This is the presentation I made to our City\'s Transportation and Safety Commission, the Public Safety Commission, and various community organizations in favor of a red light camera system for out City.
Project is used to control traffic signal system automatically with IR sensors. Signal timing changes automatically on sensing the traffic density at junctions.
This project represents a way of developing an
interface to detect driver drowsiness based on continuously
monitoring eyes and DIP algorithms. Micro sleeps that are short
period of sleeps lasting 2 to 3 seconds are good indicator of
fatigue state. Thus by continuously monitoring the eyes of the
driver by using camera one can detect the sleepy state of driver
and timely warning is issued.
Aim of the project is to develop the hardware which is very
advanced product related to driver safety on the roads using
controller and image processing. This product detects driver
drowsiness and gives warning in form of alarm and as well as
decreases the speed of vehicle.Along with the drowsiness
detection process there is continuous monitoring of the distance
done by the Ultrasonic sensor. The ultrasonic sensor detects the
obstacle and accordingly warns the driver as well as decreases
speed of vehicle.
Automatic water level monitoring and control system using IoTDanish Mehraj
This is the documentation for making Automatic water level monitoring and control system using Internet of Thimgs (IoT) which will help is to save water and removes the efforts to take care of watering u[ the tanks in homes and offices.
Intelligent traffic information and control systemSADEED AMEEN
As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state of the art of traffic control. In current situation, the signal remains green until the present cars have passed. To avoid those problems we propose a system for controlling the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. For this purpose, edge detection has been carried out and according to percentage of matching traffic light-durations can be controlled. In addition, when an emergency vehicle is approaching the junction, it will communicate to the traffic controller in the junction to turn ON the green light. This module uses ZigBee modules for wireless communications between the ambulance and traffic controller. Intelligent traffic control system helps to pass emergency vehicles smoothly. Traffic signal management system is developed for the traffic police, to control the traffic lights manually. Additionally an information system is added using a chat bot module to avail traffic information to user.
TRAFFIC SIGNAL CONTROL USING IR SENSORSKunal Kabra
The main objective of this project is to design an intelligent auto traffic signal control system.
Traffic congestion is one of the major issues to be considered. Generally Vehicular traffic
Intersects at the junctions of the road and are controlled by the traffic signals .Traffic signals
Need a good coordination and control to ensure the smooth and safe flow of the vehicular traffic.
During the rush hours, the traffic on the roads is at its peak. Also, there is a possibility for the
Emergency vehicles to stuck in the traffic jam. Therefore; there is a need for the dynamic control
of the traffic during rush hours. Hence I propose a smart traffic signal controller .The proposed
System tries to minimize the possibilities of traffic jams, caused by the traffic lights, to some
Extent by clearing the road with higher density of vehicles and also provides the clearance for the Emergency vehicle if any. The system is based on the AVR micro controller and IR sensors
Technology.
Project is used to control traffic signal system automatically with IR sensors. Signal timing changes automatically on sensing the traffic density at junctions.
This project represents a way of developing an
interface to detect driver drowsiness based on continuously
monitoring eyes and DIP algorithms. Micro sleeps that are short
period of sleeps lasting 2 to 3 seconds are good indicator of
fatigue state. Thus by continuously monitoring the eyes of the
driver by using camera one can detect the sleepy state of driver
and timely warning is issued.
Aim of the project is to develop the hardware which is very
advanced product related to driver safety on the roads using
controller and image processing. This product detects driver
drowsiness and gives warning in form of alarm and as well as
decreases the speed of vehicle.Along with the drowsiness
detection process there is continuous monitoring of the distance
done by the Ultrasonic sensor. The ultrasonic sensor detects the
obstacle and accordingly warns the driver as well as decreases
speed of vehicle.
Automatic water level monitoring and control system using IoTDanish Mehraj
This is the documentation for making Automatic water level monitoring and control system using Internet of Thimgs (IoT) which will help is to save water and removes the efforts to take care of watering u[ the tanks in homes and offices.
Intelligent traffic information and control systemSADEED AMEEN
As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state of the art of traffic control. In current situation, the signal remains green until the present cars have passed. To avoid those problems we propose a system for controlling the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. For this purpose, edge detection has been carried out and according to percentage of matching traffic light-durations can be controlled. In addition, when an emergency vehicle is approaching the junction, it will communicate to the traffic controller in the junction to turn ON the green light. This module uses ZigBee modules for wireless communications between the ambulance and traffic controller. Intelligent traffic control system helps to pass emergency vehicles smoothly. Traffic signal management system is developed for the traffic police, to control the traffic lights manually. Additionally an information system is added using a chat bot module to avail traffic information to user.
TRAFFIC SIGNAL CONTROL USING IR SENSORSKunal Kabra
The main objective of this project is to design an intelligent auto traffic signal control system.
Traffic congestion is one of the major issues to be considered. Generally Vehicular traffic
Intersects at the junctions of the road and are controlled by the traffic signals .Traffic signals
Need a good coordination and control to ensure the smooth and safe flow of the vehicular traffic.
During the rush hours, the traffic on the roads is at its peak. Also, there is a possibility for the
Emergency vehicles to stuck in the traffic jam. Therefore; there is a need for the dynamic control
of the traffic during rush hours. Hence I propose a smart traffic signal controller .The proposed
System tries to minimize the possibilities of traffic jams, caused by the traffic lights, to some
Extent by clearing the road with higher density of vehicles and also provides the clearance for the Emergency vehicle if any. The system is based on the AVR micro controller and IR sensors
Technology.
Final Year Engineering Project Title List for Electronics & Electrical Branch...zettanetworks
Zetta Networks is a Final Year Project Training in Bangalore India has been relentlessly working to bridge the gap between potential Employers and the skillful employees in the field of Information Technology by selecting, Project training and placing IT professionals nationwide.
Network Traffic Trends Prediction Using Machine Learning Modelling of Packet ...Rangaprasad Sampath
This deck proposes a method to predict network traffic trends ans spot traffic anomalies. The machine learning modelling is done on the packet lengths that constitute network traffic and this provides an elegant way to digest a histogram of packet lengths in time t into a pair of data points. An unsupervised machine learning method is applied on the obtained dataset and the resulting clusters are labeled. Changes in cluster composition indicate traffic trends that may be then interpreted for network insights.
it is a presentation based on image processing used in the field of fatigue detection while driving which can save many life as well as prevent accident.
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads
A collision prevention warning system is an automobile safety system which enables vehicles to identify the chances of collision and give visual and audio warning to the driver so that the driver can take necessary action to avoid `a collision.
Final Year Engineering Project Title List for Electronics & Electrical Branch...zettanetworks
Zetta Networks is a Final Year Project Training in Bangalore India has been relentlessly working to bridge the gap between potential Employers and the skillful employees in the field of Information Technology by selecting, Project training and placing IT professionals nationwide.
Network Traffic Trends Prediction Using Machine Learning Modelling of Packet ...Rangaprasad Sampath
This deck proposes a method to predict network traffic trends ans spot traffic anomalies. The machine learning modelling is done on the packet lengths that constitute network traffic and this provides an elegant way to digest a histogram of packet lengths in time t into a pair of data points. An unsupervised machine learning method is applied on the obtained dataset and the resulting clusters are labeled. Changes in cluster composition indicate traffic trends that may be then interpreted for network insights.
it is a presentation based on image processing used in the field of fatigue detection while driving which can save many life as well as prevent accident.
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads
A collision prevention warning system is an automobile safety system which enables vehicles to identify the chances of collision and give visual and audio warning to the driver so that the driver can take necessary action to avoid `a collision.
The Gesture Recognition Technology is rapidly growing technology and this PPT describes about the working of gesture recognition technology,the sub fields in it, its applications and the challenges it faces.
ELS is the first year hardware group project. This aims at improving safety on highways by enforcing law, driver assisting, geo tracking and automatic responding in case of emergency.
Local Motors Awesome System is a self optimized sustainable autonomous vehicle system.
It is safe, affordable and enable new business models.
Join the mobility revolution.
(V3.0)
transportation is the back bone of countries economical development. providing good and effective transportation facility will help in developing countries economy. transportation will save time, money, and work can be done easily. intelligent transportation system provides more benefits to the nation.
Portland Tames Speed for Safety, a Case Study for Vision Zero Citiesvisionzeronetwork
Portland, Oregon has a comprehensive approach to managing speed for safety. Their work provides a model for other Vision Zero cities to ensure action on this core value of Vision Zero.
ReferenceNewman, Earl E. Yellow Signal Timing – Lessons Learn.docxdebishakespeare
Reference
Newman, Earl E. “Yellow Signal Timing – Lessons Learned from a Red Light Camera Program.” Conference Paper ID AB10H2601, Presented at the 2010 ITE Annual Meeting and Exhibit, Vancouver, Canada, August 8th-10th, 2010. ( second attachment )
Read the above referenced paper and answer the questions below. The paper is on the shared drive (handouts directory). Write your answers directly into this handout and turn it in on the due date listed above. If you look up any information online and use it in your response, be sure to include a link to the document’s location.
1. Figure 1 in the document shows the MUTCD defined boundary for a red light violation, which begins at the stop bar in each direction. In Arizona, the extension of the curb line is used for this purpose (example shown in Figure 1). Presuming the distance between the stopbar and the extension of curb line is 25’ and the speed limit is 25mph in the example shown in Figure 1, mathematically show how this difference would impact the duration of the ‘Yellow’ and ‘All Red’ intervals. (4)
Direction
of Travel
Extension of
Curb Line
Figure 1: Curb Line Extension
2. The article states that a “…complete conversion to LED traffic signal lamps…” was one of their Red Light Running countermeasures. Why would this help in reducing red light running? (Hint: Google ‘LED traffic signal’) Name at least one other benefit of LED traffic signal lamps. (4)
3. Looking at Table 2, rear end crashes increased after the installation of red light cameras not just at intersections where cameras were installed, but at all locations. What might be the cause of this system-wide increase? (4)
4. In this paper, the City of Springfield and the Missouri DOT used a Memorandum of Understanding (MOU) to establish common practices for timing clearance intervals. What other items in a transportation system might be improved if agencies engaged in more coordination across jurisdictional boundaries? Name 2. (4)
5. In this paper, the agencies involved used a perception-reaction time of 1.5s for timing clearance intervals, while the recommended value for practice is 1.0 seconds. What was the justification given for this choice? (4)
page 2 of 2
Yellow Signal Timing –
Lessons Learned from a Red Light Camera Program
Earl E. Newman
Abstract: The City Council for the City of Springfield, Missouri, approved a contract to install
up to sixteen cameras for automated red light enforcement in the spring of 2006. During the
implementation phase of the program, test sampling of potential intersections for placement of
the cameras revealed significant differences in yellow timings and red light running at city
signals compared to Missouri DOT signals inside the city.
This difference prompted city and state traffic engineers to review their respective methods of
calculating the yellow and all-red timings. Despite using the same equation recommended by
ITE, the agencies used different assumpt ...