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Technology Used To Improve Traffic Flow And Road Safety

MARTA project. (Credit: Image courtesy of Universitat Politècnica de Catalunya)

The Research Group in Mathematical Programming, Logistics and Simulation (PROMALS) and the Seat Chair of Innovation and Sustainable Development (Seat-UPC) create technological solutions to improve traffic flow, make driving safer and more comfortable, lower the accident rate and reduce traffic congestion and emissions of contaminant gases.

New advances will see vehicles equipped with sensors and interfaces which gather information on the traffic situation and display it on screen or alert the driver through automated voice announcements. The Seat-UPC Chair is involved in designing and fitting human machine interfaces (HMIs) and running automated tests of the electronic systems used in the MARTA project, which incorporate new technologies such as specialized image recognition applications.

New on-board sensors will be able to monitor the status of mechanical components such as brakes when a vehicle is in motion, while others will provide automatic control of driving speed and the distance maintained from the vehicle in front. Interfaces will enable data to be shared between vehicles, providing updated information on their position and speed every 200 meters. A system of nodes installed in the road network transmits the data to a mobility management center, where they are processed and used to maintain traffic flow by providing real-time information on congestion spots and suggesting optimum routes in the event of an accident.

The PROMALS group, attached to the Department of Statistics and Operations Research at the UPC, is looking at ways of using the data received by the management center. Its researchers are designing simulated traffic scenarios in which to test the new technologies developed under the MARTA project: a recent example is a traffic priority system in which the real-time data are used to determine the ideal intervals between traffic light phases across a given area, which optimizes traffic flow and reduces congestion.

The MARTA project has a budget of over thirty-five million euros and receives funding from the Center for the Development of Industrial Technology (CDTI). The project, scheduled for completion in 2011, is coordinated by the company FICOSA as part of a wider program run by the National Strategic Consortium in Technical Research (CENIT), and brings together experts and researchers from nineteen companies and nineteen scientific centers and national universities.

Source : sciencedaily


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‘Smart’ Traffic Boxes Could Help Monitor Roads, Save Money

Taken from sciencedaily.com

ScienceDaily (July 5, 2007) — Ohio State University engineers are working to make the traffic control boxes that stand beside major freeways smarter.

They’ve developed new software that helps the computerized boxes locate road incidents — such as traffic back-ups or accidents — and notify transportation authorities at lower cost, especially in rural areas.

For a large city like Columbus, Ohio, the savings could add up to tens of thousands of dollars a month. For a state like California the savings could be over a million dollars a year.

Over the last few decades, transportation departments around the country have installed devices called “loop detectors” to monitor traffic at key points on the road network, explained Benjamin Coifman, associate professor of civil and environmental engineering and geodetic science at Ohio State. He is also an associate professor of electrical and computer engineering.

The car-sized wire loops buried in the pavement effectively act as metal detectors. When a car passes over a loop, the detector sends a signal to a computer in a control box at the side of the road.

The controller may simply count the number of cars that pass by and calculate average speed, or it may actively control traffic. Ramp meters are one example — they limit the number of cars entering a freeway by controlling a traffic signal on the on-ramp.

But Coifman knows that the controller boxes can do much more.

“The basic technology of these devices is very reliable, and such detectors are becoming more widespread as congestion increases,” he said. “But little attention has been paid to how they are used.

“It’s as if you handed a teenager a cell phone and said, ‘make all the calls you like.’ A lot of information gets transmitted, you might only be interested in a small amount of it, and you get a large phone bill at the end of the month.”

The main cost of using such devices is the cost of sending electronic signals between them and the transportation center that is doing the monitoring. Normally, controller boxes transmit their data very frequently. Some do so as often as once every twenty seconds.

“When the number of controller boxes in use around the country was small, the communication costs were small, but now that the numbers are increasing, so are the bills,” Coifman said. He wants to help states leverage those detector stations and keep costs down.

He and former graduate student Ramachandran Mallika wrote software that enabled the controller boxes to detect traffic incidents and get important messages back to the traffic control center using a fraction of the bandwidth that was previously required.

In the October 2007 issue of the journal Transportation Research Part A, they report that their software achieved better than 90 percent accuracy in reporting traffic conditions at the interchange between two busy Columbus, Ohio interstates — using up to 200 times fewer signals than before.

Instead of sending all of the data all of the time, the new software infers road conditions based on traffic patterns. It determines whether conditions are critical enough for an alert to be sent to a state transportation authority. Otherwise, it sits quietly and leaves the communication channel free.

For example, if traffic stalls at an interchange, the controller box could alert authorities that it suspects an accident. If conditions are fine, no data are sent.

“With this approach, no news is good news,” Coifman said.

The approach is more efficient, because the controller boxes only send signals to the control center when absolutely necessary, which reduces communications costs. The transportation authorities would only need to electronically “ping” a quiet station once in a while, to make sure it was still working.

Between pings, the station would store non-critical data — such as the traffic counts that authorities use to determine if a road needs resurfacing — to be retrieved later.

Traffic detectors are being deployed in larger numbers to address the costs of traffic congestion, Coifman pointed out. He cited a report that estimated the net cost of urban congestion in the United States to be over $63 billion in 2003, almost double the cost of 10 years earlier. The average American also loses 47 hours to traffic delays every year. More than half of those costs — both in time and money — were found to be due to roadway incidents such as accidents.

Coifman hopes that his software can help traffic control centers identify incidents more efficiently, so that people can spend less time in traffic, and recoup some of those costs.

Columbus was a good place to develop the software. Ohio is the seventh-most-populated state in the United States, and nearly two million of its 11 million residents live in the Columbus metropolitan area. The population is growing, and so is the traffic.

Coifman and Mallika tested their software using loop detector data from one of the heaviest-traveled corridors in Columbus: the interchange between Interstates 70 and 71, which cross near the middle of downtown.

Given the signals captured by loop detectors during four known traffic incidents that occurred in 2005, the software accurately identified when — and approximately where — each incident occurred.

Whenever a detector noticed a dramatic decrease in the speed of cars or the number of cars that passed by, it communicated with the traffic management center, which then pinged the neighboring detector stations to perform a kind of triangulation to locate the incident that was affecting traffic.

The engineers found in all four test cases, the software didn’t trigger a data signal to the control center until it had correctly determined that an incident had happened.

On average, the controller boxes in this simulation sent fewer than 10 signals a day — 200 times less than they would normally send.

The engineers also looked at dozens of detector stations over an entire month. Even using fewer than 10 signals a day, the software was able to accurately calculate traffic speeds with greater than 90 percent accuracy, compared to situations when all the data were sent.

“We found that, even though we were sending a lot less information, we could still get the same picture of what was happening on the road,” Coifman said.

In Columbus, his communication scheme would pay off the most for data gathered from rural areas.

That’s because the Ohio Department of Transportation (ODOT) has already reduced its ongoing data transmission costs within Columbus by purchasing its own communication lines; ODOT-owned fiber optic cable now connects most loop detector stations inside the city limits. So the city has virtually unlimited bandwidth to capture data from the most congested areas.

But ODOT doesn’t own data lines outside the city proper, where burgeoning suburbs are pushing out into once-rural areas. There, just as residents have to pay for phone and Internet service to their homes, ODOT has to pay for the use of pre-existing communications lines to get data from its loop detectors.

“Under the current practice of sending all of the data back to the traffic management center, it does not make sense to place instruments at locations that only occasionally see congestion,” Coifman said. But if these distant detector stations sent data to ODOT headquarters only when necessary, communications costs would likely drop.

“When an incident occurs, the authorities could know much quicker, and ODOT would have a more complete picture,” he added. “The same strategy would work in any city.”

This work was partially supported by the National Science Foundation. Other funding came from the California Partners for Advanced Highways and Transit Program of the University of California, in cooperation with the State of California Business, Transportation and Housing Agency, Department of Transportation.

Adapted from materials provided by Ohio State University.

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Self-organized Traffic Light Control System Could Improve Traffic Flow 95 Percent

Taken from http://www.sciencedaily.com

ScienceDaily (Nov. 16, 2007) — Traffic flows account for as much as one-third of global energy consumption. But unconventional changes in managing traffic flow could significantly reduce such waste and lower harmful CO2 emissions, says Dirk Helbing.

Dr. Helbing, Professor of Sociology at the ETH Zurich Chair of Sociology, a specialist in modelling and simulation, supports his claim with a recent study called ‘Efficient Self-Control of Traffic Flows in Urban Networks Using Short-Sighted Anticipation’. Professor Helbing and co-author, Stefan Lämmer of the Institute for Transport and Economics at Dresden University of Technology, propose a self-organized control system for traffic lights that could improve vehicular traffic flow by up to 95 percent. The system relies on the joining of two distinct strategies.

Traffic light system antiquated

The problem, Professor Helbing explains, is that heavy investments in traffic light systems were made in the 1960s and 70s rendering most systems today, due to use, age and technological advancement, antiquated. Forty to fifty years ago when traffic volume was lighter, the main job of traffic light systems was to manage peak traffic during the day or, for example, sporting events. The lights were centrally controlled, and not programmed to adjust in real time. Rather, they were mostly optimised for pre-established assumed situations, meaning for situations that traffic planners had faced in the past.

The disadvantage of this strategy, especially today, is that the more traffic lights there are to coordinate, the more difficult it is to optimize control of the lights. Why? The dilemma is well-known: the larger the number of nodes, or lights, in a system the more computation is necessary until finally computational time “explodes”. “Even for normal-sized cities, super computers are just not fast enough to compute all of the different options that exist for controlling traffic lights. So the number of choices actually considered by the optimization program is significantly reduced,” says Professor Helbing.

Most traffic lights, therefore, continue to be programmed offline, regardless of the realities of the road. Unfortunately, “the variation in the number of vehicles that queue up at a traffic light at any minute of the day is huge,” Professor Helbing says. None of this variation is considered when optimizing for typical Monday or Friday traffic volume curves. “You are optimizing for a situation that basically is true on average but that is never true for any single day or minute: essentially for a situation that never exists. Plus, even adaptive traffic lights in modern control schemes are usually restricted to a variation of cycle-based control.”

One strategy is not enough

Professor Helbing and Stefan Lämmer propose a decentralized system instead that would make travel time more predictable, though traffic light sequence less so. First, the researchers tried to optimize the flow of traffic at one light of an intersection. This localized approach worked well as long as traffic flow through the intersection was not too high. Once volume rose, however, locally programmed lights did not clear traffic off of side roads fast enough and led to back-ups at other intersections. Professor Helbing concluded “On its own, this optimizing strategy was worse than traffic light controls already in place.”

Another component, a stabilizing strategy, was then studied. This strategy cleared traffic when it reached a critical threshold, but it was inconsistent with travel time minimization. Unlike the optimization strategy, the stabilizing strategy performed poorly at all volumes. On its own, it too could not compete with today’s traffic light control systems.

However, “it turns out that the two strategies properly combined perform better than today’s traffic light controls at all traffic volumes. So the combination of two inferior strategies can perform much better – if we do it right,” Professor Helbing says.

Simulation tests show the combined strategies work well. With non-periodic – not cyclically repeated – traffic lights releasing long traffic queues, travel time even becomes more predictable. Flow is kept stable, fuel consumption and emissions are reduced.

Succes depends on motorists

However, the success of the new system will depend on how motorists react, Professor Helbing points out. Drivers are used to the present cycle of traffic lights and anticipate ‘their turn’ to enter an intersection. The combined strategy would disrupt such expectations: if the traffic load is heavy in one direction, that road will be served two times, while others will be served only once. To support driver acceptance and avoid undesirable side effects, such as increased frustration or even accidents, any new traffic control system would need government support and funding by way of a well-publicised awareness campaign directed to the general public during the system’s introductory phase.

In Asian countries, where infrastructure is still being built, is where Professor Helbing thinks investment in the combined strategies might first take place. In Europe the “pain and pressure for change may still not be great enough”. In the end, cost will be a determining factor. The new technologies will have to show that they are cheaper to run than the present system.

Testings ahead

The need to lower CO2 emissions could, however, accelerate the development, suggests Professor Helbing. “You have to decide whether it is necessary to force people to use their cars less, or if the same goals can be achieved through coordinating traffic flows better. If the answer is coordination, then let’s go for the better technology.”

Politicians need to be informed of the options. And the traffic light systems themselves must now be tested through practical application. Professor Helbing is nonetheless optimistic that they will out-perform the systems of today. “What we don’t know is how big an advantage the news systems will be. But all the facts point to decentralised traffic control. This will be the paradigm of the future.”

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Method Uses ‘Bluetooth’ To Track Travel Time For Vehicles, Pedestrians

From http://www.sciencedaily.com

ScienceDaily ( May 28, 2008 ) — Engineers have created a method that uses pervasive Bluetooth signals from cell phones and other wireless devices to constantly update how long it takes vehicles and pedestrians to travel from one point to another.

The method envisioned by engineers at the Indiana Department of Transportation represents a potentially low-cost leap in technology to provide information for everything from the speed of the morning commute to the sluggishness of airport security lines.

“This is incredibly valuable information that could be used for many purposes, including better traffic signal timing and management of construction work zones to reduce congestion, as well as real-time traffic information for motorists,” said Darcy Bullock, a professor of civil engineering at Purdue University. “Now we have a way to measure how slow traffic is on a given stretch of road or how long it’s taking people to get through airport security at a given concourse and time of day.”

Bullock is developing the method with Jason S. Wasson and James R. Sturdevant, engineers from the Indiana Department of Transportation.

“We came up with the idea at INDOT and developed the prototype this year from off-the-shelf hardware,” Wasson said.

The method picks up the identifying “addresses” from Bluetooth devices in consumer electronics. Because each device has its own distinct digital signature, its travel time can be tracked by detectors installed at intersections or along highways and other locations.

Travelers could access the travel-time information using the same portable electronic devices that make the system possible.

“Information is a commodity people are aggressively seeking, and this method promises to cost effectively provide information that has never been widely available to travelers,” Bullock said.

Research findings will be detailed in a paper appearing in the June issue of the ITE Journal, published by the Institute of Transportation Engineers. The paper was written by Wasson, Sturdevant and Bullock.

Bluetooth technology connects and exchanges information for cell phone hands-free headsets, wireless keyboards, Internet access for personal digital assistants, and wireless networks for laptops and personal computers. The new travel-time estimation procedures detect and record “media access control,” or MAC identification signals, every time a Bluetooth device passes a detector.

“It gives you quantitative 24-hour feedback on traffic flow, information we can use for design and operation decisions,” Wasson said. “Agencies need quantitative data so they can make informed decisions about how to allocate resources and how well design changes are working.”

Data from such a system would provide not only information about short-term factors such as congestion from construction work zones, but also long-term trends requiring design changes, Sturdevant said.

The researchers tested the method on sections of Interstate 65, Interstate 465 and roads in and around Indianapolis, tracking 1.2 percent of the average daily traffic on specific routes.

“That’s important because it means basically every hundredth vehicle is tracked, so the travel-time information is accurate and updated,” Bullock said. “With improved antenna mounting we expect to do even better.”

Pedestrian walking speeds also could be tracked to learn how long it takes people to negotiate airports and other facilities.

Future work may involve expanding the research to additional sections of roadways. The researchers have filed a patent on the method, and the basic technology is available commercially to create the tracking system, Bullock said.

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