Evaluating Alternative Operations Strategies to Improve Travel Time ...

SHRP 2 L11: Final Report
Considerable work has been performed in the past 30 years to make traffic-control systems more
flexible in order to improve their performance. The most common of these changes is to allow
signal-timing plans to change based on observed traffic volumes. Two examples of such
flexibility are the use of signal phases that only occur when vehicles are present to use them
(traffic actuated phases) and variable phase lengths, which change based on the traffic volumes
present on conflicting movements (variable phase lengths). Similarly, many freeway ramp
metering algorithms change given a combination of traffic volumes and speeds on the freeway
compared to ramp queue length.
Basic data on traffic-control plans, such as signal cycles, phase length, order, signal offsets, and
base ramp metering rates, are routinely available to all traffic agencies operating those trafficcontrol
systems. What is rarely available are the specific timing plans implemented. That is, an
agency in control of a signal timing plan will know that a given green phase is designed to
operate for between 30 and 50 seconds, depending on various factors (e.g., the presence of traffic
on opposing movements or whether a pedestrian button has been activated). What they do not
have is a record of exactly what phase length was actually operated over the course of a
day/week/month/year. That is, rarely (if ever) do agencies track exactly how their signal systems
took advantage of the flexibility they have been given. As a result, most agencies do not have a
direct means of confirming if their plans are working as really intended, or whether they could be
improved by minor changes in these control parameters.
Bottlenecks
Bottlenecks are most commonly formed either at changes in roadway geometry (e.g., lane drops)
or where significant traffic movements reduce effective roadway capacity for a given number of
roadway lanes (e.g., merge and weave sections). A number of other causes for bottlenecks also
occur. These include common visual disruptions (e.g., the sight of a mountain or lake that drivers
encounter only periodically) or physical features such as uphill grades, which can reduce the
effective capacity of a roadway.
All roadway agencies have good data on where significant geometric changes cause congestion
to occur. Most roadway agencies also have a good understanding of where merges and other
major traffic disruptions cause routine congestion, all of which are considered bottlenecks. Data
on other types of minor changes in functional capacity that can form congestion “routinely
enough” to be considered a bottleneck can also be obtained by most agencies. However, these
less significant bottlenecks are not as well documented. Those based on visual disruptions are
particularly hard to record as they occur based on factors not routinely recorded by roadway
agencies (e.g., the weather conditions and visibility between a roadway and a distant mountain).
The SHRP2 L03 project (1) also includes information about the sources and procedures for
disruption data.
POTENTIAL PERFORMANCE MEASURES FOR AGENCY USE
Based on the current needs of highway users and the availability of roadway-performance and
disruption data, this section discusses the basic performance measures that roadway agencies
could report. By combining the needs of individual travelers and freight movers, along with the
needs and limitations of agencies, performance measures aimed at improving travel-time
reliability could be developed within the following three areas:
• Roadway Performance: measures related to roadway performance (“outcome” measures).
GOALS AND PERFORMANCE TARGETS Page 24