and 5% advanced composites. Peterson expressed confidence that the design had 

the potential to meet federal safety standards. Nusholtz emphasized that computational 

crash simulations involving more advanced materials were less reliable than those 

involving traditional metals such as aluminum and steel. 

Deleted: engineering

Deleted: fleet wide

Deleted: by significant

Deleted: reduction methodologies
Nusholtz presented a revised data-based fleet safety model in which important 

vehicle parameters were modeled based on trends from current NCAP crash tests. For 

example, crash pulses and potential intrusion for a particular size vehicle were based on 

existing distributions. Average occupant deceleration was used to estimate injury risk. 

Through a range of simulations of modified vehicle fleets, he was able to estimate the net 

effects of various design strategies for lighter weight vehicles, such as various scaling 

approaches for vehicle stiffness or intrusion. The approaches were selected based on 

engineering requirements for modified vehicles. Transition from the current fleet was 

considered. He concluded that protocols resulting in safer transitions (e.g., removing 

more mass from heavier vehicles with appropriate stiffness scaling according to a 3/2 

power law) were not generally consistent with those that provide the greatest reduction in 

GHG production.

German discussed several important points on the future of mass reduction. 

Similar to Kahane’s discussion of the difficulties of isolating the impact of weight 

reduction, German stated that other important variables, such as vehicle design and 

compatibility factors, must be held constant in order for size or weight impacts to be 

quantified in statistical analyses. He presented results that, compared to driver, driving 

influences, and vehicle design influences, the safety impacts of size and weight are small 

and difficult to quantify. He noted that several scenarios, such as rollovers, greatly 

favored the occupants of smaller and lighter cars once a crash occurred. He pointed out 

that if size and design are maintained, lower weight should translate into a lower total 

crash force. He thought that advanced material designs have the potential to “decouple” 

the historical correlation between vehicle size and weight, and felt that effective design 

and driver attributes may start to dominate size and weight issues in future vehicle 

models. 

Other presenters noted industry’s perspective of the effect of incentivizing weight 

reduction. Field highlighted the complexity of institutional changes that may be 

necessitated by weight reduction, including redesign of material and component supply 

chains and manufacturing infrastructure. Schmidt described an industry perspective on 

the complicated decisions that must be made in the face of regulatory change, such as 

evaluating goals, gains, and timing. 

Field and Schmidt noted that the introduction of technical innovations is generally 

an innate development process involving both tactical and strategic considerations that 

balance desired vehicle attributes with economic and technical risk. In the absence of 

challenging regulatory requirements, a substantial technology change is often 

implemented in stages, starting with lower volume pilot production before a commitment 

is made to the infrastructure and supply chain modifications necessary for inclusion on a 

high-volume production model. Joining, damage characterization, durability, repair, and 

significant uncertainty in final component costs are also concerns. Thus, for example, the 

Deleted: . 

Comment [DOE6]: This last sentence is very 

convoluted and unclear. 

Deleted: and

Deleted: data

Deleted: showing

Deleted: efficiency

Deleted: to the point “that neither size nor 

weight [will have] a whole lot of impact on the 

overall safety of the overall fleet when you 

consider all the different type of crashes 

involved.”
widespread implementation of high-volume composite or magnesium structures might be 

problematic in the short or medium term when compared to relatively transparent 

aluminum or high strength steel implementations. Regulatory changes will affect how 

these tradeoffs are made and these risks are managed. 

Koichi Kamiji presented data showing in increased use of high strength steel in 

their Honda product line to reduced vehicle mass and increase vehicle safety. He stated 

that mass reduction is clearly a benefit in 42% of all fatal crashes because absolute 

energy is reduced. He followed up with slides showing the application of smart design 

can improve safety even when controlling for weight and size. 

A philosophical theme developed that explored the ethics of consciously allowing 

the total societal harm associated with mass reduction to approach the anticipated benefits 

of enhanced safety technologies. Lund conceded that there may eventually be specific 

fatalities that would not have occurred without downsizing, but asserted “Those of us 

whose mission is highway safety will have to adapt our strategies to the reality created by 

consumer choices,” but that “We will be ok if we let data on what works – not wishful 

thinking – guide our strategies.” 

5. How have the agencies estimated safety effects for the proposed standards? 

a. What was the agencies’ methodology for estimating safety effects for the 

proposed standards? 

As explained above, the agencies consider the 2011 statistical analysis of 

historical crash data by NHTSA to represent the best estimates of the potential 

relationship between mass reduction and fatality increases in the future fleet. This 

section discusses how the agencies used NHTSA’s 2011 analysis to calculate specific 

estimates of safety effects of the proposed standards, based on the analysis of how much 

mass reduction manufacturers might use to meet the proposed standards. 

Neither the proposed CAFE/GHG standards nor the agencies’ analysis mandates 

mass reduction, or mandates that mass reduction occur in any specific manner. However, 

mass reduction is one of the technology applications available to the manufacturers and a 

degree of mass reduction is used by both agencies’ models to determine the capabilities 

of manufacturers and to predict both cost and fuel consumption/emissions impacts of 

improved CAFE/GHG standards. We note that the amount of mass reduction selected for 

this rulemaking is based on our assumptions about how much is technologically feasible

without compromising safety. While we are confident that manufacturers will build safe 

vehicles, we cannot predict with certainty that they will choose to reduce mass in exactly 

the ways that the agencies have analyzed in response to the standards. In the event that 

manufacturers ultimately choose to reduce mass and/or footprint in ways not analyzed or 

Deleted: for

Deleted: intelligent

Comment [DOE7]: We recommend avoiding 

the term “intelligent design”! 

Comment [DOE8]: We recommend deleting 

this paragraph. We think your point is that 

NHTSA should do everything in its power to 

adopt cost-effective safety regulations, 

regardless of the anticipated effect of the fuel 

economy/GHG regulations on safety. 

Deleted: Kahane of 

Deleted: our

Deleted: the 

Deleted: amounts in the agencies’ analysis

Deleted: were chosen

Deleted: both

Deleted: , and to find a way by which 

manufacturers could comply with the standards 

in a

Deleted: -neutral manner
anticipated by the agencies, the safety effects of the rulemaking may likely differ from 

the agencies’ estimates. 

NHTSA utilized the 2011 Kahane study relationships between weight and safety, 

expressed as percent changes in fatalities per 100-pound weight reduction while holding 

footprint constant. However, as mentioned previously, there are several identifiable 

safety trends already occurring, or expected to occur in the foreseeable future, that are not 

accounted for in the study. For example, the two important new safety standards that 

were discussed above for electronic stability control and head curtain airbags, have 

already been issued and began phasing in after MY 2008. The recent shifts in market 

shares from pickups and SUVs to cars and CUVs may continue, or accelerate, if gasoline 

prices remain high, or rise further. The growth in vehicle miles travelled may continue to 

stagnate if the economy does not improve, or gasoline prices remain high. And

improvements in driver (and passenger) behavior, such as higher safety belt use rates, 

may continue. All of these will tend to reduce the absolute number of fatalities in the 

future. The agency estimated the overall change in fatalities by calendar year after 

adjusting for ESC, Side Impact Protection, and other Federal safety standards and 

behavioral changes projected through this time period. The smaller percent changes in 

risk from mass reduction (from the 2011 NHTSA analysis), coupled with the reduced 

number of baseline fatalities, results in smaller absolute increases in fatalities than those 

predicted in the 2010 rulemaking. 

NHTSA examined the impacts of identifiable safety trends over the lifetime of the 

vehicles produced in each model year. An estimate of these impacts was contained in a 

previous agency report.27 The impacts were estimated on a year-by-year basis, but could 

be examined in a combined fashion. Using this method, we estimate a 12.6 percent 

reduction in fatality levels between 2007 and 2020 for the combination of safety 

standards and behavioral changes anticipated (ESC, head-curtain air bags, and increased

belt use). Since the same safety standards are taking effect in the same years, the 

estimates derived from applying NHTSA fatality percentages to a baseline of 2007 

fatalities were thus multiplied by 0.874 to account for changes that NHTSA believes will 

take place in passenger car and light truck safety between the 2007 baseline on-road fleet 

used for this particular safety analysis and year 2025. 

 

ls technologies, JOM Journal of the Minerals, Metals and Materials Society, Volume 59, Number 10, 21-

32. Available at http://msl.mit.edu/pubs/docs/Field_KirchainCM_StratEvalMatls.pdf (last accessed Aug. 

22, 2011). 

27 Countermeasures could potentially involve improved front end structure, knee bags, seat ramps, buckle

pretensioners, and others. 

27 Blincoe, L. and Shankar, U, “The Impact of Safety Standards and Behavioral Trends on Motor Vehicle 

Fatality Rates,” DOT HS 810 777, January 2007. See Table 4 comparing 2020 to 2007 (37,906/43,363 = 

12.6% reduction (1-.126 = .874). Since 2008 was a recession year, it does not seem appropriate to use that 

as a baseline. We believe this same ratio should hold for this analysis which should compare 2025 to 2008. 

Thus, we are inclined to continue to use the same ratio. 

Deleted: percentage increases

Comment [DOE9]: The 2011 NHTSA study 

finds that mass reduction in heaver LTVs and 

CUVs/minivans will reduce fatalities. 

Deleted: , and examined the weight effects 

assumed in this rulemaking analysis.

Deleted: in place

Deleted: will be

Deleted: Additionally, we anticipate 

continued

Deleted: .

Deleted: calculated

Deleted: Thus, while

Deleted: percentage increases in 

Deleted: (2011) were applied,

Deleted: base has resulted

Deleted: that were 

Deleted: report

Deleted: NHTSA assumed that the safety 

trends will result in a reduction in the target 

population of fatalities from which the weight 

impacts are derived. Using this method, we 

found

Deleted: increase

Deleted: ration
After applying these percentage increases to the estimated weight reductions per 

vehicle size by model year assumed in the Volpe model, Table Error! No text of 

specified style in document.-4 shows the results of NHTSA’s safety analysis separately 

for each model year.28 These are estimated increases or decreases in fatalities over the 

lifetime of the model year fleet. A positive number means that fatalities are projected to 

increase, a negative number (indicated by parentheses) means that fatalities are projected 

to decrease. The results are significantly affected by the assumptions put into the Volpe 

model to take more weight out of the heavy LTVs, CUVs, and minivans than out of other 

vehicles. As the negative coefficients only appear for LTVs greater than 4,594 lbs., 

CUVs, and minivans, a statistically improvement in safety can only occur if more 

weight is taken out of these vehicles than passenger cars or smaller light trucks. 

Combining passenger car and light truck safety estimates for the proposed standards 

results in an increase in fatalities over the lifetime of the nine model years of MY 2017-

2025 of 76 fatalities, broken up into an increase of 193 fatalities in passenger cars and 

117 decrease in fatalities in light trucks. NHTSA also analyzed the results for different 

regulatory alternatives in Chapter IX of its PRIA; the difference in the results by 

alternative depends upon how much weight reduction is used in that alternative and the 

types and sizes of vehicles that the weight reduction applies to. 

Table Error! No text of specified style in document.-4 NHTSA Calculated 

Mass-Safety-Related Fatality Impacts of the Proposed Standards over the Lifetime 

of the Vehicles Produced in each Model Year 

MY 

2017

MY 

2018

MY 

2019

MY 

2020

MY 

2021

MY 

2022

MY 

2023

MY 

2024

MY 

2025 Total

Passenger 

cars 

6 11 29 27 26 25 25 21 22 193

Light 

trucks (5) (14) 2 (23) (17) (22) (18) (13) (7) (117)

Total 1 (3) 31 (4) 9 3 7 8 15 76

Using the same coefficients from the 2011 Kahane study, EPA used the OMEGA 

model to conduct a similar analysis. After applying these percentage increases to the 

estimated weight reductions per vehicle size by model year assumed in the Omega model, 

Table Error! No text of specified style in document.-5 shows the results of EPA’s 

safety analysis separately for each model year. These are estimated increases or 

 

28 NHTSA has changed the definitions of a passenger car and light truck for fuel economy purposes 

between the time of the Kahane 2003 analysis and this final rule. About 1.4 million 2 wheel drive SUVs 

have been redefined as passenger cars instead of light trucks. The Kahane 2011 analysis continues with the 

definitions used in the Kahane 2003 analysis. Thus, there are different definitions between Tables IX-1 and 

IX-2 (which use the old definitions) and Table IX-3 (which uses the new definitions). 

Deleted: Table II-15

Deleted: Table Error! No text of specified 

style in document.-4

Deleted: 

Deleted: 15

Deleted: 4

Formatted Table

Deleted: Table II-16

Deleted: Table Error! No text of specified 

style in document.-5
decreases in fatalities over the lifetime of the model year fleet. A positive number means 

that fatalities are projected to increase; a negative number means that fatalities are 

projected to decrease. For details, see the EPA RIA Chapter 3. 

Table Error! No text of specified style in document.-5 EPA Calculated MassSafety-Related Fatality Impacts of the Proposed Standards over the Lifetime of the 

Vehicles Produced in each Model Year 

MY 

2017

MY 

2018

MY 

2019

MY 

2020

MY 

2021

MY 

2022

MY 

2023

MY 

2024

MY 

2025 Total

Passenger 

cars 

-3 -6 -9 -12 -16 7 31 56 83 131

Light 

trucks 0 -1 -1 -2 -3 -34 -66 -98 -131 -336

Total -3 -7 -10 -14 -18 -27 -35 -42 -48 -204

b. Why might the real-world effects be less than or greater than what the 

agencies have calculated? 

As discussed above the ways in which future technological advances could 

potentially mitigate the safety effects estimated for this rulemaking: lightweight vehicles 

could be designed to be both stronger and less aggressive; restraint systems could be 

improved to deal with higher crash pulses in lighter vehicles; crash avoidance 

technologies could reduce the number of overall crashes; roofs could be strengthened to 

improve safety in rollovers. As also stated above, however, while we are confident that 

manufacturers will strive to build safe vehicles, it will be difficult for both the agencies 

and the industry to know with certainty ahead of time how crash trends will change in the 

future fleet as lightweight vehicles become more prevalent. We will have to continue to 

monitor the crash data going forward. 

Additionally, we note that the total amount of mass reduction used in the 

agencies’ analysis for this rulemaking were chosen based on our assumptions about how 

much is technologically feasible without compromising safety. Again, while we are 

confident that manufacturers are motivated to build safe vehicles, we cannot predict with 

certainty that they will choose to reduce mass in exactly the ways that the agencies have 

analyzed in response to the standards. In the event that manufacturers ultimately choose 

to reduce mass and/or footprint in ways not analyzed by the agencies, the safety effects of 

the rulemaking may likely differ from the agencies’ estimates. 

Deleted: 16

Deleted: 5

Formatted Table

Deleted: 

Deleted: not more

Deleted: .

Deleted: lightweighted

Deleted: amounts

Deleted: both 

Deleted: , and to find a way by which 

manufacturers could comply with the standards 

in a

Deleted: -neutral manner.

Deleted: will
c. Do the agencies plan to make any changes in these estimates for the final 

rule? 

As discussed above, the agencies have based our estimates of safety effects due to 

the proposed standards on Kahane’s 2011 report. That report is currently undergoing 

peer review and is docketed for public review;29 the peer review comments and response 

to peer review comments, along with any revisions to the report in response to that 

review, will also be docketed there. Depending on the results of the peer review, our 

calculation of safety effects for the final rule will also be revised accordingly. The 

agencies will also consider any comments received on the proposed rule, and determine 

at that time whether and how our estimates should be changed in response to those 

comments. Additional studies published by the agencies or other independent researchers 

as previously discussed will also be considered, along with any other relevant 

information. 

 

29 Kahane, C. J. (2011). “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2000-

2007 Passenger Cars and LTVs,”, July 2011. The report is available in the NHTSA docket, NHTSA-2010-

0152. You can access the docket at http://www.regulations.gov/#!home by typing ‘NHTSA-2010-0152’ 

where it says “enter keyword or ID” and then clicking on “Search.”

Deleted: to