Travel time is a crucial factor for travelers, shippers, and businesses. With advancements in data collection, travel time reliability can now be accurately quantified. This article explores the concept of travel time, its importance, and how it’s measured.
Understanding Travel Time Reliability
Traffic congestion is a common issue in many cities. While drivers expect some delays during peak hours and adjust their schedules accordingly, unexpected delays can be particularly problematic. These unforeseen delays can cause lateness for work, missed appointments, and disruptions to just-in-time delivery and manufacturing processes.
Traditionally, traffic congestion has been communicated through simple averages. However, this doesn’t fully represent the experiences of commuters, whose travel times can vary significantly from day to day. These unexpected delays are what travelers remember most.
Travel time reliability refers to the consistency and dependability of travel times, measured across different days and times. It quantifies the extent of unexpected delays.
For instance, on a commuter route in Seattle, Washington, travel times can be as low as 12 minutes during periods of no congestion. On regular weekdays, the average travel time might be 18 minutes. However, traffic incidents and weather can cause unexpected delays, increasing travel time to nearly 25 minutes. This variability requires commuters to plan for these worst-case scenarios.
Commuters often build a “buffer” into their trip planning to account for this variability. While arriving early isn’t necessarily negative, this extra time is still taken from their day.
Why is Travel Time Reliability Important?
Travel time reliability is important to vehicle drivers, transit riders, freight shippers, and air travelers. It allows personal and business travelers to better utilize their time. Predictable travel times are essential for shippers and freight carriers to remain competitive. Considering travel time reliability as a key performance measure is valuable for transportation planners and decision-makers.
Traffic professionals recognize the importance of travel time reliability as it quantifies the benefits of traffic management and operation activities more effectively than simple averages. For example, improvements in average travel time from incident management or ramp metering programs may appear modest, but reliability measures will demonstrate a more significant improvement by capturing the effect of improving the worst days of unexpected delay.
Key Measures for Quantifying Travel Time Reliability
Several measures can be used to quantify travel time reliability. Most of these compare days with high delay to days with average delay. Here are four recommended measures:
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90th or 95th Percentile Travel Time: This indicates how bad delays will be on the heaviest travel days, reported in minutes and seconds. It’s easily understood by commuters and suitable for traveler information. However, it’s difficult to compare across trips of different lengths or combine travel times into area-wide averages.
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Buffer Index: This represents the extra time travelers add to their average travel time to ensure on-time arrival, expressed as a percentage. A higher buffer index indicates worse reliability. For example, a buffer index of 40% means that for a 20-minute average travel time, a traveler should budget an additional 8 minutes.
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Planning Time Index: This represents the total travel time that should be planned, including both typical and unexpected delay. It compares near-worst-case travel time to free-flow travel time. For example, a planning time index of 1.60 means that for a 15-minute trip in light traffic, the total planned time should be 24 minutes.
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Frequency of Congestion Exceeding Expected Threshold: This is expressed as the percentage of days or time that travel times exceed X minutes or travel speeds fall below Y mph.
Statistical measures like standard deviation and coefficient of variation are discouraged as performance measures due to being harder to understand.
Steps to Develop Travel Time Reliability Measures
To start producing travel time reliability statistics, follow these steps:
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Determine how the reliability measures will be used: Consider if the measures will quantify traffic operations benefits, monitor statewide travel conditions, or compare multi-modal investment scenarios.
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Develop a plan based on intended uses and users: The plan should outline data collection, measure calculation, and results reporting.
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Collect and process required data: This involves direct calculation from probe vehicle data, estimation from detector data, special studies, or computer simulation.
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Calculate reliability measures using route/trip travel times: Use basic equations to calculate percentile travel times, buffer index, planning time index, and congestion frequency.
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Communicate measures in easy-to-understand tables and graphics: Display the results in a way that resonates with commuters and travelers, using analogies like “the worst traffic day of the month” to explain statistical formulations.
Real-World Applications of Travel Time Reliability Measures
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National Traffic Congestion and Reliability Monitoring: The FHWA tracks reliability measures in over 30 cities, communicating current information through monthly dashboard reports.
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Freight Performance Measurement: The FHWA monitors travel times in freight-significant corridors to support global connectivity.
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State DOT Performance Measures: The Washington State Department of Transportation (WSDOT) reports congestion measures, including reliability, for the Seattle region.
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International Border Crossings: Studies calculate buffer time and buffer index for commercial vehicles at border crossings to measure delay.
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SCAG Goods Movement Study: Travel time reliability is incorporated into analysis of infrastructure improvements, identifying time savings from projects like separate truck lanes.
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NTOC Performance Measure Initiative: Buffer time was identified as a key performance measure by the NTOC team.
Conclusion
Understanding travel time and its reliability is crucial for improving transportation systems. By using key measures and following a methodical approach, agencies can effectively assess and communicate travel time reliability, ultimately benefiting travelers, shippers, and businesses.
