scholarly journals Performance measures for managing urban traffic signal systems

2009 ◽  
Author(s):  
D. M. Bullock ◽  
C. M. Day
Keyword(s):  
Performance Measures ◽  
Traffic Signal ◽  
Urban Traffic ◽  
Signal Systems

Data-Driven Ranking of Coordinated Traffic Signal Systems for Maintenance and Retiming

2018 ◽  
Vol 2672 (18) ◽  
pp. 167-178 ◽  
Author(s):  
Christopher M. Day ◽  
Howell Li ◽  
James R. Sturdevant ◽  
Darcy M. Bullock
Keyword(s):  
Performance Measures ◽  
Capacity Allocation ◽  
Traffic Signal ◽  
System Level ◽  
High Resolution Data ◽  
Individual Agency ◽  
Signal Systems ◽  
Analysis Process ◽  
Quantitative Performance ◽  
Further Development

Automated traffic signal performance measures (ATSPMs) have been deployed with increasing frequency. At present, the existing ATSPMs are focused on the performance of individual movements or intersections. As the number of ATSPM users has increased, a need for system-level metrics has emerged. This paper proposes a method of evaluating corridor performance at the system level using high-resolution data. The method is demonstrated for eight signalized corridors in Indiana, including 87 intersections. This method develops five subscores for the areas of communication, detection, safety, capacity allocation, and progression; these five interrelated aspects of performance are each given a category subscore based on quantitative performance measures, with scales appropriate to the context of the operation. An overall score for each corridor is determined from the lowest subscore of each of the five areas. This approach simplifies the analysis process, as opposed to examining several hundred individual movements as currently would be required using ATSPM tools that are commonly available at present. The methodology is presented as a prototype for further development and adaptation to individual agency objectives and data sources.

scholarly journals Performance Measures for Traffic Signal Systems: An Outcome-Oriented Approach

2014 ◽  
Author(s):  
Christopher Day ◽  
Darcy Bullock ◽  
Howell Li ◽  
Stephen Remias ◽  
Alexander Hainen ◽  
...  
Keyword(s):  
Performance Measures ◽  
Traffic Signal ◽  
Signal Systems ◽  
Oriented Approach

Scalable and Actionable Performance Measures for Traffic Signal Systems using Probe Vehicle Trajectory Data

2020 ◽  
Vol 2674 (11) ◽  
pp. 304-316
Author(s):  
Jonathan M. Waddell ◽  
Stephen M. Remias ◽  
Jenna N. Kirsch ◽  
Stanley E. Young
Keyword(s):  
Performance Measures ◽  
Transportation Network ◽  
Traffic Signal ◽  
Third Party ◽  
Travel Time Reliability ◽  
Trajectory Data ◽  
Average Delay ◽  
Signal Systems ◽  
Vehicle Trajectory ◽  
High Level

Scalable and actionable performance measures for traffic signal systems provide opportunities for practitioners to measure and improve the transportation network. Historically, traffic signal improvements have relied on scheduled signal retiming based on limited data collection, or on the public to call and alert engineers of an issue. This inefficient method of improving signal timing led to the creation of automated traffic signal performance measures (ATSPMs). These metrics rely on expensive infrastructure, including detection and communications, which has produced barriers for numerous agencies to fully adopt. Recently, third-party data providers have begun to release vehicle trajectory data, which allows for enhanced signal metrics with no investment in physical equipment. The purpose of this study is to demonstrate the use of these data and summarize the scalability of the created metrics. This work builds on previous efforts to quantify signal performance on nine intersections in Michigan, U.S. Ten signalized corridors in Columbus, Ohio, were chosen to scale a performance assessment using crowdsourced trajectory data. A total of 136 intersections were assessed in 2-h intervals using data from all weekdays in 2017. High-level corridor summary metrics including average percent of vehicles stopping (18%–32%), average delay (9.4–20.5 s), and level of travel time reliability (1.23–2.73) were calculated for each corridor direction. Intersection-level metrics were also introduced, which can be used by practitioners to identify problems, improve signal timings, and prioritize future infrastructure investments.

Extremum-Seeking for Adaptation of Urban Traffic Signal Control

2014 ◽  
Vol 47 (3) ◽  
pp. 5067-5072 ◽  
Author(s):  
Ronny Kutadinata ◽  
Will Moase ◽  
Chris Manzie ◽  
Lele Zhang ◽  
Tim Garoni
Keyword(s):  
Traffic Signal ◽  
Urban Traffic ◽  
Extremum Seeking ◽  
Signal Control ◽  
Traffic Signal Control

scholarly journals Signal Preemption Control of Emergency Vehicles Based on Timed Colored Petri Nets

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Haibo Mu ◽  
Linzhong Liu ◽  
Xiaojing Li
Keyword(s):  
Petri Nets ◽  
Control Strategies ◽  
Traffic Signal ◽  
Urban Traffic ◽  
Colored Petri Nets ◽  
Current Phase ◽  
Emergency Vehicle ◽  
Phase Switching ◽  
Emergency Vehicles ◽  
Timed Colored Petri Nets

This paper focuses on the use of timed colored Petri nets (TCPN) to study emergency vehicle (EV) preemption control problem. TCPN is adopted to establish an urban traffic network model composed of three submodels, namely, traffic flow model, traffic signal display and phase switch model, and traffic signal switch control model. An EV preemption optimization control system, consisting of monitoring subsystem, phase time determination subsystem, and phase switching control subsystem, is designed. The calculation method of the travelling speed of EV on road sections is presented, and the methods of determining the actual green time of current phase and the other phase are given. Some computational comparisons are performed to verify the signal preemption control strategies, and simulation results indicate that the proposed approach can provide efficient and safe running environments for emergency vehicles and minimize EV’s interference to social vehicles simultaneously.

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