Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Abstract

The effectiveness of adaptive signal control strategies depends on the level of traffic observability, which is defined as the ability of a signal controller to estimate traffic state from connected vehicle (CV), loop detector data, or both. This paper aims to quantify the effects of traffic observability on network-level performance, traffic progression, and travel time reliability, and to quantify those effects for vehicle classes and major and minor directions in an arterial corridor. Specifically, we incorporated loop detector and CV data into an adaptive signal controller and measured several mobility- and event-based performance metrics under different degrees of traffic observability (i.e., detector-only, CV-only, and CV and loop detector data) with various CV market penetration rates. A real-world arterial street of 10 intersections in Seattle, Washington was simulated in Vissim under peak hour traffic demand level with transit vehicles. The results showed that a 40% CV market share was required for the adaptive signal controller using only CV data to outperform signal control with only loop detector data. At the same market penetration rate, signal control with CV-only data resulted in the same traffic performance, progression quality, and travel time reliability as the signal control with CV and loop detector data. Therefore, the inclusion of loop detector data did not further improve traffic operations when the CV market share reached 40%. Integrating 10% of CV data with loop detector data in the adaptive signal control improved traffic performance and travel time reliability.

The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality

“…Although data about speed and position from connected vehicles can be useful, penetration remains low, so they must be integrated with data from traditional detectors. [61] showed in simulations that connected vehicle data could improve adaptive control even with limited penetration. Furthermore, agencies may configure their detectors differently.…”

Effects of Connectivity and Automation on Saturation Headway and Capacity at Signalized Intersections

“…Vehicle connectivity is also expected to be essential in improving mobility and safety ( 4 – 8 ). Current studies show that AVs are programmed to behave conservatively, perhaps to reduce the likelihood of severe crashes in the absence of information from other vehicles and obstacles that are not visible to the sensors of AVs ( 9 , 10 ).…”