Evaluating Alternative Operations Strategies to Improve Travel Time ...

SHRP 2 L11: Final Report
penalties for late delivery have to be balanced against the cost of unproductive use of labor and
equipment, the 80 th percentile travel time may be a more useful statistic. Of course, for trucking
firms that deliver highly time sensitive cargoes, the 95 th percentile is more likely the travel time
used for planning purposes.
In addition, the mean travel time is a function of the relationship between vehicular demand and
basic roadway capacity. The 95 th percentile is often a function of the occurrence and nature of
significant travel disruptions (e.g., heavy snowfall, an accident involving large trucks, or
significant vehicle fires). Preliminary findings from the SHRP2 L03 (1) project indicate that on
congested urban freeways, the 80 th percentile travel time is often a function of the effectiveness
of incident response programs, while the 95 th percentile travel time is fairly insensitive to the
effects of most incident response activities. Therefore, all three basic travel time statistics are
important for developing comprehensive travel-time reliability measures. Each represents a
different, but significant, measure of performance.
The fourth suggested performance measure is the percentage of time that a roadway segment
fails to operate at a desired level (an adopted performance standard or an adopted performance
reporting standard). This statistic simulates an “on-time” performance measure. It allows the
roadway agency to state that a facility should operate at a given level, and then track
performance against that goal. The difficulty with adopting an “on-time” performance measure is
in setting the “expected” travel-time (or speed) goal against which success will be measured. For
general purpose lanes, this may be free-flow speed. This is often appropriate for roads in
uncongested rural areas. In some urban areas, agencies have adopted “speed at maximum
vehicular throughput” (roughly 45 mph) as the standard. However, in heavily congested
roadways, even this slower vehicle speed standard may result in a large number of “failures” due
to the high demand in comparison to the available capacity. This results in the agency appearing
to fail no matter what possible actions they can take within their financially constrained
environment. In these cases, slower vehicle speed standards may be adopted.
The last proposed performance measure is of interest mostly to roadway facility managers.
Volume (i.e. use) is a key indicator of how well measures to improve or maintain reliability are
working. For example, if the implementation of an incident management or ramp metering
program results in a small reduction in the mean and 95 th -percentile travel times but traffic
volumes on the facility double, the conclusion would be that these measures to improve
reliability were successful. On the other hand, if the same increase occurred, but volume dropped
by 20 percent, the agency may conclude that these programs were not effective in achieving the
desired benefits. Table 3.1 is an example of the various performance measures that can be related
to the broad passenger traveler needs.
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