Implications of Alternative Communications and Sensing Technologies for Implementing Variable Speed Limit Control through Connected Vehicles: Sag Curve as a Case Study

Abstract

Connected vehicles (CVs) will enable various applications to improve traffic flow. This paper’s focus is to investigate how the potential implementation of variable speed limit (VSL) through different types of communication and sensing technologies on CVs makes it possible to mitigate congestion at a sag curve bottleneck. A VSL algorithm is developed and implemented in a simulation environment for controlling the inflow of vehicles to a sag curve to minimize delays and increase throughput. Both vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) options for CVs are investigated when implementing the VSL control strategy in a simulation environment. Also, for measuring traffic density in real-time either a fixed sensor (e.g., inductive loop) or distance (i.e., space headway) measuring device on CVs is considered. Through a feedback control algorithm, the speeds of CVs are manipulated at upstream of the sag curve to avoid the formation of bottlenecks caused by the change in longitudinal driver behavior. Various market penetration rates for CVs are considered in the simulations for three alternative communications and sensing technologies. Critical rates of CVs under each alternative are found at which the control system improves the system performance. It is demonstrated that for higher Market Penetration Rates (MPRs) the performance is about the same for all three scenarios. The results demonstrate that not only the MPR of CVs but also how CVs are distributed in the traffic stream is critical for system performance.