Understanding & Using Measures of Effectiveness (MOEs)
December 30, 2009
by Jon Meusch, PE and Mark Rodgers
When developing timing for traffic controllers we often wish the intersection itself could tell us which settings are working well and which are not. Northwest Signal Supply (NWS) has programmed powerful data collection tools into its Voyage ATC software and M1 NEMA controller that log specific measurement data about an intersection’s operational effectiveness, or Measures of Effectiveness (MOE). Northwest Signal Supply’s MOEs provide time-stamped performance information for actuated and coordinated signal operation.
In practice, timing optimization is an iterative process involving data collection, analysis, timing modification, and more data collection for verification. Accurate observations of “what is” are essential to effective optimizations. Voyage / M1 capture MOE data as a background operation while the controller operates according to its current timing parameters. With no knowledge of this data collection, the controller is basically doing what it has been programmed to do. Surprisingly, routine operation produces large volumes of data that must be stored until the user downloads it. To help manage memory usage, MOE logging can be turned on or off so only data for specific operation periods is captured. Analysis performed using the downloaded data helps determine which performance measures associate with which timing parameters.
For an actuated signal running in FREE, Voyage / M1 MOE logs provide information about:
- How many times a vehicle phase was serviced in the sample period
- How many times a pedestrian phase was serviced in the sample period
- Average length of green time by phase
- Phase termination type: (Gap Out (desired), Max Out, Force-Off)
For an actuated signal running in Coordination, Voyage / M1 log data might include:
- Cycle length and coordination plan in effect
- Split utilization by phase
- Percent of vehicles arriving during phase green time (vs. arriving during non-green time)
- Vehicle Arrival Type by phase
MOE data for a FREE running signal can help determine if the phases being recalled are appropriate for a specific part of the day. Consider this example in which the north-south approaches of an intersection are heavier during the AM peak, yet during the PM peak the east-west approaches are heavier. Typical signal timing assigns recalls to two mainline phases and never changes. Altering the recall phases assures control will return to the high demand phases as soon as all other phases terminate. If the approaches are balanced in demand, consider using soft-recall or a no-recall mode.
If an intersection has significant pedestrian crossing usage, Voyage / M1 provide a number of features that provide enhanced service and safety to pedestrians. Conditional Ped, for example, is a function that provides for late and multiple services to pedestrians.
When an intersection is congested the MOE log is marked by patterns of Max Outs or Force-Offs occurring in both rings and both sides of the barrier. Creating a solution for congestion is a two step process. The first step is to constrain the cycle time, which for a FREE running signal is the sum of phase max times for the longer ring. The resulting virtual cycle time accounts for total waiting time per phase and provides a framework for distributing cycle time. The second step is to determine the amount of green time that will allow each phase to Gap Out while enabling all phases to fit into the virtual cycle time. Voyage / M1 provide a number of gap management features that provide more efficient gap termination, including gap reduction and lane-by-lane gap out.
If the intersection is NOT congested, Voyage / M1 can adjust Max Time using: TOD Max Plans or Auto-Max which dynamically increases / decreases Max Times based on cycle-by-cycle volume fluctuations in each phase.
During SYSTEM operation MOE data helps determine if Lead-Lag adjustments can help by moving phases that usually gap out to the lead phase position. Cycle time surrendered by the gap-terminated phase can be used by subsequent phases, helping to reduce some force-off terminations. If analysis of the splits shows that each phase has sufficient time to gap out, the splits may be reapportioned for greater efficiency.
In coordination, the system performs best when a well-defined platoon of vehicles moves without delay through the entire corridor. Two measures help to determine the volume of traffic that arrives on green and how well the platoon boundaries are defined. Percent arrival on green indicates how accurately the offset is set for the current operation. In many cases, offset is a compromise of bi-directional progression objectives, yet some fine tuning is still practical. Arrival Type [1] is a statistical score related to the quality of the platoon. At the lower boundary score of one (1), arrivals are completely random and lack predictability. As arrivals become more cohesive and defined the scores approach the upper limit of six (6). Combined with other system measures, Arrival Type is useful for determining progressions relative to other signals surrounding the data source location.
Voyage 2070 and ATC software and the M1 NEMA controller are products of Northwest Signal Supply. Both product families provide extensive logging capabilities that help traffic operations engineers measure timing effects and make meaningful positive adjustments. Learn more about MOEs and the ways that Voyage / M1 can help enhance your traffic signal operations and maintenance at NWSignal.com or call our support staff at: 503-635-4351 (Mon-Fri 8am-5pm Pacific Time).
Bibliography:
[1] ASCE Journal of Transportation Engineering, July 2007, Vol. 133, No. 7, pp 415-422, “A Pilot Study on Real-Time Calculation of Arrival Type for Assessment of Arterial Performance”, Smaglik, E; E.M.Bullock; A. Sharma
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