Assessing Drivers’ Compliance with Restrictive Yellow Traffic Lights in a Developing Country

2020 ◽  
pp. 036119812097365
Author(s):  
Abdoul-Ahad Choupani
Keyword(s):  
Developing Country ◽  
Red Light ◽  
Yellow Light ◽  
Red Light Running ◽  
Traffic Lights ◽  
Light Passing ◽  
Yellow Lights ◽  
Behavioral Issue ◽  
Stop Line ◽  
Restrictive Policy

Driving rules adopt permissive or restrictive policies concerning yellow light running (YLR). In a restrictive policy, vehicles behind the stop line are not allowed to enter the intersection on yellow no matter how close they are to the stop line. YLR policy affects driving risks, safety, and operation. There is limited knowledge about the restrictive policy and drivers’ compliance with this rule. Previous studies on YLR are limited in scope since they tended to use binary stop/go decision models without considering red light running decisions. This potentially results in the loss of information about drivers’ conformity to red signals. This paper examines whether drivers are only non-compliant with yellow lights or whether non-conformity to any prohibitive yellow/red signal emerges as a wider behavioral issue. This study develops regression choice models to predict drivers’ illegal yellow-light passing decisions in a developing country with a poor safety record and explores reasons for drivers’ non-compliance. The results obtained show that the restrictive policy is ineffective in relation to driver compliance, especially in cases where drivers’ non-conformity to any restrictive rule emerges as a behavioral issue of concern. Drivers make their stop/go decisions according to the time needed to cross the intersection, and they consider the yellow light as an opportunity for crossing. Yellow (red) light running rates were 101 (31) per 1,000 vehicles per hour (vph) for the restrictive policy, whereas these rates for the U.S.A., with a permissive policy, were at most 29 (6) per 1,000 vph.

scholarly journals Comparison of Red-Light Running (RLR) and Yellow-Light Running (YLR) traffic violations in the cities of Enna and Thessaloniki

2020 ◽  
Vol 45 ◽  
pp. 947-954 ◽  
Author(s):  
Tiziana Campisi ◽  
Giovanni Tesoriere ◽  
Antonino Canale ◽  
Socrates Basbas ◽  
Panagiotis Vaitsis ◽  
...  
Keyword(s):  
Red Light ◽  
Yellow Light ◽  
Red Light Running ◽  
Traffic Violations

scholarly journals Perubahan perilaku Callosobruchus maculatus Faaabricius terhadap warna cahaya pada kacang-kacangan di penyimpanan

Jurnal Agro ◽  
10.15575/3735 ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 15-23
Author(s):  
Lukmanul Hakim ◽  
Irhamni Irhamni
Keyword(s):  
Callosobruchus Maculatus ◽  
Oviposition Behavior ◽  
Red Light ◽  
Bean Seed ◽  
Yellow Light ◽  
Green Beans ◽  
Randomized Design ◽  
Completely Randomized Design ◽  
Yellow Lights ◽  
Copulation Behavior

Callosobruchus maculatus (Fab.) adalah salah satu species serangga dari ordo Coleoptera, family Brucidae yang merupakan hama kacang-kacangan di gudang penyimpanan. Kerusakan kacang selama penyimpanan diawali dengan perilaku oviposisi telur serangga betina dewasa pada kotiledon biji kacang. Serangga C. maculatus (Fab.) tidak menyukai tempat dengan cahaya terang. Penelitian ini bertujuan untuk mengamati perubahan perilaku oviposisi dan kopulasi serangga dewasa pada kacang-kacangan dengan penerangan empat warna cahaya pada ruang penyimpanan. Pengamatan dan analisis data menggunakan Rancangan Acak Lengkap Faktorial. Faktor petama menggunakan cahaya lampu merah, kuning, hijau dan putih, sedangkan faktor kedua terdiri dari tiga jenis kacang (Fabaceae) yaitu kacang hijau, kacang kedelai dan kacang merah. Hasil penelitian menunjukkan perilaku oviposisi telur terjadi pada cahaya lampu kuning, sedangkan perilaku kopulasi terjadi  pada cahaya lampu merah. Cahaya lampu merah dan kuning dapat memengaruhi perilaku oviposisi dan kopulasi Callosobruchus maculatus (Fab.).ABSTRACTCallosobruchus maculatus (Fab.) is one of the insect species of the order Coleoptera, family Brucidae which is a pest for stored beans. Damage to beans during the storage starts with the behavior of the egg oviposition of adult female insects on bean seed cotyledons. C. maculatus (Fab.) do not like to be in a bright place. This study aimed to observe changes in the behavior of oviposition and copulation of adult insects in beans with four-colour lighting in the storage. The observation and analysis of data used factorial completely randomized design. The first factor were light colors; red, yellow, green, and white light while the second factor consists of three types of beans (Fabaceae); green beans, soybeans and red beans. The results showed that copulation behavior occurred in red light. While the oviposition behavior of eggs occured in yellow light. The red and yellow lights can affect the behavior of oviposistion and copulation of C.maculatus (Fab.). 

Perancangan Sistem Kontrol Lampu Lalulintas Cerdas Dengan Menggunakan Mikrokontroler dan Kamera

Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 200
Author(s):  
Tjerie Pangemanan ◽  
Arnold Rondonuwu
Keyword(s):  
Real Time ◽  
Digital Image ◽  
Red Light ◽  
Green Light ◽  
Processing Method ◽  
Traffic Lights ◽  
Traffic System ◽  
Road Users ◽  
Adjustment System ◽  
System Time

Masalah lalu lintas  merupakan salah satu  masalah yang sangat sulit diatasi dengan hanya menggunakan system waktu (timer). Oleh sebab itu diperlukan suatu system pengaturan otomatis yang bersifat real-time sehingga waktu pengaturan lampu lalu lintas dapat disesuaikan dnegan keadaan di lapangan. Penelitian ini bertujuan mengembangkan suatu simulasi sistem yang mampu mengestimasi panjang antrian kendaraan menggunakan metoda pengolahan citra digital hanya dengan menggunakan satu kamera untuk dijadikan parameter masukan  dalam menghitung lama waktu nyala lampu merah dan lampu hijau. Oleh karena itu, sistem lalulintas sangatlah diperlukan, sebagai sarana dan prasarana untuk menjadikan lalulintas lancar, aman, bahkan sebagai media pembelajaran disiplin bagi masyarakat pengguna jalan raya. Penelitian ini penulis menggunakan sistem pengontrolan berbasis citra digital dimana camera sebagai sensor. Untuk aplikasi dari  semua metode dalam penelitian ini digunakan Microcontroller AurdinoTraffic problems is one of the problems that is very difficult to overcome by only using the system time (timer). Therefore we need an automatic real-time adjustment system so that the time settings for traffic lights can be adjusted according to the conditions on the ground. This study aims to develop a system simulation that is able to estimate the length of the vehicle queue using a digital image processing method using only one camera to be used as input parameters in calculating the length of time the red light and green light. Therefore, the traffic system is very necessary, as a means and infrastructure to make traffic smooth, safe, even as a medium for disciplined learning for road users. In this study the authors used a digital image-based control system where the camera as a sensor. For the application of all methods in this study, Aurdino Microcontroller is used

scholarly journals Autonomous Vehicles and Vulnerable Road-Users—Important Considerations and Requirements Based on Crash Data from Two Countries

2021 ◽  
Vol 11 (7) ◽  
pp. 101
Author(s):  
Andrew Paul Morris ◽  
Narelle Haworth ◽  
Ashleigh Filtness ◽  
Daryl-Palma Asongu Nguatem ◽  
Laurie Brown ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Red Light ◽  
Road User ◽  
Red Light Running ◽  
Crash Data ◽  
Passenger Vehicles ◽  
Road Users ◽  
Vulnerable Road User ◽  
Vulnerable Road Users ◽  
Road Intersections

(1) Background: Passenger vehicles equipped with advanced driver-assistance system (ADAS) functionalities are becoming more prevalent within vehicle fleets. However, the full effects of offering such systems, which may allow for drivers to become less than 100% engaged with the task of driving, may have detrimental impacts on other road-users, particularly vulnerable road-users, for a variety of reasons. (2) Crash data were analysed in two countries (Great Britain and Australia) to examine some challenging traffic scenarios that are prevalent in both countries and represent scenarios in which future connected and autonomous vehicles may be challenged in terms of safe manoeuvring. (3) Road intersections are currently very common locations for vulnerable road-user accidents; traffic flows and road-user behaviours at intersections can be unpredictable, with many vehicles behaving inconsistently (e.g., red-light running and failure to stop or give way), and many vulnerable road-users taking unforeseen risks. (4) Conclusions: The challenges of unpredictable vulnerable road-user behaviour at intersections (including road-users violating traffic or safe-crossing signals, or taking other risks) combined with the lack of knowledge of CAV responses to intersection rules, could be problematic. This could be further compounded by changes to nonverbal communication that currently exist between road-users, which could become more challenging once CAVs become more widespread.

Real-Time Prediction of Vehicle Trajectories for Proactively Identifying Risky Driving Behaviors at High-Speed Intersections

2018 ◽  
Vol 2672 (38) ◽  
pp. 233-244 ◽  
Author(s):  
Chaopeng Tan ◽  
Nan Zhou ◽  
Fen Wang ◽  
Keshuang Tang ◽  
Yangbeibei Ji
Keyword(s):  
Phase Transition ◽  
High Speed ◽  
Red Light ◽  
Risky Behaviors ◽  
Risky Driving ◽  
Red Light Running ◽  
Driving Behaviors ◽  
Vehicle Trajectories ◽  
Single Vehicle ◽  
Risky Driving Behaviors

At high-speed intersections in many Chinese cities, a traffic-light warning sequence at the end of the green phase—three seconds of flashing green followed by three seconds of yellow—is commonly implemented. Such a long phase transition time leads to heterogeneous decision-making by approaching drivers as to whether to pass the signal or stop. Therefore, risky driving behaviors such as red-light running, abrupt stop, and aggressive pass are more likely to occur at these intersections. Proactive identification of risky behaviors can facilitate mitigation of the dilemma zone and development of on-board safety altering strategies. In this study, a real-time vehicle trajectory prediction method is proposed to help identify risky behaviors during the signal phase transition. Two cases are considered and treated differently in the proposed method: a single vehicle case and a following vehicle case. The adaptive Kalman filter (KF) model and the K-nearest neighbor model are integrated to predict vehicle trajectories. The adaptive KF model and intelligent driver model are fused to predict the following vehicles’ trajectories. The proposed models are calibrated and validated using 1,281 vehicle trajectories collected at three high-speed intersections in Shanghai. Results indicate that the root mean square error between the predicted trajectories and the actual trajectories is 5.02 m for single vehicles and 2.33 m for following vehicles. The proposed method is further applied to predict risky behaviors, including red-light running, abrupt stop, aggressive pass, speeding pass, and aggressive following. The overall prediction accuracy is 95.1% for the single vehicle case and 96.2% for the following vehicle case.

Prediction of Red Light Running Based on Statistics of Discrete Point Sensors

2009 ◽  
Vol 2128 (1) ◽  
pp. 132-142 ◽  
Author(s):  
Liping Zhang ◽  
Kun Zhou ◽  
Wei-bin Zhang ◽  
James A. Misener
Keyword(s):  
Red Light ◽  
Discrete Point ◽  
Red Light Running

scholarly journals Evaluation of Automated Enforcement Program in Amman

2018 ◽  
Author(s):  
Hana Naghawi ◽  
Bushra Al Qatawneh ◽  
Rabab Al Louzi
Keyword(s):  
Traffic Safety ◽  
Questionnaire Survey ◽  
Positive Impact ◽  
Red Light ◽  
Crash Frequency ◽  
Red Light Running ◽  
Red Light Cameras ◽  
Percent Confidence Level ◽  
Before And After ◽  
Traffic Violations

This study aims, in a first attempt, to evaluate the effectiveness of using the Automated Enforcement Program (AEP) to improve traffic safety in Amman, Jordan. The evaluation of the program on crashes and violations was examined based on a “before-and-after” study using the paired t-test at 95 percent confidence level. Twenty one locations including signalized intersections monitored by red light cameras and arterial roads monitored by excessive speed cameras were selected. Nine locations were used to study the effectiveness of the program on violations, and twelve locations were used to determine the effectiveness of the program on frequency and severity of crashes. Data on number and severity of crashes were taken from Jordan Traffic Institution. Among the general findings, it was found that the AEP was generally associated with positive impact on crashes. Crash frequency was significantly reduced by up to 63%. Crash severities were reduced by up to 62.5%. Also, traffic violations were significantly reduced by up to 66%.  Finally, drivers’ opinion and attitude on the program was also analyzed using a questionnaire survey. The questionnaire survey revealed that 35.5% of drivers are unaware of AEP in Amman, 63.9% of drivers don’t know the camera locations, most drivers knew about excessive speed and red light running penalties, most drivers reduce their speed at camera locations, 44.4% of drivers think that the program satisfies its objective in improving traffic safety and 52% of drivers encourage increasing the number of camera devices in Amman.

scholarly journals Dynamic Traffic Light Control

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Monitoring ◽  
Intelligent Transport System ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control ◽  
Traffic Management System

Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).

scholarly journals Analysis of the Extent of Red Light Running in Minna, North-Central Nigeria

2019 ◽  
Vol 3 (2) ◽  
pp. 124-136
Author(s):  
SAMUEL MEDAYESE ◽  
◽  
MOHAMMED TAUHEED ALFA ◽  
NELSON T.A ABD’RAZACK ◽  
FAITH O. AGBAWN ◽  
...  
Keyword(s):  
Red Light ◽  
Red Light Running ◽  
North Central
Sign in / Sign up

Export Citation Format

Share Document