V.   BENEFITS ANALYSIS

Human Factors Issues

The Tire Pressure Monitoring Systems (TPMS) will provide notification to drivers that their tire pressure has dropped below the level recommended by the manufacturer. However, driver response to this information may vary depending upon the nature of the information provided by the TPMS. NHTSA believes that almost all drivers will respond in some manner to the warning, but the level of information presented to the driver by different display systems may result in different behavior by drivers.

The direct measurement systems could display individual tire pressures and tell the driver which tire(s) are low. Although individual tire pressures are not proposed to be required, this analysis assumes in Compliance Option 1 that all of the vehicles will be supplied with direct measurement systems that will display individual tire pressures because it will be helpful to drivers in terms of fuel economy, tread wear and safety. This was done because of uncertainty regarding the exact nature of displays that manufacturers will install. The indirect and hybrid measurement systems can only provide a warning lamp that tire pressure is low. Compliance Options 2 and 3 assume all vehicles will be equipped with only a warning lamp.

We anticipate that drivers will react differently to the different amounts of information. Some drivers will keep track of the individual tire pressures and will add pressure to their tires whenever necessary, say at 10 percent below placard, even before the warning is given. These drivers will accrue more safety benefits and more benefits in terms of fuel economy and tread life than drivers that wait longer for a warning. On the other hand, some drivers who currently check their own tires frequently enough to avoid significant under-inflation may start to rely on the TPMS to indicate under-inflation, rather than checking their tires frequently and filling them up whenever they were below the placard level. We believe this would happen more often under Compliance Options 2 and 3, where only a warning lamp comes on when tire pressure goes below a specified threshold, rather than under Compliance Option 1, where individual tire pressures could be monitored continuously. These drivers would actually accrue fewer safety, tread wear and fuel economy benefits than they did without the TPMS.

The agency has little information that would help it estimate how a TPMS would affect overall driver tire maintenance behavior. A survey question in the Bureau of Transportation Statistics Omnibus Survey of July 2001 asked 1,004 respondents “To what extent do you agree that an indicator lamp in your vehicle that warns the driver about under-inflation in any of the vehicle’s tires would allow you to be less concerned with routinely maintaining the recommended tire pressure?”  The responses were 40 percent to “a very great extent”, 25 percent to “a great extent”, 18 percent to “some extent”, 7 percent to “a little extent”, and 10 percent to “no extent”. Putting this information together with survey data from the tire pressure survey, where one-third of those surveyed indicated that they check their tire pressure at least once a month, indicates that some people would check their tire pressure less frequently.

The agency has some information that would help it estimate what percent of drivers would put to use the information on individual tire pressures. From the agency’s tire pressure survey, we found that about one-third of the interviewed drivers indicated that they check their tire pressure once a month or more frequently. For Compliance Option 1, we assume that one-third of the drivers would pay attention to the individual tire pressure information provided on a monitor and would refill their tires when they were 10 percent below the placard. This means that if the average passenger car tire placard is 30 psi, we assume for Compliance Option 1 that one-third of the drivers would refill their tires when they get to 27 psi. The other two-thirds of the drivers would refill their tires when the warning is given at 25 percent below placard, or 22.5 psi for the average passenger car.

The second question is whether drivers, given a warning, will stop and inflate their tires back to the placard pressure. We do not expect driver compliance with the TPMS telltale, which is amber or yellow, to be 100 percent. In the Final Economic Assessment, we assumed that 95 percent of drivers will fill the low tire(s) to make sure they don’t get a flat tire and be stranded somewhere. Given just a telltale, the driver will probably need to check all the tires. Given a reading of tire pressure on all four tires with a direct measurement system, the driver will know which tire(s) are low and need to be filled.

This assumption was based on NHTSA’s own estimates and a study relating to the Cycloid Pump. “Examining the Need for Cycloid’s Pump:  An Analysis of Attitudes and a Study of Tire Pressure and Temperature Relationships”, December 7, 2001 by the University of Pittsburgh Department of Mechanical Engineering, Department of Industrial Engineering. This study included a survey of people’s attitudes. The survey was not a random survey of consumers representing a national picture. The 225 respondents to the survey were:

1. classmates, faculty, and anyone they thought would respond to an E-mail survey
2. a group of consumers at a supermarket who were willing to participate.

One of the questions was:
Q21.  Would you respond to a dashboard warning lamp informing you that your tire pressure was low?

a)  Yes
b)  No.

Note that there were several questions before this one on how often do you check your tire pressure, when was the last time you checked your tire pressure, what is the recommended tire pressure in your vehicle, etc. These types of questions set up the respondents to thinking that tire pressure is an important topic worthy of checking out.

While this is not a random sample, the question format may have biased the responses, and driver’s actual deeds are often different from their telephone response, the response is overwhelming and leads some small credence to a very high estimate (our initial estimate was  95 percent of drivers will respond to a warning lamp).

In 2003, NHTSA collected information on direct and indirect systems, in terms of tire pressure and asked the owners several questions. This report is still in progress. Preliminary results from questions in this survey to determine consumer reaction to existing TPMS systems indicated that in almost 95% of cases where vehicles had direct systems, and the driver was given a low tire pressure warning, the drivers responded by taking appropriate action. These preliminary survey results thus validate NHTSA’s initial assumption. However, considering that these are all new vehicles and relatively expensive vehicles that have a direct TPMS, and that typically the reactions of purchasers of more expensive vehicles to behavioral warnings will be higher than the reactions of the average or second-time owners, we have assumed a more conservative 90 percent response rate to a warning.

In the Final Economic Assessment we assumed that there will be a natural process whereby, people fill up their tires and then the tires lose air over time. Thus, the benefits of the system are going from the level of pressure in the tire survey to an average level of pressure between times the tires are refilled using the following assumptions:

1. Given a warning lamp goes on, 90 percent of people will check their tires and refill them back to the placard level.
2. Tires lose air at an average of 1 psi per month.
3. The warning has to be given at 25 percent below placard. For passenger cars, assuming the average placard is 30 psi, the warning would be given at 22.5 psi. In Compliance Options 2 and 3, the tires would be refilled at the time of the warning, and then would slowly lose air down to 29 psi at the end of month 1, 28 psi at the end of month 2, etc, until they reached 22.5 psi again when a new warning would be given. Thus, the average steady state psi in this example is 26.3 psi [(30+29+28+27+26+25+24+23+22.5/2)/8.5].
4. For Compliance Option 1, we assume the display that will show individual tire pressures and that one-third of the drivers would pay attention to the display and fill up their tires every time they got to 10 percent below placard or 27 psi. For these individuals that pay attention to the display, the average steady state psi in this example is 28.5 psi. We also assume that the other two-thirds of the drivers will not pay attention to the display and will fill up their tires when they get a warning at 22.5 psi. Thus, their average steady state psi is 26.3 psi. A weighted average of these is 27.0 psi (28.5*.333 + 26.3*.667).
5. These same assumptions are used for the light truck fleet, except we assume that the average placard for light trucks is 35 psi. The following table shows the results of the steady state assumptions for the different compliance options. These mean that benefits are taken from the psi level at which vehicles would be getting a warning under each of the compliance options to the steady state assumptions of where the average fleet psi would be over time. The benefits would then be multiplied by the 90 percent response rate to get the final estimated benefits.

	Steady State psi Level for Passenger Cars	Steady State psi Level for Light Trucks
Compliance Option 1	27.0 psi	31.5 psi
Compliance Option 2	26.3 psi	30.6 psi
Compliance Option 3	26.3 psi	30.6 psi

Skidding and Loss of Control

For loss of control crashes, speed is the most critical factor. Excessive speed alone can cause a loss of control in a curve or in a lane change maneuver. Tread depth, inflation pressure of the tires, and road surface condition are the most notable of a long list of factors including vehicle steering characteristics and tire cornering capabilities that affect the vehicle/tire interface with the road. In the Indiana Tri-Level Study, under-inflation was not considered a contributing factor to a crash when there was high speed involved. It was only considered when the tires were significantly under-inflated (an undefined term generally taken by the investigators to mean at least 10 to 15 psi below recommended pressure). Still, it is hard to know whether correcting this one problem area could result in the collision being avoided or reduced in severity. That is one reason why under-inflation was never cited as the definite cause of a crash. We tried to consider this by comparing under-inflation as a percentage of all of the probable causes in crashes. Certainly, reducing under-inflation is an important area and a move in the right direction. However, it is difficult to determine what the effectiveness of increasing tire pressure would be on these crashes. The following discussions describe how inflation pressure affects these crash types to the extent known.

Skidding and/or loss of control in a curve

Low tire pressure generates lower cornering stiffness because of reduced tire stiffness. When the tire pressure is low, the vehicle wants to go straight and requires a greater steering angle to generate the same cornering force in a curve. The maximum speed at which an off-ramp can be driven while staying in the lane is reduced by a few mph as tire inflation pressure is decreased. An example provided by Goodyear shows that when all four tires are at 30 psi the maximum speed on the ramp was 38 mph, at 27 psi the maximum speed was 37 mph, and at 20 psi the maximum speed was 35 mph while staying in the lane. Having only one front tire under-inflated by the same amount resulted in about the same impact on maximum speed. But, the influence of having only one rear tire under-inflated by the same amount was only about one-half of the impact on maximum speed (a 1.5 mph difference from 30 psi to 20 psi).

The agency also has run a series of tests to examine the issue of decreases in tire pressure on vehicle handling. A 2001 Toyota 4-Runner was run through 50 mph constant speed/decreasing radius circles to see the effects of inflation pressure on lateral road holding. We examined lefthand turns from 0 to 90 degrees handwheel angle for tire inflation pressures varied from 15 to 35 psi. The data indicate to us that in on-ramps/off ramps, tire inflation pressure is a critical factor in vehicle handling. The data show how much friction the vehicle can utilize, in terms of lateral acceleration (g’s), before it slides off the road. The more lateral g’s the vehicle can utilize, the better it stays on the road. So, if you are going around an off-ramp and need to turn the wheel 50 degrees at 50 mph, you can utilize 0.27 g’s at 15 psi, or you can utilize 0.35 g’s at 30 psi.

Skidding and/or loss of control in a lane change maneuver

In a quick lane change maneuver, under-inflated tires result in a loss of tire sidewall stiffness, causing poor handling. Depending upon whether the low tire(s) are on the front or rear axle impacts the vehicle’s sensitivity to steering inputs, directional stability, and could result in a spin out and/or loss of control of the vehicle.

Skidding and/or loss of control benefits estimate

In Chapter IV, we estimated a target population for skidding and loss of control crashes for under-inflated tires of 247 fatalities, 23,100 injuries and 53,130 property-damage-only crashes. The agency assumes that 90 percent of drivers will fill their tires back to placard pressure.

It is difficult to determine the effectiveness estimate, (i.e. , what percent of the crashes would be avoided by just improving low tire pressure). For this analysis, we assume 20 percent effectiveness to go from a very low pressure, where a warning would be given, to the steady state condition, although it could potentially be much higher. Thus, the benefits by Compliance Option are shown in Table V-1. An example calculation resulting in the estimated 44 fatalities is (247*.90*.20*.99 to account for one percent current compliance).

Table V-1
Impacts for Skidding/Loss of Control Crashes

	PDO	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Non-Fatal Inj.	Total
Opt. 1	-9,468	-3,529	-393	-168	-16	-10	-4,116	-44
Opt. 2	-9,468	-3,529	-393	-168	-16	-10	-4,116	-44
Opt. 3	-9,468	-3,529	-393	-168	-16	-10	-4,116	-44

Note that the benefits are the same for all the Compliance Options, since they all require warnings at 25 percent below placard pressure. It is assumed that the benefits would come from increasing tire pressure from a low state to a pressure close to placard pressure. This reflects the finding that the levels of under-inflation in the Indiana Tri-Level study were higher than 25 percent to have under-inflation reported as a probable cause.

Stopping Distance

Tires are designed to maximize their performance capabilities at a specific inflation pressure. When tires are under-inflated, the shape of the tire’s footprint and the pressure it exerts on the road surface are both altered. This degrades the tire’s ability to transmit braking force to the road surface. There are a number of potential benefits from maintaining the proper tire inflation level including reduced stopping distances, better handling of the vehicle in a curve or in a lane change maneuver, and less chance of hydroplaning on a wet surface, which can affect both stopping distance and skidding and/or loss of control.

 The relationship of tire inflation to stopping distance is influenced by the road conditions (wet versus dry), as well as by the road surface composition. Decreasing stopping distance is beneficial in several ways. First, some crashes can be completely avoided by stopping quicker. Second, some crashes will still occur, but they occur at a lower impact speed because the vehicle is able to decelerate quicker during braking.

In Chapter III, a variety of stopping distance test results are discussed. For the Preliminary Economic Assessment, NHTSA examined test results submitted by Goodyear Tire and Rubber Company as well as tests conducted at its own Vehicle Research Test Center (VRTC). In tests conducted by Goodyear Tire and Rubber Company, significant increases were found in the stopping distance of tires that were under-inflated. By contrast, tests conducted by NHTSA at their VRTC testing ground found only minor differences in stopping distance, and in some cases these distances actually decreased with lower inflation pressure. The NHTSA tests also found only minor differences between wet and dry surface stopping distance. It is likely that some of these differences were due to test track surface characteristics. The NHTSA track surface is considered to be aggressive in that it allows for maximum friction with tire surfaces. It is more representative of a new road surface than the worn surfaces experienced by the vast majority of road traffic. The Goodyear tests may also have been biased in other ways. Their basic wet surface tests were conducted on surfaces with .05” of standing water. This is more than would typically be encountered under normal wet road driving conditions and may thus exaggerate the stopping distances experienced under most circumstances. A general problem that applied to both data sets was that they measured stopping distance impacts for new tires only, while most vehicle miles are traveled on tires that are worn down to a level that is somewhere between full and minimal tread depths. Since tread depth and tread profile can greatly influence both water retention and tire friction, this could have a significant impact on estimates of tire pressure on stopping distance. Generally speaking, the Goodyear test results implied a significant impact on stopping distance from proper tire pressure, while the NHTSA tests implied these impacts would be minor or nonexistent at lesser water depths. The PEA estimated stopping distance impacts using the Goodyear data to establish an upper range of potential benefits. A lower range of no benefit was implied based on the NHTSA test results.

In the earlier PEA and in a subsequent memo to the docket (Docket No. 8572-81), NHTSA expressed concern regarding the adequacy of the currently available test data. In response, Goodyear conducted a new and comprehensive series of tests to evaluate the effects of tire inflation pressure on stopping distance. The Goodyear tests were conducted using two different vehicles (Dodge Caravan and Ford Ranger), two different tires (P235/75R15 Wrangler and 215/70R15 Integrity), three inflation pressures (35, 28, and 20 psi), two tread depths (full tread and half tread), and three water depths (dry, .02 inches, and .05 inches). In addition, the tests were run with vehicles with ABS and without ABS. The stopping distance was collected from 45 mph to 5 mph. Goodyear found that collecting the data at 5 mph reduced the variability in the results as compared to a full stop to 0 mph. A separate set of traction truck tests were also run to establish peak and slide coefficients of friction for these tires under similar circumstances but at speeds of 20, 40, and 60 mph.

NHTSA examined the new data submitted by Goodyear and determined that it provided a much more comprehensive data set than was used previously for the earlier PEA. The variety of   water depths and tread depths were particularly important to resolving critical concerns with the initial data sets used in the earlier PEA. During the comment period, NHTSA contracted with the National Oceanic and Atmospheric Administration (NOAA) (See Docket No. 8572-167) to develop a data base that could be used to analyze the relative frequency of rainfall intensity in the U.S. Based on these data, the conditions which are likely to produce a surface water depth level of .05 inch, which was the basis for the original Goodyear tests, only occur about 10 percent of the time that it rains. Thus, the addition of a second lesser water depth test of .02 inch was critical to measuring the impact on crashes that occur under most wet road conditions. The new Goodyear data also confirmed that tread depth has a significant influence on stopping distance. Overall, the new test data provided a comprehensive picture of the impacts of tire inflation on stopping distance, and were relatively free of the contradictions found in the earlier data sets. For these reasons, NHTSA based the final analysis on the new data set provided by Goodyear, rather than average the results of the two previous conflicting sets of data.

Impact Speed/Injury Probability Model

In order to estimate the impact of improved stopping distance on vehicle safety, NASS-CDS data were examined to derive a relationship between vehicle impact speed (delta-V) and the probability of injury. Following is a description of the derivation of this model.

Data: From 1995-1999 CDS, all passenger vehicle occupants involved in crashes where at least one passenger vehicle used brakes.

Methodology:

(1)  The percent probability risk of MAIS 0, MAIS 1+, MAIS 2+, MAIS 3+,

MAIS 4+, MAIS 5+, and fatal injuries was calculated for each delta-V between 0 and 77 mph. The percent probability risk of each MAIS j+ injury level at each delta-V i mph is defined as the number of MAIS j+ injury divided by the total number of occupants involved at i mph delta-V. If j = 0 represents MAIS 0 injuries and j = 6 represents fatalities, the probability of injury risk can be represented by the following formula:

   i = 0 to 77, j = 0 to 6

Where :

p⁺_i,j = percent probability risk of MAIS j+ injuries at i mph delta-V,

x _i,j = the number of j+ injuries (i.e. , MAIS 0, MAIS 1+, MAIS 2+, …, fatal) at i mph delta-V

T_i = total number of occupants at i mph delta-V

Note that p⁺_i,0 = percent probability risk of MAIS 0 injuries at i mph delta-V and p⁺_i,6 = percent probability risk of fatalities at i mph delta-V. I_i,0 = the number of MAIS 0 injuries and I_i,6 the number of fatalities at i mph delta-V.

(2)  The risk-prediction curve for each j injury level was derived using a mathematical modeling process. The process used delta-V as the independent variable (i.e. , predictor) and p⁺_i,j as the dependent variable and modeled all the data points (delta-V, percentage risk) for each j injury level. For example, for MAIS 1+ injuries, the process used the data points: (0, p⁺_0,1), (1, p⁺_1,1), (2, p⁺_2,1), …, (75, p⁺_75,1), (76, p⁺_76,1), (77, p⁺_77,1) to derive the MAIS 1+ risk curve. Table V-2 shows all the risk-prediction formula. These formulas were developed under two assumptions: a) no one was injured at 0 mph, i.e. , p⁺_0,0 = 100 percent, and p⁺_0,j = 0 percent for j=1…6, and b) everyone was assumed to have at least MAIS 1 injuries for 36 mph and higher delta-V, i.e. , p⁺_i,0 = 0 , for i >=36 mph. This assumption was based on the injury distribution derived from 1995-1999 CDS.

Table V-2
Injury Probability Risk Curve Formula

Injury Level	Risk-Prediction Formula
MAIS 0
MAIS 1+
MAIS 2+
MAIS 3+
MAIS 4+
MAIS 5+
Fatal (j=6)

(3)  The percent probability risk p_i,j  was calculated for individual MAIS level. For MAIS 0 (j=0) and fatal injuries (j=6), p_i,0 = p⁺_i,0 and p_i,6 = p⁺_i,6 . The percentage risk for each MAIS 1 to MAIS 5 injury level is the difference between the two predicted risks. Thus, p_i,1 (risk of MAIS 1 at i mph delta-V) = p⁺_i,1 - p⁺_i,2, p_i,2 = p⁺_i,2 - p⁺_i,3, p_i,3 = p⁺_i,3 - p⁺_i,4, p_i,4 = p⁺_i,4 - p⁺_i,5, and p_i,5 = p⁺_i,5 - p⁺_i,6.

(4)  Adjusted total row percent risk to 100 percent. Because of statistical measurement variation and predicting errors, the row risk percentages at some delta-Vs do not add to 100 percent. To adjust to a total of 100 percent for these delta-Vs, an adjustment factor (f_i) is applied to every risk probability. The adjustment factor is 100/(actual total percentage), i.e. ,

 where j = 0…6.

The adjusted risk probabilities for i mph delta-V would be f_i * p_i,j. For example, at 10 mph delta-V, f₁₀ = 100/85 = 1.1765. The risk probability for MAIS 0 becomes 52.5 (= 44.6*1.1765) and MAIS 1 becomes 43.5 (= 37.0*1.1765). These adjusted risk probabilities are higher than those predicted by the original curves listed in Table V-2. However, the general shape of each curve does not alter significantly. Table V-3 shows the adjusted percent probabilities of risk. Note that cell probabilities were rounded to the nearest tenth. Therefore the sum of the individual cells may not total exactly 100 percent.

Once this relationship was established, crash data from 1999 CDS and FARS were distributed across this matrix to establish a “base case” injury distribution. This was done separately for 3 different groups of crashes stratified according to the speed limits on the roadways where crashes occurred. The roadway stratification was selected because stopping distances are largely dependent on initial pre-braking travel speed, and speed limits were assumed to provide a reasonable stratification for this variable. However, actual travel speeds differ from speed limits. For this analysis, it was assumed that actual travel speeds were 5 mph higher than the mean speed limit in each category. The 3 speed limit categories were 0-35mph, 36-50mph, and 51 mph and over. The mean speed limits for each category were 30, 44, and 57. There were only minor differences between speed limits for wet and dry surfaces, or for passenger cars and LTVs. Therefore, the same average speed limit is used regardless of road surface or vehicle type. Allowing for a 5 mph difference for travel speed, the three assumed average speeds that  represent the speed limit categories are 35, 49, and 62 mph.

Table V-3
Adjusted Percent Probabilities of Injury Risk

Delta-V (mph)	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal	Total
0	100.0	0.0	0.0	0.0	0.0	0.0	0.0	100.0
1	95.6	3.5	0.4	0.3	0.1	0.0	0.0	99.9
2	91.0	8.0	0.4	0.4	0.0	0.1	0.0	99.9
3	86.3	12.5	0.5	0.5	0.0	0.1	0.0	99.9
4	81.3	17.2	0.7	0.7	0.0	0.1	0.0	100.0
5	76.3	21.9	0.9	0.7	0.0	0.0	0.1	99.9
6	71.3	26.6	1.0	0.8	0.1	0.0	0.1	99.9
7	66.4	31.2	1.3	0.9	0.1	0.0	0.1	100.0
8	61.5	35.7	1.5	1.1	0.1	0.0	0.1	100.0
9	56.9	39.6	2.0	1.2	0.0	0.1	0.1	99.9
10	52.5	43.5	2.4	1.3	0.1	0.1	0.1	100.0
11	48.2	47.1	2.8	1.5	0.1	0.1	0.1	99.9
12	44.3	50.2	3.4	1.6	0.2	0.0	0.2	99.9
13	40.5	53.1	3.9	2.0	0.1	0.1	0.2	99.9
14	37.1	55.6	4.6	2.2	0.2	0.1	0.2	100.0
15	33.9	57.6	5.5	2.4	0.2	0.1	0.3	100.0
16	31.0	59.1	6.5	2.6	0.3	0.1	0.3	99.9
17	28.3	60.4	7.6	2.9	0.3	0.2	0.3	100.0
18	25.8	61.1	8.8	3.3	0.3	0.2	0.4	99.9
19	23.5	61.5	10.1	3.7	0.3	0.2	0.5	99.8
20	21.4	61.4	11.7	4.1	0.4	0.3	0.5	99.8
21	19.6	61.0	13.4	4.5	0.5	0.3	0.6	99.9
22	17.8	60.1	15.4	5.0	0.5	0.4	0.7	99.9
23	16.3	58.8	17.4	5.6	0.5	0.4	0.9	99.9
24	14.9	57.1	19.6	6.2	0.6	0.5	1.0	99.9
25	13.7	55.1	21.9	6.9	0.7	0.5	1.2	100.0
26	12.6	52.7	24.4	7.6	0.8	0.7	1.3	100.1
27	11.5	50.0	26.9	8.4	0.9	0.7	1.6	100.0
28	10.5	47.1	29.5	9.2	1.0	0.9	1.8	100.0
29	9.6	43.9	32.1	10.1	1.2	1.0	2.1	100.0
30	8.9	40.6	34.5	11.0	1.4	1.2	2.4	100.0
31	8.2	37.1	36.8	12.1	1.5	1.4	2.8	99.9
32	7.6	33.7	38.9	13.3	1.7	1.5	3.3	100.0
33	7.0	30.2	40.9	14.4	1.9	1.8	3.8	100.0
34	6.4	26.7	42.5	15.7	2.2	2.0	4.4	99.9
35	6.0	23.2	43.9	17.1	2.4	2.3	5.1	100.0
36	0.0	26.4	44.3	18.1	2.7	2.6	5.9	100.0
37	0.0	23.3	44.7	19.3	2.9	3.0	6.8	100.0
38	0.0	20.4	44.7	20.4	3.3	3.4	7.8	100.0
39	0.0	17.8	44.3	21.5	3.6	3.8	9.0	100.0
40	0.0	15.5	43.5	22.5	4.0	4.2	10.3	100.0
41	0.0	13.4	42.5	23.3	4.3	4.7	11.8	100.0
42	0.0	11.6	41.1	24.0	4.6	5.3	13.4	100.0
43	0.0	10.0	39.5	24.4	4.9	5.9	15.3	100.0
44	0.0	8.5	37.7	24.8	5.2	6.4	17.4	100.0
45	0.0	7.3	35.7	24.9	5.5	6.9	19.7	100.0
Table V-3 Adjusted Percent Probabilities of Injury Risk,Cont.
46	0.0	6.3	33.6	24.7	5.7	7.5	22.2	100.0
47	0.0	5.3	31.5	24.4	5.8	8.0	25.0	100.0
48	0.0	4.5	29.4	23.7	6.0	8.5	27.9	100.0
49	0.0	3.9	27.2	22.9	6.0	8.9	31.1	100.0
50	0.0	3.3	25.1	21.9	6.0	9.2	34.5	100.0
51	0.0	2.8	23.0	20.8	6.0	9.4	38.0	100.0
52	0.0	2.4	21.0	19.6	5.8	9.6	41.6	100.0
53	0.0	2.0	19.2	18.2	5.6	9.6	45.4	100.0
54	0.0	1.7	17.4	16.9	5.3	9.5	49.2	100.0
55	0.0	1.4	15.8	15.5	5.0	9.3	53.0	100.0
56	0.0	1.2	14.2	14.1	4.7	9.1	56.7	100.0
57	0.0	1.0	12.8	12.8	4.3	8.7	60.4	100.0
58	0.0	0.9	11.4	11.5	3.9	8.3	64.0	100.0
59	0.0	0.7	10.3	10.2	3.6	7.7	67.5	100.0
60	0.0	0.6	9.2	9.1	3.2	7.2	70.7	100.0
61	0.0	0.5	8.2	8.0	2.9	6.6	73.8	100.0
62	0.0	0.4	7.4	7.0	2.5	6.1	76.6	100.0
63	0.0	0.4	6.5	6.1	2.2	5.6	79.2	100.0
64	0.0	0.3	5.8	5.3	2.0	5.0	81.6	100.0
65	0.0	0.3	5.1	4.6	1.7	4.5	83.8	100.0
66	0.0	0.2	4.6	4.0	1.4	4.0	85.8	100.0
67	0.0	0.2	4.0	3.5	1.2	3.6	87.5	100.0
68	0.0	0.2	3.5	3.0	1.1	3.1	89.1	100.0
69	0.0	0.1	3.2	2.5	0.9	2.8	90.5	100.0
70	0.0	0.1	2.8	2.2	0.8	2.4	91.7	100.0
71	0.0	0.1	2.5	1.8	0.7	2.1	92.8	100.0
72	0.0	0.1	2.2	1.5	0.6	1.8	93.8	100.0
73	0.0	0.1	1.9	1.3	0.5	1.6	94.6	100.0
74	0.0	0.1	1.7	1.1	0.4	1.4	95.3	100.0
75	0.0	0.1	1.4	1.0	0.3	1.2	96.0	100.0
76	0.0	0.0	1.4	0.8	0.2	1.1	96.5	100.0
77	0.0	0.0	1.2	0.7	0.2	0.9	97.0	100.0




Separate target populations were also derived for passenger cars and LTVs, and for crashes that occur on wet and dry pavement. These distinctions were necessary because stopping distance is strongly influenced by pavement conditions and vehicle characteristics. In addition, LTVs have significantly different levels of under-inflation than passenger cars and this impacts calculations of delta-V reductions. Note that the presence or absence of anti-lock brakes also has a significant influence on stopping distance. However, because reliable data on the presence of these systems is not included in crash databases, these differences will be accounted for at a different stage of the analysis. A total of 12 separate target population cells were thus produced. The fatalities and injuries for each cell are summarized in Table V- 4 for passenger cars and Table V-5 for LTVs. Table V-6 summarizes the target populations across all passenger vehicles.

Table V-4
Passenger Vehicle Occupants in Crashes Where
at Least One Passenger Car Used Brakes
1995-1999 CDS, Annual Average

	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal	Total
WET
0-35mph	85606	75611	6775	3101	275	163	362	171892
36-50mph	54150	68246	6886	3007	249	161	361	133060
51+mph	22209	23586	2391	1064	94	70	146	49560
DRY
0-35mph	195969	180663	17018	7616	654	438	965	403322
36-50mph	218895	219066	20463	9123	860	480	1273	470158
51+mph	58407	73930	13700	5237	554	423	959	153208
Total	635236	641101	67233	29147	2685	1735	4064	1381201

Table V-5
Passenger Vehicle Occupants in Crashes Where
at Least One LTV Used Brakes
1995-1999 CDS, Annual Average

	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal	Total
WET
0-35mph	23345	27243	2621	1156	101	66	135	54668
36-50mph	34549	42404	3664	1729	121	95	212	82774
51+mph	8183	9810	1535	649	79	66	182	20503
DRY
0-35mph	98640	99100	11291	4800	466	293	699	215290
36-50mph	87072	98763	12016	4985	460	341	911	204547
51+mph	44147	50883	9399	3687	412	321	726	109575
Total	295936	328204	40526	17006	1639	1182	2865	687358

Table V-6
Passenger Vehicle Occupants in Crashes Where
at Least One Vehicle Used Brakes
1995-1999 CDS, Annual Average

	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal	Total
WET
0-35mph	108951	102854	9396	4257	376	229	497	226561
36-50mph	88699	110650	10551	4736	370	256	573	215835
51+mph	30392	33396	3926	1712	173	136	328	70064
DRY
0-35mph	294609	279763	28310	12416	1120	731	1664	618612
36-50mph	305966	317828	32478	14108	1320	821	2184	674705
51+mph	102554	124813	23098	8924	966	744	1684	262783
Total	931172	969305	107759	46153	4325	2917	6930	2068560

Preventable Crashes

The impact of small reductions in stopping distance will, in most cases, result in a reduction in the impact velocity, and hence the severity, of the crash. However, in some cases, reduced stopping distance will actually prevent the crash from occurring. This would result, for example, if the braking vehicle were able to stop just short of impacting another vehicle instead of sliding several more feet into the area it occupied.

The benefits that would accrue from preventable crashes would only impact that portion of the fleet that:

a)  Has low tire pressure, and
b)  Would be notified by the TPMS
c)  Is driven by drivers who will respond to the warning

Data from NHTSA’s tire pressure survey (see Table III-1) indicate that 26 percent of passenger cars and 29 percent of LTVs have at least one tire that is 25 percent or more below recommended placard pressure. For these vehicles, notification of this under-inflation would not be given until the system is triggered. For example, under the proposed requirements, a direct TPMS will trigger at 25% below placard pressure, or roughly 22.5 psi for passenger cars and 26.25 psi for trucks. The portion of the vehicle fleet that is below these levels will potentially experience some reduction in crash incidence due to improved stopping distance. However, in order to experience this reduction in stopping distance, the driver must respond to the warning. For the March 2002 Final Economic Assessment, NHTSA assumed that 95 percent would respond to a warning and refill their tires back to the placard level.

Preliminary results from a recent survey conducted to determine consumer reaction to existing TPMS systems indicated that in 95% of cases where vehicles had direct systems, the drivers responded by taking appropriate action. These preliminary survey results thus validate NHTSA’s initial assumption. However, the vehicles that have existing TPMS tend to be more expensive luxury vehicles that are typically purchased by upper income populations. Since these groups are typically more safety conscious than lower income groups, it is likely that the survey results imply a lower level of response for the overall driving public. Based on this, the overall response rate across all income groups will be estimated to be 90%.

The portion of crashes that would actually be preventable is unknown. However, an estimate can be derived from relative stopping distance calculations for vehicles that were involved in crashes. The average stopping distance was calculated for the existing crash-involved vehicle fleet, and for that fleet if they had correct tire inflation pressure. The method used to calculate these stopping distances is described later in this section of the analysis. The results indicate that the existing passenger car fleet would, on average, experience a stopping distance of 86.5 feet, while the crash-involved LTV fleet experienced an average stopping distance of 91.9 feet. These differences between passenger car and LTV stopping distances reflect the distribution of injuries by speed and road conditions for each vehicle type. By contrast, the average stopping distance for passenger cars with correctly inflated tires would be 85.2 feet, while for LTVs it would be 90.7 feet.

In theory, current crashes occur under a variety of stopping distances but if these distances were shortened due to improved inflation pressure then a portion of these crashes would be prevented. Crashes could be prevented over a variety of travel speeds and braking distances. For example, a vehicle might be able to avoid an intersection crash by slowing quickly enough to miss a speeding vehicle running a red light. In an angular head-on crash, better braking could reduce the chance of two vehicles striking their corners, given that crash avoidance maneuvers are also taking place. An example for rear impacts could involve sudden braking to avoid a vehicle swerving to cross lanes on an interstate highway. We anticipate that a large portion of the fatality and serious injury benefits for crash avoidance would occur in intersection crashes, since both vehicles are moving at high speeds, and a small change in braking efficiency could result in the avoidance of a high-impact crash.

NHTSA does not have data that indicate average stopping distance in crashes. Under these circumstances, it is not unreasonable to assume that crashes are equally spread over the full range of stopping distances. Under this assumption, the change in stopping distance under proper inflation conditions can be used as a proxy for the portion of crashes that are preventable. With equal distribution of crashes across all stopping distances, the portion of crashes that occur within the existing stopping distance that exceeds the stopping distance with correct pressure represents the portion of crashes that are preventable. For passenger cars, this portion is (86.5-85.2)/86.5 or 1.38 percent of all current crashes. For LTVs, this portion is (92.0-90.7)/92.0 or 1.36 percent.

Benefits from preventable crashes were thus calculated as follows:

Ip_(s)=Pp*I_(s)*Pu*Pr

Where,

Ip_(s)= Preventable injuries of severity (s)

Pp = portion of crashes that are preventable

I_(s)= Existing injuries of severity (s)

Pu = portion of vehicles with under-inflated tires that will receive notification from TPMS

Pr = portion of drivers who will respond to the TPMS notification

The results of this analysis are shown for passenger cars under Compliance Options 2 and 3 in Table V-7. The results for LTVs are shown in Table V-8, and for all passenger vehicles Table V-9. Results for Compliance Option 1 will be summarized at the end of this section, but will not be demonstrated. Note that these results have been adjusted to reflect a small amount of overlap that occurred in the separate examination of passenger car and LTV crashes, as well as potential overlap with“loss of control”crashes, which are accounted for separately in a previous section. A combined adjustment factor of .959 was applied to account for this overlap. This factor was derived by comparing the sum of the two separate crash counts to a total count based on all passenger vehicles. These estimates were also adjusted to reflect the impact of threshold braking, as well as current compliance. These concepts are discussed in detail in the following section on non-preventable crashes.

The benefits from preventable crashes, shown in Tables V-7, 8 and 9 were assumed to occur over all crash types and severities. This assumption recognizes that there are a variety of crash circumstances for which marginal reductions in stopping distance may prevent the crash from occurring. Crash prevention may be more likely under some circumstances than others. For example, it is possible that a larger portion of side impacts might be prevented than head-on collisions. In side impacts where vehicles are moving perpendicular to each other, improved braking by one vehicle reduces the speed at which it enters the crash zone and potentially allows the second vehicle to move through the crash zone, thus avoiding the impact. In a head-on collision, both vehicles are moving toward the crash and a reduction in stopping distance for one vehicle may be less likely to avoid a high-speed crash than in the case discussed above for side impacts. Further, if a separate analysis were conducted for different crash types and severities, the portion of crashes prevented would be greater for crashes at higher speeds. However, NHTSA does not have sufficient information to conduct a separate analysis of each crash circumstance and has used an overall estimate across all crash types instead.

Note that this analysis only addresses injury crashes. Property-damage-only crashes would also be impacted by proper tire inflation. These crashes are addressed separately in a later section of this analysis.

Table V-7
Potential Benefits from Preventable Crashes,
Passenger Cars Adjusted for Properly Inflated Vehicles,
90% Response Rate, Overlap, Threshold Braking and Current Compliance
Compliance Option 2 and 3

	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal
WET
0-35mph	170	-150	-13	-6	-1	0	-1
36-50mph	108	-136	-14	-6	0	0	-1
51+mph	44	-47	-5	-2	0	0	0
DRY
0-35mph	210	-194	-18	-8	-1	0	-2
36-50mph	235	-235	-22	-10	-1	-1	-2
51+mph	63	-79	-15	-6	-1	0	-2
Total	829	-840	-87	-38	-3	-2	-7

Table V-8
Potential Benefits from Preventable Crashes, LTVs
Adjusted for Properly Inflated Vehicles,
90% Response Rate, Overlap, and Threshold Braking

Compliance Option 2 and 3

	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal
WET
0-35mph	53	-62	-6	-3	0	0	0
36-50mph	79	-97	-8	-4	0	0	-1
51+mph	19	-22	-4	-1	0	0	0
DRY
0-35mph	122	-122	-14	-6	-1	0	-1
36-50mph	107	-122	-15	-6	-1	0	-2
51+mph	54	-63	-12	-5	-1	0	-1
Total	434	-488	-58	-25	-2	-2	-6

Table V-9
Potential Benefits from Preventable Crashes, All Passenger Vehicles
Adjusted for Properly Inflated Vehicles,
90% Response Rate, Overlap, and Braking Threshold

Compliance Options 2 and 3

	MAIS0	MAIS 1	MAIS 2	MAIS 3	MAIS 4	MAIS 5	Fatal
WET
0-35mph	223	-212	-19	-9	-1	0	-1
36-50mph	186	-232	-22	-10	-1	-1	-1
51+mph	63	-69	-8	-4	0	0	-1
DRY
0-35mph	332	-316	-32	-14	-1	-1	-3
36-50mph	342	-357	-37	-16	-1	-1	-4
51+mph	117	-142	-26	-10	-1	-1	-3
Total	1263	-1328	-145	-62	-6	-4	-13

Non-Preventable Crashes

In the vast majority of crashes, small changes in stopping distance will not prevent the crash, but will reduce the speed at impact and thus the severity of the crash. As noted above, 1.38 percent of braking passenger cars and 1.36 percent of braking trucks could have avoided crashes with proper tire inflation. The remaining 98.6 percent of passenger car and LTV crashes would still occur, but at a reduced impact speed. To estimate the impact of reduced crash speeds, changes in stopping distance will be estimated and used as inputs to recalculate impact speeds for the population of non-preventable crashes. These changes in impact speeds will then be used to redefine the injury profile of this crash population shown in Table V-3, and safety benefits will be calculated as the difference between the existing and the revised injury profiles.

Stopping Distance

Stopping distance can be computed as a function of initial velocity and tire friction. The formula for computing stopping distance is as follows:

SD = Vi²/(2*g*Mu*E)

Where:

SD =Stopping Distance (in feet)

Vi = initial velocity (mean speed limit for specific data group + 5 mph)

g = gravity constant (32.2 ft/second squared)

Mu = tire friction constant (ratio of friction force/vertical load )

E = ABS braking efficiency (estimated @ 0.8)

About a third of all passenger vehicles sold in the U.S. do not have anti-lock brakes, although the portion is higher in the on-road fleet. For these regular braking systems, the term for anti-lock brake efficiency (E) would not be used.

Calculating Mu

The value of Mu is dependent on surface material (concrete, asphalt, etc.), surface condition (wet vs. dry), inflation pressure, and initial velocity. Based on data provided by The Goodyear Tire and Rubber Company in response to the NPRM, NHTSA developed a model that predicts Mu based on Vi and inflation pressure. Separate models were developed for Mu at both peak (the maximum level of Mu achieved while the tire still rotates under braking conditions) and slide (the level of Mu achieved when tires cease to rotate while braking (i.e., skid)). The peak models are used for vehicles with antilock brake systems. The slide models are appropriate for vehicles with non-antilock brake systems. The models are as follows:

For Wet surface conditions

Mp = 0.83140+(.0037109*ip)-(0.0038408*Vi)+(0.000023292*Vi²)

Ms = 0.55093+(0.0029423*ip)-(0.0036979*Vi)-(0.000020146*Vi²)

For Dry surface conditions

Mp = 0.978764+(.002557*ip)-(0.005542*Vi)+(0.0000470863*Vi²)

Ms = 0.717073+(0.000618*ip)-(0.005242*Vi)+(0.000082917*Vi²)

Where:

Mp = Mu peak value

Ms = Mu slide value

ip = inflation pressure (psi)

V_i= initial vehicle speed (mph)

Note that the wet surface condition model is based on 2 separate models. One was derived from the Goodyear tests conducted with .05 inches of water, and one with .02 inches of water. As noted previously, data from NOAA (See Docket No. 8572-167) indicate that only about 10 % of rainfall events occur at rates that would be necessary to produce .05 inches of water on road surfaces. The 2 wet condition models were therefore weighted to produce a single model based on weights of 90% for the .02 inch model and 10% for the .05 inch model

Mu Surface Adjustments

The above formulae were derived from tests conducted on a Traction Truck surface (this is a specific surface calibrated to specifications of OEM customers). In order to relate them to real world surfaces, predicted values from the formulas were compared to actual test results obtained using the same tires mounted on vehicles. The vehicles used were a Dodge Caravan with a 215/70R15 Integrity tire, and a Ford Ranger with a P235/75R15 Wrangler tire. Generally, the Integrity tests were intended to represent passenger cars while the Wrangler tests were intended to represent LTV performance. The tests were all run with an initial velocity of 45 mph, with braking measured down to 5 mph. Goodyear did not record data to a complete stop. In order to compare the predicted stopping distance results from the Mu regressions to real world results, braking distance was measured using the following equation:

SD = (Vi^{2 -}Vii²)/(2*g*Mu*E)

Where:

SD = braking distance

Vi = initial speed before braking

Vii = speed to which vehicle braking is measured

This is a simple modification of the formula previously discussed for stopping distance. The Vii term is necessary to adjust for the 5 mph braking limit in the vehicle tests. Mu peak and slide values were estimated for each of the 3 psi levels used in the Goodyear vehicle tests at 45 mph. The resulting predicted SDs were then compared to the actual stopping distance found in the corresponding vehicle tests. The actual SDs were weighted to reflect an average of the full and half tread tests. Weighting factors for the actual SDs were derived from tread depth data obtained in NHTSA’s tire inflation survey. Full tread for the Integrity tire (assumed to represent passenger tires) was 10/32 inch and half tread was 5/32 inch. For the Wrangler tire (assumed to represent LTVs), full tread was 13/32 inch and half tread was 6.5/32 inch). Data from the NHTSA survey indicate that about 2/3 of all vehicle tires had tread depths more similar to the½tread level and about 1/3 had tread depths more similar to the full depth levels.

A comparison of the predicted and actual weighted SDs indicated close similarity across the three different psi levels. Therefore, factors were averaged across the 3 levels. However, they differed significantly by tire type, surface condition, and for peak vs. slide. Overall, the results of this comparison indicate that factors of from roughly 1.3 to 1.8 are required to adjust the stopping distances predicted using the Mu-based algorithms. The Wrangler factors were applied to LTV estimates and the Integrity factors were applied to passenger car estimates. Wet and dry factors were also applied to their corresponding cases. Peak factors were applied to vehicles with antilock brakes, while slide factors were applied to vehicles without antilock brakes. The factors used are summarized in Table V-11.

Table V-11
Vehicle Surface Adjustment Factors

	Wrangler	Integrity
Wet Peak	1.8379	1.7246
Wet Slide	1.4856	1.2709
Dry Peak	1.7586	1.6260
Dry Slide	1.5954	1.5203

Anti-lock and Normal Braking Systems

Roughly 2/3 of all passenger vehicles sold in the U.S. have anti-lock brakes, but the portion is smaller in the on-road fleet. For vehicles with anti-lock brake systems, Mp is used to calculate stopping distance because it represents the peak controlled braking force that anti-lock brakes attempt to maintain. For vehicles with regular brake systems, Ms is used because it represents the level of friction encountered under normal braking by most drivers without assistance from anti-lock brakes. Also, for these regular braking systems, the term for anti-lock brake efficiency (E) would not be used.

Delta-V

Changes in stopping distances were then used to calculate the decrease in crash forces (measured by delta-V) that would occur due to the decrease in striking velocity of the vehicle. The formula used to calculate striking velocity is:

V(d) =

Where:

V(d) = velocity of vehicle at distance d after braking

Vi = initial velocity before braking

a = deceleration

d = distance traveled during braking of vehicle

In this case, V_(d)is a measure of the speed at which the vehicle with under-inflated tires would be traveling when it reaches the distance at which it would have stopped had its tires been correctly inflated (d). Deceleration (a) is calculated for the vehicle with under-inflated tires. The derived formula for deceleration is:

a = (V(d)²-Vi²)/(2*d)

Since V = 0 at d, the formula becomes:

a = (Vi²)/(2*d) (the negative sign that would precede the formula indicates deceleration and will be ignored from this point on)

The distance over which a is calculated is the stopping distance for the vehicle with under-inflated tires. This will be designated as SDu. The formula thus becomes:

a = (Vi²)/(2*SDu)

Where:

SDu = stopping distance with under-inflated tires

The striking velocity is then expressed in mph by multiplying by 1/ 5280 ft.*3600 sec. hour. The delta-V experienced by each vehicle would be dependent on vehicle mass. For this analysis, the mass of each vehicle was assumed to be equal, giving a delta-V of 1/2 V(d) for each vehicle or:

DELTA-V = (V(d)*3600/5280)/2

Where:

DELTA-V = the change in velocity resulting from increased tire pressure.

The base case target population represents the injury profile that results from the fleet of passenger vehicles that were on the road at that time. In order to determine the inflation pressure that exists in that fleet, NHTSA conducted a survey of both recommended and actual inflation pressures on vehicles. (Details of that survey are discussed elsewhere in this analysis). The results of the survey indicate that 74% of all passenger vehicles are driven with under-inflated tires. However, because TPMS would not notify drivers of low pressure until it dropped 25% below placard, no stopping distance benefits would accrue to vehicles with smaller tire pressure deficits. Weighting factors were derived from the tire pressure survey to represent the affected population under this requirement. The distribution of each level of under-inflation is shown in Table V-12. The left column indicates the average under-inflation of the 4-tires, given that one tire was under-inflated by 25 percent or more.

Table V-12
Percent of Vehicles Under-inflated 25% or more below Placard Level

Under-Inflated	Percent Under-Inflated	Percent Under-Inflated
Pressure (psi)	PCs	LTVs
-1	0.2%	0.2%
-2	7.4%	4.9%
-3	11.2%	6.0%
-4	11.8%	8.2%
-5	13.7%	8.4%
-6	12.3%	13.1%
-7	12.2%	11.2%
-8	9.7%	11.2%
-9	7.4%	8.5%
-10	4.8%	7.6%
-11	3.1%	5.1%
-12	2.4%	3.5%
-13	1.3%	2.2%
-14	0.6%	1.6%
-15	0.8%	0.9%
-16	0.4%	1.7%
-17	0.2%	1.0%
-18	0.1%	0.7%
-19	0.0%	0.4%
-20	0.1%	0.4%
-21	0.1%	0.4%
-22	0.1%	0.3%
-23	0.0%	0.4%
-24	0.1%	0.4%
-25	0.0%	0.3%
-26	0.1%	0.2%
-27	0.0%	0.3%
-28	0.0%	0.1%
-29	0.1%	1.3%
Total	100.0%	100.0%

As noted previously, the value of Mu in the formula for stopping distance is dependent on inflation levels. For each speed limit category, a set of delta-Vs corresponding to each under-inflation level was calculated. In each case, an average placard pressure of 30 psi was assumed for passenger cars. For LTVs, an average pressure of 35 psi was assumed. The rates of under-inflation in Table V-12 were used to weight the change in delta-V that results from each corresponding psi under-inflation level to an overall weighted average change across all levels. The resulting changes in delta-V are summarized in Table V-13 for each passenger car and LTV target population category for vehicles with ABS systems, non-ABS systems and combined systems, based on weighting factors representing the relative portion of the vehicle fleet that has Anti-lock brakes. Note that these estimates do not reflect any impact for vehicles with inflation levels that are less than the assumed set point for the TPMS system. This analysis assumes a set point of 25 percent below the placard pressure, or 7.5 psi based on the assumption of a 30 psi recommended pressure. Benefits would only accrue to those tires that are more than 7.5 psi beneath their recommended pressure. For LTVs, benefits would accrue for those tires that are more than 8.75 psi beneath their recommended pressure.