Traffic Signal Optimization under Connected-Vehicle Environment: An Overview

Abstract

Traffic signal optimization is a significant means for smoothing urban traffic flow. However, the operation of traffic signals is currently seriously constrained by the data available from traditional point detectors. In recent years, an emerging technology, connected vehicle (CV), which can percept the overall traffic environment in real time, has drawn researchers’ attention. With the new data source, traffic controllers should be able to make smarter decisions. A lot of work has been done to develop a new traffic signal control pattern under connected-vehicle environment. This paper provides a comprehensive review of these studies, aiming at sketching out the state of the arts in this research field. Several basic control problems, communication, control input, and objectives, are briefly introduced. The commonly used optimization models for this problem are summarized into three types: rule-based models, mathematical programming-based models, and artificial intelligence-based models. Then some major technical issues are discussed in detail. Finally, we raise the limitation of the existing studies and give our perspectives of the future research directions.

RF-Enhanced Pavement Markings for Mobile Robot Lane Detection

“…Applying computer vision technologies for sign detection has been widely studied and adopted [38,25], however, it still face challenges in nighttime detection and occlusion conditions. Other approaches use communication technologies such as DSRC and Zigbee to overcome the constraints of vision-based method [22,43,14]. A significant limitation of this approach is the energy consumption, since continuous power supply is needed for traffic signs This necessitates additional effort for managing and maintaining the battery.…”

Distributed Traffic Signal Optimization at V2X Intersections

“…Connected vehicle (CV) technology, or Vehicle-to-Everything (V2X) Communications, could provide mobility, safety, and environmental benefits to arterial traffic operations [1][2][3]. The National Highway Traffic Safety Administration (NHTSA) performed a detailed benefit study in 2016 [4].…”

“…However, budgetary, institutional, technological, and training constraints have cast uncertainty over deployment timelines. To help state DOTs and local agencies, the objective of the research was to create Traffic Signal Control System (TSCS) models and implementation algorithms for the early deployment of V2X (10% penetration rate, for example) and examine its mobility, safety, fuel, and emissions benefits [1][2][3].…”

“…This paper presents the core of the system and the novel models and algorithms. In the prior reports and Transportation Research Board (TRB) papers [1][2][3], it was assumed that Basic Safety Messages (BSMs) from each Roadside Unit (RSU) would be forwarded to a central computer for storing and processing without considering the communication network bandwidth and processing computing power. This might be acceptable for a rural community where the number of RSUs is of moderate quantity (under one hundred units, for example).…”

“…To make the proposed algorithm work under the above scenario, a distributed system should be explored to see if there is still a significant benefit. [2] IBM defines distributed computing as "A distributed computer system consisting of multiple software components on multiple computers but run as a single system. .…”