Stoplight Research Articles

Blue-wavelength light therapy for post-traumatic brain injury sleepiness, sleep disturbance, depression, and fatigue: A systematic review and network meta-analysis.

This review aimed to determine the efficacy of blue-wavelength light therapy (BWLT) for post-traumatic brain injury (TBI) sleepiness, sleep disturbance, depression, and fatigue. Pubmed, Scopus, Web of Science, Cochrane Library, Academic Search Complete, and CINAHL. Included trials were randomized controlled trials (RCTs) of BWLT in adults with a history of TBI. Outcomes of interest included sleepiness, sleep disturbance, depression, or fatigue. Two reviewers independently screened the searched items, selected the trials, extracted the data, and rating the quality of trials. We aggregated the data using a random-effect, frequentist network meta-analysis (NMA). We searched the databases on July 4, 2020. This review included four RCTs of 117 patients with a history of TBI who were randomized to received BWLT, amber light therapy (ALT), or no light therapy (NLT). Moderate-quality evidence revealed that: i) BWLT was significantly superior to NLT in reducing depression (SMD = 0.81, 95% CI = 0.20 to 1.43) ii) BWLT reduced fatigue at a significantly greater extent than NLT (SMD = 1.09, 95% CI = 0.41 to 1.76) and ALT (SMD = 1.00, 95% CI = 0.14 to 1.86). Low-quality evidence suggested that BWLT reduced depression at a greater extent than ALT (SMD = 0.57, 95% CI = 0.04 to 1.10). Low-quality evidence found that the dropout rates of those receiving BWLT and ALT were not significantly different (RR = 3.72, 95% CI = 0.65 to 21.34). Moderate-quality evidence suggests that BWLT may be useful for post-TBI depression and fatigue.

Smart traffic light control system using image processing

Traffic congestion has become a serious issue due to the growing number of vehicles in Malaysia. Traffic light control system is widely used to control the flow of road junction. Currently, most of the traffic light system used pre-time and count down timers to control traffic flow. Due to the fixed-time setting, often the system unable to handle unexpected heavy traffic flows and cause traffic jam. Thus, there is a need of adaptive traffic signals which are able to do real time monitoring to control traffic light signal based on traffic density. This study proposed an adaptive traffic light control system that uses image processing and image matching technique in controlling the traffic in an effective manner by taking images of each lane at a junction. The density of traffic in the images at each junction are compared. Results show that more time are allocated for the vehicles on the densest road to pass compared to other less dense road. Edge operation detector is used to detect the density of traffic at each lane. In this study, a comparison study was carried out by applying five different edge detectors namely Roberts, Sobel, Log, Canny and active contour. Among these detectors, Canny edge operation detector has found to be the best as it could extract actual edges with average time of 0.453 second.

Road Traffic Light in New Configuration

The three-color system containing signals of the same circular shape has been in existence for over a hundred years. Each traffic signal has been justifiably selected to have a special color light to correspond to human psychoemotional reaction (red – stop, yellow – caution, green – go) to a given color signal (British Standards, 2015) and to comply with the laws of physics (The Motivated Engineer, 2015) – Rayleigh’s scattering law (Banc SpaceTek, 2017). The main downsides of the traditional road traffic light include the following: • The uniform circular shape of light signals results in uncertainty and difficulties for road users with color blindness and visual impairments, resulting in the need for restrictions or bans on driving license issuance in some countries. This uncertainty becomes particularly acute in conditions of low visibility. • According to the concept of harmony of form and color (Itten, 1961), a green light alone corresponds to the circular (spherical-like) shape of the signal. Red and amber lights harmoniously combine with other geometrical shapes. • The uniform shape of light signals prevents the implementation of the original compact combined model of traffic lights. For example, during the day, colorblind people can tell which signal is which because there is a standard position assigned: top – bottom or right – left (Oliveira, Souza, Junior, Sales & Ferraz, 2015). This becomes problematic if the compact combined models of traffic lights are used. Engineers and inventors have been trying to solve these problems by introducing random changes in the light signal shape and complicating the traffic light design. For a long time there have been different proposals about how to eliminate the demerits of the existing traffic lights: from arbitrary changes in the signal shape (Patterson, 1988) to transformation of traffic lights into a single-section display panel (Kulichenko, 2011) which replaces among others stationary road signs. However, technical solutions like these deprive the traffic light of its signal uniformity and conciseness (simplicity, clarity and precision of its controlling effect), features which help safe traffic regulation in a busy and dynamic mode. Technical modernization of individual signal components has been going hand in hand with technological developments as light sources, diffusers, lenses, controllers, materials, control systems, timers, etc. are improved. However, adequate design and aesthetic proposals are considerably behind. The aim of this paper is to propose a concept of creating control signals of traffic light that harmonize color and form, and, as a result, to create a new model of traffic light that will be convenient for all road users.

Poems by Tsitsi Jaji

I. At Independence Hall In the amber light, the heat bottoms out below ground level. This khaki-clad woman guidesus: one day, she says, we will all look back on fossil fuels the same way....

A Visual Analytics Approach for Anomaly Detection from a Novel Traffic Light Data

Traffic signals are part of our critical infrastructure and protecting their integrity is a serious concern. Security flaws in traffic signal systems have been documented and effective detection of exploitation of these flaws remains a challenge. In this paper we present a visual analytics approach to look for anomalies in traffic signal data (i.e., abnormal traffic light patterns) that may indicate a compromise of the system. To our knowledge it is a first time a visual analytics approach is applied for the processing and exploration of traffic signal data. This system supports level-of-detail exploration with various visualization techniques. Data cleaning and a number of preprocessing techniques for the extraction of summary information (e.g., traffic signal cycles) of the data are also performed before the visualization and data exploration. Our system successfully reveals the errors in the input data that would be difficult to capture with simple plots alone. In addition, our system captures some abnormal signal patterns that may indicate intrusions into the system. In summary, this work offers a new and effective way to study attacks or intrusions to traffic signal control systems via the visual analysis of traffic light signal patterns.

A computer vision algorithm for locating and recognizing traffic signal control light status and countdown time

It is of practical importance for individual vehicles to automatically identify traffic signal light status to facilitate their decision makings for traffic safety performance enhancement and operation efficiency maximization when they are approaching intersections, especially in near-future fully-or semi-autonomous vehicle-penetrated traffic systems. Traditional methods aim to directly extract information from the light emitting area of a traffic signal light head, but this can easily result in missed or false signal light status identification due to changes in detection distance and lighting conditions. To address these research gaps, an innovative computer vision-based algorithm is developed for signal control light status identification and countdown time recognition. Based on the unique characteristics of black traffic light boards, color segmentation is conducted in both RGB and HSV channels, and traffic light boards and countdown time display boards are located through cascade filtering algorithms. In the HSV color space, the H component can be extracted and highlighted to determine the current signal status by distinguishing the distribution of the pixel points of the H component. Based on the nearest neighbor interpolation algorithm, an adaptive threading method is developed to improve countdown time recognition. The experimental tests were conducted to verify the effectiveness of the developed approach under various scenarios with acceptable recognition accuracy and execution efficiency. The developed approach can be applied and integrated with other detection and control algorithms to strengthen vehicle-crossing safety performance and operational efficiency at intersections.

ВЛИЯНИЕ ЛОГИКИ УПРАВЛЕНИЯ СВЕТОФОРНЫМИ ОБЪЕКТАМИ НА ЭМИССИЮ ОТРАБОТАННЫХ ГАЗОВ АВТОМОБИЛЕЙ

An objective social process is an increase in the number of cars, which complicates the envi-ronmental situation in cities. The formation of toxic substances in exhaust gases is closely related to the processes of fuel oxidation and engine operating modes, which are dependent on the mode of movement of cars. The analysis of the influence of the method used to control traffic signals on exhaust gas emissions was performed using a microscopic simulation model. We compared the use of pre-calculated traffic light signals with adaptive control in real intersection conditions, taking into account the dynamics of transport demand. The conditions under which the use of adaptive control of traffic lights signals can significantly reduce the volume of exhaust gas emissions of cars are identified.

A cellular automation traffic flow model for traffic light signal management in intersection system with and without random driving behaviour

In this study, traffic light management in intersection system was simulated based on cellular automata traffic flow model. Characteristic of vehicles flow is defined according to the NS model. Our model was developed by adding driving behaviours, which are randomly defined in different maximum vehicle speed of mixed flow for two-lane traffic flow without lane-changing. The relation between time duration of traffic light signal and the traffic flow by analyzing vehicle density and averaged speed were investigated. The results show that the time duration of traffic light signal affects the traffic flow. Our model can be used to find the appropriated time duration to handle the traffic and can eventually reduce traffic jam. Additionally. Our result also presents an effect of the driving behaviour on the traffic flow.

Guatemala Makes COVID-19 the Responsibility of the People

It’s a muggy August evening and a thundershower is forming over the hilly treescape that frames Guatemala City’s urban center. I am rushing home from the supermarket, hoping to beat the storm. I’ve lived in Guatemala since 2018, though, recently, going to the supermarket is the only time I leave my apartment, as COVID-19 cases rise across the country. Driving through the city, neon-lit signs flicker on for restaurants and cafes that had, at one point, been under nationally mandated closure. At a stop light, I get a clear view into a well-known restaurant that had been one of my favorites, pre-COVID. Several clusters of people are seated inside a closed indoor space. None of them are wearing masks- a dramatic shift in the panorama from just months ago.

A Study on the Effect of the Lamp Position of Traffic Signal Lights on Right Turn Behavior

A Study on the Effect of the Lamp Position of Traffic Signal Lights on Right Turn Behavior

Speed Planning and Energy Optimal Control of Hybrid Electric Vehicles Based on Internet of Vehicles

Under the premise of no red light running and collision accidents, a hierarchical optimization control strategy is proposed to optimize the energy distribution of a hybrid electric vehicle adapting to multi working conditions in the environment of internet of vehicles, so as to reduce the energy consumption of acceleration or deceleration, and achieve the purpose of energy saving. Traffic signal light timing vehicle tracking speed controller is used to generate the reference speed according to the traffic signal timing, front vehicle speed and position. Model predictive controller (MPC) is used to optimize the reference speed to obtain the target speed sequence and acceleration sequence for a lower layer. Then the upper level target speed is transformed into vehicle driving demand torque and power through the equilibrium equation of total road load force and tractive force in the lower level control. The certain rules are provided to realize adaptive distribution about engine torque, motor torque and mechanical braking force. Based on the simulation platform provided by E-COSM 2021, the effectiveness and real-time performance of the hierarchical optimization control strategy are verified under seven working conditions. The simulation results show that the control strategy proposed in this paper can avoid red light running and collision accidents, reduce red light parking, and save the total fuel consumption by 11.88%~19.25% compared with he traffic signal timing + PID + MPC control scheme provided by the organizer of the competition, realizing the comprehensive improvement of system economy and working conditions adaptability.

Optimal Capacity Allocation for Heavy-Traffic Fixed-Cycle Traffic-Light Queues and Intersections

Setting traffic light signals is a classical topic in traffic engineering, and important in heavy-traffic conditions when green times become scarce and longer queues are inevitably formed. For the fixed-cycle traffic-light queue, an elementary queueing model for one traffic light with cyclic signaling, we obtain heavy-traffic limits that capture the long-term queue behavior. We leverage the limit theorems to obtain sharp performance approximations for one queue in heavy traffic. We also consider optimization problems that aim for optimal division of green times among multiple conflicting traffic streams. We show that inserting heavy-traffic approximations leads to tractable optimization problems and close-to-optimal signal prescriptions.

Blue-Light Therapy Strengthens Resting-State Effective Connectivity within Default-Mode Network after Mild TBI.

Background:Emerging evidence suggests that post concussive symptoms, including mood changes, may be improved through morning blue-wavelength light therapy (BLT). However, the neurobiological mechanisms underlying these effects remain unknown. We hypothesize that BLT may influence the effective brain connectivity (EC) patterns within the default-mode network (DMN), particularly involving the medial prefrontal cortex (MPFC), which may contribute to improvements in mood.Methods:Resting-state functional MRI data were collected from 41 healthy-controls (HCs) and 28 individuals with mild traumatic brain injury (mTBI). Individuals with mTBI also underwent a diffusion-weighted imaging scan and were randomly assigned to complete either 6 weeks of daily morning BLT (N = 14) or amber light therapy (ALT; N = 14). Advanced spectral dynamic causal modeling (sDCM) and diffusion MRI connectometry were used to estimate EC patterns and structural connectivity strength within the DMN, respectively.Results:The sDCM analysis showed dominant connectivity pattern following mTBI (pre-treatment) within the hemisphere contralateral to the one observed for HCs. BLT, but not ALT, resulted in improved directional information flow (ie, EC) from the left lateral parietal cortex (LLPC) to MPFC within the DMN. The improvement in EC from LLPC to MPFC was accompanied by stronger structural connectivity between the 2 areas. For the BLT group, the observed improvements in function and structure were correlated (at a trend level) with changes in self-reported happiness.Conclusions:The current preliminary findings provide empirical evidence that morning short-wavelength light therapy could be used as a novel alternative rehabilitation technique for mTBI.Trial registry:The research protocols were registered in the ClinicalTrials.gov database (CT Identifiers NCT01747811 and NCT01721356).

Leveraging Multiple Connected Traffic Light Signals in an Energy-Efficient Speed Planner

Connecting automated vehicles to traffic lights can lead to significant energy savings by enabling them to pass through intersections in an energy-efficient way without unnecessary stops. A cellular-based communication system connecting multiple traffic lights can help realize the full potential of energy-efficient driving at intersections. Thus, we propose a hierarchical speed planner that can leverage information from multiple connected traffic lights. The proposed speed planner consists of two modules: a green window selector and a reference trajectory generator. The green window selector, based on Dijkstra's algorithm, finds a series of “green windows” for connected traffic lights that builds an energy-optimal path for vehicles to follow. The reference trajectory generator finds optimal entering times, based on the selected green window at each intersection, and then computes reference trajectories. Deriving and using analytical optimal entering speeds as a function of entering times allows us to guarantee the computational simplicity suitable for real-time implementation. We also demonstrate how to balance energy and traffic flow perspectives in the reference trajectory generator. Finally, a high-fidelity simulation framework is used to evaluate the proposed speed planner and quantify the extent to which it can save energy in various real-world urban route scenarios.

Can I Trust You? Estimation Models for e-Bikers Stop-Go Decision before Amber Light at Urban Intersection

Electric bike (e-bike) riders’ inappropriate go-decision, yellow-light running (YLR), could lead to accidents at intersection during the signal change interval. Given the high YLR rate and casualties in accidents, this paper aims to investigate the factors influencing the e-bikers’ go-decision of running against the amber signal. Based on 297 cases who made stop-go decisions in the signal change interval, two analytical models, namely, a base logit model and a random parameter logit model, were established to estimate the effects of contributing factors associated with e-bikers’ YLR behaviours. Besides the well-known factors, we recommend adding approaching speed, critical crossing distance, and the number of acceleration rate changes as predictor factors for e-bikers’ YLR behaviours. The results illustrate that the e-bikers’ operational characteristics (i.e., approaching speed, critical crossing distance, and the number of acceleration rate change) and individuals’ characteristics (i.e., gender and age) are significant predictors for their YLR behaviours. Moreover, taking effects of unobserved heterogeneities associated with e-bikers into consideration, the proposed random parameter logit model outperforms the base logit model to predict e-bikers’ YLR behaviours. Providing remarkable perspectives on understanding e-bikers’ YLR behaviours, the predicting probability of e-bikers’ YLR violation could improve traffic safety under mixed traffic and fully autonomous driving condition in the future.

Internet of Thing Based Smart Traffic Control Signal Using Solar Energy

Nowadays traffic congestion is major problem in all over the cities. The cities are renovated to “smart cities” by using Information and Communication Technologies (ICT). The IoT are playing a vital role in smart cities. This work proposes Internet of Thing (IoT) based smart traffic control signal using solar energy for smart cities. This signal is always coordinated with the emergency vehicle like ambulance to discover the signal and select the route where road traffic is dynamically controlled and the traffic violation vehicles are identified by traffic monitoring officers through internet. The traffic control signal lights are automatically controlled by Raspberry Pi controller with the help of IR sensor and RF signal. If any emergency vehicle will come nearby traffic control signal then the green signal shows for emergency vehicle and the remaining paths are shows as red signal.

Nutritional Analysis of Foods and Beverages Depicted in Top-Grossing US Movies, 1994-2018

Many countries now restrict advertisements for unhealthy foods. However, movies depict foods and beverages with nutritional quality that is unknown, unregulated, and underappreciated as a source of dietary influence. To compare nutritional content depicted in top-grossing US movies with established nutrition rating systems, dietary recommendations, and US individuals' actual consumption. In this qualitative study, a content analysis was performed from April 2019 to May 2020 of the 250 top-grossing US movies released from 1994 to 2018. The proportion of movies with less healthy nutrition ratings using the Nutrient Profile Index, the proportion of movies with medium or high food nutrition ratings according to the United Kingdom's "traffic light" guidelines (in which green is low and indicates the healthiest foods; amber, medium; and red is high and indicates the least healthy foods), and how the movie-depicted nutritional content compared with US Food and Drug Administration-recommended daily levels and US individuals' actual consumption according to National Health and Nutrition Examination Survey 2015-2016 data. Secondary outcomes compared branded and nonbranded items and tested whether outcomes changed over time or for movies targeting youths. Across 9198 foods and 5748 beverages, snacks and sweets (2173 [23.6%]) and alcoholic beverages (2303 [40.1%]) were most commonly depicted. Alcohol comprised 23 of 127 beverages (18.1%) in G-rated movies, 268 of 992 beverages (27.0%) in PG-rated movies, 1503 of 3592 beverages (41.8%) in PG-13-rated movies, and 509 of 1037 beverages (49.1%) in R-rated movies. Overall, 178 of 245 movies (72.7%) earned less healthy Nutrient Profile Index food ratings and 222 of 246 movies (90.2%) earned less healthy beverage ratings, which would be unhealthy enough to fail legal limits for advertising to youths in the United Kingdom. Among foods, most movies depicted medium or high (amber or red traffic light) levels of sugar (229 of 245 [93.5%]), saturated fat (208 of 245 [84.9%]), total fat (228 of 245 [93.1%]), and, to a lesser extent, sodium (123 of 245 [50.2%]). Only 1721 foods and beverages (11.5%) were visibly branded, but branded items received less healthy nutrition ratings than nonbranded items. Overall, movies failed recommended levels of saturated fat per 2000 kcal by 25.0% (95% CI, 20.6%-29.9%), sodium per 2000 kcal by 3.9% (95% CI, 0.2%-7.9%), and fiber per 2000 kcal by 45.1% (95% CI, 42.9%-47.0%). Movies also depicted 16.5% (95% CI, 12.3%-21.0%) higher total sugar content per 2000 kcal and 313% (95% CI, 298%-329%) higher alcohol content per 2000 kcal than US individuals consume. Neither food nor beverage nutrition scores improved over time or among movies targeting youths. This study suggests that popular US movies depict an unhealthy diet that fails national dietary recommendations, akin to US individuals' actual diets. Depicting unhealthy consumption in media is a sociocultural problem that extends beyond advertisements and branded product placements.

An Artificial Intelligence Edge Computing-Based Assistive System for Visually Impaired Pedestrian Safety at Zebra Crossings

This article proposes a wearable assistive system based on artificial intelligence (AI) edge computing techniques to help visually impaired consumers safely use marked crosswalks, or zebra crossings. The proposed wearable assistive system consists of a pair of smart sunglasses, a waist-mounted intelligent device, and an intelligent walking cane (stick). A deep learning technique is adopted for zebra crossing image recognition in real time. Visually impaired consumers need to wear the proposed smart sunglasses and waist-mounted intelligent device and hold the proposed intelligent walking cane when they approach a zebra crossing. When a visually impaired pedestrian reaches a zebra crossing, they will immediately receive a message about the current situation at the crossing and the traffic light signal. Experimental results show that the accuracy of real-time zebra crossing recognition of the proposed system can reach up to 90%.

Photoresponsivity enhancement of SnS porous film

Tin (II) sulfide (SnS) films have been deposited on glass substrates by oblique angle deposition (OAD) technique. The structural properties of the prepared samples were investigated by using XRD, Raman, and FESEM characterization techniques. The optical properties of the specimens were studied by UV–Vis spectroscopy technique. The photosensitivity properties of the samples were measured by red and amber lights with different intensities. The OAD technique was found able to reduce the response time of the samples from 2.15s to 0.69s for the amber light, and from 3.59s to 1.49s for the red light. Besides, a significant reduction in the decay time of the specimens was found from 12.21s to 8.48s and from 11.18s to 8.77s for amber and red lights, respectively.

Optimization of automotive color filter arrays for traffic light color separation

Traffic light (TL) classification is an important feature for automated driving, and it requires correct color separation of the TL signals captured using cameras. A key camera component for the color separation performance is the color filter array (CFA). For common automotive-specific CFAs, we have observed unsatisfactory performance for TL color separation, which indicates the need for an optimization. Based on typical scenarios for TL classification and a set of recorded TL signals, we evaluate the performance of common automotive CFAs. For a quantitative evaluation, we propose a suitable color distance metric. We also propose a method for optimization of the CFA and show that using this method, reference color separation performance can be achieved, trading in only a small amount of sensitivity.