20-06-2014, 11:09 AM
COMPARISON OF ORDINARY TRAFFIC LIGHT SYSTEM WITH AN INTELLIGENT TRAFFIC SYSTEM
[attachment=65091]
INTRODUCTION
Traffic congestion is a severe problem in many modern cities around the world Traffic congestion has been causing many critical problems and challenges in the major and most populated cities. To travel to different places within the city is becoming more difficult for the travelers in traffic. Due to this congestion problems, people lose time, miss opportunities, and get frustrated. There are chances that people lose their lives in the ambulance itself, as it is stuck in a traffic jam. The fire brigade may not reach in time, thus leading in damage to life and property. The traffic congestion directly impacts the companies. Due to traffic congestions there is a loss in productivity from workers, trade opportunities are lost, delivery gets delayed, and there by the costs goes on increasing. To solve these congestion problems, we have to build new facilities and infrastructure but at the same time make it smart. The only disadvantage of making new roads on facilities is that it makes the surroundings more congested. So for that reason we need to change the system rather than making new infrastructure twice. Thus there is a need for an intelligent traffic light system
Intelligent transport technologies
Intelligent transport systems vary in technologies applied, from basic management systems such as car navigation; traffic signal control systems; container management systems; variable message signs; automatic number plate recognition or speed cameras to monitor applications, such as security CCTV systems; and to more advanced applications that integrate live data and feedback from a number of other sources, such as parking guidance and information systems; weather information; bridge deicing systems; and the like. Additionally, predictive techniques are being developed in order to allow advanced modeling and comparison with historical baseline data. Some of the constituent technologies typically implemented in ITS are described in the following sections:
Wireless communications
Various forms of wireless communications technologies have been proposed for intelligent transportation systems. Radio modem communication on UHF and VHF frequencies are widely used for short and long range communication within ITS.
Short-range communications (less than 500 yards) can be accomplished using IEEE 802.11 protocols, specifically WAVE or the Dedicated Short Range Communications standard being promoted by the Intelligent Transportation Society of America and the United States Department of Transportation. Theoretically, the range of these protocols can be extended using Mobile ad-hoc networks or Mesh networking.
Longer range communications have been proposed using infrastructure networks such as WiMAX (IEEE 802.16), Global System for Mobile Communications (GSM), or 3G. Long-range communications using these methods are well established, but, unlike the short-range protocols, these methods require extensive and very expensive infrastructure deployment. There is lack of consensus as to what business model should support this infrastructure.
Computational technologies
Recent advances in vehicle electronics have led to a move toward fewer, more capable computer processors on a vehicle. A typical vehicle in the early 2000s would have between 20 and 100 individual networked microcontroller/Programmable logic controller modules with non-real-time operating systems. The current trend is toward fewer, more costly microprocessor modules with hardware memory management and Real-Time Operating Systems. The new embedded system platforms allow for more sophisticated software applications to be implemented, including model-based process control, artificial intelligence, and ubiquitous computing
Floating car data/floating cellular data
Virtually every car contains one or more mobile phones. These mobile phones routinely transmit their location information to the network – even when no voice connection is established. This allows them to be used as anonymous traffic probes. As the car moves, so does the signal of the mobile phone. By measuring and analyzing network data, using triangulation, pattern matching or cell-sector statistics – in an anonymous format – the data is converted into accurate traffic flow information. With more congestion, there are more cars, more phones, and thus, more probes. In metropolitan areas, the distance between antennas is shorter and, thus, accuracy increases. No infrastructure needs to be built along the road; only the mobile phone network is leveraged. In some metropolitan areas, RFID signals from ETC transponders are used. Floating car data technology provides great advantages over existing methods of traffic measurement:
1. Much less expensive than sensors or cameras
2. More coverage: all locations and streets
3. Faster to set up (no work zones) and less maintenance
4. Works in all weather conditions, including heavy rain
Travel time data on freeways and arterial roadways is also being collected using sensors based on Bluetooth technology. Travel times and speed are calculated by comparing the time at which a specific device signal is recorded by pairs of sensors.
Sensing technologies
Technological advances in telecommunications and information technology coupled with state-of-the-art microchip, RFID (Radio Frequency Identification), and inexpensive intelligent beacon sensing technologies have enhanced the technical capabilities that will facilitate motorist safety benefits for intelligent transportation systems globally. Sensing systems for ITS are vehicle and infrastructure based networked systems, e.g., Intelligent vehicle technologies. Infrastructure sensors are indestructible (such as in-road reflectors) devices that are installed or embedded on the road, or surrounding the road (buildings, posts, and signs for example) as required and may be manually disseminated during preventive road construction maintenance or by sensor injection machinery for rapid
Inductive loop detection
Inductive loops can be placed in a roadbed to detect vehicles as they pass over the loop by measuring the vehicle's magnetic field. The simplest detectors simply count the number of vehicles during a unit of time (typically 60 seconds in the United States) that pass over the loop, while more sophisticated sensors estimate the speed, length, and weight of vehicles and the distance between them. Loops can be placed in a single lane or across multiple lanes, and they work with very slow or stopped vehicles as well as vehicles moving at high-speed.
TRAFFIC LIGHT SIGNAL COMPNENTS
Most traffic signals will have the following components or parts:
A) Main display with red, yellow, and green lights.
B) Pedestrian crossing lights containing both the “WALK” and “DON’T WALK” light indications.
C) Traffic signal cabinet containing the traffic signal controller.
And Vehicle Detection Systems, either
D) Sensors OR inductive loops,
Or
E) Video detection system
Location of Loop
Location, Location, Location! The position of the loop relative to the vehicles you are trying to detect is extremely important. Vehicles entering a fast food restaurant drive-thru lane will stop at the menu board with the driver’s window positioned in line with the speaker post. The front axle is the only metal surface whose relative position to the driver is consistent from vehicle to vehicle. Because of this fact, the vehicle detector is designed to pick up the front axle, not the vehicle’s engine. Therefore, the loop should be positioned 1 ½ to 2 feet ahead of the speaker post, with the long axis of the loop running perpendicular to the traffic lane. This positions the axle of the vehicle directly over the loop in the same direction as the loop. The proper installation and location of the loop are the most important aspects of reliable vehicle detection. In recent years, there has been an increase in the number of missed and false detections due to the popularity of SUVs. The missed detections can be attributed to two factors. First, and most obvious, is that the metal surface area of the taller vehicles is farther away from the loop which makes the vehicle more difficult to detect. Second, and less obvious, is that larger vehicles have
[attachment=65091]
INTRODUCTION
Traffic congestion is a severe problem in many modern cities around the world Traffic congestion has been causing many critical problems and challenges in the major and most populated cities. To travel to different places within the city is becoming more difficult for the travelers in traffic. Due to this congestion problems, people lose time, miss opportunities, and get frustrated. There are chances that people lose their lives in the ambulance itself, as it is stuck in a traffic jam. The fire brigade may not reach in time, thus leading in damage to life and property. The traffic congestion directly impacts the companies. Due to traffic congestions there is a loss in productivity from workers, trade opportunities are lost, delivery gets delayed, and there by the costs goes on increasing. To solve these congestion problems, we have to build new facilities and infrastructure but at the same time make it smart. The only disadvantage of making new roads on facilities is that it makes the surroundings more congested. So for that reason we need to change the system rather than making new infrastructure twice. Thus there is a need for an intelligent traffic light system
Intelligent transport technologies
Intelligent transport systems vary in technologies applied, from basic management systems such as car navigation; traffic signal control systems; container management systems; variable message signs; automatic number plate recognition or speed cameras to monitor applications, such as security CCTV systems; and to more advanced applications that integrate live data and feedback from a number of other sources, such as parking guidance and information systems; weather information; bridge deicing systems; and the like. Additionally, predictive techniques are being developed in order to allow advanced modeling and comparison with historical baseline data. Some of the constituent technologies typically implemented in ITS are described in the following sections:
Wireless communications
Various forms of wireless communications technologies have been proposed for intelligent transportation systems. Radio modem communication on UHF and VHF frequencies are widely used for short and long range communication within ITS.
Short-range communications (less than 500 yards) can be accomplished using IEEE 802.11 protocols, specifically WAVE or the Dedicated Short Range Communications standard being promoted by the Intelligent Transportation Society of America and the United States Department of Transportation. Theoretically, the range of these protocols can be extended using Mobile ad-hoc networks or Mesh networking.
Longer range communications have been proposed using infrastructure networks such as WiMAX (IEEE 802.16), Global System for Mobile Communications (GSM), or 3G. Long-range communications using these methods are well established, but, unlike the short-range protocols, these methods require extensive and very expensive infrastructure deployment. There is lack of consensus as to what business model should support this infrastructure.
Computational technologies
Recent advances in vehicle electronics have led to a move toward fewer, more capable computer processors on a vehicle. A typical vehicle in the early 2000s would have between 20 and 100 individual networked microcontroller/Programmable logic controller modules with non-real-time operating systems. The current trend is toward fewer, more costly microprocessor modules with hardware memory management and Real-Time Operating Systems. The new embedded system platforms allow for more sophisticated software applications to be implemented, including model-based process control, artificial intelligence, and ubiquitous computing
Floating car data/floating cellular data
Virtually every car contains one or more mobile phones. These mobile phones routinely transmit their location information to the network – even when no voice connection is established. This allows them to be used as anonymous traffic probes. As the car moves, so does the signal of the mobile phone. By measuring and analyzing network data, using triangulation, pattern matching or cell-sector statistics – in an anonymous format – the data is converted into accurate traffic flow information. With more congestion, there are more cars, more phones, and thus, more probes. In metropolitan areas, the distance between antennas is shorter and, thus, accuracy increases. No infrastructure needs to be built along the road; only the mobile phone network is leveraged. In some metropolitan areas, RFID signals from ETC transponders are used. Floating car data technology provides great advantages over existing methods of traffic measurement:
1. Much less expensive than sensors or cameras
2. More coverage: all locations and streets
3. Faster to set up (no work zones) and less maintenance
4. Works in all weather conditions, including heavy rain
Travel time data on freeways and arterial roadways is also being collected using sensors based on Bluetooth technology. Travel times and speed are calculated by comparing the time at which a specific device signal is recorded by pairs of sensors.
Sensing technologies
Technological advances in telecommunications and information technology coupled with state-of-the-art microchip, RFID (Radio Frequency Identification), and inexpensive intelligent beacon sensing technologies have enhanced the technical capabilities that will facilitate motorist safety benefits for intelligent transportation systems globally. Sensing systems for ITS are vehicle and infrastructure based networked systems, e.g., Intelligent vehicle technologies. Infrastructure sensors are indestructible (such as in-road reflectors) devices that are installed or embedded on the road, or surrounding the road (buildings, posts, and signs for example) as required and may be manually disseminated during preventive road construction maintenance or by sensor injection machinery for rapid
Inductive loop detection
Inductive loops can be placed in a roadbed to detect vehicles as they pass over the loop by measuring the vehicle's magnetic field. The simplest detectors simply count the number of vehicles during a unit of time (typically 60 seconds in the United States) that pass over the loop, while more sophisticated sensors estimate the speed, length, and weight of vehicles and the distance between them. Loops can be placed in a single lane or across multiple lanes, and they work with very slow or stopped vehicles as well as vehicles moving at high-speed.
TRAFFIC LIGHT SIGNAL COMPNENTS
Most traffic signals will have the following components or parts:
A) Main display with red, yellow, and green lights.
B) Pedestrian crossing lights containing both the “WALK” and “DON’T WALK” light indications.
C) Traffic signal cabinet containing the traffic signal controller.
And Vehicle Detection Systems, either
D) Sensors OR inductive loops,
Or
E) Video detection system
Location of Loop
Location, Location, Location! The position of the loop relative to the vehicles you are trying to detect is extremely important. Vehicles entering a fast food restaurant drive-thru lane will stop at the menu board with the driver’s window positioned in line with the speaker post. The front axle is the only metal surface whose relative position to the driver is consistent from vehicle to vehicle. Because of this fact, the vehicle detector is designed to pick up the front axle, not the vehicle’s engine. Therefore, the loop should be positioned 1 ½ to 2 feet ahead of the speaker post, with the long axis of the loop running perpendicular to the traffic lane. This positions the axle of the vehicle directly over the loop in the same direction as the loop. The proper installation and location of the loop are the most important aspects of reliable vehicle detection. In recent years, there has been an increase in the number of missed and false detections due to the popularity of SUVs. The missed detections can be attributed to two factors. First, and most obvious, is that the metal surface area of the taller vehicles is farther away from the loop which makes the vehicle more difficult to detect. Second, and less obvious, is that larger vehicles have