Traffic Analysis Toolbox Volume VI:
Definition, Interpretation, and Calculation of
Traffic Analysis Tools Measures of Effectiveness

5.0 Critique of Current MOE Estimation Methods

This chapter highlights the limitations of current MOEs and their computation.

5.1 Limitations in How MOEs Are Currently Computed

Our ability to measure the MOEs in the field and the ability of simulation tools to estimate the MOEs are both severely strained by extreme congestion (see Table 27 and Table 28).

Table 27. Strengths and Weaknesses of Common MOEs

MOE	Strengths	Weaknesses
HCM Level of Service	Widely known and used. Readily understood by Decision-Makers. Most LOSs can be either estimated or measured in field.	Totally loses sensitivity once LOS "F" (capacity) is reached. LOS measures not available for many situations (e.g., local residential streets, rural highways with signals, etc.). Average delay, average density used in LOS, miss hot spots. Misleading on extent of time which given LOS is present at location in network (peak 15 minutes versus 2½ hours.
Volume/Capacity	Readily understandable. Gives indication of how close to breakdown.	Expensive to measure in field once v/c 1(must gather queue data).
Travel Time	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field.
Speed	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field.
Delay	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field. Definitional issues.
Queue	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field. Definitional issues.
Stops	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field. Definitional issues.
Density	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field. Definitional issues.
Travel Time Variance	Can be directly measured in field. Indicates relative benefits of alternatives.	Must be related to some standard in order to determine if result is good or bad. Expensive to measure in field. Definitional issues.

 

Table 28. Common Limitations of MOEs in Practice

MOE Building Blocks of Performance Measurement Systems	Limitations
Travel Time	Treatment of delays and travel time for incomplete trips or trips that cannot start within the analysis period is an issue. Difficult for a decision-maker to interpret (no value of time is obviously too high or too low without knowing more about the trip characteristics).
Speed	Treatment of incomplete or un-begun trips is an issue, as for travel time. Interpretation is facility specific. Low speed may be quite acceptable on an arterial, but not on a freeway. Once all vehicles come to a stop, the mean speed conveys no further information on the severity of congestion (speed cannot go below zero). Speed is a poor indicator of how close the facility is to breakdown (capacity).
Delay	Treatment of incomplete trips or trips that have not started is an issue. Definition of free-flow speed, against which delay is measured, is a problem. Some use the posted speed limit for the free-flow speed; others use the mean speed under very low flow conditions (can be higher or lower than the posted speed limit).
Queue	Definition of when vehicle joins a queue and when it leaves a queue is a problem. Interpretation is road segment and facility specific. Queues are normal for signals, but queues that overflow turn bays or block cross streets are not desirable. Tallying of queued vehicles unable to enter the road segment is an issue for many tools. Many tools cannot report a queue longer than the storage capacity of the road segment or turn bay. Tallying of vehicles, which have not been able to enter the road network during the analysis period, is an issue.
Stops	Definition of what minimum speed is a stop is an issue. (One reviewer has recommended that stop time be tallied only for full stops, zero mph, to better match two-fluid models of traffic flow.) Since tallying of stops is normally suspended while a vehicle is moving up within a queue, the definition of a queue is an issue. Once all vehicles are queued on a road segment, further increases in congestion have no effect on stops.
Density	Once all vehicles are queued, then further increases in congestion have no effect on density.
Travel Time Variance	Rarely used due to difficulty of computation. Prediction tools are close to non-existent. Once all vehicles are queued on a road segment, the variation in travel time tends to drop towards zero. Variance will tend to peak when the volume is around capacity.

 

MOE Indicators of Performance	Limitations
HCM Level of Service	HCM LOS is designed to convey how close the facility is to reaching capacity or unacceptable LOS. Once LOS "F" reached, HCM LOS letter grades give no further information on relative severity of different degrees of congestion. HCM LOS ratings do not exist for several situations: roundabouts, collector/distributor roads, local residential streets.
Volume/Capacity	Cannot measure in field or simulate volumes passing a given point that are greater than capacity (measured v/c is always less than 1.00). In such situations, must add to the measured flow rate the buildup in the queue.

Under severe congestion conditions it is very difficult to study a large enough geographic area over a long enough analysis period to ensure that congestion does not extend back beyond the limits of the study area and congestion is not present at the start or the end of the analysis period. Thus most simulation modeling of severe congestion conditions usually has queues that extend beyond the temporal and physical limits of the model.

Failure to include in the MOEs the queues that stretch beyond the geographic and the temporal bounds of the study area will bias the computation of travel time, speed, and delay, making capacity improvements within the study area appear to perform worse than no improvements.

There also are problems with reporting queues that extend beyond the turn bay and/or beyond the link. Only one simulation tool will track the buildup of queues beyond the subject link, and none of them will track congestion beyond the temporal or geographic limits of the model. With one exception, the reported queue is, by definition, never longer than the storage capacity of the turn bay or the link. Thus, the analyst cannot rely upon the reported queue length to identify queue overflow problems. The analyst must find the upstream links and review the reported queues there.

5.2 Inherent Limitations of Current MOEs

Most MOEs are satisfactory measures of traffic performance for uncongested conditions. Travel time, delay, queues, stops, density, and travel time variance all increase as traffic demand increases relative to capacity and traffic operations worsen.

Among these MOEs, speed is a less satisfactory indicator of how close a facility is to breakdown, because speed is comparatively insensitive to changing traffic flow rates until capacity is reached.

Most all of the MOEs tend to break down under extreme congestion conditions. Speed, density, stops, and travel time variance are invariant under "parking lot" conditions where no movement is possible (speed equals zero, density equals jam density, and travel time variance is zero). The only MOEs that continue to function under parking lot conditions are travel time and delay, which continue to increase over the length of the analysis period.