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Recent advances in traffic signal performance evaluation

Journal of traffic and Transportation Engineering(English Edition) 2022年第4期9卷 507-531页

作者： Dallas Leitner Piro Meleby Lei Miao Department of Engineering Technology Middle Tennessee State UniversityMurfreesboroTN 37132USA

signal retiming is a prominent way that transportation agencies use to fight congestion and change of traffic *** evaluations of traffic conditions at signalized intersections and arterials provide actionable data for agencies to make well-informed and prioritized signal retiming ***,the abundance of data sources,the lack of standardized evaluation methods and oftentimes the shortage of resources make it a difficult *** review detailed in this paper examines the advances made in traffic signal performance *** establish the necessity for the evaluations,study the process of continuous improvement of traffic signal performance using the evaluations,and then examine multiple methodologies in a plethora of research ***,we focus on probe vehicles and sensors data,the two major sources of *** discuss how sensors are connected to signal controllers to provide relevant in-depth traffic data including speed and occupancy *** also review the nature of probe vehicles and the level of *** then define and summarize performance measures derived from both sources,to aid in performance *** performance evaluation methods,we discuss the research studies and provide summaries including advantages and disadvantages of the methods used,as well as a holistic outlook for future *** paper is aimed to provide a comprehensive review on the state-of-the-art to benefit researcher,traffic agencies,and commercial entities that thrive to improve safety and efficiency of traffic signals through performance evaluations.

关键词： Intelligent transportation systems traffic signal performance evaluation traffic signal retiming traffic signals optimization Intersection control evaluation

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Integrated Performance Measures for Bus Rapid Transit System and traffic signal Systems Using Trajectory Data

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Journal of Transportation Technologies 2022年第4期12卷 833-860页

作者： Jijo Kulathintekizhakethil Mathew Howell Li Enrique Saldivar-Carrranza Matthew Duffy Darcy Michael Bullock Purdue University West Lafayette USA Indygo Indianapolis USA

Bus rapid transit (BRT) systems have been implemented in many cities over the past two decades. Widespread adoption of General Transit Feed Specification (GTFS), the deployment of high-fidelity bus GPS data tracking, and anonymized high-fidelity connected vehicle data from private vehicles have provided new opportunities for performance measures that can be used by both transit agencies and traffic signal system operators. This paper describes the use of trajectory-based data to develop performance measures for a BRT system in Indianapolis, Indiana. Over 3 million data records during the 3-month period between March and May 2022 are analyzed to develop visualizations and performance metrics. A methodology to estimate the average delay and schedule adherence is presented along a route comprised of 74 signals and 28 bus stations. Additionally, this research demonstrates how these performance measures can be used to evaluate dedicated and non-dedicated bus lanes with general traffic. Travel times and reliability of buses are compared with nearly 30 million private vehicle trips. Results show that median travel time for buses on dedicated bi-directional lanes is within one minute of general traffic and during peak periods the buses are often faster. Schedule adherence was observed to be more challenging, with approximately 3% of buses arriving within 1 minute on average during the 5AM hour and 5% of buses arriving 6 - 9 minutes late during the 5PM hour. The framework and performance measures presented in this research provide agencies and transportation professionals with tools to identify opportunities for adjustments and to justify investment decisions.

关键词： Connected Vehicle Trajectory Bus Rapid Transit Performance traffic signal retiming Schedules

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