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Customer Stories

Traffic Anomalies No Longer a Mystery Thanks to Drivers’ Bluetooth Devices

Thanks to years of collecting traffic data, based on the movement of Bluetooth devices, Aarhus municipality in Denmark can now see the effects of construction projects, roadwork, traffic accidents and faulty traffic lights.

[/vc_column_text][/vc_column][vc_column width=”1/6″][/vc_column][/vc_row][vc_row][vc_column width=”1/6″][/vc_column][vc_column width=”2/3″][vc_column_text css_animation=”none”]Aarhus, Denmark’s second-largest city, has been using Veovo Bluetooth sensors and Traffic Management solution for several years to collect traffic information, based on the movement of road users´ Bluetooth devices. The sensors, placed on the entire road network, including adjacent highways, provides the city with both real-time and historical traffic information, including driving times, speed, dwell times and flow.

Besides the benefits of real-time reporting, which enables the city to gain in-depth insight and understanding of current road density, flow, and formation of queues, and share traffic information with road users on signs, the historical data is now being used to detect driving time anomalies. Effectively, this means that the city can pinpoint road sections and intersections where driving times deviate from the norm as a result of construction projects, incidents, roadwork, faulty traffic lights and other factors.

Traffic Management data provides a thorough comparison of current vs typical driving times, minute-by-minute throughout the day. The standard driving times, which are continuously updated, are based on various type of days (weekdays, weekend, vacation season or not) and time of day.

If driving times deviate from the typical driving time, the system automatically raises a flag. As the system logs and visualises all deviations, traffic engineers can create historical performance and reliability reports based on deviations from the norm. The city is provided with an overview of the current situation and tendencies over time, to initiate countermeasures.

Alarm visualisation can be displayed in various ways; for example, over time and for each road section, based on intersection errors, or the impact of a major traffic accident. It can show the scattering effect that can cause both deterioration and improvement of driving times – depending on what alternative routes motorists choose to take advantage of – or if road users are prevented from reaching parts of roads.

“The benefits we have gained from the solution since implementation are very significant. We now discover errors and irregularities that we would not have a chance to see otherwise. In addition, it is extremely educational and easy accessible to study how the incidents of various kinds influence the road network,” says Asbjørn Halskov-Sørensen, ITS Project Manager at Aarhus Municipality.

Aarhus has around 230 intersections regulated by traffic lights. If just one of these traffic signal installations is not working optimally or breaks down, it directly affects traffic flow in a large surrounding area.

While the many traffic light installations do have built-in alarm systems that warn about mechanical errors, such as broken bulbs, programming errors and communication trouble in the connection to other linked systems, these alarm systems are “dumb”, unable to report on the consequences of the errors or traffic regulation programs. The alarm systems cannot see whether a mistake is causing queue formation or longer driving times for the road users, and they cannot see whether the amount of traffic has changed over time, calling for a change to the traffic light system program. It means, for example, that sudden or continuous traffic increase could result in significant gridlock, without warning.

To meet this challenge, Aarhus opted to turn the problem on its head and to see the traffic flow from the road users’ perspective. Since the Bluetooth sensors measure both short and long distances, as well as the turn flow movements through intersections, and groups of traffic lights in the road network, the solution provides an objective, measurable expression of road users’ driving experience. Now, issues are detected, enabling the city to ensure that traffic lights are working correctly and will be programmed optimally with excellent traffic management, Aarhus is ready for any issues that should arise.

The solution has quickly become an indispensable supplement to the existing surveillance system for the Aarhus traffic light installations. Various unfavourable situations have proven to be detectable with direct reference to driving time data, such as:

[icon name=”plus” class=”” unprefixed_class=””]  Errors caused by incorrect activation of traffic light programs, such as the rush hour program

[icon name=”plus” class=”” unprefixed_class=””]  Missing or lengthy activation of turn phases

[icon name=”plus” class=”” unprefixed_class=””]  Defective surveillance systems

[icon name=”plus” class=”” unprefixed_class=””]  Human error, such as forgetting to switch back to the standard program following maintenance

[icon name=”plus” class=”” unprefixed_class=””]  Incorrect timing of coordination chains (“green wave”)

All these factors play a crucial role in identifying traffic signal installations that need optimisation, but also regarding what needs to be optimised and, ultimately, whether the efforts had the intended effect.

“The data is generally used for much more than just being able to measure the effect of signal optimisation and roadwork/construction projects, but this is clearly an important part of its application,” says Asbjørn Halskov-Sørensen. “Ultimately, the data contributes to an improved economy and a better environment through reduced driving times and fuel consumption, and thus reductions in greenhouse gas emissions from vehicles.”

With the new approach of managing traffic, Aarhus now enjoys a full overview and understanding of all dynamics of its traffic. Since the city has full access to all the raw data, unlike similar solutions, the plan is to combine the solution with existing surveillance systems. It would enable the city to qualify the individual system’s alarms to an even greater extent.

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