United States Department of Transportation
i
Analysis of travel time reliability on Indiana interstates.
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2009-09-15
[PDF-3.76 MB]
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Abstract:Travel-time reliability is a key performance measure in any transportation system. It is a
measure of quality of travel time experienced by transportation system users and reflects the efficiency
of the transportation system to serve citizens, businesses and visitors. Travel-time reliability (the
variability in travel times on the same route at the same time from one day to the next) is critical to
travelers, shippers, receivers and carriers for trip decisions and on-time arrivals at destinations. Thus,
understanding travel time reliability is important to travelers in order for them to plan their trips
effectively as well as shippers for them to plan and select routes appropriately.
The first objective of this study is to formulate a methodology to obtain travel time data using
Bluetooth technology on a freeway segment and collect travel time data. Bluetooth technology enables
to collect real travel time data with a high sampling rate of up to 10% of the traffic flow. It also
eliminates that need to use complex and often inaccurate algorithms use to calculate travel time from
point speed data. Another benefit of this technology is it’s the fact that it is relatively inexpensive to
implement; every station where travel time is desirable needs to be equipped with a processing unit,
power source and Bluetooth dongle.
The second objective is to observe daily and inter-daily variations as well as those due to poor
weather conditions and estimate econometric models to predict travel time and variability. Within the
context of this study, travel times were collected for two sections of freeway that experience heavy
congestion during the peak hours. These travel times were then used to estimate three econometric
models that predict travel time as a function of traffic flow parameters including speed and volume. The
first model, which is linear regression with lagged dependent variable terms, aims to predict individual
travel times during all times of day. The second model, a survival model, seeks to evaluate the
probability of the trip lasting any specified length of time. In addition, it can predict the probability of
exiting the freeway segment given that the vehicle has been traversing the segment up to that time. The
third model seeks to describe travel time and the variability of travel time using the seemingly unrelated
regression equations.
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