Real-time Journey Time and Flow Measurement

Understanding who is using the road, where they are going and whether they get there on time is essential for policymakers, traffic managers and drivers alike.

However, the cost of processing this data by hand means that even the most comprehensive survey can still only ever be a snapshot. This constrained timeframe means that any models built from the survey data could end up being based on unusual driver behavior caused by unknown events such as traffic incidents or bad weather.

By placing BlipTrack sensors along the road, it is possible to measure flow and calculate journey times by detecting Bluetooth and Wi-Fi devices in passing vehicles.

With this data traffic managers can monitor the roads in real time, allowing them to detect incidents and congestion in a matter of seconds.

This rapid detection allows traffic managers to respond to situations before they are exacerbated by additional congestion. Always-available congestion and speed monitoring also allows traffic managers to collect data from a far wider range of situations that can then be used to build predictive traffic models.

Journey Time Measurement

Journeytime-illustration1By placing BlipTrack sensors along the road, it is possible to measure and calculate average speed and journey times by detecting Bluetooth and Wi-Fi devices, such as mobile phones, tablets and hands-free installations in passing vehicles.

BlipTrack is able to measure journey times on road segments with parallel train tracks, bus lanes and roads, such as freeway sections with collector lanes.

The raw data from the sensors is encrypted and transferred in real-time via ethernet or mobile broadband to a secure cloud server, where it is extracted and separated.

The devices collected can be filtered and catagorized based on device type, speed, location or historical data.

The results are presented in an online multilingual graphical user interface (GUI), which can be customized to each individual user.

BlipTrack can easily be integrated with existing Traffic Management Systems through various data output facilities and open standard protocols.

BlipTrack ensures privacy by having the individual sensors convert the detected devices into anonymized and encrypted hashes.  This fine-grained approach to privacy allows local authorities to meet the requirements of the Data Protection Act by installing a system that only collects the necessary data while remaining expandable if required in the future.

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Queue Monitoring

Queue-Measurement1BlipTrack´s segment-based incident detection provides detailed real-time journey times, both in the sensor´s coverage and between the sensors. This allows road operators to monitor the entire road segment, unlike traditional point-based solutions with limited coverage.

Journey times between sensors and the number of vehicles are measured 24/7 and if fluctuations exceed pre-set levels, an alarm is raised on the server. Time spent in sensor´s coverage is used as a point-based indication for the flow at the sensor. This data can be used to indicate free-flow or stand-still traffic, and can also be used to trigger alarms.

With data from both measurements, faster and more precise queue warnings can be provided.

With real-time journey time information, BlipTrack is able to provide data for queue warnings via variable message signs, TMC feeds in navigation systems, mobile applications, traffic announcements, and more.

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Origin and Destination Analysis

Origin-Destination-Bubble_1With the BlipTrack Origin and Destination Analysis tool, traffic engineers and managers are able to obtain specific and accurate statistical information about each road user, their dwell time and movement patterns—from the moment they enter an area until they leave, and everywhere in between. This data provides key information on the use of the road network, enabling decision makers to optimize operation of each and every area, day-by-day, hour-by-hour, and minute-by minute, to its best potential.

Road user profile
BlipTrack reviews the flow of each road user to retrieve information about specific patterns based on the visitors movements such as “Start, Via and Exit Point,” “Time and Location” and “Visitor Type” based on sensor placements, routes, frequency and more.

Traffic management are able to extract any combination of data both real-time, and historically, to provide the desired output. The statistical combinations are as general or precise as the management wishes it to be for review and optimization purposes.

The BlipTrack solution provides key information on the use of the road network, enabling decision makers to understand various traffic-related matters, such as the impact of traffic control, weather-related traffic patterns, congestion patterns at roadworks, accidents and events, and driving behavior and patterns in high-density areas. With this information, decision makers are able to evaluate and validate existing traffic models and plan ahead.

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Travel Information

Travel-InformationIn a world where more and more cars fill up already congested roads, the need for providing road users with reliable and accurate travel information is vital.

With data from the BlipTrack solution, traffic operations are able to promote the ability for road users to make informed decisions by providing real-time journey information through VMS signage, websites, mobile applications, TMC feeds in navigation systems, and more.

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Signal Optimization

Intersection_newBy placing sensors between intersections and collecting data from Bluetooth and Wi-Fi devices, the solution is able to accurately detect and record journey times and driving patterns, segment by segment, and in total.

This provides historic data for analyzing high-volume routes and re-time signals to give a more fluent flow of traffic. It also enables real-time feedback to changes in signal programs along with the ability to continuously detect traffic levels and journey times to trigger transitions among programs.

The solution can cover entire cities and road networks, and continuosly map congestion. The data is used to identify where to prioritize expansions and optimizations.

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