Effectiveness of Disseminating Traveler Information on Travel Time Reliability: Implement Plan and Survey Results Report
EXECUTIVE SUMMARY
Travel time variability is that characteristic of the transportation system that means a traveler's trip will vary from what is normally expected and will potentially take longer than planned. This transportation system characteristic is important for travelers and shippers. It also is a component of the congestion problem for which transportation agencies can make significant and measurable gains, even as travel demand grows. By providing the means to help travelers make travel choices that take into account travel time variability, agencies have the potential to reduce roadway congestion. This reduced congestion has the added benefit of reducing primary and secondary crashes, vehicle emissions, and fuel use, as well as yielding other benefits.
One measure of travel time variability is Travel Time Reliability (TTR). Transportation professionals describe TTR in terms of historical average travel times calculated over periods of a year or longer. TTR information includes static data about traffic speeds or trip times that capture historic variations from day to day and enable individuals to understand the level of variability in traffic. TTR information is considerably different from real-time travel time information and may have different uses. A traveler can use reliability information to plan and budget in advance for a trip rather than simply react to current conditions. A key component to addressing the reliability issue related to urban mobility is conveying this TTR information to system users so that they can make informed decisions about their travel. The challenge for transportation professionals lies in selecting the best means of conveying that information so that it is usable and effective to the traveler and other stakeholders.
The Strategic Highway Research Program 2 (SHRP2) Reliability Project L14 established a preliminary set of suggested terminology and guidelines for conveying TTR information to road users so that they may make optimal travel choices from their point of view, such as whether to take a trip or not, departure time, mode choice, and/or route choice. Specifically, a Lexicon of phrases was developed for each of eight TTR terms, which contained detailed guidelines for TTR information that would most likely be understood and used by travelers. To help agencies and other transportation-related entities better deploy and use the recommended Lexicon terminology, a field study was conducted to test the phrases to demonstrate the technical and institutional feasibility of their use and determine the potential costs and benefits of using these products of L14. Two Lexicon assemblies and three dissemination platforms were tested in the field study.
The field study was conducted in three locations: Houston, Texas; Columbus, Ohio; and Raleigh-Durham, North Carolina. Using a custom Smartphone application, study participants collected Global Positioning System (GPS) and travel characteristic data for all trips made over a four-week period along specific travel corridors in each study location. The travel period was divided into two equal phases. Only travel data was collected during the first phase, while in the second phase, TTR information also was provided to participants according to their randomly assigned Lexicon assembly and dissemination platform (i.e., App, 511, website). Baseline and exit surveys were administered, as well, to obtain participants' typical travel patterns and perceptions of the provided TTR information. Four rounds of data collection occurred between April 2015 and April 2016, with more than 750 participants completing all phases of data collection.
Local partners from each study location provided historical traffic datasets as a source for determining the TTR calculations utilized in the study. Based on the availability of data in each region, datasets were provided from different sources, timeframes, and formats. In order to present the data in a consistent format, the data from each region had to be manipulated into a common data format. The final result of the data manipulation was a comma-delimited file for each region for each day of the week containing location identification information, aggregation start time, average travel time, and 95th percentile travel time.
Overall, the field study found that the particular Lexicon phrases tested performed equally well. Only one survey question resulted in statistically significant differences between the Lexicon phrases. The biggest finding of the field study was that dissemination of TTR information via the 511 information channel was less preferred than via the Web or App access channels. In a few instances, the App access demonstrated superior responses over both the Web and 511 access.
Statistical models accounted for several exogenous factors, and this clearly seems important to properly interpreting the results of interest for the Lexicon assemblies and information channels. The city of the participants only rarely appeared as a significant factor in the models, suggesting that location was not an important differentiator in the outcomes. Among other exogenous variables, education level and the number of Phase 2 trips taken with the TTR information were found to significantly correlate with responses for multiple questions.
Following the first round of data collection, the project team and the Federal Highway Administration (FHWA) held a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis meeting with the partner agencies to try to identify lessons learned by the project team and the partner agencies through the testing of the Lexicon in the field deployment. The intent was to use the lessons learned and the project research results to refine the Lexicon for voluntary deployment in other cities. Although the final study results were not available at the time, the workshop participants agreed that the information provided at the conclusion of the study could be used for a variety of purposes by operating agencies. For example, TTR information could be used by operating agencies to help mitigate the impact of traffic congestion or the effects due to construction activities to the extent that reliability information and information pertinent to construction events is readily accessible. The availability of the information to travelers could help them compare real-time conditions with reliability (historic) conditions and possibly change travel behavior to avoid congestion. Additionally, the information could be used by agencies to share reliability information to key decision-makers and planners.
