Evaluating Alternative Operations Strategies to Improve Travel Time ...

SHRP 2 L11: Final Report
while many trucking firms do not have data on travel time, some use vehicle-location technology
to estimate point-to-point travel times for their vehicles on the basis of historical travel times and
use those estimates in fleet and driver planning.
Collection of accurate performance data on urban arterials and smaller rural roadways will still
be problematic in the near future, though the blue-tooth and GPS technology cited above offer
the potential for significant improvements. On rural roads, data gathering will be most
problematic because of the large number of center-line roadway miles and modest number of
instrumented vehicles using those roadways at any given time of day that does not allow the
estimation of travel times within statistically reliable boundaries. The large number of center-line
miles means that infrastructure-based technologies, such as Bluetooth or ALPR readers, are
prohibitively expensive to deploy because of the number of devices required to provide wide
geographic coverage. The low volumes on roadways, particularly the low volumes of trucks,
means that an insufficient number of instrumented vehicles may be present to provide
statistically valid travel-time and delay information when vehicle probe-based data collection
approaches are used.
Four additional factors complicate the collection of travel-time reliability data on urban arterials.
The first is the difficulty of accounting for mid-block vehicle stops (e.g., short shopping trips
and/or pick-up and delivery stops) when vehicle probes are used. Short vehicle stops affect both
point-based travel-time systems, such as Bluetooth readers, and systems that aggregate spot
speed-data collected from GPS-equipped vehicle probes. The second difficulty is the effect of
control delays on travel-time estimates produced from spot speed-data collected by vehicle
probes. The third difficulty is that vehicles often take a variety of paths within an arterial
network. This makes the placement and use of point-based travel-time systems less effective
(except on simple arterial corridors). Finally, arterial travel times are inherently variable, simply
because of the variety of control delays that can affect any given trip. Therefore, a considerable
number of travel-time runs are required to collect sufficient data to determine statistically valid
changes in travel-time reliability.
Near-Real-Time versus Long-Term Planning Data
It is important to note that there is a difference in the availability of data in near-real time (used
for real-time decision making by travelers, shippers, carriers, and operating agencies) and the
availability of long-term planning and reporting data (used for longer term planning and agency
management). The collection and dissemination of data in real-time or near-real time costs more
than the collection and dissemination of data within a longer “planning time” horizon. As a
result, much of the traffic and truck volume data available around the country are only available
well after the fact. The systems that collect these data rely heavily on manual equipment
placement and pick up. As a result, data are only available periodically. These data systems serve
multiple purposes, are heavily budget-constrained, and therefore collect data in the most costeffective
manner possible. The manual equipment placement allows a small number of pieces of
data collection equipment and a small staff to collect data at a large number of geographically
separated locations at a very modest cost. When collected properly and statistically manipulated,
these data collection programs yield fairly good estimates of average facility use. However, the
vast majority of data are not available in real time to improve the operational decision making
necessary to increase travel-time reliability.
Unlike volume data, the majority of the travel-time data are available in near-real time. This is
because these data are primarily collected to improve operational decision making and to provide
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