This case study is the second of five, performed by the project team in order to validate the approaches to travel time reliability monitoring described in the Travel Time Reliability Monitoring Guidebook. The goal of each case study is to illustrate how agencies apply best practices for: monitoring system deployment; travel time reliability calculations; and agency use and analysis of the system. To accomplish this goal, the team is implementing prototype travel time reliability monitoring systems at each of the five sites. These systems take in sensor data from a variety of transportation networks, process this data inside a large data warehouse, and generate reports on travel time reliability for agencies to help them better operate and plan their transportation systems. This case study consists of the following sections:
- Monitoring System
- Methodological Advancement
- Use Case Analysis
- Lessons Learned
This monitoring system description section details the reasons for selecting Northern Virginia as a case study and gives an overview of the region. It briefly summarizes agency monitoring practices, discusses the existing sensor network, and describes the software system that the team used to analyze use cases. The section also details the development of travel time reliability software systems, and their relationships with other systems. Specifically, it describes the steps and tasks that the research team completed in order to transfer data from a pre-existing collection system into a travel time reliability monitoring system.
The section on methodology describes the implementation of a multi-state travel time reliability model, developed by the SHRP 2 L10 research team, using the Northern Virginia freeway data. It is intended to showcase a tractable method for assembling travel time probability density functions from historical travel time data, as well as highlight the tie-ins of this project with others under the SHRP 2 umbrella. It was selected for emphasis in this case study because the original work was performed using model-generated travel times from the same I- 66 corridor being monitored as part of this case study. Work on refining the Bayesian travel time reliability calculation methodology outlined in this project’s Task 7 document and introduced in the San Diego case study will resume as part of the final three case study sites.
Use cases are less theoretical, and more site specific. Their basic structure is derived from the user scenarios described in the Task 2/3 document, which are the results of a series of interviews with transportation agency staff regarding agency practice with travel time reliability. Since the focus of this case study is to describe the required steps and considerations for integrating a travel time reliability monitoring system into existing data collection systems, only one use case is described in this case study.
Lessons Learned summarizes the lessons learned during this case study, with regard to all aspects of travel time reliability monitoring: sensor systems, software systems, calculation methodology, and use. These lessons learned will be integrated into the final guidebook for practitioners.