This document summarizes a study on performance measures for two-way, two-lane highways. It discusses the measures and methodologies used over time in the Highway Capacity Manual (HCM), including their shortcomings identified in other research. Alternative performance measures proposed in other studies are also reviewed. The document aims to provide an extensive literature review on capacity and level of service for two-way, two-lane highways, comparing different performance measures and factors affecting capacity estimations.

1. University of Florida
Capacity and Level of Service at Two-
way, Two-lane Highways
Traffic Flow Theory Course Project
Kiarash Fariborzi
December 2015

2. 2
Abstract
This study concentrates on the performance measures of two-way two-lane highways. First, the
measures and methodologies used by HCM over time are discussed, followed by the shortcomings
of these methodologies addressed in the literature, which justifies the need for more research to
develop alternative performance measures. Second, a discussion on the alternative performance
measures proposed on various studies are provided, so are the empirical models relating those
measures to platooning factors such as flow, percentage of heavy vehicles, etc. In addition, a
framework is presented that can be used to compare a set of performance measures based on their
correlation with platooning factors. Finally, recommendations for future research in this area are
provided so as to overcome the drawbacks found in the reviewed studies.

3. 3
1. Introduction
Two-Lane Two-Way Highways (TLTWHW) are undivided roads with two lanes where the
direction of traffic in one is the opposite of that in the other. Two-lane highways comprise the
majority of the road system in the US. Measuring capacity and quality of service of TWTLHW’s
are crucial for planning purposes as well as decision to upgrading them to a multilane highways.
Ever since its first edition, the HCM has offered models estimating TWTLHW capacity. The HCM
method is to come up with a capacity corresponding to the base conditions, and then to account
for the prevailing conditions, adjustment factors are applied. For example, in the HCM 1965 the
capacity of a two-lane highway is estimated 2000 pcph to which two factors are applied capturing
the effects of truck and lane width. However, there are many other contributing factors that are
overlooked such as directional distribution, road environment, presence of no-passing zones,
access points etc. Aside from the analytical approach adapted by the HCM, several studies have
developed simulation models to estimate TWTLHW capacity which attempt to explicitly deal with
the factors that are ignored or implicitly considered in the HCM analyses. Also, since there are a
few TWTLHW’s operating near their capacity, estimation of capacity based on field observation
is not always feasible, hence the need for simulation.
In terms of TWTLHW quality of service, various performance measures are proposed in literature.
Earlier versions of the HCM would use “percent time delay” meaning the percentage of
accumulative travel time of a vehicle spent in queue which is a space-averaged value. The
surrogate measure of percent time delay which could be measured in the field was percentage of
vehicles traveling at headways less than or equal to 5 seconds, recorded at certain points along the
road. More recent versions use “percent time spent following” and the average travel speed. These
performance measures are also reported as the outputs of simulation tools which are capable of
modeling TWTLHW. Several studies have discussed these measures and the HCM procedures.
The intent of this paper is to provide an extensive review of the studies dealing with capacity and
level of service of TWTLHW. It provides a discussion of relevant factors found in literature which
are affecting the TWTLHW capacity estimations and the way they are incorporated in the models.
Furthermore, the various performance measures used in literature as representatives of the level of
service will be compared and contrasted.

4. 4
2. Literature Review
Section 2.1 presents a review of the performance measures, analytical models and procedures of
HCM used to determine the level of service in two-lane highways. Section 2.2 provides the
advantages and shortcomings of the HCM methods addressed in the literature. Section 2.3 goes
over other performance measures relevant to the LOS of two-lane, two-way highways that are
discussed in the literature and can potentially be a substitute for current methods of HCM. Section
2.4 reviews the empirical studies that have compared a few of these performance measures and
their findings regarding the “best” indicator of quality of service.
2.1. HCM Approach
The 1965 HCM presents the capacity and a service measure procedure for two-lane highways.
Accordingly, the quality of service is attributed to a combination of volume-to-capacity ratio and
the operating speed of traffic with six levels (A through F) being defined. Certain conditions such
as passing sight distance and average highway speed are also taken into account in the 1965 HCM
procedure. Furthermore, the capacity of two-lane highways is estimated 2000 passenger car per
hour for both directions combined, regardless of directional split.
The LOS metrics proposed by the 1965 HCM remained unchanged until the subsequent edition of
the HCM in 1985. Meanwhile, Morall and Werner (1982) questioned the criteria of the 1965 HCM
through a study conducted on two-lane rural highways in western Canada. They found that using
HCM, high level of service were obtained in the rural two-lane highways due to relatively low
volumes. But nevertheless, drivers perceived a low level of service. They attributed their finding
to the fact that although vehicles drive with fairly high speed, they are stock in platoons for a long
time with limited opportunity to overtake which causes frustration for road users, hence adopting
a negative perception. Therefore, this study suggests that aside from operating speed and flow, the
time vehicles spend in platoons as well as overtaking opportunities should be reflected in the level
of service of two-lane highways. This notion is adapted in the later edition of the HCM (i.e. 1985
HCM).
In the 1985 HCM two performance measures are used to determine the LOS for two-lane
highways; average upgrade travel speed for specific upgrades and percent time delay (PTD) for
general terrain segment. PTD is defined as the average percent of time that the vehicles are delayed
due to their inability to overtake a slow-moving leading vehicle, which is approximated by a
surrogate measure, that is, the percentage of vehicles driving at headways less than or equal to 5
seconds at certain points along the road segment. Capacity under ideal conditions is estimated
2,800 pcph for both directions. For particular conditions, capacity (i.e. flow rate corresponding to
LOS E) is adjusted for directional split, percent of heavy vehicle, percent of passing zone, lane and
shoulder width, terrain type (in general terrain procedure) and percent grade (in specific grade
procedure).

5. 5
Harwood et al. (1999) did a research to identify the drawbacks of the 1985 HCM through surveying
the HCM users. Their conclusions were threefold: 1) the term “percent time delay” caused
confusion for users, and its surrogate measure based on 5-second headway should be modified, 2)
There should be only one LOS applicable to the sections of the same highway, 3) Design speed as
well as the effect of passing and climbing lanes should be reflected on LOS procedure. To address
these issues thus providing modifications to the next edition of the HCM (i.e. HCM 2000), they
collected data and used TWOPAS models to modify the procedures. As the result, PTD was
renamed as percent time spent following (PTSF), which is a more intuitive term. It is an indicator
of freedom of maneuver and comfort of travel. As for the surrogate measure of PTSF practicable
for field measurements, the simulation study indicated that it can be defined as the percent of
vehicles driving with a headway of 3 seconds or less at a particular point down the roadway.
In the 2000 HCM, the LOS measures are PTSF for class II highways (roads where drivers do not
expect traveling with high speed), and PTSF and average travel speed (ATS) combined for class I
highways (where high travel speeds are expected), thereby making LOS sensitive to design speed,
and in turn, allowing for using the same procedure for both general grade and specific grade
conditions. In this version, “directional segment” procedure is provided for specific up- and down-
grade analysis. Unlike the previous version, the estimation of capacity is irrespective of
distributional split, with 1,700 pcph for each direction and 3,200 pcph for both directions.
2.2. Shortcomings of the HCM methodologies
Various studies are conducted to evaluate the validity of the HCM 2000 methods for two-lane
highways. Lutinnen (2001) applied the 2000 HCM method to the traffic data obtained in Finish
roadways. He found that the HCM overestimate the PTSF, and that the impact of directional split
on PTSF model is higher than HCM estimation whereas the impact of no-passing zone is lower.
He, therefore, recommended that HCM procedure be adjusted for Finish two-lane highways
environment. In addition, it was suggested that an alternative measure based on space headway
should be replaced for oversaturated conditions in that PTSF is based on time headway which
cannot be representative of those conditions. Nevertheless, it is pointed out frequently in the
literature that two-lane highways rarely operate under such conditions.
Romana and Perez (2006) and Lutinnen (2001) pointed out that the HCM 2000 has not proposed
guidelines regarding the location(s) in which headway data collection should be conducted.
Romana and Perez (2006) that sometimes it is not intuitive that in which type (I or II according to
HCM classification of two-lane roads) a road should be categorized, and they question the use of
the same set of thresholds by HCM in determining LOS for all types of two-lane roads. Lutinnen
(2001) mentions that since PTSF is an exclusive measure to two-lane highways, it cannot be useful
for planning purposes as it is not comparable with service measures of multi-lane facilities. For
this reason, it is suggested that the HCM methodology for freeways be extended to multi-lane
highways.

6. 6
Al-Kaisy and Durbin (2008) discussed the inconsistencies of modeling assumptions and the HCM
surrogate measure with the definition of PTSF. In fact, the time a vehicle spends following a lead
vehicle even with short headways should not be considered as PTSF unless the follower has a
higher desired speed than the speed of the lead vehicle. This fact is not taken into account in the
HCM 2000 methodologies, neither in the analytical models nor in the field measurement method.
2.3. Alternative Service Measures
This section provides a review of different approaches presented in the literature in regard to the
LOS of two-lane, two-way roads. Restricting assumptions as well as merits of each method are
also discussed.
Al-Kaisy and Durbin (2008) suggest “percent following” (PF) (or “percent impeded” (PI), so
called by Al-Kaisy and Freedman (2010)) as an alternative to the HCM surrogate measure (i.e.
PTSF). They also come up with two methods estimating PF using field data such as headway and
speed distributions. The first method is called probabilistic method which says that the PF is the
product of two probabilities:
𝑃𝐹 = 𝑃𝑝 𝑃𝑖 (1)
Where 𝑃𝑝 is the probability that a vehicle is traveling in a platoon—platoons are differentiated
based on headway data, and 𝑃𝑖 is the portion of vehicles whose desired speeds are greater than the
speed of the platoon. The former is calculated based on headway distribution. That is, the portion
of vehicles traveling with headways less than 6 seconds (headway data is collected at particular
section(s)). The latter is computed based on the desired speed distribution obtained using headway
data. In other words it is the portion of vehicles that would drive faster than the average speed of
slow-moving vehicles if not impeded (the lead vehicles in platoons). This method is based on the
assumption that the distribution of desired speed of the vehicles inside platoons is identical to that
for vehicles out of platoon as well as platoon leaders (Al-Kaisy and Freedman (2010))
The other method used by Al-Kaisy and Durbin (2008) to estimate PF is called “weighted- average
method”. In this method vehicles are divided to heavy vehicles and passenger vehicle. This method
is based on the assumption that the average speed is weighted average of the speed of passenger
and heavy vehicles, where the weights are the percentage of these two categories. In other words:
𝑆 𝑎𝑡𝑜𝑡 = 𝑆 𝑎𝑝𝑣 𝑃𝑝𝑣 + 𝑆 𝑎ℎ𝑣 𝑃ℎ𝑣 (2)
Where 𝑆 𝑎𝑝𝑣 and 𝑃𝑝𝑣 are the speed and proportion of passenger vehicles, and 𝑆 𝑎ℎ𝑣 and 𝑃ℎ𝑣 are those
of heavy vehicles. Dividing the passenger cars into impeded and not impeded (whose speed is
denoted by 𝑆𝑖𝑝𝑣 and 𝑆 𝑑𝑝𝑣, respectively). Therefore, we have:
𝑆 𝑎𝑡𝑜𝑡 = 𝑆 𝑑𝑝𝑣 𝑃𝑝𝑣1 + 𝑆𝑖𝑝𝑣 𝑃𝑝𝑣2 + 𝑆 𝑎ℎ𝑣 𝑃ℎ𝑣 (3)
𝑃𝑝𝑣 = 𝑃𝑝𝑣1 + 𝑃𝑝𝑣2 (4)

7. 7
In which 𝑃𝑝𝑣1 is the percentage of vehicles driving at their desired speed whereas 𝑃𝑝𝑣2 is the
proportion of passenger vehicles impeded by slow-moving vehicles. The equations above can be
solved for 𝑃𝑝𝑣2 (which is equal to 𝑃𝑝 in the previous method). Assuming that 𝑆𝑖𝑝𝑣 is approximately
equal to 𝑆 𝑎ℎ𝑣, 𝑃𝑝𝑣2 will be calculated easily from the available field data. This method is based on
the assumption that heavy vehicles cannot be impeded by passenger vehicle which needs further
investigations to be validated.
The two methods explained above together with the HCM field estimation method were applied
to field data gathered from three sites. They found that all the three approaches generally result in
comparable PF values and all of them are significantly less than the PTSF estimated using the
HCM analytical models. It was concluded that none of the proposed approaches are superior to the
HCM method.
Romana and Perez (2006) presents an LOS estimation approach based on ATS and PTSF (the
same MOE’s used the HCM methodology). The motivation behind this method was to eliminate
the need for facility classification, and to provide different thresholds considering different road
environments. This method determines a threshold speed as the minimum speed that road users
deem acceptable under heavy traffic conditions, which can be set by polling the users. If the ATS
is more than the specified threshold, PTSF will be used as the measure distinguishing the LOS’s
ranging from A through D; otherwise LOS is determined based on ATS. Figure 1 shows the LOS
ranges based on the threshold speed of 80 km/h. In this method it is not made clear how the ranges
of LOS should be determined, and how the survey for estimating the threshold speed should be
conducted. The authors, however, believe that this method better reflects road users’ perception of
LOS.
Fig. 1. LOS thresholds suggested by Romana and Perez (2006)
Source: Romana, M., & Pérez, I. (2006). Measures of effectiveness for level-of-service assessment of two-lane
roads: An alternative proposal using a threshold speed. Transportation Research Record: Journal of the
Transportation Research Board, (1988), 56-62

8. 8
Cohen and Polus (2011) suggest a theoretical model based on queuing theory for calculating PTSF.
This study assumes that a platoon is a one-server queuing system. Given that, “service time” is the
time interval that a fast vehicle in the second position in platoon drives right behind the first vehicle
in platoon. “Customers” are the vehicles joining the queue. This model uses only headway data as
its input. It is considered an advantage that unlike the HCM model this model is not based on
simulation since the author believes that assumptions regarding driver behavior in passing
maneuvers are not realistic. The model is as follow:
𝑃𝑇𝑆𝐹 =
{
100.
𝑄̅
𝑁̅ + 𝑄̅
𝑖𝑓 𝜋 = 0
100.
𝑄̅ − 1
𝑁̅ + 𝑄̅ − 1
𝑖𝑓 𝜋 = 1 − 𝜌
100.
𝑄2̅̅̅̅
𝑄̅ − 1
𝑁̅ +
𝑄2̅̅̅̅
𝑄̅ − 1
𝑖𝑓 𝜋 = 𝑃𝑟𝑜𝑏(𝑄 = 2)
(5)
Where the parameters of the model 𝑄̅ and 𝑁̅ that are average number of headways inside a platoon
and average number of headways between two platoons, respectively. 𝜋 is the probability that a
free-moving vehicle will create a platoon. This parameter is unobserved from field data.
The assumptions in this method are as follow:
1. Service time should not exceed the inter-arrival time.
2. An M/M/1 queuing model is assumed to apply to this queuing system, implying that the
headway distribution must be exponential and the flow should be relatively low.
3. Platoons are distinguished based on headways greater than or equal to 3 seconds.
4. Number of headways in queue (Q) (i.e. queue length) follows a geometric distribution. This
should be verified using chi-square test.
𝑃𝑟𝑜𝑏 (𝑄 = 𝑖) = (1 − 𝜌). 𝜌𝑖−1
𝑖 = 1,2,3, … (6)
𝜌 = 1 −
1
𝑄̅
Where 𝜌 is traffic intensity, and 𝑄̅ is the average number of headways in platoon.
5. Drivers are assumed to overtake as soon as a suitable gap is available, so presence of no-
passing zones are ignored in the model.
This model was applied to the field data and the estimated PTSF was plotted against flow as
shown in diagram below. Each data point corresponds to a 1-hour headway data. It is seen that
the estimated values are significantly less than the estimation of the analytical model of HCM
2000. This finding is consistent with other studies comparing HCM analytical models for PTSF
estimation with the PTSF estimated from field data.

9. 9
Fig. 2. Empirical model relating PTSF to flow developed by Cohen and Polus (2011)
Source: Cohen, M., & Polus, A. (2011). Estimating percent-time-spent-following on two-lane rural
highways. Transportation research part C: emerging technologies, 19(6), 1319-1325.
2.4. Comparison of Performance Measures
Regarding the comparison of performance measures, a few methodologies have been proposed in
literature. One of these methodologies (Al-Kaisy and Karjala (2008), and Al-Kaisy and Freedman
(2010)) is based on exploring a relationship between these measures and such platooning factors
as traffic flow in the direction of travel, opposing traffic flow, percent heavy vehicle, standard
deviation of free-flow speed, presence of no-passing zone. To figure out this relationship, this
method uses correlation analysis and/or regression analysis where the measures are dependent
variables and the platooning factors are explanatory variables. Subsequently, an F-test will be
carried out to compare the regression model with the bench mark model (i.e. constant-only model).
Based on the r-squared value of the regression model, the suitability of performance measures are
evaluated, and the t-value of the platooning factors (i.e. the independent variables of the model)
indicates the contribution of that factor to platooning. This methodology assumes that platooning
is the major indicator of operational performance in two-way two-lane highways.
Al-Kaisy and Karjala (2008) explored the correlation of platooning factors with six indictors of
quality of service, namely average travel speed, average travel speed of passenger cars, average
travel speed as a percentage of free flow speed, average travel speed as a percentage of free flow
speed for passenger cars, percent follower and follower density. Percent follower was calculated
using 3-second cut-off point as the criterion to distinguish between platoons. Follower density by
definition is the “number of followers in a directional traffic stream over a unit length”. The
surrogate measure of that for field measurement could be determined based on occupancy
percentage of traffic detectors, or based on measuring flow and speed and usage of fundamental
formula. The regression analyses are conducted both within each of the sites and across the sites.

10. 10
Regarding across-site examination, the F-test showed that except for the regression models
corresponding to percent follower and follower density, the other four regression models were not
better than the base model according to the F-test results. The regression model corresponding to
follower density had the highest r-squared value. Accordingly, It is concluded that among the
measures studied, follower density is best correlated with platooning factors followed by percent
follower (currently used by HCM), and that traffic flow in direction of travel is the best indicator
of platooning with having the only statistically significant t-value in the models. Also, it is pointed
out that follower density is superior to percent follower in that it is reflective of traffic level
whereas percent follower is not. That is, a traffic flow with low AADT could have the same percent
follower value as a high-AADT traffic flow if say the variability in latter was higher than that in
former. In this situation one would expect that the low-AADT flow should have a lower LOS than
the high-AADT one, but percent follower alone cannot capture that. Therefore, follower density
represents the quality of flow better than percent follower does, and in turn, this study suggest the
use of follower density as the performance measure of two-way two-lane highways. This measure
is currently used as the LOS measure in South Africa (Van As (2003)). A shortcoming of the study
is that the transformed version of dependent variable were not experimented in analysis, which
implies that a curvilinear relationship between platooning factors and performance measures is not
investigated.
In a similar study conducted by Al-Kaisy and Freedman (2010), beside the performance measures
experimented by Al-kaisy and Karjala (2008), another measure called percent impeded (PI) (PI is
discussed in the preceding section) is tested. Unlike Al-Kaisy and Karjala (2008), Al-Kaisy and
Freedman (2010) found that the corresponding regression model to PI has by far the highest r-
squared value followed by percent follower, follower density and ATS/FFS. The flow of the same
and opposing direction of travel turned out to be significant in the regression model of PI and
follower density whereas it is insignificant in the other two models. This is consistent with the
notion that percent follower and ATS/FFS are not necessarily dependent on traffic flow level (Al-
Kaisy and Karjala (2008)).
Polus and Cohen (2009) proposed and evaluated five parameters that could be indicators of the
quality of flow by developing theoretical models based on the queuing theory. The model
parameters include number of headways inside and outside platoon, which are easy to observe in
the field. In-platoon headways based on the HCM suggestion are assumed 3 seconds although
other studies (e.g. Alkaisy and Durbin (2008)) used headway of 6 sec to distinguish platoons. PTSF
was one of the parameters studied. In comparison to the HCM model, this model predicts lower
PTSF values, which is consistent with the premise mentioned frequently in the literature (e.g. Al-
Kaisy and Durbin (2008)) that HCM overestimates PTSF. Furthermore, the issue of defining a
surrogate measure for PTSF for field observation does not exist in this model in that it relates PTSF
to headways observed in the field. Furthermore, this study maintains that “freedom of flow” is the
best indicator of level of service. Freedom of flow by definition is the ratio between the average
travel time between platoons and the expected time that the first vehicle behind a slow-moving

11. 11
vehicle in the platoon spends before finding a suitable gap to overtake, so the higher the freedom
of flow, the higher the LOS.
3. Conclusions
LOS concept was first introduced in the 1965 HCM suggesting that quality of flow for two-lane
two-way highways should be measured based on the operating speed and volume-to-capacity ratio
taking into account the impact of passing sight distance and the average speed. In this version of
HCM, capacity was estimated 2,000 pcph for both directions irrespective of directional
distribution. Travelling in platoons for a long time without having enough passing opportunity
causes frustration for drivers which should be reflected in LOS (Morall and Werner (1982)).
However the LOS measures used by the 1965 HCM cannot take that into account.
In the 1985 HCM, two different set of models for specific grade and general terrain were proposed
which caused confusion for HCM users arguing that one procedure should apply to all the sections
of the same roadway, and that two methods would result in different LOS for the same section
(Harwood et al. (1999)). Two service measures (i.e. percent time delay (PTD) and average travel
speed) were used by the 1985 HCM admitting that measurement of PTD in the field is not feasible,
hence suggesting a surrogate measure which would differentiate between platoons using headways
of 5 seconds or more. The 1985 HCM estimates 2,800 pcph as the maximum flow rate of a two-
lane highway corresponding to a 50/50 split.
The 2000 HCM proposes LOS models for two classes of highways, and for two-way and
directional segments. Percent time spent following (PTSF) and average travel speed (ATS) are
used as performance measures for type I highways whereas PTSF alone is the determinant of LOS
for type II highways. The surrogate measure of PTSF is based on 3- second headways. The 2000
HCM estimate the capacity as 1,700 for each direction and 3,200 for both directions combined
regardless of directional split.
An issue associated with the surrogate measure of PTSF is that it suggests that all the vehicles in
platoon desire to overtake if a suitable gap is found. But in fact, even in presence of a long gap,
they overtake as long as the speed of the platoon is less than their desired speed. This results in
overestimation of PTSF. This notion has also been confirmed by the empirical studies (Lutinnen
(2001), and Al-Kaisy and Durbin (2008)) saying that the PTSF estimated based on the surrogate
measure is less than the HCM analytical model estimation.
Given the shortcomings of the measures suggested by HCM, the following studies have
recommended alternative measures which partly deal with these shortcomings:
1- Given the headway and speed data and desired speed distribution, Al-Kaisy and Durbin
(2008) come up a method to calculate a measure called “percent impeded” as the surrogate
measure for PTSF that deals with the issue stated above.

12. 12
2- To eliminate the need for classifying roads and account for unique road environments,
Romanna and Perez (2006) offers a methodology for evaluating LOS in Spanish roads
using the same performance measures as HCM but a different way of determining the LOS
boundaries.
3- An alternative approach to estimate PTSF using field data is proposed by Cohen and Polus
(2011) based on queuing theory which has quite a few simplifying assumptions.
Nevertheless, the PTSF estimation of this method using headway data collected in Israel is
less than the PTSF estimated by HCM, so it could solve the issue of HCM PTSF
overestimation.
4- To deal with overestimated values of PTSF by the HCM models, Polus and Cohen (2009)
developed a PTSF model whose parameters were number of headways inside and out of
platoon, which are easy to observe in the field as well.
5- A model based on “Freedom of flow” as a measure explaining quality of flow was
established and evaluated by Polus and Cohen 2009.
Al-Kaisy and Karjala (2008) provided a framework for comparison of quality of service measures
based on regression and/or correlation analysis where the independent variables are the measures
to be tested, and the dependent variables are platooning factors such as traffic flow, percent heavy
vehicle, presence of no-passing zone, etc. Based on the r-squared value of the regression model,
the most suitable performance measure will be selected. This framework was applied to field data
by Al-Kaisy and Karjala (2008) and Al-Kaisy and Freedman (2010) who found follower density
and percent impeded as the best indicator of quality of flow, respectively.
4. Recommendations
Almost all the studies comparing the PTSF estimated by HCM analytical models and the surrogate
measure of PTSF for field calculations mentioned that there is inconsistencies between them, and
that the analytical models overestimate PTSF. This should be considered in later versions of HCM.
There is inconsistencies between the minimum time headways used in different studies to
differentiate between platoons. For example, Cohen and Polus (2011) went with 3-second merely
because it is suggested by HCM 2000 whereas Al-Kaisy and Durbin (2008) used 6 seconds since
they believed that the interaction between the lead and the following vehicle vanishes when their
headway exceeds 6 seconds. Also it should be noted that HCM 1985 uses 6-second headway as
the cut-off point of platoons whereas in HCM 2000 this value has decreased to 3 seconds.
Therefore, as for future research, it is recommended that a systematic study be conducted to
provide a more objective guideline for headway cut-off point.
Different countries suggest different methodologies and/or performance measures for LOS
evaluation. For instance, in South Africa follower density is used as the performance measure of
two-way, two-lane highways (Van As (2003)), or In Germany average travel speed is used as they

13. 13
care more about the functionality of their facilities than comfort of the road users (Brillon and
Weiser (2006)). Therefore, different countries can independently do studies on two-way, two-lane
highway performance considering their own concerns rather than blindly following the HCM
propositions.
5. References
1. Manual, H. C. (1965). Highway capacity manual. Washington, DC.
2. Manual, H. C. (1985). Highway capacity manual. Washington, DC.
3. Manual, H. C. (2000). Highway capacity manual. Washington, DC.
4. Morrall, J. F., & Werner, A. (1982). Measurement of level of service for two-lane rural
highways. Canadian Journal of Civil Engineering, 9(3), 385-398.
5. Brilon, W., & Weiser, F. (2006). Two-lane rural highways: the German
experience. Transportation Research Record: Journal of the Transportation Research
Board, (1988), 38-47.
6. Luttinen, R. (2001). Percent time-spent-following as performance measure for two-lane
highways. Transportation Research Record: Journal of the Transportation Research
Board, (1776), 52-59.
7. Al-Kaisy, A., & Durbin, C. (2008). Evaluating new methodologies for estimating
performance on two-lane highways. Canadian Journal of Civil Engineering,35(8), 777-
785.
8. Van As, C. (2003). The development of an analysis method for the determination of level
of service of two-lane undivided highways in South Africa. Project Summary, South
African National Roads Agency, Limited, Pretoria.
9. Polus, A., & Cohen, M. (2009). Theoretical and empirical relationships for the quality of
flow and for a new level of service on two-lane highways. Journal of Transportation
Engineering, 135(6), 380-385.
10. Cohen, M., & Polus, A. (2011). Estimating percent-time-spent-following on two-lane
rural highways. Transportation research part C: emerging technologies,19(6), 1319-
1325.
11. Romana, M., & Pérez, I. (2006). Measures of effectiveness for level-of-service assessment
of two-lane roads: An alternative proposal using a threshold speed. Transportation
Research Record: Journal of the Transportation Research Board, (1988), 56-62.
12. May, A. D., Anderson, I. B., Leiman, L., & Archilla, A. R. (1999). Capacity and quality
of service of two-lane highways. Kansas City, MO: Midwest Research Institute.
13. Al-Kaisy, A., & Karjala, S. (2008). Indicators of Performance on Two-Lane Rural
Highways: Empirical Investigation. Transportation Research Record: Journal of the
Transportation Research Board, (2071), 87-97.
14. Al-Kaisy, A., & Freedman, Z. (2010). Estimating performance on two-lane highways:
Case study validation of a new methodology. Transportation Research Record: Journal
of the Transportation Research Board, (2173), 72-79.