A Bluetooth Traffic Light Time Extension System for Pedestrians with Disabilities

2019 ◽  
Author(s):  
Pavlos Kokozidis ◽  
Iordanis Kostelidis ◽  
Myrsini Stasinou ◽  
Alexandra Salpigkti ◽  
Elpida-Vasiliki Theoxaridou ◽  
...  
Keyword(s):  
Traffic Light ◽  
Extension System ◽  
Time Extension

Different Future Time Perspectives Interplay in Predicting Life Satisfaction

GeroPsych ◽  
2018 ◽  
Vol 31 (3) ◽  
pp. 103-113 ◽  
Author(s):  
Minjie Lu ◽  
Angel Y. Li ◽  
Helene H. Fung ◽  
Klaus Rothermund ◽  
Frieder R. Lang
Keyword(s):  
Life Satisfaction ◽  
Time Perspective ◽  
Well Being ◽  
Future Time Perspective ◽  
Hong Kong Chinese ◽  
Future Time ◽  
Time Perspectives ◽  
Time Extension ◽  
Future Self ◽  
The Relationship

Abstract. This study addresses prior mixed findings on the relationship between future time perspective (FTP) and well-being as well as examines the associations between three aspects of FTP and life satisfaction in the health and friendship domains. 159 Germans, 97 US Americans, and 240 Hong Kong Chinese, aged 19–86 years, completed a survey on future self-views (valence) and life satisfaction. They also reported the extent to which they perceived future time as expanded vs. limited (time extension) and meaningful (openness). Findings revealed that individuals with more positive future self-views had higher satisfaction. However, those who perceived their future as more meaningful or perceived more time in their future reported higher satisfaction even when future self-views were less positive.

HSI COLOR CONVERSION AND HOG FEATURE EXTRACTION IN TRAFFIC LIGHT DETECTION USING AdaBSF

2017 ◽  
Vol 5 (3) ◽  
pp. 20
Author(s):  
JEBISHA J ◽  
MONISHA V ◽  
JEMI B. FEMILA ◽  
◽  
◽  
...  
Keyword(s):  
Feature Extraction ◽  
Traffic Light ◽  
Light Detection ◽  
Color Conversion

PENINGKATAN KINERJA SIMPANG MELALUI MANAJEMEN HAMBATAN SAMPING DAN PENGATURAN ARUS LALU LINTAS

2017 ◽  
Vol 16 (2) ◽  
pp. 38
Author(s):  
Rama Dwi Aryandi ◽  
Ari Sandhyavitri ◽  
Reni Suryanita
Keyword(s):  
Net Present Value ◽  
Cost Ratio ◽  
Present Value ◽  
Traffic Light ◽  
Benefit Cost Ratio ◽  
Benefit Cost

Penelitian ini bertujuan untuk menganalisis tingkat pelayanan simpang berdasarkan data lalu lintas simpang tersebut apakah derajat jenuhnya sudah melewati ambang batas DS = 0,75, jika nilai DS>0,75, akan dikaji penerapan beberapa alternatif penanganan untuk meningkatkan tingkat pelayanan simpang, untuk kemudian dipilih lagi alternatif terbaik untuk jangka pendek, menengah dan panjang. Metode pengumpulan data yang digunakan dalam penelitian ini adalah metode traffic counting, sedangkan untuk pengkajian alternatif penanganan simpang secara teknik menggunakan metode MKJI 1997, secara ekonomi menggunakan metode LAPI ITB, analisa nilai waktu dengan nilai waktu hasil penelitian Dirjen Bina Marga dan analisa biaya investasi dengan analisa Benefit Cost Ratio dan Net Present Value.  Dari tiga alternatif manajemen lalu lintas yang diajukan, hanya alternatif ke-3 yaitu kombinasi peniadaan hambatan samping, pelarangan belok kiri dan optimasi traffic light  yang menghasilkan nilai DS<0,75 untuk kondisi eksisting, sedangkan untuk tahun 2020 nilai DS-nya adalah 0,79 untuk Hari Selasa dan 0,83 untuk Hari Rabu. Sedangkan dengan alternatif pembangunan flyover, untuk jangka pendek atau 5 tahun nilai BCR dan NPV-nya 1,25 dan 48,9 milyar rupiah, tahun ke-10  2,29 dan 256,4 milyar rupiah, serta tahun ke-15 3,35 dan 472,19 milyar rupiah, sehingga dapat disimpulkan bahwa pembangunan flyover adalah solusi penanganan terbaik untuk menignkatkan kinerja Simpang Pasar Pagi Arengka.

Traffic Light Options

2006 ◽  
Author(s):  
Peter Løchte Jørgensen
Keyword(s):  
Traffic Light

The Traffic Sign Detection Algorithm Based on Region of Interest Extraction and Double Filter

2019 ◽  
Vol 13 ◽  
Author(s):  
Dongxian Yu ◽  
Jiatao Kang ◽  
Zaihui Cao ◽  
Neha Jain
Keyword(s):  
Region Of Interest ◽  
Detection Algorithm ◽  
Light Filter ◽  
Support Vector ◽  
Detection Accuracy ◽  
Traffic Light ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Sign Detection ◽  
Traffic Sign Detection

In order to solve the current traffic sign detection technology due to the interference of various complex factors, it is difficult to effectively carry out the correct detection of traffic signs, and the robustness is weak, a traffic sign detection algorithm based on the region of interest extraction and double filter is designed.First, in order to reduce environmental interference, the input image is preprocessed to enhance the main color of each logo.Secondly, in order to improve the extraction ability Of Regions Of Interest, a Region Of Interest (ROI) detector based on Maximally Stable Extremal Regions (MSER) and Wave Equation (WE) was defined, and candidate Regions were selected through the ROI detector.Then, an effective HOG (Histogram of Oriented Gradient) descriptor is introduced as the detection feature of traffic signs, and SVM (Support Vector Machine) is used to classify them into traffic signs or background.Finally, the context-aware filter and the traffic light filter are used to further identify the false traffic signs and improve the detection accuracy.In the GTSDB database, three kinds of traffic signs, which are indicative, prohibited and dangerous, are tested, and the results show that the proposed algorithm has higher detection accuracy and robustness compared with the current traffic sign recognition technology.

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