Framework for Quantitative Annual Evaluation of Traffic Signal Systems

Author(s):  
Danilo Radivojevic ◽  
Aleksandar Stevanovic

The evaluation of traffic signal systems on an agency level can be of great importance for identifying problems, self-assessing, budgeting, creating a strategy for future steps, and so on. The most famous similar effort of this type is the National Traffic Signal Report Card, which is used as an evaluation methodology for agencies countrywide. The main difference in the proposed methodology is that it steps away from qualitative evaluation and grading and presents a new set of procedures for implementation of quantitative—and therefore more unbiased—evaluation methodology. The proposed methodology should enable self-evaluation and comparison between agencies in relation to agency management, traffic signal operations, signal timing practices, traffic monitoring, data collection, and maintenance. For two agencies, the numerical and logical values of the answers are used in the evaluation process to obtain preliminary results that are displayed with a confidence measure to explain that process. The proposed methodology shows potential, especially if the number of the available data types increases with the introduction of high-resolution data-logging controllers into regular operations. With those additional performance measures, the methodology could be used for tracking the results of operating traffic signals by government institutions or private companies.

Author(s):  
Christopher M. Day ◽  
Howell Li ◽  
James R. Sturdevant ◽  
Darcy M. Bullock

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.


Author(s):  
Tingting Huang ◽  
Subhadipto Poddar ◽  
Cristopher Aguilar ◽  
Anuj Sharma ◽  
Edward Smaglik ◽  
...  

Automated traffic signal performance measures (ATSPMs) are designed to equip traffic signal controllers with high-resolution data-logging capabilities which may be used to generate performance measures. These measures allow practitioners to improve operations as well as to maintain and operate their systems in a safe and efficient manner. While they have changed the way that operators manage their systems, several shortcomings of ATSPMs, as identified by signal operators, include a lack of data quality control and the extent of resources required to use the tool properly for system-wide management. To address these shortcomings, intelligent traffic signal performance measurements (ITSPMs) are presented in this paper, using the concepts of machine learning, traffic flow theory, and data visualization to reduce the operator resources needed for overseeing data-driven ATSPMs. In applying these concepts, ITSPMs provide graphical tools to identify and remove logging errors and data from bad sensors, to determine trends in demand intelligently, and to address the question of whether or not coordination may be needed at an intersection. The focus of ATSPMs and ITSPMs on performance measures for multimodal users is identified as a pressing need for future research.


Author(s):  
Marija Ostojic ◽  
Archak Mittal ◽  
Hani S. Mahmassani

Connected environments offer more information, improved data availability and quality which can lead to better decision making; new meaningful information adds new functionalities and opportunities to advance operational efficiency. Can traffic signal system efficiency and mobility be measured and enhanced in innovative and meaningful ways by combining two data sources - connected vehicle-generated and controller event logs? This paper develops a comprehensive signal systems performance assessment framework that aims to offer better understanding of current traffic signal practices and standards and add new functionalities and opportunities to enhance signal systems operations. Its core is a novel performance metric that provides a holistic representation of the system which traditional metrics do not offer. To develop and demonstrate the concept, the study used simulation data in a format that corresponds to high resolution data (signal status and vehicle positions) on a tenth of a second level. Vehicle trajectory information is processed, fused with control data, synthesized to produce "information" required to develop a signalized approach performance estimation method. The data analysis platform presented in this study is intended to comprehensively characterize the state of the signalized system and help identify causes of inferior intersection performance by defining a set of visual and quantitative success indicators. The practicality of this method is reflected in reducing the time and effort required by the existing signal design/retiming practice, since trajectory-signal signatures distinguish between incidents and retiming opportunities caused by changing traffic conditions.


Author(s):  
Rashi Maheshwari

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.


2020 ◽  
Author(s):  
Mark Brinton ◽  
Elliott Barcikowski ◽  
Tyler Davis ◽  
Michael Paskett ◽  
Jacob George ◽  
...  

AbstractThis paper describes a portable, prosthetic control system for at-home use of an advanced bionic arm. The system uses a modified Kalman filter to provide 6 degree-of-freedom, real-time, proportional control. We describe (a) how the system trains motor control algorithms for use with an advanced bionic arm, and (b) the system’s ability to record an unprecedented and comprehensive dataset of EMG, hand positions and force sensor values. Intact participants and a transradial amputee used the system to perform activities-of-daily-living, including bi-manual tasks, in the lab and at home. This technology enables at-home dexterous bionic arm use, and provides a high-temporal resolution description of daily use—essential information to determine clinical relevance and improve future research for advanced bionic arms.


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