### Subject: DOE's interagency comments on EPA/DOT CAFE/GHG emi ssions 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 interagenc y 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 NP RM for MY 2017-2025



### Tom – Per your request, here are the comments provi ded to OMB. Thank you,

Betsy

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

DOE Comments on II G Safety Considerations in Estab lishing 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 sta rt at a multiplier value of 1.6 in MY 2017 and phas e down to a value of 1.3 in MY 2021. 1 

### The multiplier would be 1.0 for MYs 2022-2025.” Th e multipliers appear to be related to the hybridization degree of the powertrain (I.e., BEVs have a higher multiplie r than PHEVs). If so, perhaps the multiplier should b e proportional to the hybridization degree. This wo uld allow differentiating PHEVs with different EV range s. 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 tr ucks would be eligible for a per vehicle credit of 10 g/mi 2 

### 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 o f 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 dedic ated 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 th is conclusion was reached.
Page 112 – “ Shift optimization is a strategy whereby the engine and/or transmissi on controller(s) emulates a CVT by continuously evaluating all possi ble 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 d rive 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 benefi ts 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 sub stitution, design optimization, part consolidation, improving manufac turing process, etc. The agencies applied mass reduction of up to 20 percent relative to MY 2008 l evels 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 th e glider?
Page 182 – The table list the incentives for EV/PHE V/FCV multipliers in the same column. This is diffe rent than the statement on page 39 that mentions that EV s and FCVs start with 2 and PHEVs with 1.6 in 2017. The same values are also in Table III-14 on page 26 3
Page 271 - We find the CNG vehicle utility factor d iscussion for dual fuel CNG is confusing in the sec ond paragraph this page of the preamble. More explanat ion 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 h ave 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 cu rrent technology costs with the values in 2025 alon g with a percentage improvement per year to reach the se 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 analysi s of this section? These technologies are being consi dered in large production by the auto manufacturers

. Page 407, Table III-66: The “Total” effect on vehic le electrification of the proposed standards is ver y 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 wor k was expanded to include an 8-speed DCT, a power-split hybrid, which was used to determine a P 2 hybrid cost, and a mild hybrid with stop-start technology”. Additional explanation of how the po wer-split hybrid cost was used to determine the P2 hybrid cost, as the cost of power split and P2 hybr id are different, would be beneficial.
Page 570 – “NHTSA notes that, in developing technol ogy 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, d rivability, durability, noise, vibration and harshn ess (NVH) and towing and hauling capacity. More discus sion on the criteria used for durability, noise, vibration, and harshness would be useful.
Page 576 – The Volpe model begins with an initial s tate of the domestic vehicle market, which in this case is the market for passenger cars and light tru cks 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, suc h 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 veh icles at the vehicle platform level, which are binn ed into 5 year timeframes instead of year-by-year. I t would be beneficial for the agencies to describe the necessity to use two separate tools and provide fur ther explanations about how the difference in the tool methodologies and assumptions influence the ov erall results.
Page 585 – “In past rulemaking analyses, as noted a bove, both agencies have used a learning curve algorithm that applied a learning factor of 20 perc ent for each doubling of production volume. NHTSA has used this approach in analyses supporting recen t CAFE rules. In its analyses, EPA has simplified the approach by using an “every two years” based learni ng progression rather than a pure production volume progression (i.e., after two years of produc tion 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 on ly has been formally peer-reviewed and tested and reviewed through three rulemakings, but also ha s 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 engineerin g differences between specific vehicle models.“ Mo re

### information elaborating about the impact of these f eatures and how it would affect their results if th ey

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 differenc es between vehicle models and avoid unlikely technology combinations.” Additional text elaborat ing on the impact of addressing technologies individually vs. packages would be useful.
Page 621 – “The model calculates the cost of this e lectricity, 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 g eneration around the U.S., and the resulting differ ences 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 requir ed (1% SHEV1_2 by 2025) when EPA states that as much as 15% would be necessary (Table III-23 page 3 14)?
Page 5-71: It is highly unlikely that the g/mi val ues shown for automobiles for start-stop technology and solar roofs would be so close (2.9 vs. 3.0, respect ively). We believe that the value of start-stop ha s got to be much larger compared to solar since it is not dependent on the climate (sunny in Dallas vs. rain y in Seattle vs. snowy in Vermont) or time of day (dayli ght vs. night). The same argument applies to solar control. Is it possible that someone is off by a d ecimal 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 impa cts should also be considered on a global scale. A s 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 oi l producers, and for that stated reason are not counted in the EPA’s cost-benefit analysis. This d ecision is mistaken because it insures that one or the other problem cannot be efficiently solved.
Monopsony benefits arise from the fact that when th e 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 reducti on 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 aris e 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-monops ony issue is essentially an adversarial zero-sum problem. If oil producers can collect monopoly pro fits they come out ahead but oil consumers lose; if oil consumers can reclaim some of the monopoly profit v ia use of monopsony power, they benefit but oil producers lose. In this case, the EPA is arguing t hat 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. Inevitab ly, following this line of reasoning will lead to t oo little investment in solving the nation’s energy security problem.
On the other hand, GHG mitigation for climate prote ction is a genuine global concern. The costs of GH G emissions and the benefits of mitigation accrue thr oughout the globe. This is an entirely different

### problem, a problem of the tragedy of the global com mons 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 le ad to too little investment in solving the problem of global climate change.
The flaw in this logic is to assume that the two di fferent problems must have the same cost-benefit accounting rules, regardless of the nature of the p roblems. In fact, applying a consistent set of cos tbenefit rules to both problems inevitably guarantee s that one or the other problem cannot be efficient ly solved. The EPA should recognize that energy secur ity is a problem of national interest while protect ing 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 be nefits to the entire world. Only this approach can solve both problems efficiently.
**Inconsistency in Valuation of Global Costs and Bene fits of CO**  **2** 

### Energy Security
Another issue is that when EPA calculates the energ y 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 CO 2 

### and energy security on a global basis the energy security benefit should be calculated on a global b asis. However, if EPA includes both the monopsony premium and the global GHG benefits in its rulemaki ng estimates, this current calculation of the disruption component is consistent and need not be changed.
**DOE’s Comments on the EPA Regulation Impact Analysi s Document Section 8** 
In calculating the vehicle sales impacts starting o n page 8-1 EPA used real discounts of 3 and 7 perce nt per OMB Circular A-4. However, annual payments der ived from the loan rates were calculated using a nominal (current) interest rate, resulting in nomin al (current dollars). These payments should be in real dollars to be consistent with the OMB discount rate s. This could be done using the All Urban Consumer Price Index found in AEO 2011. Section 8-3 should b e 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 (inflat ion-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 intere st rates. Insurance rates should probably go up in nominal dollars to reflect a constant (real) ins urance 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 als o change, as will Table 8.2-6 (pg. 8-32).
Pg 8-4 paragraph 1. Does the vehicle demand elastic ity literature address using total operating cost rather than the initial cost of the vehicle? Addit ional text describing the literature on vehicle dem and 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 ca lculation 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 a mount 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 per cent discount rate, the increase is -4.0 percent.”
Since both the purchaser and the lender are private parties, barring additional information they shoul d discount costs and benefits at the same rate. In th e 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 correcte d 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 paym ent. 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 retur n, lenders are lending at 5.5 percent but should re quire 7 percent. The -4 percent reduction in discounted p ayments 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 an alysis. Incorporation of a separate auto loan rate just reflects calculation of an arbitrary financial inco nsistency between the current loan rate and the assumed discount rates presented in the OMB guidanc e. 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 Stan dards

1. Why do the agencies consider safety?

The primary goals of the proposed CAFE and GHG stan dards are to reduce fuel consumption and GHG emissions from the on-road ligh t-duty vehicle fleet, but in addition to these intended effects, the agencies al so 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 C AFE 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 NHTS A CAFE standards were attribute-based), and the agenc ies must be mindful of the possibility of future ones. These past safety trad e-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 small er and lighter vehicles did not fare as well in crashes as larger and heavier vehicles. Hi storically, 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 respons e 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 CO 2 emissions in order to meet the proposed standards, and the agencies ha ve incorporated this expectation into our modeling analysis supporting the proposed stand ards. 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 red uction is discussed below.

1 In this rulemaking document, “vehicle safety” is d efined as societal fatality rates per vehicle miles traveled (VMT), which include fatalities to occupants of all the v ehicles involved in the collisions, plus any pedestrians. 2 This practice is recognized approvingly in case la w. As the United States Court of Appeals for the D .C. Circuit stated in upholding NHTSA’s exercise of jud gment in setting the 1987-1989 passenger car standards, “NHTSA has always examined the safety co nsequences of the CAFE standards in its overall consideration of relevant factors since its earlies t 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. C ir. 1981).(EPA may consider safety in developing standards under section 202 (a) and did so appropri ately 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 featuresManufacturers 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 ef fects on safety is the application of footprint-based standards, which create a disincent ive for manufacturers to produce smaller-footprint vehicles. See section II. C.1, a bove. This is because, as footprint decreases, the corresponding fuel economy/GHG emiss ion target becomes more stringent. We also believe that the shape of the f ootprint curves themselves is approximately “footprint-neutral,” that is, that it should neither encourage manufacturers to increase the footprint of their fleets, nor to d ecrease it. Upsizing footprint is also discouraged through the curve “cut-off” at larger f ootprints. 4 However, the footprintbased standards do not discourage downsizing the po rtions 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. Additional ly, 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 th e 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 t he target curves and the incentives they provide generally will not encourage down-sizi ng (or up-sizing) in terms of footprint reductions (or increases). 5

Given that we expect manufacturers to reduce vehicl e mass in response to the proposed standards, and do not expect manufacturers to reduce vehicle footprint in response to the proposed standards, the agencies mu st 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 th e curve, manufacturers who make small cars and truc ks below 41 square feet (the small footprint cut-off p oint) have some incentive to downsize their vehicle s to make it easier to meet the constant target. That c ut-off may also create some incentive for manufactu rers who do not currently offer models that size to do s o in the future. However, at the same time, the ag encies believe that there is a limit to the market for car s and trucks smaller than 41 square feet: most con sumers likely have some minimum expectation about interior volume, for example, among other things. Additionally, vehicles in this segment are the lowe st price point for the light-duty automotive market , with several models in the $10,000-$15,000 range. Manuf acturers who find themselves incentivized by the cu toff 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 th e 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 Jo int 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 sa fety 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 concer ns from what the industry has previously faced. The principal difference between the heavier vehicles, especially truckbased LTVs, and the lighter vehicles, especially pa ssenger cars, is that mass reduction has a different effect in collisions with another car o r LTV. When two vehicles of unequal mass collide, the change in velocity (delta V) is h igher in the lighter vehicle, similar to the mass ratio proportion. As a result of the hig her change in velocity, the fatality risk may also increase. Removing more mass from the hea vier 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 lig hter, 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 occup ants 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 ve hicle stiffness may help mitigate the effects of increased vehicle stiffness. Another fa ctor 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 an d GHG standards. The agencies seek to ensure that the standards are designed to encour age manufacturers to pursue a path toward compliance that is both cost-effective and s afe.
To estimate the possible safety effects of the MY 2 017-2025 standards, then, the agencies have undertaken research that approaches t his 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 da ta available, and is considered as the agencies’ best estimate of potential mass-safety ef fects. The agencies recognize that negative safety effects estimated based on the hist orical 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 potentiallyfleet. Second, we are using an engineering approa ch to investigate what amount of mass

reduction is affordable and feasible while maintain ing vehicle safety and other major functionalities such as NVH and acceleration perfor mance. Third, we are also studying the new challenges these lighter vehicles might bri ng to vehicle safety and potential countermeasures available to manage those challenge s effectively.
The sections below discuss more specifically the st ate of the research on the mass-safety relationship, and how the agencies inte grate 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 statis tical 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 fo r many years, and continue to refine their techniques over time. In the MY 2012-2016 fi nal rule, the agencies stated that we would conduct further study and research into the i nteraction of mass, size and safety to assist future rulemakings, and start to work collab oratively 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 possib le, 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 t o direct research in preparation for future CAFE/GHG rulemaking in regards to statis tical analysis of historical data.
First, NHTSA would contract with an independent ins titution to review the statistical methods that NHTSA and DRI have used to analyze historical data related to mass, size and safety, and to provide recommendatio n 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 mult icollinearity in the historical data and how best to address it in a regression analysis. T he 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 A dministration). 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 k eyword or ID” and then clicking on “Search.”Second, NHTSA and EPA, in consultation with DOE, wo uld 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 databa se that could be made publicly available to help address concerns that differences in data were leading to different results in statistical analyses by different resear chers.
And third, in order to assess if the design of rece nt model year vehicles that incorporate various mass reduction methods affect t he relationships among vehicle mass, size and safety, the agencies sought to identify ve hicles 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 relation ship 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 s ince 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 Tr ansportation 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 Charle s 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 d iscussed below. Some commenters in recent CAFE rulemakings, including some vehicle man ufacturers, suggested that the designs and materials of more recent model year veh icles 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 mat erials, 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 databa se used in prior NHTSA analyses which was based on model years 1991–1999 vehicles i n 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 p ublic, 7 enabling other researchers to analyze the same data and hopefully minimizing d iscrepancies in the results that would

7 The new databases are available at http://www.nhts a.gov/fuel-economy (look for “Download Crash Databases for Statistical Analysis of Relationships Between Vehicles’ Fatality Risk, Mass, and Footpri nt.” 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: possibilityhave been due to inconsistencies across databases. 8 The agencies recognize, however,

that the updated database may not represent the fut ure fleet, because vehicles have continued and will continue to change.
The agencies are aware that several studies have be en initiated using NHTSA’s 2011 newly established safety database. In additio n 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 Inte rnational Council on Clean Transportation (ICCT). These studies may take some what different approaches to examine the statistical relationship between fatali ty 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 as sessments will be available prior to the final rule. DRI has also indicated that it exp ects 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 mo nths and as comments to the rulemaking that may also inform our consideration o f these issues for the final rule. Kahane’s updated study for 2011 is currently underg oing peer-review, and is available in the docket for this rulemaking for review by commen ters.
Finally , EPA and NHTSA with DOT’s Volpe Center, part of th e Research and Innovative Technology Administration (RITA), attemp ted to investigate the implications of “Smart Design,” by identifying and describing th e types of “Smart Design” and methods for using “Smart Design” to result in vehic le 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 avail able data for specific crash scenarios was insufficient to produce consistent results that cou ld be used to support conclusions regarding historical performance of “smart designs. ”

8 75 Fed. Reg. 25324 (May 7, 2010); the discussion o f planned statistical analyses is on pp. 25395-2539 6. 9 –Wenzel, T.P. (2011b). Assessment of NHTSA’s Report “Relationships between Fatality Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars an d LTVs” , available at... Deleted: by

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Deleted: 9 Need reference to LBNL study - EPAUndertaking these tasks has helped the agencies com e closer to resolving some of

the ongoing debates in statistical analysis researc h of historical crash data. We intend to apply these conclusions going forward, and we belie ve that the public discussion of the issues will be facilitated by the research conducte d. The following sections discuss the findings from these studies and others in greater d etail, 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 ma ss 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 ag encies with a broad understanding of current research in the fiel d and provide stakeholders and the public with an opportunity to weigh in on this issu e. 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. (DR I), Jeya Padmanaban of JP Research, Inc., Adrian Lund o f the Insurance Institute for Highway Safety, Paul Green of the University of Mic higan Transportation Research Institute (UMTRI), Stephen Summers of NHTSA, Gregg Peterson of Lotus Engineering, Koichi Kamiji of Honda, John German of the Internat ional Council on Clean Transportation (ICCT), Scott Schmidt of the Allianc e of Automobile Manufacturers, Guy Nusholtz of Chrysler, and Frank Field of the Massac husetts Institute of Technology.
The wide participation of the workshop allowed the agencies to hear from a broad range of experts and stakeholders. The contributio ns were particularly relevant to the agencies’ analysis of the effects of weight reducti on for this proposed rule. The presentations were divided into two sessions that a ddressed the two expansive sets of issues – statistical evidence of the roles of mass and size on safety, and engineering realities – structural crashworthiness, occupant in jury and advanced vehicle design.
The first session focused on previous and ongoing s tatistical studies of crash data that attempt to identify the relative effects of ve hicle mass and size on fleet safety. There was consensus that there is a complicated relations hip with many confounding influences in the data. Wenzel summarized a recent study he conducted compa ring four types of risk (fatality or casualty risk, per vehicle regist ration-years or per crash) using police-

10 A video recording, transcript, and the presentati ons 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
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Deleted: Wenzel identified qualitatively similar trends in resultsreported 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 (fatalit y or casualty) or what exposure metric was used (e.g., registration y ears, 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 driv ers of other vehicles, in order to account for societal risk, mutes the trend of decreasing ri sk with increasing vehicle size or weight, and in the case of fatality risk for pickups revers es the trend (with fatality risk increasing as pickup size and weight increases). However, ther e were some differences in the various risks analyzed for certain vehicle types.
Although Wenzel’s analysis was focused on differenc es 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 g ender, crash location (urban vs. rural), and the state in which the crash occurred (to accou nt 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 vehic le group (e.g., sports cars, two-door cars, early crossover SUVs) were outliers that conf ound the trend or unique datasets that isolate specific vehicle characteristics. Unfortuna tely, specialty vehicle groups are usually adopted by specific driver groups, often with outly ing 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 great er 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 large st and heaviest vehicles but predicted

“ the sky will not fall ” as the fleet downsizes, we will not see an increas e in absolute injury risk because smaller cars will become increa singly protective of their occupants. Padmanaban also noted in her research of the histor ical trends that mass ratio and vehicle stiffness are significant predictors with mass rati o consistently the dominant parameter when correlating harm. Reducing the mass of any ve hicle 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 S tates , March 2011, LBNL-4897E, available at: http://eetd.lbl.gov/EA/teepa/pub.html#Vehicle Deleted: showed
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.

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Deleted: societal effects as it increases the injury risk in the lightened vehicle and decreases them in the partner vehicle.in the fatality risk to occupants of any lighter ve hicles it might strike in a crash However,

the net effect would likely be a benefit in terms o f 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 multicollineari ty) 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., con ducting multiple analyses for data subsets with similar footprint values) may be the m ost 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 vehicl es should have improved handling and braking characteristics and “may be more likely to avoid collisions”. Lund presented crash involvement data that implied that, among veh icles 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 f uture as new technologies will be used that were not available when the data were collecte d. The advances in technology through the decades have dramatically improved safety for a ll weight and size classes. A video of IIHS’s 50 th anniversary crash test of a 1959 Chevrolet Bel Air and 2009 Chevrolet Malibu graphically demonstrated that stark differen ces in design and technology that can possibly mask the discrete mass effects, while vide os 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 report 12 that found that a scenario which took some mass out of heavier vehicles but little o r no mass out of the lightest vehicles did not impact safety in absolute terms. Kahane no ted 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 co nsistency with other presentations (e.g., Padmanaban, Nusholtz) that reducing the overall ran ges of masses and mass ratios seems to reduce overall societal harm. That is, the effec t of mass reduction exclusively does not appear to be a “zero sum game” in which any increas e 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 red uced by a larger percentage, the changes in velocity from the collision are more nearly equa l and the injuries suffered in the lighter Deleted: is highly
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increased. Alternatively, a fixed mass reduction ( say, 100 lbs) in all vehicles could increase societal harm whereas a fixed percentage m ass 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 t han 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 incr ease in fatalities in truck-to-car crashes while removing the same amount from light t rucks would cause an overall decrease in fatalities.

c. Report by Green et al., UMTRI – “Independent Review : Statistical Analyses of Relationship Between Vehicle Curb Weigh t, Track Width, Wheelbase and Fatality Rates,” April 2011.

As explained above, NHTSA contracted with the Unive rsity of Michigan Transportation Research Institute (UMTRI) to conduc t an independent review 13 of a set of statistical analyses of relationships between ve hicle curb weight, the footprint variables (track width, wheelbase) and fatality rates from ve hicle crashes. The purpose of this review was to examine analysis methods, data source s, and assumptions of the statistical studies, with the objective of identifying the reas ons 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 manus cripts provided by NHTSA (listed in Appendix A of UMTRI’s report, whic h is available in the docket to this rulemaking) that examined the statistical relationships between fat ality or casualty rates and vehicle properties such as curb weight, t rack width, wheelbase and other variables.
It is difficult to summarize a study of that lengt h and complexity for purposes of this discussion, but fundamentally, the UMTRI te am concluded the following:

• Differences in data may have complicated comparison s of earlier analyses, but if the methodology is robust, and the methods were app lied 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 orchanges in data should not lead to different conclu sions. The main conclusions and findings should be reproducible. The data base created by Kahane appears to be an impressive collection of files from appropria te sources and the best ones available for answering the research questions cons idered in this study.

• In statistical analysis simpler models lead to impr oved inference, assuming the data and model assumptions are appropriate . In that regard, the disaggregate logistic regression model used by NHTSA in the 2003 report 14 seems to be the most appropriate model, and valid for the analysis in th e context that it was used : finding general associations between fatality risk and mass reduction

.
• The two-stage logistic regression model in combinat ion 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 coe fficients from two separate models to arrive at conclusions about the effects o f 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 h istorical correlation between curb weight, wheelbase, and track width. Including three variables that are correlated in the same model can have adverse effec ts 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 multicollinearit y 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 vehi cle mass and footprint. Kahane has combined wheelbase and track width int o one variable (footprint) to compare with curb weight. NHTSA believes that the 2011 Kahane analysis has done all it can to lessen concerns abo ut 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 relationsh ips between risk, weight, and size. However, least squares linear re gression models, without modification, are not exposure-based risk m odels 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 difficult ies associated with separating out the contributions of weight and size variables when analyzing fatality risk properly recognized the pro blem arising from multicollinearity and included a clear explanation of why fatality risk is expected to increase with increasing mass ratio. U MTRI concluded that the increases in fatality risk associated with a 100-pound reduction in Deleted: general, for
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, are broadly more convincing than the 6.7 percent r eduction in fatality risk associated with mass reduction whi le 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 f atality risk, and finding that changing the mean mass of the vehicle populati on (leaving variability unchanged) has a stronger influence on fatality ris k than corresponding (feasible) changes in mean vehicle dimensions, conc luded unequivocally that reducing vehicle mass while maintaining consta nt vehicle dimensions will increase fatality risk. UMTRI concluded that if one accepts the methodology, this conclusion is robust against real istic 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 in cluded passenger cars, vans, and SUVs in the same model. UMTRI concluded t hat some of the claims in the commentary paper appear to be oversta ted, and intermediate results and more documentation would help the reade r determine if these claims are valid. The second paper focused largely on the effects of electronic stability control (ESC), but generally f ollowed on from the first paper except that curb weight is not fit and fuel e conomy is used as a surrogate.

The UMTRI study provided a number of useful suggest ions 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 – “Relationship s Between Fatality Risk, Mass, and Footprint in Model Year 2000-2007 P assenger Cars and LTVs,” 2011

The relationship between a vehicle’s mass, size, an d fatality risk is complex, and it varies in different types of crashes. NHTSA, al ong with others, has been examining this relationship for over a decade. The safety ch apter 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 LT Vs (light trucks and vans), based on calendar year (CY) 1995-2000 crash and vehicle-r egistration data. 15 The 2010

15 Kahane, C. J. (2010). “Relationships Between Fatal ity 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 Ligh t Trucks . Washington, DC: National Highway Deleted: vehicle

Deleted: of fatalities

Deleted:

, Deleted: paperanalysis used the same data as the 2003 analysis, b ut 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 heavie r 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 exte nt, in the heavier LTVs and limited in the lighter cars – would likely be approximately sa fety-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 bot h found a significant protective effect for footprint
, and that reducing mass and footprint together (downsizing) on smaller vehicles was harmful. DRI’s analyses estim ated 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 t he initial DRI and NHTSA results. 16

Immediately after issuing the final rule for MYs 20 12-2016 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 sta tistical analysis of the relationships between fatality rates, mass and foot print, updating the crash and exposure databases to the latest available model years, refi ning the methodology in response to

Traffic Safety Administration, pp. 464-542, availab le at http://www.nhtsa.gov/staticfiles/rulemaking/pdf/caf e/CAFE_2012-2016_FRIA_04012010.pdf

. 16 Van Auken, R. M., and Zellner, J. W. (2003). A Further Assessment of the Effects of Vehicle Weig ht 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 Rese arch, 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 Lig ht Trucks and Vans . Paper No. 2005-01-1354. Warrendale, PA: Society of Automotive Engineers; Va n 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 Mod el 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 Deleted: and conclusions
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The previous databases of MY 1991-1999 vehicles in CY 1995-2000 crashes has become outdated as new safety technologies, vehicle design s and materials were introduced. The new databases comprising MY 2000-2007 vehicles in C Y 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 meaningf ul analyses. NHTSA has made the new databases available to the public 17 , 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 th e 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 Report 19 analyzes MY 2000-2007 cars and LTVs in CY 2002-200 8 crashes. Fatality rates were derived from FARS dat a, 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 (CU V), which are SUVs of unibody construction, often but not always built upon a pla tform 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, beca use 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 c omplex 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 de veloped 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 o f planned statistical analyses is on pp. 25395-2539 6. 19 Kahane, C. J. (2011). “Relationships Between Fatal ity Risk, Mass, and Footprint in Model Year 2000- 2007 Passenger Cars and LTVs,”, July 2011. The rep ort 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 clicki ng 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.
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, Deleted: , in separate
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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 a nnual fatality distribution baseline 21 was not decreased in the period between 2017 and 2025 f or the safety statistics analysis, but is taken into account later in the Volpe model analysi s, since all vehicles in the future will be equipped with ESC 22

. For the 2011 report, vehicles are now grouped into five classes rather than four: passenger cars (including both 2-door and 4-door ca rs) 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.

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- 1 Results of 2011 NHTSA report Fatality Increase (%) per 100-Pound Mass Red uction 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 redu ction in CUVs, minivans, and the heavier truck-based LTVs. Based on these results, potential combinations of mass reductions that maintain footprint and are proporti onately somewhat higher for the

21 MY 2004 -2007 vehicles with fatal crashes occurred in CY 2004-2008 are selected as the annual fatalit y 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 b ehavior changes anticipated. Deleted: percent Deleted: has been reduced
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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 c ars increased by 5 percent from 2000 to 2007 and the average mass of pickup trucks incre ased by 19 percent. Other types of vehicles became heavier, on the average, by interme diate 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 hea vier 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 NHT SA’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:

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- 2 2010 Report: MY 1991- 1999, CY 1995-2000 Fatality Increase (%) per 100-Po und 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

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- 3 Fatality Increase (%) per 100-Pound Mass Reduction While Holding Footprin t 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
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Formatted Table

Deleted: 14
Deleted: 3The new results are directionally the same as in 20 10: fatality increase in the

lighter cars, safety benefit in the heavier LTVs, b ut the effects may have become weaker at both ends. (The agencies do not consider this c onclusion to be definitive because of the relatively wide confidence bounds of the estima tes.) 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 m ade some good drivers more willing to buy them. Both agencies believe that at the oth er end of the weight/size spectrum, blocker beams and other voluntary compatibility imp rovements 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 miniv ans as a separate class of vehicles may have relieved some inaccuracies in the 2010 reg ression results for LTVs. Interestingly, the new actual-regression results ar e 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 tren d toward higher crash rates in smaller and lighter cars.
The principal difference between the heavier vehicl es, especially truck-based LTVs, and the lighter vehicles, especially passenge r 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 vehicl e, where fatality risk is high, resulting in a large benefit, offset by a small penalty becau se 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 pe nalty offset by a small benefit – adding up to net harm. These considerations drive the ove rall result: fatality increase in the lighter cars, reduction in the heavier LTVs, and li ttle effect in the intermediate groups. However, in some types of crashes, especially 1 st -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 steeri ng and are often more stable because their center of gravity is lower. Offsetting that benefit is the continuing historical Deleted: “real” factors (
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Deleted: that do not involve collisions between cars and LTVstendency of lighter and smaller vehicles to be driv en less well – although it continues to

be unknown why that is so, and to what extent, if a ny, the lightness or smallness of the vehicle contributes to people driving it less safel y.

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, becau se 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 t he 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 env ironment, the model may become somewhat less accurate and it is difficult t o assess the sensitivity to additional mass reduction greater than 100 pounds. The agenci es recognize that the light

- duty vehicle fleet in the 2017-2025 timeframe will be di fferent than the 2000-2007 fleet analyzed for this study. Nevertheless, one conside ration provides some basis for confidence. This is NHTSA’s fourth evaluation of t he effects of mass reduction and/or downsizing, comprising databases ranging from MY 19 85 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 s ubstantially in mass, sometimes as much as 30-40 percent. 23 If the statistical analysis has, over the past ye ars, been able to accommodate mass increases of this magnitude, perha ps it will also succeed in modeling the effects of mass reductions on the order of 10-2 0 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 Foo tprint 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 vehicl e miles traveled, and to provide an analysis of the effect of mass and footprint reduct ion 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 fi nal 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 sma ll 4-door sedans increased in curb weight from 1,93 9 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 pi ckup truck from 3,390 to 4,742 pounds (40%) in the basic model with 2-door cab and rear-wheel drive; a nd a popular minivan from 2,940 to 3,862 pounds (31%). Deleted: reductions. According to the regression results
Deleted: or decreases
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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.

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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. B oth reports will be peer reviewed by

outside experts.
The LBNL report replicates Kahane’s analysis for NH TSA, using the same data and methods, and in many cases using the same SAS p rograms. 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 veh icle miles travelled (VMT), the increase is small, is overwhelmed by other factors, and is s omewhat sensitive to changes in specifications of the regression models and what da ta 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 m odels in drivers, safety features installed, and crash times and locations. This sec tion 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 mas s and footprint reduction, on risk. It first converts the log-odds effects from the SAS output i nto probabilities; this conversion has no effect on variables that have small effects, suc h as mass and footprint reduction, but increases the magnitude of variables that have larg er 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 footpr int reduction. For example, the models indicate that a 100-lb increase in the mass of a li ghter 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 compar ison 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 tors o side airbags.
The 1.44% increase in risk from reducing mass in th e 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 distributio n of crashes, rather than adjusting the distribution to that expected after full adoption o f ESC, reduces the effect to 1.18%; excluding the calendar year variables from the mode l, which may be weakening the modeled benefits of vehicle safety technologies, re duces the effect to 1.39%; and including vehicle make in the model increases the e ffect to 1.81%. The results also are sensitive to the selection of data to include in th e analysis: excluding bad drivers increases the effect to 2.03, while excluding crash es involving alcohol or drugs increases the effect to 1.66, and including sports, police, a nd all-wheel drive cars increases the effect to 1.64. Finally, changing the definition o f risk also affects the result for lighter cars: using the number of fatalities per induced ex posure crash reduces the effect to -0.24 (that is, a 0.24 reduction in risk), while using th e 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 aresomewhat sensitive to small changes in the model sp ecifications or using different sets of

data.
Using two or more variables that are strongly corre lated in the same regression model (referred to as multicollinearity) can lead t o 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 gre ater than 0.60 (or a variance inflation factor of 2.5) raises concern about multicollineari ty. 24 The correlation between vehicle mass and footprint ranges from over 0.80 for four-d oor 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 betwe en 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 inva lidate the results from a regression model that includes both variables (a point NHTSA a rgued against DRI using this approach in previous studies). Even so, NHTSA has made several attempts to account for the near-multicollinearity between mass and foo tprint.
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 mul ticollinearity was so great that including both variables in the same model gave mis leading results, removing footprint from the model would give much different results th an keeping it in the model. NHTSA’s sensitivity indicates that when footprint i s 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 eff ect of mass reduction on light trucks is unchanged, and is still not statistically significa nt for CUVs/minivans.
Second, NHTSA conducted a stratification analysis o f 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 cras h 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 sepa rately for vehicles with similar footprint. The analysis indicates that mass reduct ion 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 ar e statistically significant. On the other hand, mass reduction decreases risk in a majority o f 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 mainta ining footprint inherently leads to an

24 Light-Duty Vehicle Greenhouse Gas Emission Standar ds and Corporate Average Fuel Economy Standards; Final Rule, April 1, 2010, Section II.G. 3., page 139.increase in risk, the coefficients on mass reductio n should be more consistently positive,

and with a larger R 2 , across the 27 vehicle/crash combinations, than sh own in the analysis.
One limitation to using logistic regression to esti mate 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-R 2 value for logistic regression models; in almost all of the NHTSA regression models this valu e is less than 0.10). For this reason LBNL conducted an analysis of risk versus mass by v ehicle model. LBNL used the results of the NHTSA logistic regression model to p redict the number of fatalities expected after accounting for all vehicle, driver, and crash variables included in the NHTSA regression model except for vehicle weight an d footprint. LBNL then plotted expected fatality risk per VMT by vehicle model aga inst the mass of each model, and analyzed the change in risk as mass increases, as w ell as how much of the change in risk was explained by all of the variables included in t he model.
The analysis indicates that, after accounting for a ll 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 a ll other vehicle types (as shown in Figure x). This means that, on average, risk decre ases 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 actu ally increases as mass increases, with an R 2 of 0.43. LBNL also examined the relationship betw een residual risk, that is the remaining unexplained risk after accounting for all vehicle, driver and crash variables, and mass, and found similarly poor correlations. T his implies that the remaining factors not included in the regression model that account f or 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 t oday 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 dri ver age and gender, safety features installed, and crash times and locations, there are numerous examples of models from different manufacturers with similar weight and foo tprint 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 t he 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 varia bles except mass and footprint

Increasing vehicle mass does not inherently increas e safety in all kinds of crashes. For example, installing a stronger roof a nd support pillars, which happen to weigh an additional 100 lbs, will provide increased protection in rollovers but little additional protection in crashes with other vehicle s; 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 rollov ers. 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 inhere ntly 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 con sider to be the current state of statistical research on vehicle mass and safety?
The agencies believe that statistical analysis of h istorical crash data continues to be an informative and important tool in assessing t he potential safety impacts of the proposed standards. The effect of mass reduction w hile maintaining footprint is a complicated topic and there are open questions whet her 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 w ith technologies more representative of vehicles on the road today, they still do not fu lly represent what vehicles will be on the road in the 2017-2025 timeframe. The vehicles manu factured 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 6 000 6400 6800 7200 7600Predicted US fatality risk (crash fdatalities per 1010VMT)

Curb weight (lbs) 2-dr cars 4-dr cars Small pickups Fullsize pickups SUVs CUVs Minivans

Formatted: Normal,Normal Preamble Text

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Deleted: datatimeframe 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 vehi cles 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 veh icles that will be on the road in 2017 and beyond.
While we recognize that statistical analysis of his torical crash data may not be the only way to think about the future relationship bet ween vehicle mass and safety, we also recognize that other assessment methods are also su bject to uncertainties, which makes statistical analysis of historical data an importan t starting point if employed mindfully and recognized for how it can be useful and what it s limitations may be.
NHTSA undertook the independent review of statistic al studies and held the mass-safety workshop in February 2011 in order to h elp the agencies sort through the ongoing debates over what statistical analysis of h istorical data is actually telling us. Previously, the agencies have assumed that differen ces in results were due in part to inconsistent databases; by creating the updated com mon database and making it publicly available, we are hopeful that that aspect of the p roblem has been resolved , and moreover, the UMTRI review suggested that differenc es in data were probably less significant than the agencies may have thought. Th e agencies also more recently concluded, in the MY 2012-2016 final rule, that mul ticollinearity was likely a significant factor in statistical analysis of historical crash data t hat could lead to inaccurate results. The agencies will continue to monitor issues with m ulticollinearity in our analyses, and hope that outside researchers will do the same. An d finally, based on the findings of the independent review, the agencies continue to be con fident that Kahane’s analysis is one of the best for the purpose of analyzing potential safety effects of future CA FE 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 statist ically significant relationships between vehicle mass, size, and footprint, as discussed abo ve. 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 vehi cles. NHTSA considers part of the reason that more recent historical data shows a dam pened effect in the relationship between mass reduction and safety is that all vehic les, including traditionally lighter ones, grew heavier during that timeframe (2000s). As lig hter vehicles become more prevalent in the fleet again over the next decade, it is poss ible that the trend could strengthen again

. On the other hand, extensive use of new lightweight materi als may make vehicles simultaneously lighter and safer, while maintaining size. Future updated analyses will be necessary to determine how the effect of mass reduc tion on risk changes over time. Deleted:

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, 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
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Deleted: show that.Both agencies agree that there are several identifi able 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 th at 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 b y 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 avoidanc e 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 coeffic ients in the Kahane 2011 study for estimating the potential safety effects of the prop osed CAFE and GHG standards for MYs 2017-2025, based on our assumptions regarding t he 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 t he 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 th at any statistically significant results warrant careful consideration of the assumptions ab out appropriate levels of mass reduction on which to base future CAFE and GHG stan dards, and have acted accordingly in developing the proposed standards.

4. How do the agencies think technological solutions m ight affect the safety estimates indicated by the statistical analysis?

As mass reduction becomes a more important technolo gy option for manufacturers in meeting future CAFE and GHG standa rds, manufacturers will invest more and more resources in developing increasingly lightweight vehicle designs that meet their needs for manufacturability and the publ ic’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 ma y be able to be put into production in the rulemaking timeframe. Discussion of lightweigh t material designs from NHTSA’s workshop is presented below.
Besides “lightweighting” technologies themselves, t hough, there are a number of considerations when attempting to evaluate how futu re technological developments might affect the safety estimates indicated by the statis tical analysis. As discussed in the first part of this chapter, for example, careful changes in design and/or materials use may Deleted: futures

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Deleted: in a cost-effective way

Deleted: if reducingmitigate 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 gre ater aggressivity against other vehicles in crashes. Manufacturers may develop new and bett er 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 moni tor trends in the crash data to see whether changes to the safety standards (or new saf ety standards) become necessary. Manufacturers are also increasingly employing a var iety of crash avoidance technologies – ABS, electronic stability control (ESC), lane dep arture warnings, vehicle-to-vehicle ( V2V ) communications – that, as they become more prevale nt 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 d ifficult 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 function ality 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 rele ased prior to July 2012, in order for them to inform the final rule.

A. NHTSA has awarded a contract to Electricore, with E DAG and George Washington University (GWU) as subcontractors, to s tudy 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 ar e consulting industry leaders and experts for each component and sub-system when deci ding which technologies are feasible. Electricore and its sub-contractors are also building detailed CAD/CAE/powertrain models to validate vehicle safet y, stiffness, NVH, durability, drivability and powertrain performance. For OEM-supplied parts, a detailed cost model is being built based on a Techn ical Cost Modeling (TCM) approach developed by the Massachusetts Institute o f Technology (MIT) Materials Systems Laboratory’s research 25 to estimate the costs to OEMs for manufacturing

25 Frank Field, Randolph Kirchain and Richard Roth, P rocess cost modeling: Strategic engineering and economic evaluation of materials technologies, JOM Journal of the Minerals, Metals and Materials Socie ty, 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: (“
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Deleted: for estimatingparts. The cost will be broken down into each of t he 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 f ixed cost, such as tooling, equipment, and facilities; and variable costs such as labor, material, energy, and maintenance. These costs will be assessed through a n interactive process between the product designer, manufacturing engineers
, and cost analysts. For OEMpurchased parts, the cost will be estimated by cons ultation with experienced cost analysts and Tier 1 system suppliers. This study wi ll help to inform the agencies about the extent to which vehicle mass can be cost-effectivel y reduced

.
B. EPA has awarded a

similar contract to FEV, with EDAG and Monroe & Associates, Inc. as subcontractors, to study the ma ximum feasible amount of mass reduction for a mid-size CUV (cross over vehicle) s pecifically, a Toyota Venza. This study builds upon the low development (20% mas s 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 m ass reduction for a mid-size CUV (cross over vehicle) specifically, a Toyota Ven za. The study will concentrate on the Body-in-White and closures in th e high development design (40% mass reduction) in the Lotus Engineering study cited above. The study will provide an updated design with crash simulation, de tailed 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 rela tionship of light- weight vehicle design and injuries and fatalities. This study wil l also include an evaluation of potential countermeasures to reduce any safety conc erns associated with lightweight vehicles. NHTSA will include three lig ht-weighted vehicle designs in this study: the one from Electricore/EDAG/GWU ment ioned above, one from Lotus Engineering funded by California Air Resource Board for the second phase of the study, evaluating mass reduction levels arou nd 35 percent of total vehicle mass, and two funded by EPA and the International C ouncil on Clean Transportation (ICCT). This study will help to inf orm 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 f easible amounts of mass reduction.

Volume 59, Number 10, 21-32. Available at http://msl.mit.edu/pubs/docs/Field_KirchainCM_Strat EvalMatls.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
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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 2010vehicle, 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

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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, 20 11, NHTSA hosted a workshop on mass reduction, vehicle size, and fleet safety at the Headquarters of the US Department of Transportation in Washington, DC. Th e 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 opportu nity to weigh in on this issue. The agencies also created a public docket to receive co mments from interested parties that were unable to attend. The presentations were divi ded into two sessions that addressed the two expansive sets of issues. The first sessio n 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 cr ashworthiness, occupant injury and advanced vehicle design, and is summarized here. T he speakers in the second session included Stephen Summers of NHTSA, Gregg Peterson o f Lotus Engineering, Koichi Kamiji of Honda, John German of the International C ouncil on Clean Transportation (ICCT), Scott Schmidt of the Alliance of Automobile Manufacturers, Guy Nusholtz of Chrysler, and Frank Field of the Massachusetts Inst itute of Technology.
The second session explored what degree of weight r eduction and occupant protection are feasible from technical, economic, a nd manufacturing perspectives. Field emphasized that technical feasibility alone does no t constitute feasibility in the context of vehicle mass reduction. Sufficient material produc tion capacity and viable manufacturing processes are essential to economic f easibility. Both Kamiji and German noted that both good materials and good designs wil l be necessary to reduce fatalities. For example, German cited the examples of hexagonal ly 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 reductio n will reduce the kinetic energy of all crashes which should produce some beneficial ef fect.
Summers described NHTSA’s plans for a model to esti mate fleetwide safety effects based on an array of vehicle-to-vehicle com putational crash simulations of current and anticipated vehicle designs. In particular, thr ee 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 developmen t” derivative of a Toyota Venza developed by Lotus Eng ineering and discussed by Mr. Peterson. Its structure currently contains about 7 5% aluminum, 12% magnesium, 8% steel, and 5% advanced composites. Peterson expres sed confidence that the design had the potential to meet federal safety standards. Nu sholtz emphasized that computational crash simulations involving more advanced materials were less reliable than those involving traditional metals such as aluminum and s teel. Deleted: engineering

Deleted: fleet wide

Deleted: by significant
Deleted: reduction methodologiesNusholtz presented a revised data-based fleet safet y model in which important

vehicle parameters were modeled based on trends fro m current NCAP crash tests. For example, crash pulses and potential intrusion for a particular size vehicle were based on existing distributions. Average occupant decelerat ion 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 we ight vehicles, such as various scaling approaches for vehicle stiffness or intrusion. The approaches were selected based on engineering requirements for modified vehicles. Tr ansition from the current fleet was considered. He concluded that protocols resulting i n safer transitions (e.g., removing more mass from heavier vehicles with appropriate st iffness 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 fu ture of mass reduction. Similar to Kahane’s discussion of the difficulties of isolating the impact of weight reduction, German stated that other important varia bles, such as vehicle design and compatibility factors, must be held constant in ord er 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 s cenarios, such as rollovers, greatly favored the occupants of smaller and lighter cars o nce a crash occurred. He pointed out that if size and design are maintained, lower weigh t should translate into a lower total crash force. He thought that advanced material des igns 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 an d weight issues in future vehicle models

. Other presenters noted industry’s perspective of th e effect of incentivizing weight reduction. Field highlighted the complexity of ins titutional changes that may be necessitated by weight reduction, including redesig n of material and component supply chains and manufacturing infrastructure. Schmidt d escribed 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 te chnical innovations is generally an innate development process involving both tactic al and strategic considerations that balance desired vehicle attributes with economic an d technical risk. In the absence of challenging regulatory requirements, a substantial technology change is often implemented in stages, starting with lower volume p ilot production before a commitment is made to the infrastructure and supply chain modi fications necessary for inclusion on a high-volume production model. Joining, damage chara cterization, durability, repair, and significant uncertainty in final component costs ar e also concerns. Thus, for example, the Deleted:

. Comment [DOE6]: This last sentence is very convoluted and unclear.

Deleted: and
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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 compar ed to relatively transparent aluminum or high strength steel implementations. R egulatory changes will affect how these tradeoffs are made and these risks are manage d.
Koichi Kamiji presented data showing in increased u se of high strength steel in their Honda product line to reduced vehicle mass an d 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 showi ng the application of smart design can improve safety even when controlling for weight and size.
A philosophical theme developed that explored the e thics of consciously allowing the total societal harm associated with mass reduct ion to approach the anticipated benefits of enhanced safety technologies. Lund conceded tha t there may eventually be specific fatalities that would not have occurred without dow nsizing, 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 le t 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 s afety 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 in creases in the future fleet. This section discusses how the agencies used NHTSA’s 201 1 analysis to calculate specific estimates of safety effects of the proposed standar ds, 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 age ncies’ analysis mandates mass reduction, or mandates that mass reduction occ ur in any specific manner. However, mass reduction is one of the technology application s 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 technol ogically feasible without compromising safety. While we are confident that manufacturers will build safe vehicles, we cannot predict with certainty that the y will choose to reduce mass in exactly the ways that the agencies have analyzed in respons e 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.

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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 sever al 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 i mportant new safety standards that were discussed above for electronic stability contr ol 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 c ontinue, 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 gasoli ne prices remain high. And improvements in driver (and passenger) behavior, su ch as higher safety belt use rates
, may continue . All of these will tend to reduce the absolute nu mber of fatalities in the future. The agency estimated the overall change in fatali ties by calendar year after adjusting for ESC, Side Impact Protection, and othe r Federal safety standards and behavioral changes projected through this time peri od. 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 t rends 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 basi s, 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 tak ing effect in the same years, the estimates derived from applying NHTSA fatality perc entages 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 2 025.

ls technologies, JOM Journal of the Minerals, Metal s and Materials Society, Volume 59, Number 10, 21- 32. Available at http://msl.mit.edu/pubs/docs/Field_KirchainCM_Strat EvalMatls.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 h old 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.
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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

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vehicle size by model year assumed in the Volpe mod el, Table Error! No text of specified style in document. -4 shows the results of NHTSA’s safety analysis separ ately for each model year. 28 These are estimated increases or decreases in fat alities over the lifetime of the model year fleet. A positive numbe r means that fatalities are projected to increase, a negative number ( indicated by parentheses ) means that fatalities are projected to decrease. The results are significantly affecte d by the assumptions put into the Volpe model to take more weight out of the heavy LTVs, CU Vs, 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 i n safety can only occur if more weight is taken out of these vehicles than passenge r cars or smaller light trucks. Combining passenger car and light truck safety esti mates for the proposed standards results in an increase in fatalities over the lifet ime of the nine model years of MY 2017- 2025 of 76 fatalities, broken up into an increase o f 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 reducti on applies to.

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- 4 NHTSA Calculated Mass-Safety-Related Fatality Impacts of the Propose d 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 st udy, EPA used the OMEGA model to conduct a similar analysis. After applyin g these percentage increases to the estimated weight reductions per vehicle size by mod el 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. Th ese are estimated increases or

28 NHTSA has changed the definitions of a passenger c ar and light truck for fuel economy purposes between the time of the Kahane 2003 analysis and th is final rule. About 1.4 million 2 wheel drive SUV s have been redefined as passenger cars instead of li ght trucks. The Kahane 2011 analysis continues wit h 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
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- 4

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- 16
Deleted: Table Error! No text of specified style in document. -5decreases in fatalities over the lifetime of the mo del year fleet. A positive number means

that fatalities are projected to increase; a negati ve number means that fatalities are projected to decrease. For details, see the EPA RIA Chapter 3.

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- 5 EPA Calculated MassSafety-Related Fatality Impacts of the Proposed Sta ndards 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 gr eater than what the agencies have calculated?

As discussed above the ways in which future technol ogical advances could potentially mitigate the safety effects estimated f or 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 lighte r vehicles; crash avoidance technologies could reduce the number of overall cra shes ; roofs could be strengthened to improve safety in rollovers. As also stated above, however, while we are confi dent 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 ti me how crash trends will change in the future fleet as lightweight vehicles become more prevalent. We will have to c ontinue 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 e xactly the ways that the agencies have analyzed in response to the standards. In the even t that manufacturers ultimately choose to reduce mass and/or footprint in ways not analyze d by the agencies, the safety effects of the rulemaking may likely differ from the agencies’ estimates. Deleted: 16
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Deleted: willc. Do the agencies plan to make any changes in these e stimates for the final rule?

As discussed above, the agencies have based our est imates of safety effects due to the proposed standards on Kahane’s 2011 report. Th at 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 t o 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 wi ll 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 b e changed in response to those comments. Additional studies published by the agen cies or other independent researchers as previously discussed will also be considered, al ong with any other relevant information.

29 Kahane, C. J. (2011). “Relationships Between Fatali ty Risk, Mass, and Footprint in Model Year 2000- 2007 Passenger Cars and LTVs,”, July 2011. The rep ort 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 clicki ng on “Search.” Deleted: to