This case study is the first 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 calculation methodology; 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 in real-time 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 San Diego as a case study and gives an overview of the region. It briefly summarizes agency monitoring practices, discusses the existing travel time 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.
The section on methodology is the most experimental and least site specific. It is dedicated to an ongoing investigation, spread across all five case studies, to test, refine, and implement the Bayesian travel time reliability calculation methodology outlined in this project’s Task 7 document. For this section, the team is using, as appropriate, site data and other data in order to investigate this approach. The goal of each case study methodology section is to advance the team’s understanding of the theoretical framework and practical implementation of the new Bayesian methodology.
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.
Lessons learned summarizes the key findings from this case study, with regards 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.
Operations Area of Practice
- Detection Systems
- Communicating Reliability Information
- SHRP2 Tools
- System Performance Definition, Monitoring and Reporting
- Travel Demand Forecasting
Organizational Capability Element
- Reliability Predictive Models
- Case Studies & Lessons Learned
Role in Organization
- Associate Engineer
- CEO / GM / Commissioner
- Director / Program Manager
- Manager / First Line Supervisor
- Principal Engineer
- Senior Engineer
- Senior Manager
- Transit Professional
- Transportation Planner
- SHRP2 Program
San Diego Case Study Validation.pdf (2.09 MB)