Abstract
Freeway traffic management and control often rely on input from fixed-point sensors. A sufficiently high sensor density is required to ensure data reliability and accuracy, which results in high installation and maintenance costs. Moreover, fixed-point sensors encounter difficulties to provide spatiotemporally and wide-ranging information due to the limited observable area. This research exploits the utilization of connected automated vehicles (CAVs) as an alternative data source for freeway traffic management. To handle inherent uncertainty associated with CAV data, we develop an interval type 2 fuzzy logic-based variable speed limit (VSL) system for mixed traffic. The simulation results demonstrate that when more 10% CAVs are deployed, the performance of the proposed CAV-based system can approach that of the detector-based system. It is demonstrated in addition that the introduction of CAVs may make VSL obsolete at very high CAV-equipment rates.
Highlights
In the past half century, various traffic control measures have been developed to improve mobility, safety and environmental performance of freeway systems
We introduce a class of fuzzy logic control systems—type-2 fuzzy logic system (T2-FLS)—which has not been used in traffic control so far
Fixed-point sensors are often associated with high installation and maintenance costs
Summary
In the past half century, various traffic control measures have been developed to improve mobility, safety and environmental performance of freeway systems. To determine proper speed limit values, conventional VSL systems use traffic data collected from fixed-point sensors, such as inductive loops. Such an observation method requires a sufficiently high sensor density (e.g., 500 m spatial resolution) to ensure data reliability and accuracy. Utilizing CAVs rather than fixed-point sensors as the data source is expected to reduce the overall cost associated with the implementation of advanced traffic control systems. Such “infrastructure-free” systems can provide a cost-effective solution, especially for jurisdictions with a lack of resources for installation of traffic monitoring infrastructure. The presented approach uses CAV data as control input and is designed based on a new class of fuzzy logic—interval type 2 fuzzy logic
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
