Requirements for automating signal timing plan design

A signal control system named Real-Time/Internal Metering Policy to Optimize Signal Timing (RT/IMPOST) has been under development for several years. It is designed to compute signal timing plans for the entire range of operating conditions from under- to oversaturation for control systems ranging from first generation (GEN 1) to highly responsive advanced traffic management systems. The different flow regimes of urban traffic control are reviewed. Then the focus is on the treatment to develop cycle-based signal timing plans for inclusion in the data libraries referenced by GEN 1 real-time traffic control systems for the undersaturated-flow regime. This approach decomposes a grid network into its constituent arterial subsystems in a way that is responsive to user-specified priorities. The user may define and rank the arterial systems subsumed within a grid network so as to satisfy strategic objectives responsive to traffic demand patterns and local needs. The procedure computes optimal signal timing plans for all these arterial subsystems in a priority-ranked sequence and integrates these arterial-based timing plans to form a networkwide signal timing plan. Field and simulation test results are presented. The field tests confirm that the IMPOST timing plans improved the operational performance of traffic along an arterial system in New York State relative to a fine-tuned existing control. The simulation studies compared the performance of traffic responding to IMPOST signal timing plans with that responding to Synchro 6.0 signal timing plans. The benefits of network decomposition and of arterial priority ranking are also documented.

For an actuated signalized intersection, pedestrian calls are likely to affect the effective greens serving the vehicle movements, which affect the capacity and delay of the intersection. However, the current procedure in the Highway Capacity Manual 2000 (HCM) for analyzing actuated signalized intersections treats pedestrian crossing and timing statically, with either pedestrian calls at all signal cycles or no pedestrians at all. In reality, pedestrian arrivals are random events with some cycles having more pedestrians than others and other cycles having no pedestrian call at all. This paper demonstrates that the current procedure can lead to erroneous results in capacity and delay estimations. A model is introduced to overcome the shortcomings in the current procedure. The model takes into account the stochastic nature of pedestrian crossings and their effects. The model computes the probability of having pedestrian calls in a cycle and the corresponding capacities and delays for traffic movements. An implementation framework was developed to help practitioners conduct capacity analyses using the model. The model's results on a semiactuated signal-controlled intersection were comparable with the results from the SimTraffic microsimulation model. The effects of pedestrians on intersection capacity and delay were analyzed using the proposed model. Depending on the pedestrian volume and traffic conditions, the current HCM procedure could produce significant error, especially when the pedestrian volume is low, because it does not consider the stochastic nature of pedestrian arrivals.

In recent years, my country’s road infrastructure has been vigorously constructed, urban road network density has increased, and road intersections have also been formed. There are more and more T-shaped intersections. Such intersections often have the characteristics of serious traffic intertwining and difficult traffic organization. Opposite the intersection of Zhan Qian Road and Min Zhu Zhong Road is the railway station. A large number of pedestrians have to pass through the intersection at rush hour or when the train arrives at the station. This road has a lot of people and a large number of non-motorized vehicles. The signal lights at the intersection are not perfect, and the traffic demand is large. In this paper, based on the current signal timing plan and the current status of the crosswalk at the intersection, based on the actual current data survey and service level analysis, the optimization design of the intersection signal timing plan and the crosswalk width optimization are completed. The results showed that the average delay at the intersection was improved by nearly 21 seconds, and the crosswalk lengths at the east entrance, west entrance and north entrance were optimized to 2.5m, 2.4m and 2.6m, respectively. Improved road capacity and reduced vehicle delays.

The main question to address in this paper is to recommend optimal signal timing plans in real time under incidents by incorporating domain knowledge developed with the traffic signal timing plans tuned for possible incidents, and learning from historical data of both traffic and implemented signals timing. The effectiveness of traffic incident management is often limited by the late response time and excessive workload of traffic operators. This paper proposes a novel decision-making framework that learns from both data and domain knowledge to real-time recommend contingency signal plans that accommodate non-recurrent traffic, with the outputs from real-time traffic prediction at least 30 min in advance. Specifically, considering the rare occurrences of engagement of contingency signal plans for incidents, it is proposed to decompose the end-to-end recommendation task into two hierarchical models—real-time traffic prediction and plan association. The connections between the two models are learnt through metric learning, which reinforces partial-order preferences observed from historical signal engagement records. The effectiveness of this approach is demonstrated by testing this framework on the traffic network in Cranberry Township, Pennsylvania, U.S., in 2019. Results show that the recommendation system has a precision score of 96.75% and recall of 87.5% on the testing plan, and makes recommendations an average of 22.5 min lead time ahead of Waze alerts. The results suggest that this framework is capable of giving traffic operators a significant time window to access the conditions and respond appropriately.

Traffic signal timings can be optimized with offline or online tools. Offline tools, such as Synchro, take a macroscopic approach, whereas genetic algorithm (GA) formulations rely on a close interaction with traffic microsimulators. Online tools, such as the Split-Cycle Offset Optimization Technique (SCOOT), optimize in real time. Offline optimization tools have the luxury of time for repetitive computation, whereas SCOOT must work quickly as it responds to traffic detected on the streets. A comparison of the best offline tools and adaptive signal control is presented. The signal timing plans are first derived from the Synchro macroscopic optimization tool. A genetic algorithm (GA)-based formulation, which is essentially stochastic, resides in the VISSIM traffic simulation software; the GA component is known as VISGAOST. The latest version of SCOOT (MC3) is modeled with upstream and stop line detectors to enable both phase skipping and overlaps. The test bed is closely modeled on a 14-intersection network in Park City, Utah. The quality of signal timings is evaluated for two traffic demand types: expected (no significant variation) and unexpected (random variations). Results indicate that the offline GA formulation provides the optimal signal timing plans, robust enough to accommodate even randomly changing traffic demand. Similar in performance to Synchro, SCOOT delivers a creditable quality of optimization for an online optimization tool.

1. Mechanoreceptors in the lamprey spinal cord have inputs to the central pattern generator (CPG) for locomotion. In the present study, imposed sinusoidal and pulsed movements were applied to the end of the in vitro lamprey spinal cord to excite the mechanoreceptors so that the relationship between entrainment and resetting of the locomotor rhythm could be examined. 2. The range over which the locomotor rhythm could be entrained by sinusoidal movements was asymmetric and occurred mostly at movement cycle times below the resting cycle time. During entrainment at the shortest cycle times, the movement phases were relatively small. 3. The phase response curves (PRCs) displayed the greatest shortening of cycle times (phase advance) for movement pulses applied during the first half of the locomotor cycle, whereas movement pulses applied during the second half of the cycle were largely ineffective. The amplitude of phase shifts in the PRC correlated with the ranges of cycle times over which entrainment occurred. 4. During resetting from movement pulses applied early in the cycle, the burst and interburst parts of the cycle shortened by about the same percentage. In addition, resetting effects occurred simultaneously along the spinal cord, suggesting a rapid distribution of timing information. 5. A computer model of the CPGs, consisting of left and right oscillators and inputs from mechanosensory elements, produced entrainment ranges that were symmetric around the resting cycle time. The PRCs from the model showed phase advance for movement pulses applied during the first half of the cycle and phase delay for pulses applied during the second half of the cycle. 6. Because of the asymmetric experimental PRCs for the lamprey spinal cord, gating was incorporated into the cooffter model such that oscillators on one side of the model gated inputs from mechanosensory elements on the same side. With gating, the model produced entrainment ranges that were asymmetric and confined to cycle times below the resting cycle time. The PRCs still showed phase advance for pulses applied at the beginning of the cycle, and the amount of phase delay produced during the second half of the cycle was substantially reduced compared with the simulations without gating.

The determination of the optimum phase scheme, cycle time, and green split for an isolated traffic signal is usually a very tedious and time-consuming activity. Several computer packages, such as the Micro-Sintral program, have been developed to assist in such situations by automating many of the calculations for a given set of inputs. Unfortunately, the inputs are often equally difficult to determine, and as they may depend upon the ultimate outcome of the optimization process, several time-consuming iterations, during which new input values must be calculated, are required. This paper presents a program called Signal Expert which automates the above iterations and therefore greatly reduces the traffic engineer's efforts in generating a new signal timing plan based on the rather sophisticated procedures that are outlined in the Canadian Capacity Guide. The benefits of applying this new program are illustrated and discussed using the example intersections that are analyzed in the Canadian Capacity Guide and in the Micro-Sintral User's Manual. Key words: isolated intersections, capacity, delay.

Data mining techniques for extracting knowledge from text have been applied extensively to applications including question answering, document summarisation, event extraction and trend monitoring. However, current methods have mainly been tested on small-scale customised data sets for specific purposes. The availability of large volumes of data and high-velocity data streams (such as social media feeds) motivates the need to automatically extract knowledge from such data sources and to generalise existing approaches to more practical applications. Recently, several architectures have been proposed for what we callknowledge mining: integrating data mining for knowledge extraction from unstructured text (possibly making use of a knowledge base), and at the same time, consistently incorporating this new information into the knowledge base. After describing a number of existing knowledge mining systems, we review the state-of-the-art literature on both current text mining methods (emphasising stream mining) and techniques for the construction and maintenance of knowledge bases. In particular, we focus on mining entities and relations from unstructured text data sources, entity disambiguation, entity linking and question answering. We conclude by highlighting general trends in knowledge mining research and identifying problems that require further research to enable more extensive use of knowledge bases.

Load-rating factors are used to evaluate the service life or safety of culverts based on the culvert wall strength and soil cover depth over the culvert. Current culvert load-rating methods have deficiencies in identifying potential critical conditions of corrugated metal culverts. Current load-rating procedures do not provide explicit guidance to the engineer for load rating and evaluation of culvert condition. To ensure good performance over the design life, corrugated metal culverts must be designed and regularly evaluated using an effective load-rating method. The main objective of this study was to investigate the effectiveness of current load-rating procedures. Recommendations are made to improve the analysis and evaluation procedures for corrugated metal culverts. The proposed load-rating procedure is based on an extensive review of load-rating procedures and design practices, experimental data, and theoretical investigations. The proposed method does not include a rating factor for cover depth. However, the design cover depth is required to be checked during the initial design stage to ensure structural stability. New capacity reduction factors are introduced for culvert wall and seam, which require different appraisals for wall and seam during annual inspections. The effect of external live loads is not included in the proposed load-rating procedure for deep culverts and for culverts subjected to low live load stresses. Field data from 39 in-service culverts showed that the proposed load-rating procedure is effective in evaluation of the existing condition of culverts.

The main problem in concluding business insurance contracts has the main obstacle – the coordination of the insurance premium between the corporation and the insurer. The notion of the Neumann-Morgenstern utility function was used to determine the level of interest of the corporation's employees. Based on the method developed earlier by the author to determine the utility function for corporations, a number of meetings were held with the management of the NGO "South" to determine the utility function of each group. To do this, they were offered a conditional game with the opportunity to win a large or small amount by paying some intermediate amount. At the same time, the probability of winning a large sum changed until the player became indifferent to winning or losing. The data were pooled and approximated by a transcendental model that included a power function, an exponent, and a sine wave. The search for model coefficients was performed by the method of optimization selection through the "Solution Search" function of Excel spreadsheets. The quality of the approximation was tested by Pearson's test with a confidence level of 0.8. The quality of the approximation is also confirmed by the almost complete coincidence of the graphs of the original function and the approximated one. The method of finding an acceptable amount of business insurance on the principle of greatest utility is given. To do this, the values of the probability of winning, the amounts of winnings and losses were the usefulness of this financial transaction with the use of approximation. Then, the weighted average utility was determined by the product of the probability of winning on the utility of the amount of gain with the addition of the product of the probability of loss on the utility of the amount of loss. According to the developed methodology, acceptable insurance premiums were calculated for four launches under the Sea Start program for the case when the insurance company independently determined the probability of a failed launch. It is shown that the sum insured demanded by the insurers significantly exceeded the amount that the corporation agreed to pay. The conclusions provide an additional calculation for a failed start-up and show that in the latter case it would be more profitable to abandon the insurance. It is also recommended before concluding the insurance contract to perform the proposed procedure to reduce the period of approval of the amount of insurance premiums.

An Evaluative Framework for Assessment of Disposal Options for Colliery Spoil

A prompt displaying of inventory in the accounting process is a key aspect of information management of the enterprise’s inventory. Themaingoalis to immediate uniform a wide range of internal users in order to provide real-time decision-making. Therefore, the objective of the article is to provide scientific basis for accounting and analytical provision of relevant information about inventory of the enterprise under conditions of restrictions based on economic and mathematical methods and models in order to make effective management decisions. In the study, the leading role was given to the organization of correct and rational accounting of current assets in enterprises. The approaches and main tasks of inventory accounting were analyzed. Procedures and techniques for inventory management in management accounting were evaluated quite critically, taking into account the limited resources of the enterprise. The article analyzes theoretical framework, methodological approaches and recommendations for the formation of accounting and analytical provision of relevant information about inventory of the enterprise under conditions of restrictions for effective management decisions based on economic and mathematical methods and models. The digitalization of accounting processes of top management demands that the fastest and most precise ways to solve management tasks be used. The analysis of the decision on inventory depends on the number of restrictions. If there are three or more constraints, linear programming is used for analysis. In other words, this is a method used for optimizing the manufacturing process by solving a series of linear equations. As a result, it was established, that the obtained optimal integer plan of required inventory is not the only one to ensure the maximum value of the target function (revenue). Obtaining specific values of the optimal plan of inventory depends on the settings of the MS Excel "Solution Search" and the initial values of the plan of inventory. While working with production inventory of the enterprise, linear programming is quite effective and can be used in any enterprise to make management decisions under conditions of limited resources based on relevant accounting information in order to ensure a competitive position in the market.

Intersections in cities are important transport hubs, where traffic flows from all roads meet, connect, disconnect or intersect. This research is dedicated to the creation of simulation models of intersections and is based on real observations of two crossroads in a city. The principle is based on observing traffic flows using real traffic counting at peak times. The aim is to reduce traffic congestion by adjusting signal plans on the monitored section using computer simulation and modelling in ExtendSim8 software, which is a universal tool allowing the user to simulate any system or process by creating a logical representation in an easy-to-use format. According to our preliminary literature research, the ExtendSim software has never before been used before to create an intersection simulation to optimize the signal plan. There are several specialized software products for simulating traffic and intersections, but not everyone has access to these, or else they require lengthy user training. Therefore, it is very advantageous to use a universal simulation tool that is not used for traffic simulation at intersections in the city. The article points out that a universal simulation program such as ExtendSim can also be used in the design or assessment of signal plans at intersections.

The prediction of an additional space for the dose sparing of organs at risk (OAR) in radiotherapy is still difficult. In this pursuit, the present study was envisaged to find out the factors affecting the bladder and rectum dosimetry of cervical cancer. Additionally, the relationship between the dose-volume histogram (DVH) parameters and the geometry and plan dose-volume optimization parameters of the bladder/rectum was established to develop the dose prediction models and guide the planning design for lower OARs dose coverage directly. Thirty volume modulated radiation therapy (VMAT) plans from cervical cancer patients were randomly chosen to build the dose prediction models. The target dose coverage was evaluated. Dose prediction models were established by univariate and multiple linear regression among the dosimetric parameters of the bladder/rectum, the geometry parameters (planning target volume (PTV), volume of bladder/rectum, overlap volume of bladder/rectum (OV), and overlapped volume as a percentage of bladder/rectum volume (OP)), and corresponding plan dose-volume optimization parameters of the nonoverlapping structures (the structure of bladder/rectum outside the PTV (NOS)). Finally, the accuracy of the prediction models was evaluated by tracking d = (predicted dose-actual dose)/actual in additional ten VMAT plans. V30, V35, and V40 of the bladder and rectum were found to be multiple linearly correlated with the relevant OP and corresponding dose-volume optimization parameters of NOS (regression R2 > 0.99, P < 0.001). The variations of these models were less than 0.5% for bladder and rectum. Percentage of bladder and rectum within the PTV and the dose-volume optimization parameters of NOS could be used to predict the dose quantitatively. The parameters of NOS as a limited condition could be used in the plan optimization instead of limiting the dose and volume of the entire OAR traditionally, which made the plan optimization more unified and convenient and strengthened the plan quality and consistency.

Accurate prediction of cycle time (CT) plays an important role in the promises of a good delivery-time for semiconductor manufacturers. However, the CTs of wafer lots are difficult to forecast since they are influent by a lot factors (e.g., workload for every machine). The identification of key factors (called CT-related) can not only improve the prediction performance but also facilitate the control of CT, which is of particular significance. This paper focuses on gathering subtle variables into the candidate variables set along with the further analysis which is required in the correlation analysis between various candidate factors and CTs of wafer lots. The candidates set is first constructed to collect all factors that may affect wafer lots’ CT. Then, a regression-based model is proposed to select CT-related variables, which consists of three parts: 1) discretization; 2) adaptive logistic regression-based correlation analysis; and 3) CT-related factor selection. Subsequently, a parallel computation model is implemented to forecast the CTs of wafer lots. In the numerical experiments, 108 CT-related factors stood out from 774 candidates and replaced six global factors (used as reference) to predict CTs of wafer lots. The results indicated that the proposed approach had higher accuracy than linear regression and back propagation network in CT forecasting in large scale data analysis.