The Effects of Vehicle-to-Infrastructure Communication Reliability on Performance of Signalized Intersection Traffic Control
Ilya Finkelberg, Tibor Petrov, Ayelet Gal-Tzur, Nina Zarkhin, Peter, Pocta, Tatiana Kovacikova, Lubos Buzna, Milan Dado, Tomer Toledo

TL;DR
This study investigates how unreliable vehicle-to-infrastructure communication affects the performance of adaptive traffic signal control at intersections, showing that communication distortions can significantly increase vehicle delays and impact fairness.
Contribution
It models the effects of communication reliability on adaptive intersection control using traffic and communication simulations, highlighting the importance of accounting for communication distortions in algorithm design.
Findings
Communication distortions increase average vehicle delays.
Delay impacts are similar whether all or single approaches are affected.
Compensating for distortions can restore delays to near-perfect communication levels.
Abstract
A vehicle-to-infrastructure communication can inform an intersection controller about the location and speed of connected vehicles. Recently, the design of adaptive intersection control algorithms that take advantage of this information evoked a lot of research, typically assuming a perfect communication. In this study, we explore possible effects of a temporal decrease in the reliability of the communication channel, on a throughput of a signalized intersection. We model road traffic and DSRC-VANET communication by integrating the well-established traffic and communication simulation tools (Vissim and OMNeT++). Comparisons of the perfect communication conditions with challenging, but realistic conditions involving communication distortions show that the adaptive intersection control may suffer from significantly increased average delays of vehicles. The level of delays is largely…
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Taxonomy
TopicsTraffic control and management · Traffic Prediction and Management Techniques · Vehicular Ad Hoc Networks (VANETs)
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
