wp-3r0 urban streets

8/14/2019 WP-3r0 Urban Streets

1/37

Working Paper 3:

Comparison of Urban Streets Methodologies inHCM 2000 and HCM 2010

J. BonnesonKittelson & Associates, Inc.

April 25, 2013


2/37


3/37

COMPARISON OF URBAN STREETS METHODOLOGIES IN

HCM 2000 AND HCM 2010

INTRODUCTION

This paper describes the findings from an examination of the urban streets methodologyin Chapter 17 of theHighway Capacity Manual 2010 (HCM 2010) (1). The examination is

focused on a comparison of this methodology with its counterpart in HCM 2000 (2). The

predicted travel speed and level of service from each methodology are used for this comparison.

The objective of the research described in this document was to determine if the

predicted travel speed and level of service for common urban street facilities tend to be different

among the two methodologies. If it is found that there is a tendency to be consistently different

in one direction (e.g., a consistently slower travel speed), then this finding would suggest that

there is a bias between the two methods. If it is found that there is a tendency to predict higher

results for some facilities and lower results for the other facilities, then this finding would

suggest that the methodologies disagree, but are inconsistent in the direction of disagreement.

Many agencies have used the HCM 2000 methodology for urban street evaluation. An

important question to these agencies is whether the new HCM 2010 methodology will produce

different results for the same facility. These agencies may be required to address capacity issues

on a given street if the results from the new methodology indicate a slower travel speed or a

decrease in level of service (i.e., results that are biased lower). Inconsistent results may pose

similar problems, but to a smaller degree.

Ground-truth data are not used as the basis of comparison in this research. Ideally,

ground truth data would be used as the basis of comparison for both methodologies. However,

this data would need to reflect a wide range of conditions and, as a result, would require anexceptional amount of resources to obtain. Fortunately, both methodologies have been calibrated

using ground-truth data as part of their original development (as documented in the

corresponding HCM chapters). Recognizing these caveats, the objective of this research can still

be achieved by a direct comparison of the two methodologies for a range of urban street

scenarios. However, any references to accuracy and precision must be qualified as pertaining to a

comparison of the predictions from the two models.

It must be remembered that the methodology in HCM 2010 represents a fundamental

change from that in HCM 2000. Hence, it should be expected that some differences in the

predicted travel speed and level of service will occur for some facilities when using the new

methodology. It should also be remembered that each of the methodological changes weredeveloped through extensive research, calibrated with field data, validated, and reviewed by

many professionals.

WP 3.0 - 1


4/37

(1)

BACKGROUND

This section provides an overview of the two methodologies being compared, with each

methodology being discussed in a separate subsection. The last subsection summarizes the

findings from research projects that have evaluated various factors affecting free-flow speed.

Highway Capacity Manual 2000

Free-Flow Speed

A key input to the HCM 2000 methodology is urban street class. This class is

designated using the Roman numerals I, II, III, or IV. The determination of class is based on

consideration of the subject streets functional category and design category. Descriptive

information is provided in Exhibit 10-4 of HCM 2000 to guide the analyst in determining

functional category and design category. The key point here is that the determination of urban

street class is subjective, and two analysts applying the guidance to the same facility can

occasionally reach different conclusions about the facilitys class designation.

The urban streets methodology in the HCM 2000 specifies the free-flow speed as an

input variable. This variable is used with urban street class to determine the segment running

time. If a field-measured value of free-flow speed is not available, then a default free-flow speed

value is provided for the analysts use. The appropriate default value is based on the urban street

class. Thus, the subjectivity of urban street class determination can permeate the determination

of free-flow speed.

Signal Delay

Travel speed is computed using the segment running time and through delay at thesignalized intersection. The delay calculation includes a progression adjustment factor that

accounts for progression quality. This factor is computed using the following equation.

where

PF= progression adjustment factor;

P= proportion of all vehicles arriving during green;

g/C= effective-green-to-cycle-length ratio; and

fPA= supplemental adjustment factor for platoon arrival during the green.

The supplemental adjustment factorfPAis used to account for situations where the front of

the platoon arrives before or after the start of green, for the same value of P. A factor value of

0.93 is applied to arrival type 2 (i.e., unfavorable progression), 1.15 for arrival type 4 (i.e.,

favorable progression), and 1.0 for all other arrival types.

Arrival type is another subjectively determined input value for HCM 2000. It is

designated using the integer numbers 1 through 6. Arrival type 1 describes very poor

WP 3.0 - 2


5/37

progression and arrival type 6 describes exceptional progression. Progression quality increases

incrementally with each value in the range 1 through 6.

Qualitative guidance is provided in the HCM 2000 to help analysts determine arrival

type. However, several researchers have noted that the subjective assessment of arrival type can

lead to significant error in delay prediction (3, 4). An analysis of the variability in the delayestimate indicates that the use of arrival type as a descriptor of arrival pattern increases the

uncertainty in the delay estimate. Specifically, the standard deviation of the computed delay

ranges from 3 to 6 s/veh due to the uncertainty associated with the arrival type estimate (5).

Running Time

HCM 2000 Exhibit 15-3 (reproduced as Table 1) is used to estimate the running time rate

for the subject segment. As indicated by the table values, shorter segments are associated with a

longer running time rate. This trend implies that segment length has some influence on speed,

with lower running speeds found on shorter segments. The effect of traffic volume, number of

lanes, and access point density on running time rate is not reflected in Table 1.

TABLE 1 HCM 2000 segment running time rate

Urban Street Class I II III IV

Free-Flow Speed,ami/h 55 50 45 45 40 35 35 30 35 30 25

Segment Length, mi Running Time Rate (tR), s/mi

0.05b b b b b b

-- -- -- 227 265

0.10b b b b b b

145 155 165 180 220

0.15b b b b b b

135 141 140 150 180

0.20

b b b

109 115 125 128 134 130 140 1650.25 97 100 104 104 110 119 120 127 122 132 153

0.30 92 95 99 99 102 110d d d d d

0.40 82 86 94 94 96 105d d d d d

0.50 73 78 88 88 93 103d d d d d

1.00 65c 72c 80c 80c 90c 103cd d d d d

Notes:

a. Default free-flow speed: Class I - 50 mi/h; Class II - 40 mi/h; Class III - 35 mi/h; Class IV - 30 mi/h.

b. If a Class I or II urban street has a segment length less than 0.20 mi (a) reevaluate the class and (b) if it remains a

distinct segment, use the values for 0.20 mi.

c. For long segment lengths on Class I or II urban streets (1 mi or longer), free-flow speed may be used to compute

running time per mile. These times are shown in the entries for a 1.0-mi segment.d. Likewise, Class III or IV urban streets with segment lengths greater than 0.25 mi should first be reevaluated (i.e.,

the classification should be confirmed). If necessary, the values above 0.25 mi can be extrapolated.

Each rate in Table 1 can converted to running speed (in mi/h) by dividing it into 3600.

The resulting speeds can be observed to converge to the free-flow speed for segment lengths of

1.0 mi. In fact, footnote c indicates that the running speed equals the free-flow speed for

segment lengths of 1.0 mi or more. Thus, regardless of the traffic volume level, the traffic stream

WP 3.0 - 3


6/37

on a 1.0 mi segment is suggested to travel at the free-flow speed. Yet, HCM 2000 defines free-

flow speed as the speed when traffic volumes are so low as to have no influence on driver speed

choice. This contradiction is not discussed in HCM 2000.

Level-of-Service Thresholds

Chapter 10 of the HCM 2000 describes the traffic conditions associated with each level

of service. For example, it indicates that Level-of-service A describes primarily free-flow

operations at average travel speeds, usually about 90 percent of the free-flow speed for the given

street class (2, p. 10-5). The percentages cited for levels of service B, C, D, and E are 70, 50,

40, and 33 percent, respectively.

The threshold speed cited for each level of service is provided in Exhibit 15-2 of HCM

2000. This exhibit is reproduced as Table 2.

TABLE 2 HCM 2000 urban street level of service.Urban

Street Class

Free-Flow

Speed, mi/h

Travel Speed Threshold (lower limit) by Level of Service, mi/h

A B C D E

I 55 >42 >34 >27 >21 >16

50 42 34 27 21 16

45 42 34 27 21 16

II 45 35 28 22 17 13

40 35 28 22 17 13

35 35 28 22 17 13

III 35 30 24 18 14 10

30 30 24 18 14 10

IV 35 25 19 13 9 7

30 25 19 13 9 7

25 25 19 13 9 7

Note: Underlined values correspond to typical free-flow speed for each class (2, p. 15-3).

Within a given urban street class, the threshold speed is shown in Table 2 to be invariant

with the free-flow speed. For example, the threshold speed associated with level-of-service A for

class I is 42 mi/h (i.e., the travel speed must exceed 42 mi/h to be level-of-service A). This value

does not change whether the free-flow speed is 45, 50, or 55 mi/h.

To appreciate the point made in the previous paragraph, consider the following three

cases for a Class I facility with an average travel speed of 39 mi/h. The question here is, What

is the level of service?

1. Free-flow speed = 55 mi/h: level-of-service B, with a 16-mi/h speed reduction.

2. Free-flow speed = 45 mi/h: level-of-service B, only a 6-mi/h reduction.

3. Free-flow speed = 45 mi/h and the facility is re-designated as Class II: level-of-service A.

WP 3.0 - 4


7/37

Therefore, if the average travel speed is 39 mi/h, then a Class I facility has a level-of-

service B, regardless of whether its free-flow speed is 45, 50, or 55 mi/h. However, it will be

very difficult for the Class-I facility with a free-flow speed of 45 mi/h to achieve level-of-

service A for typical values of control delay (i.e., typical delay values will reduce travel speed by

more than 6 mi/h). On the other hand, re-classifying this facility as Class II eliminates thisproblem (i.e., it now has its level-of-service changed from B to A). In short, the answer to the

question is, The facility operates at level-of-service B but, if the free-flow speed is 45 mi/h,

then re-classification may be the only viable way to achieve level-of-service A for this facility.

Highway Capacity Manual 2010

This subsection discusses two topics. The first topic is the urban streets methodology in

Chapter 17 of HCM 2010 (i.e., the Chapter 17 method). The second topic is the quick

estimation method (QEM) in Chapter 30 of HCM 2010. Both methods are developed to predict

travel speed and level of service. The QEM is intended to be used when minimal data are

available for the analysis and only approximate results are desired (1, p. 30-26).

HCM Methodology

Free-Flow Speed. The Chapter 17 method includes a procedure for predicting the free-

flow speed. The procedure is not based on subjective decisions by the analyst. Rather, it is a

quantitative procedure that predicts the free-flow speed value based on speed limit, median type,

outside curb presence, access point density, and number of lanes. It was calibrated using field

data, and its development is documented by Bonneson et al. (6).

Signal Delay.The delay estimate produced by the Chapter 17 method is based on (a)

predicted platoon arrival patterns using a platoon dispersion algorithm, (b) predicted platoondecay due to mid-signal access points, and (c) the analyst-provided signal offset. The proportion

of vehicles arriving during green is computed using a procedure in HCM 2010. The delay

estimate is notbased on the subjective assessment of arrival type.

Running Time.The Chapter 17 method provides a quantitative procedure for predicting

running time. The prediction is based on segment length, free-flow speed, traffic volume,

number of lanes, and delay due to left and right turns from the street into access point

intersections. The underlined variables in the previous sentence are not explicitly considered in

the running time determination for HCM 2000. Also, the corresponding running speed does not

converge to the free-flow speed (unlike HCM 2000), unless the volume level is consistent with

free-flow conditions (i.e., negligible).

Access-Point Delay. The Chapter 17 method provides a quantitative procedure for

predicting the delay due to left and right turns from the street into an access point intersection.

This delay is incurred by the through drivers on the urban street when they slow for a turning

vehicle. The delay is computed for each access point intersection and added for the segment. The

number of access points on the segment is an input. Exhibit 17-24 of HCM 2010 provides default

WP 3.0 - 5


8/37

access point density values of 34 points/mi and 21 points/mi for urban arterials and suburban

arterials, respectively. These values can be used to estimate the typical number of access points.

Level-of-Service Thresholds.The Chapter 17 method defines the level-of-service

thresholds as a percentage of the base free-flow speed. The threshold percentages cited for level-

of-service A, B, C, D, and E are 85, 67, 50, 40, and 30 percent, respectively. These percentageswere based on an examination of the values in Table 2 that are associated with the typical free-

flow speeds (as identified by underline in Table 2), and a desire to minimize the possibility that

agencies would find that a facilitys HCM 2000-based level of service was different from its

HCM 2010-based level of service. The percentages tend to be slightly smaller (more liberal) than

those cited in Chapter 10 of HCM 2000 (and also cited in the previous subsection).

The corresponding threshold speed for each level of service is provided in Table 3. The

urban street class designation is shown in the first column of this table for reference in this

document. Urban street class is not considered in HCM 2010.

TABLE 3 HCM 2010 urban street level of service.

Urban

Street Class

Free-Flow

Speed, mi/h

Travel Speed Threshold (lower limit) by Level of Service, mi/h

A B C D E

I 55 >47 >37 >28 >22 >17

50 43 34 25 20 15

45 38 30 23 18 14

II 45 38 30 23 18 14

40 34 27 20 16 12

35 30 23 18 14 11

III 35 30 23 18 14 11

30 26 20 15 12 9

IV 35 30 23 18 14 11

30 26 20 15 12 9

25 21 17 13 10 8

In contrast to HCM 2000, the threshold speed is shown in Table 3 to vary with the free-

flow speed. For example, the threshold speed associated with level-of-service A for a free-flow

speed of 50 mi/h is 43 mi/h (i.e.., the travel speed must exceed 43 mi/h to be level-of-service A).

In contrast, a free-flow speed of 45-mi/h has a threshold speed of 38 mi/h.

To appreciate the point made in the previous paragraph, consider the following two cases

for a Class I facility with an average travel speed of 39 mi/h. The question here is, What is the

level of service?

1. Free-flow speed = 55 mi/h: level-of-service B, with a 16-mi/h speed reduction.

2. Free-flow speed = 45 mi/h: level-of-service A, only a 6-mi/h reduction.

WP 3.0 - 6


9/37

(2)

Therefore, if the average travel speed is 39 mi/h, then the facility with a free-flow speed

of 55 mi/h has a level-of-service B due to the relatively large speed reduction. However, the

facility with a free-flow speed of 45 mi/h has a level-of-service A due to the small speed

reduction. In short, the answer to the question is, The facility operates at level-of-service B if

the free-flow speed is 55 mi/h, and at level-of-service A if the free-flow speed is 45 mi/h.

The threshold speeds associated with a free-flow speed of 30, 35, 40, and 50 mi/h can be

compared with their underlined counterparts in Table 2. This comparison shows the similarity

between the threshold speeds in HCM 2000 and those in HCM 2010, as was intended.

Quick Estimation Method

Free-Flow Speed.The free-flow speed prediction procedure used in the QEM is the

same as that used in the Chapter 17 method (i.e., the methodology in Chapter 17 of HCM 2010).

Signal Delay.The QEM uses effectively the same delay equations as are used in theHCM 2000. It does not use the procedure described previously for the Chapter 17 method. This

difference is consistent with the intended application for the QEM (i.e., when minimal data are

available and only approximate results are desired). The progression adjustment factor is

computed using the following equation.

where all variables as defined previously.

Equation 2 is the same as Equation 1 with the exception that the supplemental adjustmentfactorfPAhas been excluded. No reason is offered in HCM 2010 for this exclusion.

Running Time.The running speed prediction procedure used in the QEM is the same as

that used in the Chapter 17 method.

Access-Point Delay. The calculation of delay due to left and right turns from the street

into access point intersections is similar to that for the Chapter 17 method. However, the default

delay values provided in Exhibit 17-13 of HCM 2010 are used instead of the prediction

procedure.

Level-of-Service Thresholds.The threshold values used for level-of-servicedetermination are the same for the QEM and the Chapter 17 method.

Factors Affecting Free-Flow Speed

This section describes the factors found to influence free-flow speed. These factors

include: speed limit, access point density, area type, functional class, and the presence of on-

street parking.

WP 3.0 - 7


10/37

(3)

Free-flow speed is defined in Chapter 17 of the HCM 2010 to represent the average

running speed of through automobiles when traveling along a segment under low-volume

conditions and when not delayed by traffic control devices or other vehicles. It reflects the effect

of the street environment on driver speed choice. Any delay due to signals or interactions with

other vehicles is not include in the free-flow speed. Free-flow speed is an average speed, as

opposed to the 85th

percentile speed.

Influence of Speed Limit

Guidance regarding the relationship between speed limit and free-flow speed is provided

in Chapters 10 and 15 of the HCM 2000. A comparison of the speed limit ranges in Exhibit 10-4

with the typical free-flow speeds in Exhibit 15-2 indicates that speed limits in the range of 25 to

35 mi/h, 35 to 40 mi/h, 40 to 45 mi/h, and 45 to 55 mi/h coincide with free-flow speeds of 30, 35,

40, and 50 mi/h, respectively. This trend suggests that the free-flow speed is about equal to the

speed limit.

Tarko and Sinha (7) examined speed data from 116 speed measurement stations onarterial highways in Indiana. Their analysis found that several factors were correlated with free-

flow speed, they include: heavy-vehicle percentage, time of day (i.e., day, night), speed limit,

land use (i.e., urban, rural), number of lanes, and road class (i.e., freeway, nonfreeway). The

regression equations they developed indicate that urban, four-lane, non-freeway roads with speed

limits of 55 and 65 mi/h have free-flow speeds of 61.7 and 67.5 mi/h, respectively.

The Florida Department of Transportation (FDOT) (8) recommends that the free-flow

speed can be estimated as being 5 mi/h faster than the posted speed limit when conducting

arterial level-of-service analyses.

In a recent examination of speed data at 12 speed measurement stations on 12 ruralmultilane highways, Dixon et al. (9) found that multilane highways with speed limits of 55 and

65 mi/h have free-flow speeds of 61.8 and 64.9 mi/h, respectively.

Dowling et al. (10) examined speed data from 10 speed measurement stations on four

rural highways in three states. They developed the following relationship between free-flow

speed and speed limit:

where,

Spl= posted speed limit, mi/h.

The guidance provided in the HCM and by the aforementioned researchers indicates thatspeed limit is likely correlated with free-flow speed. The guidance offered is summarized in

Figure 1.

WP 3.0 - 8


11/37

Figure 1. Comparison of free-flow speed and speed limit reported by six sources.

Ivan et al. (11) collected free-flow speed data for two-lane roads in rural, suburban, and

urban areas. Data were collected for a total of 272 roads in Connecticut. The predictive models

they developed are shown in Figure 2.

The trend lines shown in Figure 1 that are attributed to FDOT, Chapter 21 of HCM 2000,

and Dowling et al. indicate that roadways the free-flow speed that is about 5 mi/h faster than the

speed limit. Moreover, they imply a one-to-one correlation between a change in speed limit and

a change in free-flow speed. The stair-stepped trend line attributed to HCM Chapter 10 is

derived from the HCM 2000. It contrasts with the other three trend lines by suggesting that thefree-flow speed is typically less than or equal to the speed limit.

The data attributed to Tarko and Sinha, and to Dixon et al, indicate that the relationship

between speed limit and free-flow speed is not one-to-one. Rather, these data suggest that free-

flow speed increases about 4 mi/h for a 10 mi/h increase in speed limit. Similarly, the trend lines

in Figure 2 suggest that free-flow speed increases about 4 mi/h for a 10 mi/h increase in speed

limit.

30

40

50

60

70

30 40 50 60 70

Speed Limit, mph

Free-Flow

Speed,mph

HCM Chapter 10

HCM Chapter 21

Dowling et al. (5 )

FDOT (3 )

1

1

Tarko & Sinha (2 )

Dixon et al. (4 )

WP 3.0 - 9


12/37

20

30

40

50

60

70

20 30 40 50 60 70

Speed Limit, mph

Free-Flow

Spee

d,mph

11

General urban street, light parking, no shoulder

Urban residential, 2 sidewalks,

parking, medium shoulder

Suburban residential, no sidewalks,

no parking, large shoulder

(4)

Figure 2. Comparison of free-flow speed and speed limit reported by Ivan et al (2009).

Numerous researchers that independently investigated the effect of a speed limit change

on observed traffic speeds report that the correlation is not one-to-one (12, 13, 14, 15). In fact,

these researchers have consistently found that the average speed changes only 2 to 3 mi/h when

the speed limit changes by 10 mi/h. This trend has been found on streets and highways, when the

speed is increased or decreased by 5 or 10 mi/h. It implies that the slope of the three trend lines

in Figure 1 is too steep.

Influence of Access Point Density, Speed Limit, and Functional Class

Data reported in the literature were used to examine the correlation between access pointdensity, speed limit, and free-flow speed. The data reported by Bonneson and McCoy (16)

describe seven urban street segments with access point densities ranging from 15 to 80 access

points per mile (points/mi) and speed limits ranging from 30 to 45 mi/h. The data reported by

Dixon et al. (9) describe 12 multilane highway segments with driveway densities ranging from 2

to 14 points/mi. The data reported by Fitzpatrick et al. (17) represent 69 urban or suburban street

segments and 9 rural highway segments. Access point densities ranged from 2 to 142 points/mi.

The cited access point densities are based on a count of access points on bothsides of the street.

Thus, the one-side densities reported by Dixon et al. were doubled for this analysis.

All total, data for 97 road segments (76 urban, 21 rural) were assembled for the purpose

of evaluating the relationship between speed limit and access point density on free-flow speed.A regression analysis of the combined database revealed the following equation for estimating

free-flow speed:

where,

Iart-coll= indicator variable for road type (1.0 for urban arterial or collector street, 0.0 otherwise);

Ilocal= indicator variable for road type (1.0 for urban local street, 0.0 otherwise); and

WP 3.0 - 10


13/37

Da= access point density (total for both sides of road), points/mi.

The coefficient of 0.61 for speed limit is smaller than 1.0 but, it is larger than 0.2 to 0.3

suggested by the aforementioned research focused solely on the effect of speed limit change.

The fit of Equation 4 to the data is shown in Figure 3. Each data point shown representsthe free-flow speed for all street or road segments having the corresponding functional

classification and posted speed limit. Each data point represents an average of 5 to 15 segments.

The trend lines shown are obtained from Equation 4 for an access density of 40 points/mi.

Figure 3. Relationship between access point density, speed limit, and free-flow speed.

The trends shown in Figure 3 indicate that free-flow speed is typically larger than the

speed limit. However, the relationship between the two speeds is not consistent with the

guidance documented previously and shown in Figure 1. This difference is due to the fact that

speed limit is correlated with access point densityhigher speed limits are associated with lower

densities.

Influence of Area Type and Functional Class

The trends shown in Figures 2 and 3 indicate that area type and functional class are

correlated with free-flow speed. This correlation is likely due to the fact that area type and

functional class designations reflect the presence of unmeasured factors in the road environmentthat directly effect the free-flow speed. If these unmeasured factors are not included in the free-

flow speed predictive model, then area type and functional class must be included to avoid

confounding the underlying effects with the variables that remain in the model.

For example, the nearly one-to-one correlation between speed limit and free-flow speed

found in Chapter 21 of HCM 2000 is likely due to a confounding between speed limit and other

unmeasured factors. In fact, well-designed studies (discussed previously) have demonstrated that

20

30

40

50

60

70

20 30 40 50 60 70

Speed Limit, mph

Free-Flow

Speed,mph

Rural Arterial Roads

Urban Arterial StreetsUrban Collector Streets

Urban Local Streets

76 urban segments

21 rural segments

40 access points/mile

11

WP 3.0 - 11


14/37

a unit change in speed limit does notproduce a unit change in free-flow speed. A more robust

predictive model would include these other factors (or, at least, area type and class) and a speed

limit coefficient that is much smaller than 1.0.

On-Street Parking

One factor that is not included in the HCM 2010 procedure for predicting free-flow speed

is the presence of on-street parking. On-street parking is frequently provided on urban local

streets and in central business districts (CBDs). Fitzpatrick et al. (17) measured free-flow speeds

at 15 streets with a 30-mi/h speed limit. Those streets with on-street parking had an average free-

flow speed that is 7.5 mi/h lower than those streets without on-street parking. More recently,

Ivan et al. (11) examined free-flow speed data for 272 urban roads. Those roads having on-street

parking that is utilized 50 percent of the time or more were found to have a free-flow speed that

is 2.3 mi/h lower than those roads with less (or no) parking.

The findings noted in the previous paragraph are consistent with the trends shown in

Figure 3, where the urban local streets trend line is shown to be shifted downward from theurban collector streets trend line by about 6 mi/h. It is possible that some of this downward

shift can be explained by the likely presence of parking on the urban local streets.

RESEARCH APPROACH

The research undertaken to achieve the research objective focused on two areas of

evaluation. The first area compared the predicted travel speed from the HCM 2000 and the HCM

2010. The second area compared the level-of-service thresholds in these two manuals. The

details of the approach used in these evaluations is described in the next two sections.

As discussed in the Introduction section, the evaluation is focused determining if there is(a) a bias in results between the two methods and (b) significant inconsistency in results among

the two methods. With regard to the measurement of inconsistency, the inconsistency in results

inherent to the HCM 2000 through its use of subjectively determined urban street class, free-

flow speed, and arrival type is not included in this examination.The evaluation undertaken

herein removes this element of uncertainty in the HCM 2000 results by a priorispecification of

the urban street class, free-flow speed, and arrival type. As a result, the comparisons

documented herein reflect only the inconsistency associated with the underlying modeling

approach or the change to the level-of-service thresholds.

Evaluation of Predicted Travel Speed

The evaluation of predicted travel speed includes two comparison activities. One activity

compares the HCM 2000 with the QEM. The second activity compares the HCM 2000 with the

methodology in Chapter 17 of HCM 2010 (i.e., the Chapter 17 method).

The comparisons are based on the application of each method to a test bed of 27 unique

urban street segments. The characteristics of these segments are provided in Tables 4 and 5.

There are a few variables that are identified in these tables as having computed values. The

WP 3.0 - 12


15/37

method used to compute these values is briefly described in the corresponding footnote to the

tables.

Each of the 27 segments is identified by a case number. The cases shown in Tables 4 and

5 correspond to segments having two through lanes in each travel direction and a volume-to-

capacity v/cratio of 0.90. Additional cases were developed for segments having one throughlane in each direction and a v/cratio of 0.67, 0.75, 0.83, or 0.97. All total, there are 270 case

combinations (= 2 lanes 5 v/cratios 27 cases) represented in the test bed.

The computed delay due to turns into the access point intersections shown in Tables 4

and 5 are based on the computed number of access points and the default delay values provided

in Exhibit 17-13 of HCM 2010. These computed delays are used with the QEM. They are not

used with the Chapter 17 method because this method includes a procedure for computing the

delay due to turns (and does not rely on the default values in Exhibit 17-13). The HCM 2000

does not consider delay due to turns in the determination of running time or travel speed.

The values shown in Tables 4 and 5 describe conditions for the subject direction of travelbeing evaluated. Specifying the conditions for only one travel direction is adequate for HCM

2000 and the QEM. However, the Chapter 17 method requires the specification of conditions for

both travel directions. Therefore, the values shown in the tables are applied to both travel

directions when using the Chapter 17 method.

The signalized intersections bounding the subject segment operate with pretimed control.

Both major-street left-turn movements are provided an exclusive lane and a signal phase. This

phase serves the left-turn movement using a protected-only mode. Both left-turn phases lead the

phase serving the opposing through movement (i.e., lead-lead phasing). The analysis period is

0.25 hours.

The QEM and HCM 2000 methods require as an input variable the volume-to-capacity

ratio for the through movement (in the subject direction of travel) at the upstream signalized

intersection. This ratio is assumed to equal that of the through movement at the downstream

signalized intersection.

The saturation flow rate for the through lane group at the downstream signalized

intersection was computed using the saturation flow rate procedure described in Chapter 18 of

HCM 2010. Notably, adjustments were applied to the base saturation flow rate (shown in

Tables 4 and 5) to account for the proportion of right-turn vehicles, heavy vehicles, and area type

(i.e., CBD or other).

WP 3.0 - 13


16/37

TABLE 4 Characteristics of test bed segments 1 to 14.Variable Variable Value by Case Number

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Segment Data

Through lanes (in one direction) 2 2 2 2 2 2 2 2 2 2 2 2 2 2

Speed limit, mi/h 25 25 25 25 30 30 30 30 35 35 35 35 40 40Segment length, ft 660 990 1320 1980 660 990 1320 1980 660 990 1320 1980 1320 1980

Width of upstream intersection, ft 24 24 36 36 24 24 36 36 24 24 36 36 36 36

Proportion with restrictive median 0 0 1 1 0 0 1 1 0 0 1 1 1 1

Proportion with non-restrictive median 1 1 0 0 1 1 0 0 1 1 0 0 0 0

Proportion with curb on right-hand side 1 1 0.5 0.5 1 1 0.5 0.5 1 1 0.5 0.5 0.5 0.5

Facility area type 1 LU LU U U LU LU U U LU LU U U U U

HCM 2000 class designation IV IV IV IV III III III III III III III III II II

HCM 2000 default free-flow speed, mi/h 30 30 30 30 35 35 35 35 35 35 35 35 40 40

Computed volume, veh/h2 1406 1406 1561 1561 1406 1406 1561 1561 1406 1406 1561 1561 1561 1561

Access Data

Proportion left turns at access points3 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

Proportion right turns at access points 3 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

Access point density, a.p./mi3, 4 34 34 34 34 34 34 34 34 34 34 34 34 34 34

Computed access points on right side 2 3 4 6 2 3 4 6 2 3 4 6 4 6

Computed delay due to a.p. turns, s/veh2,3 0.46 0.69 0.72 1.08 0.46 0.69 0.72 1.08 0.46 0.69 0.72 1.08 0.72 1.08

Intersection Signal Timing Data

Effective green-to-cycle-length ratio 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44

Computed cycle length, s5 60 60 72 108 60 60 60 90 60 60 60 77 60 68

Computed offset, s6 18 27 36 54 15 23 30 45 13 19 30 39 30 34

Intersection Traffic Data

Arrival type 5 5 4 4 5 5 4 4 5 5 4 4 4 4

Through+right lane group v/c ratio 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9

Proportion left turns 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Proportion right turns 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Proportion heavy vehicles 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

Intersection area type CBD CBD other other CBD CBD other other CBD CBD other other other other

Base saturation flow rate, pc/h/ln7 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900

Start-up lost time, s 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5

Computed through+right volume, veh/h2 1265 1265 1405 1405 1265 1265 1405 1405 1265 1265 1405 1405 1405 1405

Intersection Geometry

Through+right lane group lanes8 2 2 2 2 2 2 2 2 2 2 2 2 2 2

Notes:

1 - Facility area type: LU - large urbanized, U - urbanized, T - transition, R - rural.

2 - Calculation is based o a through+right lane group v/c ratio of 0.90.

3 - Values used are based on defaults provided in HCM 2010 Chapter 17.4 - Access point density for segments measuring 5000 ft or more is assumed to equal 10 a.p./mile due to their non-urban area type.

5 - For arrival types 4 and 5, the cycle length is equal to twice the segment travel time at the speed limit; otherwise it is 120 s. The computed cycle

length cannot be less than 60 s or more than 120 s.

6 - For arrival type 4 the offset is equal to one-half of the cycle length. For arrival type 5, the offset is equal to the segment travel time at the speed

limit. For arrival type 3, the offset is set by using the Chapter 17 method in an i terative manner such that the predicted proportion arriving

during green is similar to that obtained using the QEM.

7 - Base saturation flow rate is 1750 pc/h/ln for segments with transition (T) and rural (R) area types; otherwise it is 1900 pc/h/ln.

8 - Includes one shared through and right-turn lane.

WP 3.0 - 14


17/37

TABLE 5 Characteristics of test bed segments 15 to 27.Variable Variable Value by Case Number

15 16 17 18 19 20 21 22 23 24 25 26 27

Segment Data

Through lanes (in one direction) 2 2 2 2 2 2 2 2 2 2 2 2 2

Speed limit, mi/h 40 40 40 45 45 45 45 45 50 50 50 50 50Segment length, ft 2640 5280 7920 1320 1980 2640 5280 7920 1320 1980 2640 5280 7920

Width of upstream intersection, ft 36 60 60 36 36 36 60 60 36 36 36 60 60

Proportion with restrictive median 1 1 1 1 1 1 1 1 1 1 1 1 1

Proportion with non-restrictive median 0 0 0 0 0 0 0 0 0 0 0 0 0

Proportion with curb on right-hand side 0.5 0 0 0.5 0.5 0.5 0 0 0.5 0.5 0.5 0 0

Facility area type 1 U T R U U U T R U U U T R

HCM 2000 class designation II II II I I I I I I I I I I

HCM 2000 default free-flow speed, mi/h 40 40 40 50 50 50 50 50 50 50 50 50 50

Computed volume, veh/h2 1561 1438 1438 1561 1561 1561 1438 1438 1561 1561 1561 1438 1438

Access Data

Proportion left turns at access points3 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

Proportion right turns at access points 3 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

Access point density, a.p./mi3, 4 34 10 10 34 34 34 10 10 34 34 34 10 10

Computed access points on right side 8 5 8 4 6 8 5 8 4 6 8 5 8

Computed delay due to a.p. turns, s/veh2,3 1.44 0.65 1.04 0.72 1.08 1.44 0.65 1.04 0.72 1.08 1.44 0.65 1.04

Intersection Signal Timing Data

Effective green-to-cycle-length ratio 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44

Computed cycle length, s5 90 120 120 60 60 80 120 120 60 60 72 120 120

Computed offset, s6 45 55 25 30 30 40 55 25 30 30 36 55 25

Intersection Traffic Data

Arrival type 4 3 3 4 4 4 3 3 4 4 4 3 3

Through+right lane group v/c ratio 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9

Proportion left turns 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Proportion right turns 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Proportion heavy vehicles 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

Intersection area type other other other other other other other other other other other other other

Base saturation flow rate, pc/h/ln7 1900 1750 1750 1900 1900 1900 1750 1750 1900 1900 1900 1750 1750

Start-up lost time, s 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5

Computed through+right volume, veh/h2 1405 1294 1294 1405 1405 1405 1294 1294 1405 1405 1405 1294 1294

Intersection Geometry

Through+right lane group lanes8 2 2 2 2 2 2 2 2 2 2 2 2 2

Notes:

1 - Facility area type: LU - large urbanized, U - urbanized, T - transition, R - rural.

2 - Calculation is based o a through+right lane group v/c ratio of 0.90.

3 - Values used are based on defaults provided in HCM 2010 Chapter 17.4 - Access point density for segments measuring 5000 ft or more is assumed to equal 10 a.p./mile due to their non-urban area type.

5 - For arrival types 4 and 5, the cycle length is equal to twice the segment travel time at the speed limit; otherwise it is 120 s. The computed cycle

length cannot be less than 60 s or more than 120 s.

6 - For arrival type 4 the offset is equal to one-half of the cycle length. For arrival type 5, the offset is equal to the segment travel time at the speed

limit. For arrival type 3, the offset is set by using the Chapter 17 method in an i terative manner such that the predicted proportion arriving

during green is similar to that obtained using the QEM.

7 - Base saturation flow rate is 1750 pc/h/ln for segments with transition (T) and rural (R) area types; otherwise it is 1900 pc/h/ln.

8 - Includes one shared through and right-turn lane.

WP 3.0 - 15


18/37

Evaluation of Level-of-Service Thresholds

The evaluation of level-of-service thresholds includes two comparison activities. One

activity focuses on an examination of the threshold speed used for each level of service. The

second activity focuses on a comparison of the predicted level of service. The QEM predictions

are compared with those from the HCM 2000. Also, the Chapter 17 method predictions arecompared with those from the HCM 2000.

ANALYSIS RESULTS

This section describes the findings from the evaluation of the HCM 2000 and HCM 2010

methodologies. These findings are separately addressed in two subsections. The first subsection

summarizes the findings from an analysis of predicted travel speed. The second subsection

summarizes the findings from the analysis of level-of-service thresholds.

Findings from Analysis of Predicted Travel Speed

Comparison between QEM and HCM 2000

The predicted travel speeds from the QEM and the HCM 2000 are compared in Figure 4.

Each data point shown corresponds to one of the cases shown in Tables 4 or 5. The figures

illustrate the relationship found for one- and two-lane segments, and volume-to-capacity (i.e, v/c)

ratios of 0.67 and 0.90. The trends for the other v/cratios considered are similar. The line shown

in each figure is an x=y line. If the HCM 2000 predicted travel speed equaled the HCM 2010

predicted travel speed, then the data point would lie on this line.

In general, the data points having with a predicted speed lower than 30 mi/h are

associated with the 21 segments in urban areas having a length of 2640 ft or less and an arrivaltype of 4 or 5. The remaining data points are associated with segments in transition or rural areas

with a length of 5280 ft or more and an arrival type 3.

The trend in the data points suggests that there is a small bias where the QEM predicts a

higher speed for the 21 shorter (i.e., urban) segments and a lower speed for the six longer

segments. With regard to the shorter segments, an investigation into the observed differences

indicated that it was partly due to the QEMs omission of the supplemental adjustment factorfPAin the calculation of the progression adjustment factor. The omission of this factor explained

most of the observed differences for those sites with arrival type 4 (i.e., 15 of the 21 test cases).

Inclusion of this factor in the QEM would result in an increase in the predicted delay and a

reduction in travel speed, which would likely reduce the observed bias in Figure 4.

It was also noted that the remaining six shorter segments have arrival type 5 and are

located in the CBD. Exhibit 10-4 of HCM 2000 indicates that these segments will typically have

significant on-street parking. The discussion in the Background section indicates that the

presence of on-street parking can reduce the free-flow speed by 2.3 to 7.5 mi/h. However, this

effect is not included in the free-flow speed prediction model in the QEM (or Chapter 17

WP 3.0 - 16


19/37

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50

HCM 2000 Travel Speed, mi/h

HCM2

010TravelSpeed(QEM),

mi/h

1

1

0

5

10

15

20

25

3035

40

45

0 10 20 30 40 50


HCM2


mi/h

1

10

5

10

15

20

25

3035

40

45

0 10 20 30 40 50


HCM2


mi/h

1

1

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2


mi/h

1

1

method). Inclusion of this effect in the QEM would result in a reduction in the predicted free-

flow speed and travel speed, which would likely reduce the observed bias in Figure 4.

a. One lane and v/c ratio of 0.67. b. Two lanes and v/c ratio of 0.67.

c. One lane and v/c ratio of 0.90. d. Two lanes and v/c ratio of 0.90.

Figure 4. Travel speed prediction results comparing QEM and HCM 2000.

With regard to the longer segments, an investigation into the observed differences

indicated that it was largely due to the HCM 2000s prediction of a running speed equal to the

free-flow speed for segment lengths of 5280 ft or more. This characteristic was noted in the

discussion associated with Table 1. No evidence could be found in the literature to support this

trend. It is not clear why this characteristic of the HCM 2000 has not been identified or

discussed.

It was also noted that the default access point density values provided in Exhibit 17-24 of

HCM 2010 were creating a relatively high number of access points for some of the test bed

cases. They were particularly high in number for the longer segments. If these default values are

resulting in too many access points, then the QEM and Chapter 17 methods would predict a

longer running time and slower travel speed., which would explain the observed bias.

WP 3.0 - 17


20/37

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2

010TravelSpeed

(methodology),mi/h

1

1

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2

010TravelSpeed

(methodology),mi/h

1

1

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2

010TravelSpeed

(methodology),mi/h

1

1

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2

010TravelSpeed

(methodology),mi/h

1

1

Comparison between Chapter 17 Method and HCM 2000

The predicted travel speeds from the Chapter 17 method and the HCM 2000 are

compared in Figure 5. Each data point shown corresponds to one of the cases shown in Tables 4

or 5. The figures illustrate the relationship found for one- and two-lane segments, and v/cratios

of 0.67 and 0.90.



Figure 5. Travel speed prediction results comparing Chapter 17 method and HCM 2000.

The data shown in Figure 5 show similar trends to those noted for Figure 4. Two of the

three sources of bias identified for the QEM are equally applicable to the Chapter 17 method.

The source that stems from the omission of the supplemental adjustment factorfPAis notapplicable to the Chapter 17 method because this method does not include the progression

adjustment factor as part of the delay calculation (i.e., progression effects are accounted for

using procedures that predict platoon dispersion, decay, and arrival time relative to the start of

green).

The data in Figure 5 tend to exhibit more inconsistency (i.e., variability) than those in

Figure 4. The explanation for the larger variability in Figure 5 is that the Chapter 17 method is

WP 3.0 - 18


21/37


22/37

The standard error is shown in Table 7. The values tend to be fairly constant over the range of

lanes and volume-to-capacity ratios considered.

TABLE 7 Standard error in predicted travel speed.

Comparison1, 2, 3

Through Lanes inSubject Direction

Travel Speed Standard Error (mi/h) by Volume-to-Capacity Ratio0.67 0.75 0.83 0.90 0.97 Average

QEMHCM 2000 One 1.99 1.86 1.72 1.61 1.48 1.73

Two 2.28 2.11 1.92 1.75 1.55 1.92

Chapter 17HCM

2000

One 1.70 1.66 1.72 1.90 2.52 1.90

Two 1.56 1.54 1.50 1.55 1.76 1.58

Notes:

1. QEM: Quick estimation method in Chapter 30 of HCM 2010.

2. Chapter 17: Urban streets methodology in Chapter 17 of HCM 2010.

3. HCM 2000: Urban streets methodology in Chapter 15 of HCM 2000.

Findings from Analysis of Level-of-Service Thresholds

Level-of-Service Threshold Comparison

This subsection describes the findings from an examination of the level-of-service

thresholds used in HCM 2000 and HCM 2010. These thresholds were previously shown in

Tables 2 and 3, respectively.

The examination focused on the speed reduction associated with each threshold. The

speed reduction was computed by subtracting the threshold speed from the associated free-flow

speed. The results are shown in Tables 8 and 9 for the HCM 2000 and HCM 2010, respectively.

For a given class and level of service, the speed reduction values in Table 8 are shown to

vary more widely than those in Table 9. In fact, the variation is so extreme that a speed reduction

value of 0 is shown in Table 8 for level-of-service A and classes II, III, and IV. For these

combinations of class and free-flow speed, it is not possible to achieve level-of-service A. This

characteristic would seem to be undesirable; however, there is no acknowledgment of it or

justification offered in HCM 2000.

The potential for HCM 2010 to indicate a different level of service for a given facility

(than was previously obtained using HCM 2000) can be examined by comparing the speed

reduction for common cells of Tables 8 and 9. For example, consider a Class I facility with afree-flow speed of 55 mi/h. This combination of class and speed is associated with a 13-mi/h

speed reduction for level-of-service A using HCM 2000. However, it is associated with an 8-

mi/h reduction using HCM 2010. The small speed reduction associated with HCM 2010 for this

case will likely increasethe potential for this facility to have a lower level of service when using

HCM 2010.

WP 3.0 - 20


23/37


24/37

facilities will not likely experience a change in level of service, and the number of increases is

likely to equal the number of decreases.

Based on these findings, it is rationalized that the change in thresholds associated with

the HCM 2010 is not likely to result in a level-of-service bias, but it may cause some

inconsistency (i.e., change in level of service) for a small number of facilities. The extent towhich these changes impact a given agency or region will depend on their distribution of

facilities among the various free-flow speed, class, lanes, and arrival type categories.

Predicted Level of Service

This subsection describes the findings from an examination of the predicted levels of

service for the 270 test bed cases. It is noted that these findings reflect the distribution of free-

flow speed and class represented in the 270 cases. These cases are intended to be reasonably

representative of many urban areas. However, it is noted that some speeds, lanes, and arrival

types are not included.

The results reported in this subsection reflect the use of the HCM 2010 methods, as

compared to the HCM 2000 methods. The findings reflect the combined effect of a change in

methodology and a change in level-of-service thresholds.

The distribution of predicted level of service is shown in Table 10. None of the test bed

cases received a level-of-service A. This result is a consequence of the test bed design, and is not

intended to suggest that it is impossible for a facility to receive level-of-service A.

TABLE 10 Level-of-service distribution.

CaseDescription

Method Number of Cases by Level of Service

A B C D E F Average4

All 270 cases QEM 0 56 168 41 5 0 2.98

Chapter 17 0 44 154 54 17 1 3.17

HCM 2000 0 51 155 56 8 0 3.08

Central Business

District cases

(80 cases)

QEM 0 0 19 19 2 0 3.58

Chapter 17 0 0 10 20 10 0 4.00

HCM 2000 0 1 26 12 1 0 3.33

Notes:


2. Chapter 17: Urban streets methodology in Chapter 17 of HCM 2010.3. HCM 2000: Urban streets methodology in Chapter 15 of HCM 2000.

4. Average based on A=1, B=2, C=3, D=4, E=5, F=6.

The top three rows in the table indicate the results for the combined set of 270 test bed

cases. In general, the distributions tend to be very similar among the three methods evaluated.

The last three rows indicate the results for just the CBD cases. These cases tend to have a lower

WP 3.0 - 22


25/37

level of service when using the QEM or Chapter 17 method. However, the CBD distributions for

all three methods tend to be very similar.

The average value shown in the last column of the table is based on the assignment of a

numeric score to each level of service (e.g., A = 1, B = 2, etc.). These averages can be used to

determine if there is a bias in the assignment of level of service. They indicate that, relative tothe HCM 2000, the QEM is slightly more likely to assign a higher level of service and the

Chapter 17 method is slightly more likely to assign a lower level of service.

Another approach to evaluating the predicted levels of service is to compare them on a

pair-wise basis for each test bed case. In this situation, each level of service is assigned a

numeric score (i.e., the same score used to develop Table 10). Then, the two scores are

subtracted for each level-of-service pair. The findings from this comparison are shown in

Table 11. It should be noted that no test bed case experienced a change of more than one level

of service.

TABLE 11 Change in level of service.

Comparison1, 2, 3 Through Lanes in

Subject Direction

Number of Differences in Level of Service by Direction of Change4

Negative Change Positive Change Total

QEMHCM 2000 One 24 9 33

Two 21 10 31

Total: 45 19 64

Total as a percent of

all 270 comparisons:

16.7 7.0 23.7

Chapter 17HCM

2000

One 14 31 45

Two 14 19 33Total: 28 50 78



10.4 18.5 28.9

Notes:




4. Positive change: HCM 2000 predicts better level of service than new method.

The top four rows in Table 11 describe the results for the comparison of the QEM with

the HCM 2000. The data in the last column indicate that 23.7 percent of the 270 test bed casesexperienced a change in one level of service (i.e., 76.3 percent had no change). Most of the

locations that changed were a result of HCM 2010 predicting a better level of service (i.e., a

negative change).

The bottom four rows in Table 11 describe the results for the comparison of the

Chapter 17 method with the HCM 2000. The data in the last column indicate that 28.9 percent of

WP 3.0 - 23


26/37

(5)

the 270 test bed cases experienced a change in one level of service. Most of the locations that

changed were a result of HCM 2000 predicting a better level of service (i.e., a positive change).

The percentage of cases experiencing a change in level of service is higher for the

Chapter 17 method than it is for the QEM. This trend is due to the fact that the QEM is more

similar to the HCM 2000 in terms of the input data and the predictive procedures.

EVALUATION OF PROPOSED MODIFICATIONS

The section describes the development and evaluation of some proposed modifications to

the HCM 2010. These modifications are motivated by the findings described in the previous

section. The modifications are identified in the following list.

! Add the supplemental adjustment factorfPAto the calculation of the progression adjustment

factor (i.e., use Equation 1 instead of Equation 2).

! Add an adjustment to the base free-flow speed calculation that allows for a 3.0 mi/hreduction when on-street parking is present.

! Revise the default access point density values for arterials such that they more accurately

represent the variation in density by area type, cross section, and speed limit.

All three of the modifications in the preceding list would apply to the QEM. Only the last

two modifications would apply to the Chapter 17 method.

The objective in formulating these modifications is to reduce the bias and inconsistency

between the HCM 2010 and HCM 2000. It is not expected that these modifications will fully

eliminate the differences described in the previous section. However, it is expected that theobserved bias and inconsistency will be reduced if these modifications are used. In fact, some

inconsistency is to be expected because of the improvements made in the methodology for the

HCM 2010. These improvements have made the HCM 2010 more sensitive to the influence of a

wider range of variables (e.g., speed limit, access point presence, signal offset, etc.), and

presumably more accurate as a result.

Development of Default Access Point Density Values

This subsection describes the development of revised access point density values. These

values were derived through the statistical evaluation of segment data collected by Fitzpatrick et

al. (17). These data collectively represent 74 segments on urban, suburban, and rural roadways.After some examination of these data, the following model form was found to provide the best fit

to the data.

where

Da= access point density (total for both sides of road), points/mi;

WP 3.0 - 24


27/37


28/37


29/37

0

5

10

15

20

2530

35

40

45

0 10 20 30 40 50


HCM2

010Travel

Speed

(methodology),

mi/h

1

1

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2

010TravelSpeed

(methodology),mi/h

1

1

0

5

10

15

20

2530

35

40

45

0 10 20 30 40 50


HCM2

010Travel

Speed

(methodology),

mi/h

1

1

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50


HCM2

010TravelSpeed

(methodology),mi/h

1

1

The data still show a tendency for the longer segments (i.e., those with a predicted travel

speed in excess of about 30 mi/h) to have a small bias. Specifically, the Chapter 17 method tends

to predict a slower speed than the HCM 2000. Part of the reason for this bias is that the HCM

2000 predicts a running speed equal to the free-flow speed for segment lengths of 5280 ft or

more. This finding is believed to reflect a deficiency in the HCM 2000 method that cannot be

repaired by changing the HCM 2010.

The predicted travel speeds from the modified Chapter 17 method and the HCM 2000 are

compared in Figure 7. These figures can be compared to Figure 5 to visualize the impact of the

modifications. In general, much of the bias has been eliminated by the proposed modifications.

Also, some of the inconsistencies have been eliminated, as indicated by a slightly smaller

variation in the data points.



Figure 7. Travel speed prediction results comparing modified Chapter 17 method and HCM

2000.

WP 3.0 - 27


30/37


31/37



service and travel speed for the 270 test bed cases. As noted in a previous section, these findings

reflect the distribution of free-flow speed and class represented in the 270 cases. These cases are

intended to be reasonably representative of many urban areas. However, it is noted that somespeeds, lanes, and arrival types are not included.

Level-of-Service Threshold Comparison

The results reported in this subsection use the predicted travel speed from the HCM 2000

to compare the HCM 2000 level-of-service thresholds with the HCM 2010 level-of-service

thresholds. This comparison isolates the effect of a change in threshold values on the predicted

level-of-service. The effect of the aforementioned modifications are not reflected in these results.

The distribution of predicted level of service is shown in Table 15. None of the test bed

cases received a level-of-service A. This result is a consequence of the test bed design, and is notintended to suggest that it is impossible for a facility to receive level-of-service A.

TABLE 15 Level-of-service distribution using HCM 2000 with HCM 2010 thresholds.

Case

Description

Method1 Number of Cases by Level of Service

A B C D E F Average2

All 270 cases HCM 2000

w/2010 thresholds

0 57 158 51 4 0 3.01

HCM 2000 0 51 155 56 8 0 3.08

Central Business

District cases(80 cases)

HCM 2000

w/2010 thresholds

0 0 22 17 1 0 3.48

HCM 2000 0 1 26 12 1 0 3.33

Notes:



The top two rows in the table indicate the results for the combined set of 270 test bed

cases. In general, the distributions tend to be very similar among the two methods evaluated. The

last two rows indicate the results for just the CBD cases. It is noted that the CBD cases tend to

have a slightly lower level of service when using the HCM 2010 thresholds. However, the CBD

distributions tend to be very similar.

The top four rows in Table 16 describe the results for the comparison of the predicted

levels of service using the two sets of thresholds. The data in the last column indicate that 13.7

percent of the 270 test bed cases experienced a change in one level of service (i.e., 86.3 percent

had no change). Most of the locations that changed were a result of the HCM 2010 thresholds

predicting a better level of service (i.e., a negative change).

WP 3.0 - 29


32/37

TABLE 16 Change in level of service using HCM 2000 with HCM 2010 thresholds.

Comparison1 Through Lanes in

Subject Direction

Number of Differences in Level of Service by Direction of Change2


HCM 2000

w/2010 thresholds

HCM 2000

One 15 4 19

Two 13 5 18

Total: 28 9 37



10.4 3.3 13.7

Notes:


2. Positive change: HCM 2000 predicts better level of service than HCM 2000 w/2010 thresholds.

Predicted Level of Service


service for the 270 test bed cases. The results reported in this subsection reflect the use of themodified HCM 2010 methods, as compared to the HCM 2000 methods. The findings reflect the

combined effect of a change in methodology and a change in level-of-service thresholds.

The distribution of predicted level of service is shown in Table 17. The distributions did

not change significantly for either the modified QEM or the Chapter 17 method. They were not

expected to change for the HCM 2000 because nothing was changed for this method. For both

the QEM and Chapter 17 method, each level-of-service category tended to change for a small

number of cases.

TABLE 17 Level-of-service distribution using modified HCM 2010.Case

Description

Method Number of Cases by Level of Service

A B C D E F Average4, 5

All 270 cases QEM 0 48 175 43 4 0 3.01

Chapter 17 0 48 156 49 16 1 3.13

HCM 2000 0 51 155 56 8 0 3.08

Central Business

District cases

(80 cases)

QEM 0 0 23 16 1 0 3.45

Chapter 17 0 0 14 18 8 0 3.85

HCM 2000 0 1 26 12 1 0 3.33

Notes:

1. QEM: Quick estimation method in Chapter 30 of HCM 2010.2. Chapter 17: Urban streets methodology in Chapter 17 of HCM 2010.



5. Underlined values represent an improvement relative to the existing HCM 2010.

The average scores in the last column of Table 17 indicate that distributions for both the

modified QEM and the Chapter 17 method were shifted toward that of the HCM 2000, relative to

WP 3.0 - 30


33/37

the unmodified methods. This finding is an indication that the modifications did remove some of

the observed bias in level-of-service prediction.

The top four rows in Table 18 describe the results for the comparison of the modified

QEM with the HCM 2000. The data in the last column indicate that 17.0 percent of the 270 test

bed cases experienced a change in one level of service. This value represents a 6.7 percentimprovement from the existing QEM (= 23.7 - 17.0). A comparison of these results with those in

Table 16 suggests that the methodological differences between the QEM and HCM 2000 resulted

in 3.3 percent of the test bed cases having a different level of service (= 17.0 - 13.7).

TABLE 18 Change in level of service.

Comparison1, 2, 3 Through Lanes in

Subject Direction

Number of Differences in Level of Service by Direction of Change4, 5


QEMHCM 2000 One 19 4 23

Two 13 10 23

Total: 32 14 46



11.9 5.2 17.0

Chapter 17HCM

2000

One 13 24 37

Two 17 20 37

Total: 30 44 74



11.1 16.3 27.4

Notes:




4. Positive change: HCM 2000 predicts better level of service than new method.

5. Underlined values represent an improvement relative to the existing HCM 2010.

The bottom four rows in Table 18 describe the results for the comparison of the modified

Chapter 17 method with the HCM 2000. The data in the last column indicate that 27.4 percent of

the 270 test bed cases experienced a change in one level of service. This value represents about a

1.5 percent improvement from the existing Chapter 17 method (= 28.9 - 27.4). A comparison of

these results with those in Table 16 suggests that the methodological differences between the

Chapter 17 method and HCM 2000 resulted in 13.7 percent of the test bed cases having a

different level of service (= 27.4 - 13.7).

The percentage of cases experiencing a change in level of service is higher for the

Chapter 17 method than it is for the QEM. This trend is due to the fact that the QEM is more

similar to the HCM 2000 in terms of the input data and the predictive procedures. The extent to

which the percentages in Tables 16 and 18 can be used to characterize the changes in level of

service experienced by an agency that applies HCM 2010 to its street system will depend on the

degree to which the 270 test bed cases represent the agencys street system.

WP 3.0 - 31


34/37

SUMMARY OF FINDINGS

This paper describes the findings from a comparison of the urban streets methodology in

HCM 2010 with its counterpart in HCM 2000. The predicted travel speed and level of service

from each methodology are used for this comparison.

The methodology in HCM 2010 represents a fundamental change from that in HCM

2000. Hence, it should be expected that some differences in the predicted travel speed and level

of service will occur for some facilities when using the new methodology.

Many elements of the street environment influence free-flow speed. These factors

include: speed limit, access point density, area type, functional class, median type, curb

presence, and the presence of on-street parking. If these factors are not included in the free-flow

speed predictive model, then their effect on free-flow speed will be confounded with speed limit.

A model that includes speed limit but excludes one or more of these other variables will not

accurately describe the effect of a change in speed limit on a change in free-flow speed.

The comparisons described in this document are based on the application of the HCM

2010 and HCM 2000 methods to a test bed of 27 unique urban street segments. The volume-to-

capacity ratio and number-of-lanes for these base segments were varied to create 270 test bed

cases.

Findings from Analysis of Predicted Travel Speed

The testbed cases were used to compare the HCM 2010 and the HCM 2000 predictions of

travel speed. It was found that the average error (i.e., bias) is typically less than 1.0 mi/h. This

small bias was found to be partly due to (a) the QEMs omission of the supplemental adjustment

factorfPA, (b) the lack of an adjustment for on-street parking on streets in CBDs, (c) a tendencyfor the default access point density values in HCM 2010 to overestimate the number of access

point intersections on longer segments, and (d) the guidance in HCM 2000 to use a running

speed equal to the free-flow speed for segments that are 1.0 mi or longer in length.

The amount bias was found to vary in a systematic manner with volume-to-capacity ratio.

This trend is partly due to the fact that the QEM and Chapter 17 methods include delay due to

turns into access points (and HCM 2000 does not).

The following three proposed modifications to the HCM 2010 methods were developed

based on the findings from the evaluation:

! Add the supplemental adjustment factorfPAto the calculation of the progression adjustment

factor (i.e., use Equation 1 instead of Equation 2).

! Add an adjustment to the base free-flow speed calculation that allows for a 3.0 mi/h

reduction when on-street parking is present.

WP 3.0 - 32


35/37

! Revise the default access point density values for arterials such that they more accurately

represent the variation in density by area type, cross section, and speed limit.

The test bed cases were again used to compare the modified HCM 2010 methods with the

HCM 2000. It was found that the average error was reduced and, for segments with two-lanes in

each travel direction, is typically less than 0.5 mi/h.


The test bed cases were used to compare the HCM 2010 and the HCM 2000 predictions

of levels of service. It is noted that these findings reflect the distribution of free-flow speed and

class represented in the 270 cases. These cases are intended to be reasonably representative of

many urban areas. However, it is noted that some speeds, lanes, and arrival types are not

included. The results of this evaluation are summarized in Table 19.

TABLE 19 Summary of changes in level of service.Method that was Compared to

HCM 2000

Percent of Cases with Change in Level of Service Improvement

PercentHCM 2010 Modified HCM 2010

HCM 2000 with 2010 thresholds 13.7 13.7 not applicable

Quick estimation method (QEM) 23.7 17.0 6.7

Chapter 17 method 28.9 27.4 1.5

Incremental Change by Contributor

Changes to level of service thresholds 13.7 13.7 not applicable

Methodological changes to QEM 10.0 3.3 6.7

Methodological changes to Chapter 17 15.2 13.7 1.5

The first row of Table 19 describes the isolated effect of a change in the level-of-service

thresholds. The data indicate that 13.7 percent of the 270 test bed cases experienced a change in

one level of service (i.e., 86.3 percent had no change). Most of the locations that changed were a

result of the HCM 2010 thresholds predicting a better level of service (i.e., a negative change)

The second row of the table describes the combined effect of a change in methodology

and a change in level-of-service thresholds. Specifically, the use of the QEM resulted in a

change in level of service for 23.7 percent of the 270 test bed cases. When the modified QEM

was used, only 17.0 percent of the cases experienced a change in level of service. By comparingthese results with those in the first row, it follows that the change in methodology for the QEM

resulted in a change in level of service of 10 percent and 3.3 percent for the existing and

modified QEMs, respectively.

The third row of the table also describes the combined effect of a change in methodology

and a change in level-of-service thresholds. Specifically, the use of the Chapter 17 method

resulted in a change in level of service for 28.9 percent of the 270 test bed cases. When the

WP 3.0 - 33


36/37

modified Chapter 17 method was used, only 27.4 percent of the cases experienced a change in

level of service. By comparing these results with those in the first row, it follows that the change

in methodology for the Chapter 17 method resulted in a change in level of service of 15.2

percent and 13.7 percent for the existing and modified Chapter 17 methods, respectively.

REFERENCES

1. Highway Capacity Manual 2010. Transportation Research Board, Washington, D.C., 2010.

2. Highway Capacity Manual 2000. Transportation Research Board, Washington, D.C., 2000.

3. Eidson, W.C. and D.M. Bullock. Analysis of Arrival Type Estimation Procedures.

Transportation Research Record 1776. Transportation Research Board, Washington, D.C.,

2001, pp. 123-127.

4. Rouphail, N.M. Progression Adjustment Factors at Signalized Intersections.

Transportation Research Record 1225. Transportation Research Board, Washington, D.C.,

1989, pp. 8-17.

5. Bonneson, J.A., M. Pratt, and M. Vandehey. Predicting the Performance of Automobile

Traffic on Urban Streets. NCHRP Project No. 3-79. National Cooperative HighwayResearch Association, Transportation Research Board, Washington, D.C., January 2008.

6. Bonneson, J.A., M. P. Pratt, and M.A. Vandehey. Running Time Prediction for Signalized

Urban Streets. Transportation Research Record 2257. Transportation Research Board,

Washington, D.C., 2011, pp. 22-30.

7. Tarko, A.P. and K.C. Sinha. (2001). Model of Free-Flow Speed for Indiana Arterial

Roads. Transportation Research Record 1776. Transportation Research Board,

Washington, DC, pp. 189-193.

8. Florida Department of Transportation. (2002). Quality/Level of Service Handbook. Office of

the State Transportation Engineer, Systems Planning Office, Tallahassee, Florida.

9. Dixon, K., C-H. Wu, W. Sarasua, and J. Daniel. (1999). Estimating Free-Flow Speed for

Rural Multilane Highways. Transportation Research Record 1678. TransportationResearch Board, Washington, DC, pp. 73-82.

10. Dowling, R., W. Kittelson, A. Skabardonis, and J. Zegeer. (1996). Planning Techniques to

Estimate Speeds and Service Volumes - Final Report. NCHRP Project 3-55(2), National

Cooperative Highway Research Program, Washington, D.C.

11. Ivan, J.N., N.W. Garrick, and G. Hanson. (2009).Designing Roads that Guide Drivers to

Choose Safer Speeds. Report No. JHR-09-321. Connecticut Transportation Institute,

University of Connecticut, Storrs, Connecticut.

12. Brown, D.B., S. Maghsoodloo, and M.E. McArdle. (1990). The Safety Impact of the 65

mph Speed Limit: A Case Study Using Alabama Accident Records. Journal of Safety

Research. Vol. 21, No. 4. pp. 125-139.

13. Freedman, M., and J.R. Esterlitz. (1990). Effect of the 65 mph Speed Limit on Speeds inThree States. Transportation Research Record 1281. Transportation Research Board,

Washington, DC, pp. 52-61.

14. Parker, M.R. (1997). Effects of Raising and Lowering Speed Limits on Selected Roadway

Sections. Report No. FHWA-RD-92-084. Federal Highway Administration, Washington,

D.C.

15. TRB. (1998). Special Report 254: Managing Speed - Review of Current Practice for Setting

and Enforcing Speed Limits. Transportation Research Board, Washington, D.C., 1998.

WP 3.0 - 34


37/37

16. Bonneson, J.A. and P.T. McCoy (1997). NCHRP Report 395: Capacity and Operational

Effects of Midblock Left-Turn Lanes. Transportation Research Board, Washington, D.C.

17. Fitzpatrick, K., P. Carlson, M. Brewer, M. Wooldridge, and S-P. Miaou. (2003). NCHRP

Report 504: Design Speed, Operating Speed, and Posted Speed Practices. Transportation

Research Board, Washington, D.C.

wp-3r0 urban streets

Documents