TEMPORARY LOSSES OF HIGHWAY CAPACITY AND IMPACTS ON PERFORMANCE: PHASE 2

Title | Contents | Acknowledgements | Exec. Summary
1. Intro | 2. Approach | 3. Crashes | 4. Breakdowns | 5. Work Zones | 6. Weather | 7. Signal Timing
8. RR Crossings | 9. Toll Facilities | 10. PUD | 11. Results Summary | 12. Next Steps | 13. References

7.  Sub-optimal Signal Timing

7.1  Methodology

Capacity reduction and delay on principal arterials due to sub-optimal signal control were estimated using a three-step process.  The first step was to determine the number and type of signals on principal arterials. The next step was to estimate the total vehicle delay at these intersections, since traffic signals cause delay in comparison to free-flowing traffic. However, most of this delay is un-avoidable.  The third step was to estimate the avoidable delay due to sub-optimal signal timing.  Delay due to sub-optimal signal timing was estimated as a percent of the total delay based on evidence from the literature.  Capacity reduction was calculated in a similar manner.  However, since HPMS provides capacity estimates, it was not necessary to estimate intersection capacities. 

The primary data source for estimating signal control delay was the HPMS Sample Database.  The HPMS Sample Database contains the following information used to calculate traffic signal delays:

• Annual Average Daily Traffic (AADT)
• Directional Factor
• Prevailing Type of Signalization
• Typical Peak Percent Green Time
• Number and Type of At-Grade Signal-Controlled Intersections
• Peak Capacity
• Volume/Service Flow Ratio (V/SF)

Other data sources used in this part of the study are noted in the methodology descriptions that follow.

7.1.1  Identifying Signal-Controlled Intersections on Principal Arterials

The HPMS Sample Database provides a count of the number of intersections and traffic controls on the nation's roadways.  These include at-grade intersections at entrances to shopping centers, industrial parks, and other large traffic-generating enterprises.  The database also provides information on the type of signal control used at each intersection.  Expansion factors were applied to the totals from the Sample Database to estimate the number of signal-controlled intersections on principal arterials (see Table 29 in Section 7.2.2).

7.1.2  Estimating Total Delay for Signal-Controlled Intersections

Delay at signal-controlled intersections on principal arterials was estimated based on a methodology outlined in the Highway Capacity Manual 2000.  According to Chapter 16 in the manual, the average delay per vehicle for a lane group at a controlled intersection is given by the following equation:

Equation 23:

d = d₁ × PF + d₂ + d₃

where

d = control delay per vehicle (seconds/vehicle)

d₁ = uniform control delay, assuming uniform arrivals (seconds/vehicle)

PF = uniform delay progression adjustment factor that accounts for the effects of signal progression

d₂ = incremental delay to account for the effect of random and over-saturation queues, adjusted for the duration of the analysis period and the type of signal control (seconds/vehicle). This delay component assumes that there is no residual demand for the lane group at the start of the analysis period.

d₃ = supplemental delay to account for over-saturation queues that may have existed prior to the analysis period (seconds/vehicle)

Thus, the total control delay per vehicle was the sum of the uniform control delay, the incremental delay, and the supplemental delay.  Each of these was estimated on an hourly basis, using time-of-day distributions for a week.  Daily average delay was calculated and multiplied by 365 to calculate the delay for an entire year.  The methods used to estimate each type of delay are described in the following sections.

Uniform Delay

The next equation gives an estimate of delay, assuming uniform arrivals, stable flow, and no initial queue.  It is based on the first term of the delay formulation suggested in the Highway Capacity Manual 2000 and is widely accepted as an accurate depiction of delay for the idealized case of uniform arrivals.

Equation 24:

where

d₁ =  uniform control delay, assuming uniform arrivals (seconds/vehicle)

C = cycle length (seconds). Cycle length is used for pre-timed signal control; average cycle length is used for estimating actuated control parameters.

g = effective green time for a lane group (seconds). Green time is used for pre-timed signal control; average lane group effective green time is used for actuated control.

X = volume/capacity ratio or degree of saturation for a lane group

Effective green time and capacity were obtained from HPMS Sample Data.  The volume data used in the volume/capacity ratio was calculated by applying a time-of-day distribution to the AADT data given in HPMS.  For urban intersections, this distribution was based on a study of four cities:  San Antonio, Texas; Milwaukee, Wisconsin; San Diego, California; and Seattle, Washington (see footnote 4 on page 17).  For rural intersections, the distribution was based on hourly traffic counts in the state of Tennessee (T.DOT). Cycle length was calculated based on a methodology described in Revised Monograph on Traffic Flow Theory (U.S. DOT/FHWA 1997).

As shown in equation 23, uniform delay (d₁) is adjusted using a uniform delay progression adjustment factor (PF) that accounts for the effects of signal progression.  A suggestion of the Highway Capacity Manual 2000 was followed in using a progression adjustment factor based on Arrival Type 3 (AT-3) for uncoordinated lane groups and Arrival Type 4 (AT-4) for coordinated lane groups.  These guidelines are provided for planning situations where the arrival characteristics cannot be directly observed.  Thus, they should be suitable for our purposes.

Incremental Delay

The next equation was used to estimate the incremental delay due to non-uniform arrivals and temporary cycle failures (random delay), as well as delay caused by sustained periods of over-saturation (over-saturation delay).  Such delay is sensitive to the degree of saturation of the lane group (X), the duration of the analysis period (T), the capacity of the lane group (c), and the type of signal control, as reflected by the control parameter (k). The equation assumes that there is no unmet demand that causes residual queues at the start of the analysis period (T).

Equation 25:

where

d₂ = incremental delay to account for the effect of random and over-saturation queues, adjusted for the duration of the analysis period and the type of signal control (seconds/vehicle). This delay component assumes that there is no residual demand for the lane group at the beginning of the analysis period.

T = duration of analysis period (hours)

k = incremental delay factor that is dependent on controller settings

l = upstream filtering/metering adjustment factor

c = lane group capacity (vehicles/hour)

X = lane group volume/capacity ratio or degree of saturation

Since delay was calculated on an hourly basis in this study, T was equal to 1. The upstream filtering/metering adjustment factor (l) was also set to 1, because there is no information that would allow it to be calculated. The incremental delay factor (k) was set to 0.5 for pre-timed control, the value suggested by the Highway Capacity Manual 2000. The incremental delay factor for actuated control was based on the extension value and the degree of saturation and ranged from 0.04 to 0.5. The degree of saturation was taken from HPMS. Since timing plans for each signal are not available, an extension of 3 seconds was assumed for actuated controls. This yielded k values ranging from 0.11 to 0.50.

Supplemental Delay

When a residual demand from a previous time period causes a residual queue to occur at the start of the analysis period (T), additional delay is experienced since the residual queues must clear the intersection first.  A procedure to determine this supplemental delay is described in detail in Appendix F of the Highway Capacity Manual 2000.  This procedure is also extended to analyze delay over multiple time periods where a residual demand may be carried from one time period to the next.  Due to the lack of information on queue formation, a value of zero was used for supplemental delay (d₃).

7.1.3  Typical Delay Associated with Sub-optimal Signal Timing

According to the Institute of Transportation Engineers (ITE), there are about 300,000 traffic signals in the United States.  Over 75 percent of these signals could easily be improved by updating equipment or by simply adjusting their timing.  The total number of signal-controlled intersections specified in this ITS study is consistent with the total number of signal-controlled intersections estimated based on the HPMS Sample Database.

According to FHWA's Arterial Management Benefits database, approximately a 15–20 percent reduction in delay can be achieved by signal-timing updates and/or improvements.  Up to a 40 percent reduction in delay can be achieved by implementing automated signal control.  This study based its estimates of delay due to sub-optimal signal timing on the percentage of delay reduction that can be realized from improving signal timing. 

In order to be conservative in estimating delays, the TLC2 study assumed signal timing to be inadequate at 50 percent of signals, rather than the 75 percent estimated by ITE.  Furthermore, it was assumed that a 15 percent reduction in delay could be achieved by correcting these signals.  This is at the lower end of the range estimated by the FHWA Arterial Management Benefits database.

7.1.4  Typical Capacity Loss Associated with Sub-optimal Signal Timing

According to the ITS Deployment Analysis System (IDAS) User's Manual (Cambridge Systematics, Inc., 2001), updated and improved signal timing can increase capacity at signal-controlled intersections by about 8–23 percent.  The amount of improvement depends on traffic condition, time since the last signal-timing update, and intersection densities.  This study assumed that signal control could be improved on 50 percent of the signals and that a 10 percent increase of intersection capacity could be achieved.  Again, the assumptions were intended to be conservative.

7.2  Results

7.2.1  Delay Due to Sub-optimal Signal Control

Based on HPMS data, this study estimates that, in 1999, the nation's highway system employed signalized control at 306,177 intersections, 106,859 of which were utilized on principal arterials.  The delay from sub-optimal signal controls on principal arterial intersections is estimated at 295.8 million vehicle-hours (Table 28).  As expected, the lion's share of this delay (over 97 percent) occurred on urban principal arterials since urban streets contain more signalized intersections. In addition, most of this delay (about 61 percent) occurred during off-peak periods.

Figure 24. Delay from sub-optimal signal timing was greatest in very large urban areas.

Figure. 25. Most delay from sub-optimal signal timing occurred during off-peak periods.

7.2.2 Capacity Losses Due to Sub-optimal Signal Control

The TLC2 study estimates that capacity loss on principal arterials due to sub-optimal signal control was nearly 173 billion vehicles in 1999 (Table 29).  Again, about 97 percent of this reduction occurs on urban principal arterials.  Capacity losses estimated for signal timing are much larger than capacity losses associated with crashes and vehicle breakdowns.  This is because capacity losses at signal-controlled intersections occur 24 hours a day 365 days a year, regardless of demand.  Therefore, these reductions occur but have less actual impact. The durations for the capacity losses associated with crashes and vehicle breakdowns, on the other hand, are much shorter, and they often coincide with high traffic volumes.

7.3 Reliability

7.3.1 Methodology

The TLC2 study uses methodologies suggested by the Highway Capacity Manual to calculate delay at signal-controlled intersections. These methods are used by most traffic engineers within the United States and are well established. The delay estimates generated by these methodologies are qualified as having a high degree of confidence.

7.3.2 Data & Key Assumptions

The signal and traffic operation information used to estimate delay at signal-controlled intersections is based on "Sample" data from HPMS. This HPMS data is used extensively in the analysis of highway system condition, performance, and investment needs that make up the biennial Condition and Performance Reports to Congress. This data is accorded a high level of confidence.

Signal parameters that could not be inferred from HPMS data were based on values suggested by the Highway Capacity Manual were used. These parameters are accorded a high level of confidence.

The Institute of Transportation Engineers (ITE) estimates that signal timing is inadequate at 75 percent of all intersections in the U.S. In order to be conservative, TLC2 assumes 50 percent of the national's signal controlled intersections have inadequate signal timing. This is qualified as having a medium degree of confidence.

FHWA's Arterial Management Benefits database indicates that approximately 15–20 percent delay reductions can be achieved by signal-timing updates and/or improvements.  This information is based on numerous recent studies across United States. In order to be conservative, TLC2 assumes a 15 percent reduction in delay. This is qualified as having a high degree of confidence.

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