Academic literature on the topic 'Etichetta Multiple Traffic Light'

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Journal articles on the topic "Etichetta Multiple Traffic Light"

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Prameela, Mrs N., Ch Srujana Sri, G. Kedarnath, and P. Sairam Venkat. "Smart Traffic Light Control System Using Arduino Mega." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 4382–85. http://dx.doi.org/10.22214/ijraset.2023.60997.

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Abstract: This article presents the "Smart Traffic Light Control System using Arduino Mega" design. These systems manage traffic flow at intersections, aiming for smooth vehicle movement. However, synchronizing multiple traffic lights at adjacent junctions is complex because of a number of variables. Conventional systems struggle with fluctuating traffic flows and lack consideration for emergencies, pedestrian crossings, and accidents. This often leads to congestion and traffic jams. The suggested method resolves these problems by integrating advanced control mechanisms to adjust traffic signa
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Yeh, Tien-Wen, Huei-Yung Lin, and Chin-Chen Chang. "Traffic Light and Arrow Signal Recognition Based on a Unified Network." Applied Sciences 11, no. 17 (2021): 8066. http://dx.doi.org/10.3390/app11178066.

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We present a traffic light detection and recognition approach for traffic lights that utilizes convolutional neural networks. We also introduce a technique for identifying arrow signal lights in multiple urban traffic environments. For detection, we use map data and two different focal length cameras for traffic light detection at various distances. For recognition, we propose a new algorithm that combines object detection and classification to recognize the light state classes of traffic lights. Furthermore, we use a unified network by sharing features to decrease computation time. The result
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Hosseinyalmdary, S., and A. Yilmaz. "TRAFFIC LIGHT DETECTION USING CONIC SECTION GEOMETRY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 191–200. http://dx.doi.org/10.5194/isprsannals-iii-1-191-2016.

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Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the pose of the traffic lights with respect to the c
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Hosseinyalmdary, S., and A. Yilmaz. "TRAFFIC LIGHT DETECTION USING CONIC SECTION GEOMETRY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 191–200. http://dx.doi.org/10.5194/isprs-annals-iii-1-191-2016.

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Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the pose of the traffic lights with respect to the c
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Kareem Abdulrazzaq, Ali. "Design an Intelligent Traffic Light Controller." University of Thi-Qar Journal for Engineering Sciences 7, no. 1 (2016): 47–57. http://dx.doi.org/10.31663/utjes.v7i1.45.

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The aim of this research is to design an intelligent traffic light control system using Field Programmable Gate Array (FPGA) technology. And Very High Speed Hardware Description Language(VHDL). A structure of four road intersection (Al-Raiyah intersection) has been selected as reference site,which is located in Al-Nasiriyah city, Iraq. This intersection interconnects Bent-Al-Huda hospital, civil defense directory, the international high-way, the police office directory, and the railway station. In addition to utilizing a regular Traffic Light Controller (TLC), multiple level of functionality s
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Isdore Onyema Akwukwaegbu, Eleazar Benson Mfonobong, Jude-Kennedy Chibuzo Obichere, and Chiedozie Francis Paulinus-Nwammuo. "Smart fuzzy logic-based model of traffic light management." World Journal of Advanced Engineering Technology and Sciences 8, no. 2 (2023): 344–58. http://dx.doi.org/10.30574/wjaets.2023.8.2.0108.

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Traffic congestion difficulties have resulted in low productivity, significant air pollution, and energy losses in Owerri Metropolis, Nigeria. The paper looked at the design of a smart fuzzy logic traffic light management module, the development of a traffic control program using an Arduino microcontroller system, and the validation of the developed program's functionality using a Proteus circuit model to confirm the efficiency of fuzzy signal control. The traffic light environment of a fuzzy logic controller is simulated using Matlab software, and isolated traffic of multiple junctions is sim
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SREEVARDHAN, V., V. SANTOSH, and E. RAHUL. "AUTOMATIC SYNCHRONISED FSM BASED TRAFFIC LIGHT CONTROLLER." International Journal of Computer Science and Mobile Computing 11, no. 1 (2022): 214–20. http://dx.doi.org/10.47760/ijcsmc.2022.v11i01.029.

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Traffic light controller is designed to show the behavior of the traffic lights system and also a kind of good sequential circuit. Xilinx vivado is a tool which is being used to Annalise the heavy traffic by analyzing it through the various tools such as NEXYS-4, ARTIX -7, FPGA Board. The approach can be success by allowing a proper access to the areas shared through the multiple intersections and allocating effective time between various users, on or off the peaking hours. Theoretically the waiting times for drivers during peak hours has been reduced further, therefore this is system is bette
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TEME, Marius, and Catalin Dimon. "DEEP LEARNING - BASED OPTIMIZATION OF SMART TRAFFIC SIGNAL SYSTEMS." Annals of the Academy of Romanian Scientists Series on Science and Technology of Information 18, no. 1 (2025): 5–18. https://doi.org/10.56082/annalsarsciinfo.2025.1.5.

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This paper compares various artificial intelligence techniques applied to intelligent traffic systems for traffic light optimization. The use of Deep Learning algorithms for updating traffic light timings achieves superior results compared to the classical fixed-time approach. The traffic network is conceptualized as a modular component of the urban road infrastructure, facilitating traffic analysis in the context of an integrated management system. A case study analyzes a scenario with multiple connected intersections, with variable input flows estimated based on real data acquired from the B
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Vieira, Manuel Augusto, Manuela Vieira, Gonçalo Galvão, Paula Louro, and Mário Véstias. "Unlocking Traffic Control: Exploring Intersection Dynamics with Visible Light Communication." EPJ Web of Conferences 305 (2024): 00029. http://dx.doi.org/10.1051/epjconf/202430500029.

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This paper introduces the use of Visible Light Communication (VLC) to enhance traffic signal efficiency and vehicle trajectory management at urban intersections. By integrating VLC localization with learning-based traffic signal control, a multi-intersection traffic system is proposed. VLC enables communication between connected vehicles and infrastructure through mobile optical receivers. The primary objectives are to reduce waiting times and improve overall traffic safety by accommodating diverse traffic movements during multiple signal phases. Cooperative mechanisms and queue/response inter
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Shaharuddin, Raihanah Adawiyah, and Md Yushalify Misro. "Controlling Traffic Congestion in Urbanised City: A Framework Using Agent-Based Modelling and Simulation Approach." ISPRS International Journal of Geo-Information 12, no. 6 (2023): 226. http://dx.doi.org/10.3390/ijgi12060226.

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Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road users, particularly in densely populated urban cities. Since road capacity in urban cities changes throughout the day, an optimal traffic light signal duration might be different. Hence, in this paper, the effect of vehicle composition and traffic light phases on traffic flow during peak and off-peak hours in
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Dissertations / Theses on the topic "Etichetta Multiple Traffic Light"

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SAMPALEAN, NICULINA IUDITA. "ESPLORAZIONE DEL COMPORTAMENTO DEI CONSUMATORI NEI CONFRONTI DELLE DIVERSE ETICHETTE RELATIVE AGLI ALIMENTI DI QUALITÀ CERTIFICATA DALL'UNIONE EUROPEA." Doctoral thesis, Università Cattolica del Sacro Cuore, 2022. http://hdl.handle.net/10280/115280.

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Qualsiasi prodotto alimentare che si trova sul mercato contiene diverse etichette che aiutano i consumatori nel loro processo decisionale quando fanno acquisti. Questo aiuto può essere garantito solo se i consumatori comprendono il significato di queste etichette, le differenze tra loro e le informazioni che certificano. La tesi ha esplorato il ruolo delle etichette nel settore del marketing alimentare usando studi condotti sull'approccio del consumatore. Utilizzando diversi metodi (statistici ed econometrici), abbiamo analizzato le percezioni, la consapevolezza e la conoscenza dei consumator
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Hosseinyalamdary, Saivash Hosseinyalamdary. "Traffic Scene Perception using Multiple Sensors for Vehicular Safety Purposes." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1462803166.

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Book chapters on the topic "Etichetta Multiple Traffic Light"

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Wilbrink, Marc, and Michael Oehl. "The More the Better? Comparison of Different On-Board HMI Communication Strategies for Highly Automated Vehicles Using a LED Light-Band to Inform Passengers About Safe Interactions with Multiple Surrounding Traffic Participants." In Communications in Computer and Information Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19682-9_56.

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Anandh, B. A., A. Shankar Ganesh, and P. Nandakumar. "SMART TRAFFIC LIGHT CONTROL SYSTEM FOR EMERGENCY VEHICLES USING RF MODULE." In Futuristic Trends in Electronics & Instrumentation Engineering Volume 3 Book 1. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bdei1p5ch3.

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Traffic congestion is a growing concern for everyone, but it is extremely hard for emergency vehicles which are forced to waste important time in traffic which could be detrimental whether a life lives or not. Manual control of traffic has not proved to be efficient, also a predefined signal timing for the signal at all circumstances whether high or low traffic has not done any ease to the problem. Existing systems that use RF modules can only be used for one system at a time. A model to effectively solve the above-mentioned problems using the RF module and prioritizing algorithm is proposed.
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Roy, Gargi, Debodyuti Upadhaya, Partha Das, et al. "AUTOMATIC RAILWAY LEVEL CROSSING SYSTEM & TRAFFIC MANAGEMENT WITH REAL TIME MONITORING." In Proceedings of International Conference on Engineering Materials and Sustainable Societal Development [ICEMSSD 2024]. Iterative International Publishers (IIP), Selfypage Developers Pvt Ltd., 2025. https://doi.org/10.58532/nbennuricemssd16.

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Unmanned railway level crossings pose significant risks to road users, particularly in high-traffic or rural regions with limited surveillance and automation. This paper proposes a smart and integrated solution for automatic railway gate control and real-time traffic management using an IR sensor-based detection system, microcontroller control logic, traffic light signaling, a manual override mechanism, and a live video monitoring module. The prototype is designed to detect incoming trains, activate gates and traffic signals autonomously, and stream live footage to enhance operational safety.
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Tsiropoulou, Eirini Eleni, Panagiotis Vamvakas, and Symeon Papavassiliou. "Resource Allocation in Multi-Tier Femtocell and Visible-Light Heterogeneous Wireless Networks." In Advances in Wireless Technologies and Telecommunication. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2023-8.ch010.

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The increasing demand in mobile data traffic, data hungry services and high QoS prerequisites have led to the design of advanced multi-tier heterogeneous cellular networks. In this chapter, a multi-tier heterogeneous wireless network is examined consisting of the macrocell, multiple femtocells and multiple Visible Light Communication (VLC) cells. Distributed resource allocation approaches in two-tier femtocells are presented focusing on (a) power allocation and interference management, (b) joint power and rate allocation, and (c) resource allocation and pricing policies. Similarly, the most pr
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Moshayedi, Ata Jahangir, Amir Sohail Khan, Zeashan Hameed Khan, Arash Sioofy Khoojine, and Abolfazl Razi. "Road Space Rationing Using Vehicle's Automated License Plate Recognition." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-4571-0.ch005.

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The exponential rise in volumes of motor vehicles all over the world has led to increased pollution and negative impact on climate. Therefore, road space rationing is one strategy to control traffic volume which allows even/odd number plates on alternate days. However, it requires Automated License Plate Recognition (ALPR) systems for real time monitoring. Machine intelligence based ALPR uses multiple technologies to offer robust performance under varying imaging conditions, such as high velocities, low light, harsh weather, camera vibration, and partially obscured images. Furthermore, the rad
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Liu I-Hsien, Wang Tian-Li, and Li Jung-Shian. "An Effective Group Communications in Hybrid VANET." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-484-8-474.

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VANET applications are initially for safety purpose. Now, infotainment applications with group communication among vehicles are in the lime-light. In this research, we propose an overlay construction scheme to support multiple group communication in hybrid VANET. More specifically, we deal with group isolation which has a great impact on overlay reliability. By incorporating 3G access, the limited DSRC transmission rage is complemented with long range transmission nature of infrastructure-based 3G network. With an initialized overlay in DSRC manner, we propose 3G management scheme, including 3
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Kaltoft Mette Kjer and Dowie Jack. "Risk Classifications Interfere with Preference-Sensitive Decision Support." In Studies in Health Technology and Informatics. IOS Press, 2019. https://doi.org/10.3233/978-1-61499-975-1-217.

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Many guidelines for prevention and treatment still locate persons in risk classes (e.g. low, moderate, high) on the basis of thresholds placed on a continuous metric for a single criterion (e.g. risk of developing x). These ‘traffic light’ signals can lead to inferior decisions through their mono-criterial focus and lack of preference-sensitivity to the multiple criteria relevant to the person. It is arguably unethical to communicate to someone that they are at low, moderate, or high risk of x solely on the basis of the unpublished and often unknown preferences of the group
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Sumathi, A., and S. SanthoshKumar. "Safeguarding Journeys." In Advances in Computational Intelligence and Robotics. IGI Global, 2024. https://doi.org/10.4018/979-8-3693-4252-7.ch007.

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Drowsy driving is the combination of operating a vehicle while feeling sleepy or fatigued. It poses a significant risk factor in road traffic incidents. Implementing driver drowsiness detection systems can help alleviate and prevent fatal car accidents caused by drowsy driving. The detection of drowsiness relies on the utilization of advanced machine learning and artificial intelligence techniques, specifically tailored to monitor and analyze the condition of the driver's eyes. The alert signal originates from a setup involving multiple devices, including the Raspberry Pi with a Raspbian camer
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Cox Steven, Anderson Scott, Gray Neil, Vogt Oliver, and Kotsialos Apostolos. "Application of a Multivariate Process Control Technique for Set-Up Dominated Low Volume Operations." In Advances in Transdisciplinary Engineering. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-668-2-535.

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In traditional high-volume manufacturing applications, the timing of control adjustments to processes is based on parametric Statistical Process Control (SPC) methods, such as Shewhart X & R charts. In high-value, high-complexity and low-volume industries, where production runs are in the order of tens rather than thousands, traditional SPC approaches are not easily applicable. A manufactured component's complexity, with multiple critical features to monitor, increases the difficulty for a process operator to maintain all of them within their design tolerances. In response to this, thi
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Srinivasan, Suganthi, Rakesh Rajegowda, and Eshwar Udhayakumar. "Latest Advancements in Perception Algorithms for ADAS and AV Systems Using Infrared Images and Deep Learning." In Digital Image Processing - Latest Advances and Applications [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.1003683.

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Perception system plays an important role in Advanced driver assistance systems (ADAS) & Autonomous vehicles (AV) to understand the surrounding environment and further navigation. It is highly challenging to achieve the accurate perception of ego vehicle mimicking human vision. The available ADAS and AV solutions could able to perceive the environment to some extent using multiple sensors like Lidars, Radars and Cameras. National Highway Traffic Safety Administration Crash reports of ADAS and AV systems shows that the complete autonomy is challenging to achieve using the existing sensor su
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Conference papers on the topic "Etichetta Multiple Traffic Light"

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Zerroug, Rafik, Zibouda Aliouat, and Adel Alti. "Managing Congestions at Multiple Intersections During Disasters with Chronological Coordination of Intelligent Traffic Light Management." In 2024 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). IEEE, 2024. https://doi.org/10.1109/ict-dm62768.2024.10798932.

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Rahman, Mahfuzur, Laith Bani Khaled, Iffat Ara Ebu, and John E. Ball. "V2I communication of autonomous vehicles with traffic light infrastructures of multiple intersections to optimize vehicle speed." In Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2025, edited by Michael C. Dudzik, Theresa J. Axenson, and Stephen M. Jameson. SPIE, 2025. https://doi.org/10.1117/12.3053309.

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Mugesh, R., R. Manoj, R. Kaviprasth, and S. Gokilavani. "Integrated Recognition Approach and Fining System Towards Detection and Tracking of Traffic Violating Multiple Vehicles using Pairing Net and Light Weight Deep Sort Fast YOLO Rec Architectures." In 2025 International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2025. https://doi.org/10.1109/iciccs65191.2025.10985629.

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Jang, Chulhoon, Chansoo Kim, Dongchul Kim, Minchae Lee, and Myoungho Sunwoo. "Multiple exposure images based traffic light recognition." In 2014 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2014. http://dx.doi.org/10.1109/ivs.2014.6856541.

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Cao, Zheng, and Jian Zhang. "Simulation Design of Continuous Linear Multiple Intersection Intelligent Traffic Light." In MLMI 2023: The 6th International Conference on Machine Learning and Machine Intelligence. ACM, 2023. http://dx.doi.org/10.1145/3635638.3635661.

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Zhou, Binbin, Jiannong Cao, and Hejun Wu. "Adaptive Traffic Light Control of Multiple Intersections in WSN-Based ITS." In 2011 IEEE Vehicular Technology Conference (VTC 2011-Spring). IEEE, 2011. http://dx.doi.org/10.1109/vetecs.2011.5956434.

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Pyschny, Jan, Felix Berger, Samuel Rothen, et al. "A Multiple-Input Multiple-Output Radar-Based Rider Assistance System for Personal Light Electric Vehicles." In Automotive Technical Papers. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-5040.

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<div class="section abstract"><div class="htmlview paragraph">The use of personal light electric vehicles (PLEVs), such as electric scooters, has rapidly increased in recent years. However, their widespread use has raised concerns about rider safety due to their vulnerability in shared traffic spaces. To address this issue, this paper presents a radar-based rider assistance system aimed at enhancing the safety of PLEV riders. The system consists of an adaptive feedback system and a single-channel anti-lock braking system (ABS). The adaptive feedback system uses multiple-input multi
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Joyo, Ambteen, Kaziq Yaqub, and Nicholas Madamopoulos. "Managing traffic-light-duration by exploiting smart antenna technology (MATSAT) for coordinated multiple-intersections (CMI)." In 2015 International Conference on Emerging Technologies (ICET). IEEE, 2015. http://dx.doi.org/10.1109/icet.2015.7389226.

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Saedi, Kazem, and Amir Hossein Mohajcrzadeh. "Designing a Light-Weighted Multi-Class and Novel Multiple Logical Fuzzy Controller to Manage Intelligent Urban Traffic." In 2018 8th International Conference on Computer and Knowledge Engineering (ICCKE). IEEE, 2018. http://dx.doi.org/10.1109/iccke.2018.8566565.

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Racila, Laurentiu. "Saturation flow mathematical model based on multiple combinations of lane groups." In CIT2016. Congreso de Ingeniería del Transporte. Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.4254.

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The ideal value of the traffic stream that can pass through an intersection is known as the saturation flow rate per hour on vehicle green time. The saturation flow is important in the understanding of the traffic light cycle and from there the understanding the Level of Service. The paper wishes to evaluate through a series of applied mathematical methods the effect of different lane grouping and critical lane group concept on the saturation flow rate. The importance of this method is that it creates a base for a signalized intersections timing plan.DOI: http://dx.doi.org/10.4995/CIT2016.2016
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Reports on the topic "Etichetta Multiple Traffic Light"

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Liu, Tairan. Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2322.

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In an innovative venture, the research team embarked on a mission to redefine urban traffic flow by introducing an automated way to manage traffic light timings. This project integrates two critical technologies, Deep Q-Networks (DQN) and Auto-encoders, into reinforcement learning, with the goal of making traffic smoother and reducing the all-too-common road congestion in simulated city environments. Deep Q-Networks (DQN) are a form of reinforcement learning algorithms that learns the best actions to take in various situations through trial and error. Auto-encoders, on the other hand, are tool
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Cheng, Wen, Yongping Zhang, and Edward Clay. Comprehensive Performance Assessment of Passive Crowdsourcing for Counting Pedestrians and Bikes. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2025.

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Individuals who walk and cycle experience a variety of health and economic benefits while simultaneously benefiting their local environments and communities. It is essential to correctly obtain pedestrian and bicyclist counts for better design and planning of active transportation-related facilities. In recent years, crowdsourcing has seen a rise in popularity due to the multiple advantages relative to traditional methods. Nevertheless, crowdsourced data have been applied in fewer studies, and their reliability and performance relative to other conventional methods are rarely documented. To th
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Rushing, John, Lulu Edwards, Haley Bell, and Margarita Ordaz. Rapid assessment tools for estimating trafficability of low volume roads. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49560.

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Rapid assessment of low-volume road surfaces remains a challenge when attempting to forecast allowable vehicle crossings. Variations in soil type, compaction effort, and moisture content of the soil can greatly affect trafficability, and predictive equations for soil deformation under vehicle loads often have reduced reliability for low-strength materials. Portable tools to characterize soil stiffness and corresponding relationships to load-induced deformation are needed. In this effort, researchers performed comparative testing of multiple rapid assessment tools as potential devices for givin
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