Leverage Existing Traffic Management Systems (TMS) Assets to Automate Queue Warning Messages and Enhance Operational Efficiency.
The Suggestions, Sourced from Case Studies by Departments of Transportation (DOT) in Minnesota, Iowa, Pennsylvania, and Texas, Provide Insight into the Successful Implementation of TSMs on Interstates.
Minnesota, United States
Pennsylvania, United States
Texas, United States
Iowa, United States
Traffic Management Systems Actively Managing the Display of Queue Warning Messages
Summary Information
Freeway congestion often leads to sudden slowdowns and rear-end crashes, especially when drivers encounter unexpected queues. To reduce these risks, traffic management systems (TMS) use real-time data from sensors and other monitoring tools to detect unstable traffic conditions and display warning messages on digital road signs before drivers reach slow or stopped vehicles. By improving how traffic warnings are managed and displayed, these systems enhance roadway safety, support smoother travel through work zones or bottlenecks, and complement other smart traffic management strategies such as variable speed limits and lane-use control. This study reviewed and showcased the benefits of the current TMS nationwide, including Minnesota, Pennsylvania, and Texas State DOTs.
The report details the experiences of Minnesota, Iowa, Texas, and Pennsylvania DOTs after implementing CMS displays of queue warning messages, which were managed by TMSs.
- Current TMS asset: Assess how much of the queue warning message system can leverage existing TMS infrastructure and evaluate the current coverage and capability of TMS assets, including sensor type, spacing, and lane-level detection, which is essential to ensure adequate monitoring of traffic conditions.
- Activation logic and thresholds: Establish speed and traffic thresholds that indicate slow or stopped traffic (e.g., speeds dropping below set values) to automate warning triggering and prevent unnecessary or confusing messages.
- Data collection: Determine the most suitable data sources for traffic monitoring, which may include sensors, third-party sources, or crowdsourcing to detect unstable traffic flow. Mobile device applications could provide effective crowdsourced data.
- Analytic requirements: Define analytic requirements is critical for effective message display, including the use of algorithms to detect queues and select appropriate messages. This may necessitate additional software within the TMS and clearly defined business rules that align with other traffic management functions.
- Cost and labor considerations: The display of queue warning messages can be implemented without adding significant cost and staffing impacts, as it typically uses existing TMS infrastructure and is highly automated, requiring only supervisory oversight from current operators. However, agencies should account for the potential need for staff or contractor support when integrating field devices in select work zones to ensure successful monitoring of traffic conditions and proper display of queue warning messages within the TMS.
