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• Federated learning is applied in the regional transportation systems to improve the accuracy of traffic flow prediction and protect the privacy of vehicles. • Road weight measurement with a traffic flow prediction model is used for vehicle route optimization. • Departure strategies are used to optimize the scheduling of vehicles to improve overall regional travel efficiency. • Experiments show that the proposed scheme can optimize the transportation system while protecting data privacy. In recent years, regional traffic congestion has become increasingly frequent, which seriously affects the safety and efficiency of urban vehicles. Therefore, traffic flow prediction methods based on artificial intelligence are widely used in traffic management. However, the existing traffic flow prediction methods need to collect raw data, which involves risks of vehicle privacy leakage. Federated learning, which shares model updates without exchanging local data, has gradually become an effective solution to achieve privacy protection. A federated learning traffic flow prediction model for regional transportation systems is proposed in this paper. At the same time, due to the emergence of highly intelligent automatic driving vehicles, a vehicle scheduling system, which can control the departure and routes of vehicles in urban regions is developed in the proposed approach. A road weight measurement method combined with real time traffic information is introduced to optimize the driving routes of vehicles to reduce the average travel time. Additionally, departure strategy, is another factor that has a great influence on traffic efficiency, but is usually ignored in the past, and is also carefully compared and studied in this paper. The numerical results illustrate that the proposed schemes can effectively improve the privacy protection ability of model updates, reduce the scheduling completion time by using the traffic flow prediction model, and realize the comparative research between departure strategies, which provides a reference for developing a safe and efficient regional transportation system. [ABSTRACT FROM AUTHOR]

Today we're announcing the development of ICT technologies in the region", said Micaela Sánchez Malcolm, Argentina's public innovation secretary, said of the Tannat-Monet cable. In Brazil, Tannat connects to the already activated Monet Cable System, a 10,556km route connecting Boca Raton in the US to Fortaleza and Praia Grande in Brazil. With that, Tannat effectively provided Argentina with a key modern route to the US. [Extracted from the article]

Keywords: Health and Medicine; Human Factors and Ergonomics EN Health and Medicine Human Factors and Ergonomics 7762 7762 1 11/06/23 20231110 NES 231110 2023 NOV 10 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Researchers detail new data in human factors and ergonomics. The news correspondents obtained a quote from the research from Clemson University: "We compare two conspicuity measurement methods: magnitude estimation and conspicuity angles. [Extracted from the article]

The article offers information on transportation industry. Topics include a new asphalt additive developed by Chinese researchers that has slow-release road salt built-in, colored sculptures placed along side of road to reduce traffic violations, and proposal by transportation engineers at North Carolina State University to replace traditional traffic lights with a fourth white light that signals to human drivers that autonomous vehicles are controlling traffic flow through the intersection.

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting. [ABSTRACT FROM AUTHOR]

One of the basic parameters which describes road traffic is Annual Average Daily Traffic (AADT). Its accurate determination is possible only on the basis of data from the continuous measurement of traffic. However, such data for most road sections is unavailable, so AADT must be determined on the basis of short periods of random measurements. This article presents different methods of estimating AADT on the basis of daily traffic (VOL), and includes the traditional Factor Approach, developed Regression Models and Artificial Neural Network models. As explanatory variables, quantitative variables (VOL and the share of heavy vehicles) as well as qualitative variables (day of the week, month, level of AADT, the cross-section, road class, nature of the area, spatial linking, region of Poland and the nature of traffic patterns) were used. Based on comparisons of the presented methods, the Factor Approach was identified as the most useful. [ABSTRACT FROM AUTHOR]

TNMAide -- for use in the FHWA's Traffic Noise Model (TNM) -- is a spreadsheet tool that aids in the determination of the worst noise hour of the day, as required by 23 CFR 772. The U.S. Department ofTransportation recently designated 44 infrastructure projects around the country as Infrastructure for Rebuilding America (INFRA) Extra -- a designation that makes project sponsors eligible to apply for credit assistance for up to 49 percent of project costs. FHWA Releases Air Quality and Noise Analysis Tools In 2021, the Federal Highway Administration developed the Database for Air Quality and Noise Analysis (DANA) tool. [Extracted from the article]

Abstract: Commencing with a class of differential equation based car following models for traffic flow a simplified discrete time model on a closed loop is found. A two dimensional map, containing two free parameters, and corresponding to the behaviour of two vehicles on the loop is investigated. Bounds on the prisoner set of the map are determined, and a number of strange attractors are presented. The variation of largest Lyapunov exponent over a range of parameter space is considered. The resulting behaviour of the map is considered within a traffic flow context. [Copyright &y& Elsevier]

• We introduce a machine learning nudging framework for reduced order models. • Our approach puts forth a realtime predictive tool for wake-vortex transport and decay systems. • We explore the effects of measurements noise and state estimate uncertainty on modeling performance. • We found that our method effectively handles different levels of temporal and spatial measurement sparsity. We put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improvements. Toward emerging applications of digital twins in aviation, the proposed approach allows for constructing a realtime predictive tool for wake-vortex transport and decay systems. We build on the fact that in realistic application, there are uncertainties in initial and boundary conditions, model parameters, as well as measurements. Moreover, conventional nonlinear ROMs based on Galerkin projection (GROMs) suffer from imperfection and solution instabilities, especially for advection-dominated flows with slow decay in the Kolmogorov n -width. In the presented LSTM nudging (LSTM-N) approach, we fuse forecasts from a combination of imperfect GROM and uncertain state estimates, with sparse Eulerian sensor measurements to provide more reliable predictions in a dynamical data assimilation framework. We illustrate our concept by solving the two-dimensional vorticity transport equation. We investigate the effects of measurements noise and state estimate uncertainty on the performance of the LSTM-N behavior. We also demonstrate that it can sufficiently handle different levels of temporal and spatial measurement sparsity, and offer a huge potential in developing next-generation digital twin technologies for aerospace applications. [ABSTRACT FROM AUTHOR]

The article focuses on the Advanced Traffic Management Systems (ATMS) in Sugar Land, Texas. It states that traffic engineers installed a Cohu Inc. Electronics Division closed-circuit television (CCTV) camera and Microwave Data Systems on intersections to monitor the traffic flow and modify timing plans based on congestion, traffic patterns or incidents. It adds that with the use of these technologies, the cities, country and state will improve quality of life by reducing travel time and delay.

The article discusses how math could fix traffic jams. During rush hour traffic congestion can be sometimes caused by a seemingly unknown reason. Topics include an overview of research by a mechanical engineer at the University of Alberta, who produced a model which shows how phantom traffic jams develop. The mathematical representation of traffic jams as alternating waves of automobile density and how improving data flow could ease traffic jams is also presented.

The article describes the Fudong Che global positioning system (GPS) program in Beijing, China. The program analyzes data collected from GPS sensors in all 66,000 of Beijing's taxis in order to build real-time models of automobile traffic in the city. Through this system, drivers will be able to learn the least congested route to a given destination.

Kiosks offering free Wi-Fi, wayfinding services, transportation information and advertising will replace existing wayfinding kiosks in Cleveland, according to Crain's Cleveland Business. [ABSTRACT FROM AUTHOR]

Statistics about daily bicycle trips and motor vehicle trips in New York City from 2010 to 2015 are presented.

A new mathematical model is proposed to estimate road traffic noise at sites along a freeway where the traffic volume fluctuates from a maximum of 900 vehicles per hour in the daytime to a minimum of 300 vehicles per hour at night. The model considers traffic conditions such as the percentage of heavy vehicles, time interval between successive (two or more) heavy vehicles and measurement time interval. The A-weighted equivalent continuous sound pressure levels calculated from this model are in keeping with measured ones at several representative time intervals both in the daytime an nighttime. [ABSTRACT FROM AUTHOR]

The article discusses the construction of a new intersection of 60th Street and Mills Civic Parkway in West Des Moines, Iowa. The author focuses on the fact that the construction process was delayed because of a lawsuit between businessmen Richard Hurd and Gary Kirke. Topics include the American financial services company Wells Fargo & Co., "D" service level for driving force, established by the Institute ofTransportation Engineers, and comments from Steve Gaer, mayor of West Des Moines.

The article reports on the development of a radar device, which is capable of measuring traffic flow in Umatilla County.

The article offers information on the views of a commission on New York Mayor Michael Bloomberg's traffic congestion pricing proposal for New York City. The commission is likely to overhaul the proposal by moving the northern boundary from 86th Street to 60th Street and simplifying enforcement. According to Marc Shaw, chairman of the commission, the overview plan is to find a way to reduce congestion and do it in a way that doesn't have a negative impact on the economy.

This article reports that the British Highways Agency (HA) is focusing on the use of new technologies to inform drivers of road conditions, such as transmitting real-time images to mobile phones and adding journey time information to variable-message signs. It will also consider the use of satellite navigation devices. The HA is responsible for operating, maintaining and improving the motorway network.