ARM cortex based modelling and implementation of a self-controlled traffic light system

Author(s):  
Q. A. Al-Haija ◽  
N. A. Jebril
2021 ◽  
Vol 51 (11) ◽  
pp. 1026-1029
Author(s):  
S Savoviċ ◽  
A Djordjevich ◽  
R Min ◽  
I Savoviċ

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.


2007 ◽  
Vol 10 (3) ◽  
pp. 238-244 ◽  
Author(s):  
Gary Jones ◽  
Miles Richardson

AbstractObjectivePrevious research on nutrition labelling has mainly used subjective measures. This study examines the effectiveness of two types of nutrition label using two objective measures: eye movements and healthiness ratings.DesignEye movements were recorded while participants made healthiness ratings for two types of nutrition label: standard and standard plus the Food Standards Agency's ‘traffic light’ concept.SettingUniversity of Derby, UK.SubjectsA total of 92 participants (mean age 31.5 years) were paid for their participation. None of the participants worked in the areas of food or nutrition.ResultsFor the standard nutrition label, participant eye movements lacked focus and their healthiness ratings lacked accuracy. The traffic light system helped to guide the attention of the consumer to the important nutrients and improved the accuracy of the healthiness ratings of nutrition labels.ConclusionsConsumers have a lack of knowledge regarding how to interpret nutrition information for standard labels. The traffic light concept helps to ameliorate this problem by indicating important nutrients to which to pay attention.


Author(s):  
Laura Gulia ◽  
Stefan Wiemer

Abstract Dascher-Cousineau et al. (2020) apply the so-called foreshock traffic-light system (FTLS) model proposed by Gulia and Wiemer (2019) to two earthquake sequences that occurred after the submission of the model: the 2019 Ridgecrest (Mw 7.1) and the 2020 Mw 6.4 Puerto Rico earthquakes. We show in this comment that the method applied by Kelian Dascher-Cousineau et al. (2020) deviates in at least six substantial and not well-documented aspects from the original FTLS method. As a consequence, they used for example in the Ridgecrest case only 1% of the data available to estimate b-values and from a small subvolume of the relevant mainshock fault. In the Puerto Rico case, we document here substantial issues with the homogeneity of the magnitude scale that in our assessment make a meaningful analysis of b-values impossible. We conclude that the evaluation by Dascher-Cousineau et al. (2020) is misrepresentative and a not a fair test of the FTLS hypothesis.


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