Key Terms
- What is Adaptive Signal Control?
- What is a Signal Controller?
- What is a closed-loop system?
- What is a traffic model?
Adaptive Signal Control Technologies
- How does adaptive signal control work?
- What are the advantages of adaptive signal control?
- How well does adaptive signal control technology improve system performance?
- How long have adaptive signal controls been in use?
- How important are detection systems?
- How do Adaptive Signal Control technologies use traffic models to evaluate alternative traffic control strategies?
- Does adaptive signal control focus on improvements at an individual intersection, or does it look at the system as a whole?
- How much detail is in an effective traffic model?
- How are traffic models calibrated and adjusted?
- What are the barriers to the widespread deployment of adaptive signal controls?
Key Terms
What is Adaptive Signal Control?
Adaptive signal control refers to technologies that capture current traffic demand data to adjust traffic signal timing to optimize traffic flow in coordinated traffic signal systems.
What is a Signal Controller?
A device programmed by traffic engineers with signal timing parameters that executes signal control logic to control the signal displays at the intersection.
What is a closed-loop system?
A decentralized system that provides signal coordination and monitoring functions to local intersections.
What is a traffic model?
A traffic model is a virtual environment that characterizes the movement of vehicles within a transportation network to statistically evaluate system performance. The number of input parameters may vary, but the model must include enough information to evaluate and determine traffic strategies.
Adaptive Signal Control Technologies
How does adaptive signal control work?
The objective of adaptive signal control is to provide effective signal timing settings within a range of operating conditions. It works by collecting current demand information, evaluating performance using system specific algorithms, and then implementing modifications based on the outcome of that evaluation.
What are the advantages of adaptive signal control?
Adaptive systems can reduce traffic delay, increase average speeds, improve travel times, and decrease travel time variability. They also decrease emissions, which helps the environment. In contrast to traditional timed systems, adaptive signal control technologies can react to traffic accidents, special events, road construction, and other occurrences.
How well does adaptive signal control technology improve system performance?
Many studies have shown that adaptive signal control improves average performance metrics (travel time, control delay, emissions, and fuel consumption) by 10 percent or more. In systems with particularly poor conditions, the improvement can be 50 percent or more. Improvement might be somewhat less in areas with high-performing pre-time systems in which fluctuations are rare, but every system experiences some fluctuations.
How long have adaptive signal controls been in use?
Adaptive systems have been in use for 30 years. Within the United States, they have been in use for roughly 20 years, though they have been deployed on less than 1 percent of existing traffic signals.
How important are detection systems?
Effective detection systems are essential components of all adaptive systems. The reliability and accuracy of the decisions made by the adaptive algorithms cannot be achieved without well-maintained detection.
How do Adaptive Signal Control technologies use traffic models to evaluate alternative traffic control strategies?
Some ASCT use traffic models to characterize current traffic conditions based on data collected and fed into the model. The system then evaluates specific performance measures and develops signal timing strategies that improve those performance measures within the models. The ASCT then implements the signal timing changes and repeats the process.
Does adaptive signal control focus on improvements at individual intersections, or does it look at the system as a whole?
Each adaptive system utilizes a unique approach to optimize signal timing. Some systems provide an entire system solution evaluated on a second-by-second basis; other systems evaluate and optimize each individual signal on a cyclic basis. Each approach produces similar benefits and requires differing levels of detection, communications, and processing capability that should be selected to be consistent with an agency's needs, operations, and maintenance capabilities.
How much detail is in an effective traffic model?
Traffic models vary greatly. Some use thousands of parameters (based on the number of intersections of the deployment), while others use very few. Generally, the accuracy of a model improves when more parameters are considered.
How are traffic models calibrated and adjusted?
Calibrating and adjusting traffic models can be a time-consuming and expert-driven process during deployment. The better tuned the traffic model becomes (i.e., the more it is matched to what is happening in the real world), the better the system will perform. Some systems can automatically adjust their internal model parameters. Others require human judgment and interaction.
What are the barriers to the widespread deployment of adaptive signal controls?
The 2007 Traffic Signal Report Card revealed with a score of "F" in the section on monitoring and data collection that very few agencies actively measure performance of signal systems outside of citizen complaints. Recognizing that gaps in performance exist that can be addressed by adaptive control technology is the first barrier that must be overcome. Other barriers can include cost, complexity, uncertainty about benefits, and overhead associated with traffic detection and communications between traffic signal system components.