Traffic Incident Management Performance Measures: Ranking Agencies on Roadway Clearance Time

This study develops a procedure to rank agencies based on their incident responses using roadway clearance times for crashes. This analysis is not intended to grade agencies but to assist in identifying agencies requiring more training or resources for incident management. Previous NCHRP reports discussed usage of different factors including incident severity, roadway characteristics, number of lanes involved and time of incident separately for estimating the performance. However, it does not tell us how to incorporate all the factors at the same time. Thus, this study aims to account for multiple factors to ensure fair comparisons. This study used 149,174 crashes from Iowa that occurred from 2018 to 2021. A Tobit regression model was used to find the effect of different variables on roadway clearance time. Variables that cannot be controlled directly by agencies such as crash severity, roadway type, weather conditions, lighting conditions, etc., were included in the analysis as it helps to reduce bias in the ranking procedure. Then clearance time of each crash is normalized into a base condition using the regression coefficients. The normalization makes the process more efficient as the effect of uncontrollable factors has already been mitigated. Finally, the agencies were ranked by their average normalized roadway clearance time. This ranking process allows agencies to track their performance of previous crashes, can be used in identifying low performing agencies that could use additional resources and training, and can be used to identify high performing agencies to recognize for their efforts and performance.

Diverging Diamond Interchange Performance Measures Using Connected Vehicle Data

Since the first Diverging Diamond Interchange (DDI) implementation in 2009, most of the performance studies developed for this type of interchange have been based on simulations and historical crash data, with a small number of studies using Automated Traffic Signal Performance Measures (ATSPM). Simulation models require considerable effort to collect volumes and to model actual controller operations. Safety studies based on historical crashes usually require from 3 to 5 years of data collection. ATSPMs rely on sensing equipment. This study describes the use of connected vehicle trajectory data to analyze the performance of a DDI located in the metropolitan area of Fort Wayne, IN. An extension of the Purdue Probe Diagram (PPD) is proposed to assess the levels of delay, progression, and saturation. Further, an additional PPD variation is presented that provides a convenient visualization to qualitatively understand progression patterns and to evaluate queue length for spillback in the critical interior crossover. Over 7000 trajectories and 130,000 GPS points were analyzed between the 7th and the 11th of June 2021 from 5:00 AM to 10:00 PM to estimate the DDI’s arrivals on green, level of service, split failures, and downstream blockage. Although this technique was demonstrated for weekdays, the ubiquity of connected vehicle data makes it very easy to adapt these techniques to analysis during special events, winter storms, and weekends. Furthermore, the methodologies presented in this paper can be applied by any agency wanting to assess the performance of any DDI in their jurisdiction.

Diamond Interchange Performance Measures Using Connected Vehicle Data

Diamond interchanges are frequently used where a freeway intersects a two-way surface street. Most of the techniques to evaluate the performance of diamond interchanges rely on the Highway Capacity Manual (HCM), simulation, Automated Traffic Signal Performance Measures (ATSPMs), and historical crash data. HCM and simulation techniques require on-site data collection to obtain models’ inputs. ATSPMs need high-resolution controller event data acquired from roadway sensing equipment. Safety studies typically need 3 to 5 years of crash data to provide statistically significant results. This study utilizes commercially available connected vehicle (CV) data to assess the performance and operation of a three- and four-phase diamond interchange located in Indianapolis, Indiana, and Dallas, Texas, respectively. Over 92,000 trajectories and 1,400,000 GPS points are analyzed from August 2020 weekdays CV data. Trajectories are linear-referenced to generate Purdue Probe Diagrams (PPDs) from which arrivals on green (AOG), split failures, downstream blockage, and movement-based control delay are estimated. In addition, an extension of the PPD is presented that characterizes the complete journey of a vehicle travelling through both signals of the diamond interchange. This enhanced PPD is a significant contribution as it provides an analytical framework and graphical summary of the operational characteristics of how the external movements traverse the entire system. The four-phase control showed high internal progression (99% AOG) compared to the moderate internal progression of the three-phase operation (64% AOG). This is consistent with the design objectives of three- and four-phase control models, but historically these quantitative AOG measures were not possible to obtain with just detector data. Additionally, a graphical summary that illustrates the spatial distribution of hard-braking and hard-acceleration events is also provided. The presented techniques can be used by any agency to evaluate the performance of their diamond interchanges without on-site data collection or capital investments in sensing infrastructure.

Congruity of Multiple Performance Measures

In multi-action situation, there are losses of efficiency due to noise effect and incongruity effect. To isolate noise effect, we prove that the loss of efficiency is zero if and only if the objective of the principal is a linear representation of the performance measures when the performance measures are noiseless. Using this result, several definitions of incongruity are given. Our definitions extend the single performance definition given in Feltham and Xie （1994） to multiple performance measures situation, and reconcile the conflict between the definition given in Datar et al. （2001） and that in Feltham and Xie （1994）. A numeric example is analyzed to show the way that the variances of measures and correlation coefficient between measures affect the utility of the principal.

Continuous Flow Intersection Performance Measures Using Connected Vehicle Data

Continuous flow intersections (CFIs), also known as displaced left turns (DLTs), are a type of alternative intersection designed to improve operations at locations with heavy left-turn movements by reallocating these vehicles to the left side of opposing traffic. Currently, simulation is commonly used to evaluate operational performance of CFIs. However, this approach requires significant on-site data collection and is highly dependent on the analyst’s ability to correctly model the intersection and driver behavior. Recently, connected vehicle (CV) trajectory data has become widely available and presents opportunities for the direct measurement of traffic signal performance measures. This study utilizes CV trajectory data to analyze the performance of a CFI located in West Valley City, UT. Over 4500 trajectories and 105,000 GPS points are analyzed from August 2021 weekday data. Trajectories are linear-referenced to generate Purdue Probe Diagrams (PPDs) and extended PPDs to estimate split failures (SF), arrivals on green (AOG), traditional Highway Capacity Manual (HCM) level of service (LOS), and the distribution of stops. The estimated operational performance showed effective progression during the PM peak period at all the critical internal storage areas with AOG levels at exit traffic signals between 83% and 100%. In contrast, all external approaches with longer queue storage areas had AOG values ranging from 2% to 81% during the same time period. The presented analytical techniques and summary graphics provide practitioners with tools to evaluate the performance of any CFI where CV trajectories are available without the need for on-site data collection.

Can composite performance measures predict survival of patients with colorectal cancer?

AIM: To assess the relationship between long-term colorectal patient survival and methods of calculating composite performance scores.

Information Conductivity:Universal Performance Measure for Semantic Communications

As a novel paradigm,semantic communication provides an effective solution for breaking through the future development dilemma of classical communication systems.However,it remains an unsolved problem of how to measure the information transmission capability for a given semantic communication method and subsequently compare it with the classical communication method.In this paper,we first present a review of the semantic communication system,including its system model and the two typical coding and transmission methods for its implementations.To address the unsolved issue of the information transmission capability measure for semantic communication methods,we propose a new universal performance measure called Information Conductivity.We provide the definition and the physical significance to state its effectiveness in representing the information transmission capabilities of the semantic communication systems and present elaborations including its measure methods,degrees of freedom,and progressive analysis.Experimental results in image transmission scenarios validate its practical applicability.

Measuring Raters' Scoring Performance and Their Scoring Results in Terms of Writing Performance Measures

This explorative study investigates 1） whether and how quantitative measures of writing can be applied in finding out about scoring raters＇ specific tendency in their scoring of EFL writing; 2） how the knowledge of raters＇ tendency and scoring results would help verify the best way of combining raters＇ scores; and 3） how the prediction of the writing scores of EFL writing obtained by quantitative writing performance measures would match the real scores given by raters. Based on a tentative CAF framework of writing measures, raters＇ performance or tendency in their scoring was observed and certain patterns of similarities as well as differences were found among the raters. The resuks of multiple linear regressions indicate that all raters give prior attention to the aspect of accuracy in their scoring. Differences among raters are also obvious. When it comes to the combination of different raters＇ scores, the study also finds that weighted average is the best of the three ways of combining scores for this group of raters because it has yielded the best predicting scores than the ＂pure average＂. It is even slightly better than the results obtained by facet analysis in terms of some important indices such as R square and Durbin-Watson value. The matching of the predicted scores with the real scores is well over 50 percent. The results of the study are further discussed in relation to the application of wpm and the possible improvement of wpm framework. The methodological, theoretical and practical implications of the study have also been touched upon in the relevant part of the article.

Performance measures in evaluating machine learning based bioinformatics predictors for classifications

Many existing bioinformatics predictors are based on machine learning technology. When applying these predictors in practical studies, their predictive performances should be well understood. Different performance measures are applied in various studies as well as different evaluation methods. Even for the same performance measure, different terms, nomenclatures or notations may appear in different context. Results： We carried out a review on the most commonly used performance measures and the evaluation methods for bioinformatics predictors. Conclusions： It is important in bioinformatics to correctly understand and interpret the performance, as it is the key to rigorously compare performances of different predictors and to choose the right predictor.

A Nationwide Evaluation of the State of Practice of Performance Measurements for Intelligent Transportation Systems

State departments of transportation’s (DOTs) decisions to invest resources to expand or implement intelligent transportation systems (ITS) programs or even retire existing infrastructure need to be based on performance evaluations. Nonetheless, an apparent gap exists between the need for ITS performance measurements and the actual implementation. The evidence available points to challenges in the ITS performance measurement processes. This paper evaluated the state of practice of performance measurement for ITS across the US and provided insights. A comprehensive literature review assessed the use of performance measures by DOTs for monitoring implemented ITS programs. Based on the gaps identified through the literature review, a nationwide qualitative survey was used to gather insights from key stakeholders on the subject matter and presented in this paper. From the data gathered, performance measurement of ITS is fairly integrated into ITS programs by DOTs, with most agencies considering the process beneficial. There, however, exist reasons that prevent agencies from measuring ITS performance to greater detail and quality. These include lack of data, fragmented or incomparable data formats, the complexity of the endeavor, lack of data scientists, and difficulty assigning responsibilities when inter-agency collaboration is required. Additionally, DOTs do not benchmark or compare their ITS performance with others for reasons that include lack of data, lack of guidance or best practices, and incomparable data formats. This paper is relevant as it provides insights expected to guide DOTs and other agencies in developing or reevaluating their ITS performance measurement processes.

Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualization and Performance Measurement

Emerging connected vehicle (CV) data sets have recently become commercially available, enabling analysts to develop a variety of powerful performance measures without deploying any field infrastructure. This paper presents several tools using CV data to evaluate traffic progression quality along a signalized corridor. These include both performance measures for high-level analysis as well as visualizations to examine details of the coordinated operation. With the use of CV data, it is possible to assess not only the movement of traffic on the corridor but also to consider its origin-destination (O-D) path through the corridor. Results for the real-world operation of an eight-intersection signalized arterial are presented. A series of high-level performance measures are used to evaluate overall performance by time of day, with differing results by metric. Next, the details of the operation are examined with the use of two visualization tools: a cyclic time-space diagram (TSD) and an empirical platoon progression diagram (PPD). Comparing flow visualizations developed with different included O-D paths reveals several features, such as the presence of secondary and tertiary platoons on certain sections that cannot be seen when only end-to-end journeys are included. In addition, speed heat maps are generated, providing both speed performance along the corridor and locations and the extent of the queue. The proposed visualization tools portray the corridor’s performance holistically instead of combining individual signal performance metrics. The techniques exhibited in this study are compelling for identifying locations where engineering solutions such as access management or timing plan change are required. The recent progress in infrastructure-free sensing technology has significantly increased the scope of CV data-based traffic management systems, enhancing the significance of this study. The study demonstrates the utility of CV trajectory data for obtaining high-level details of the corridor performance as well as drilling down into the minute specifics.

PerfMon: Measuring Application-Level Performance in a Large-Scale Campus Wireless Network

WiFi has become one of the most popular ways to access the Internet.However,in large-scale campus wireless networks,it is challenging for network administrators to provide optimized access quality without knowledge on fine-grained traffic characteristics and real network performance.In this paper,we implement PerfMon,a network performance measurement and diagnosis system,which integrates collected multi-source datasets and analysis methods.Based on PerfMon,we first conduct a comprehensive measurement on application-level traffic patterns and behaviors from multiple dimensions in the wireless network of T university(TWLAN),which is one of the largest campus wireless networks.Then we systematically study the application-level network performance.We observe that the application-level traffic behaviors and performance vary greatly across different locations and device types.The performance is far from satisfactory in some cases.To diagnose these problems,we distinguish locations and device types,and further locate the most crucial factors that affect the performance.The results of case studies show that the influential factors can effectively characterize performance changes and explain for performance degradation.

A survey of time consistency of dynamic risk measures and dynamic performance measures in discrete time: LM-measure perspective

In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures,focusing on a the discrete time setup.The two key operational concepts used throughout are the notion of the LMmeasure and the notion of the update rule that,we believe,are the key tools for studying time consistency in a unified framework.

Analysis of Historic Pavement and Bridge Conditions and Alternative Funding Levels for the Michigan Department of Transportation

In 1997 the Michigan Department of Transportation (MDOT) established an ambitious set of condition targets for its pavements and bridges, and the Department received increased revenue from a 4-cent-per-gallon increase in the state motor fuels tax to help meet its targets. However, over time, actual revenue was less than both what was initially estimated as needed to meet the targets and what was projected from the tax increase. Consequently, actual conditions were projected to fall short of the target levels, so the department issued bonds to address the shortfall through 2012. To support deliberations on future funding, in 2013 MDOT performed an analysis of historic conditions to determine what additional fuel tax revenues would have been required beginning in 1997 to: replace bond revenues used to fund pavement and bridge projects from 1997 to 2012;and enable MDOT to meet its condition targets. The analysis was performed using data on actual pavement and bridge funding and conditions;as well as predicted funding and conditions for different hypothetical increases in fuel taxes. The analysis concluded that, in addition to the actual increase of 4 cents per gallon, a fuel tax increase of another 10 cents per gallon would have been required in 1997 to replace bond revenue used for pavement and bridges and allow MDOT to meet its condition targets. The analysis results were used to help inform the discussion of Michigan’s target asset conditions and funding, and demonstrate application of MDOT’s pavement and bridge management systems for performing historic analyses.

Longitudinal Performance Assessment of Traffic Signal System Impacted by Long-Term Interstate Construction Diversion Using Connected Vehicle Data

Local arterials can be significantly impacted by diversions from adjacent work zones. These diversions often occur on unofficial detour routes due to guidance received on personal navigation devices. Often, these routes do not have sufficient sensing or communication equipment to obtain infrastructure-based traffic signal performance measures, so other data sources are required to identify locations being significantly affected by diversions. This paper examines the network impact caused by the start of an 18-month closure of the I-65/70 interchange (North Split), which usually serves approximately 214,000 vehicles per day in Indianapolis, IN. In anticipation of some proportion of the public diverting from official detour routes to local streets, a connected vehicle monitoring program was established to provide daily performances measures for over 100 intersections in the area without the need for vehicle sensing equipment. This study reports on 13 of the most impacted signals on an alternative arterial to identify locations and time of day where operations are most degraded, so that decision makers have quantitative information to make informed adjustments to the system. Individual vehicle movements at the studied locations are analyzed to estimate changes in volume, split failures, downstream blockage, arrivals on green, and travel times. Over 130,000 trajectories were analyzed in an 11-week period. Weekly afternoon peak period volumes increased by approximately 455%, split failures increased 3%, downstream blockage increased 10%, arrivals on green decreased 16%, and travel time increase 74%. The analysis performed in this paper will serve as a framework for any agency that wants to assess traffic signal performance at hundreds of locations with little or no existing sensing or communication infrastructure to prioritize tactical retiming and/or longer-term infrastructure investments.

Workflow logs analysis system for enterprise performance measurement

Workflow logs that record the execution of business processes offer very valuable data resource for real-time enterprise performance measurement. In this paper, a novel scheme that uses the technology of data warehouse and OLAP to explore workflow logs and create complex analysis reports for enterprise performance measurement is proposed. Three key points of this scheme are studied: 1) the measure set; 2) the open and flexible architecture for workflow logs analysis system; 3) the data models in WFMS and data warehouse. A case study that shows the validity of the scheme is also provided.

Roundabout Performance Analysis Using Connected Vehicle Data

There are over 8000 roundabouts in the United States. The current techniques for assessing their performance require field counts to provide inputs to analysis or simulation models. These techniques are labor-intensive and do not scale well. This paper presents a methodology to use connected vehicle (CV) trajectory data to estimate delay and level of service for roundabout approaches by adapting the Purdue Probe Diagram used for traffic signal analytics. By linear referencing vehicle trajectories with a particular movement based on the location and time they exit a roundabout, delay can be calculated. The scalability is demonstrated by applying these techniques to assess over 100 roundabouts in Carmel, IN during the weekday afternoon peak period in July 2021. Over 264,000 trajectories and 3,600,000 GPS points were analyzed to rank over 300 roundabout approaches by delay and summarize in Pareto-sorted graphics and maps. The paper concludes by discussing how these techniques can also be used to analyze queue lengths and origin-destination characteristics at roundabouts. The methodology presented in this study can be used by any agency that wants to assess the performance of all roundabouts in their system.

Proposal of a Conceptual Model to Analyse the Influence of LARG Practices on Manufacturing Supply Chain Performance

The main objective of this paper is to propose a conceptual model about the influence of lean, agile, resilient, and green （LARG） practices on supply chain operational, economic and environmental performance. This model is based on the literature review about the four supply chain management paradigms and also performance measurement systems. This paper contributes to the literature by introducing a new model to improve the leanness, agility, resilience, and greenness of manufacturing supply chains. Among the suggested LARG practices, the ones influencing more the supply chain performance are the just in time and also the supplier relationships. Also the supply chain performance measures with more LARG practices influencing them are the inventory levels and the time, that is, the supply chain＇s operational performance is the most affected by the simultaneous paradigms deployment in the supply chain.

Test Rig Effect on Performance Measurement for Low Loaded Large-Diameter Fan for Automotive Application

Large diameter fans with low solidity are widely used in automotive application for engine cooling. Their designs with small chord length help reducing the torque on the electrical motor and providing a good aerodynamic compromise between several operating conditions, some of these being at high flow rate. Their global performances are measured according to the ISO standard DP 5801, which allows comparison of results from different facilities. However, some variations in global performances are observed when considering results from two different test rigs. On a fan selected for the purpose of this study, up to 6 % of efficiency is lost on the worst case. As efficiency is more than ever a key factor to select a component, some experimental and numerical investigations were conducted to analyze the fan behavior on each facility. Two sets of measurement and simulation are performed and compared. Geometries considered for the domain of computation include the test rig plenum, the torquemeter, the ground and a large domain for the atmospheric conditions. The exact fan geometry with tip clearance and under-hub ribs is also considered. Numerical results show a good agreement with experiment in both cases when convergence is reached and for low flow rate when computations are switched to unsteady mode. Comparisons show that simulations are able to capture the different fan behaviors depending on the confguration and those efficiency losses previously observed are correctly predicted. These results are further analyzed to perform some post-processing. Blade loading remains identical for both cases but disparities appear in the wake and its interaction with the surrounding. Tiny details that are often neglected during experiment and/or simulation appear to be the cause of slight variations. Position of the torquemeter and shape of the plenum are among the parameters that various and that have cumulative effects. Efficiency being a ration of pressure and torque, variations are rather important. Finally, these results are discussed in terms of rules for conception and a new geometry less sensible to loss of efficiency is proposed.

Analyzing the Operational Performance Migration of Telecom Operators

Due to the rapid development of mobile Internet services, such as Skype and WeChat, traditional telecom services have suffered a large decline in the business volumes in recent years. Thus, telecom operators pay much attention to analyzing the changes of the enterprise performance, in order to adjust market strategies in time. In this paper, we propose a new methodology to analyze the operation data of telecom operators dynamically,which can characterize the changing process of the operating states and predict the developing trends. In particular, the proposed methodology contains two steps: migration pattern analysis and trajectory pattern analysis.Firstly, migration analysis is based on the changing of operating states between two points-in-time, which is referred to as the migration paths. Applying the clustering analysis to the migration paths can obtain the migration patterns, which characterize the changing feature of telecom operators during a short period, e.g. one month. Secondly, we combine a sequence of consecutive migration paths to obtain the migration trajectory. Through analyzing different trajectories based on the hierarchical cluster method and the Markov chain model, we obtain the trajectory patterns,which describe the changing progress during a relatively long period, e.g. one year. Based on the trajectory patterns, we can predict the possible performance changes. Finally, we apply the proposed method to a Chinese telecom operator for an empirical research, and has obtained a lot of development rules which provides insights into current telecom.