Introduction
Are you interested in understanding which road routes are most congested at various times and days of the year? Do you need to investigate trends or variability in travel time along chosen routes?
Data from trucks (telematics) provides time and location information at regular polling intervals, which allows us to measure changes in travel time on road segments and quantify congestion along key freight routes.
Date range: 1/01/2019 - 30/06/2021
This interactive is currently under maintenance and coming soon.
About the data
This interactive map compares the fastest observed truck journey (typically overnight) to equivalent trips at any given hour to determine time lost due to congestion.
Underlying this visualisation is telematics data sourced from BITRE and Transport Certification Australia (TCA). This map calculates peak congestion as the slowest time taken for a truck to drive through the road segment compared to the time taken in uncongested conditions. A score of 1.0 means the time taken to traverse the road segment is the same as the free-flow speed. A score of 1.5 means it takes 50 per cent longer to travel the road segment compared to free-flow. Congestion scores are based on the roads within the Australian Bureau of Statistics (ABS) Greater Capital City Statistical Area boundaries.
Due to the small sample size, this visualisation is indicative and not yet suitable for decision-making. We are currently working to increase the sample size and reliability of this data. With a larger sample size, this type of visualisation could be used to identify patterns and trends to highlight routes that may be more congested than others. It could also improve understanding to inform investment planning, if industry participation grows and more trucks can be added to the sample.
Limitations
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Two separate data samples were combined to create this visualisation: BITRE data of 5,000 heavy vehicles reporting monthly between January 2019 to June 2021; and TCA data of 6,700 heavy vehicles travelling between July 2019 and June 2020. We are currently working to expand our data collection to increase our confidence in this product.
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The de-identification process involves aggregating data either by road segment, time and heavy vehicle type. Road segments with fewer than ten vehicle movements are reported as having '1-10 trips'.
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The number of heavy vehicles in the telematics datasets are small compared to the total number on the road network and hence not necessarily representative of movements of the broader truck fleet. Despite this, measured truck speeds will generally provide reliable measures of broader traffic speeds experienced by network users across most network segments (with the notable exceptions of steeper gradient and/or tightly curved road segments).
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There is likely a small proportion of duplicated trucks across the BITRE and TCA datasets.
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The telematics data doesn't include information of the nature of the freight being moved and includes journeys made by trucks which might be empty as well as where trucks are being repositioned.
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The TCA data has a small number of heavy vehicles which don't move freight, e.g. concrete pumps and cranes.
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There are other ways to calculate congestion, free-flow speeds could be set equal to the posted speed limit on each road segment. However, posted speed limits are not currently available digitally for all roads in Australia.
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Some truck operators are interested in helping their customers understand the impact of congestion on their operations, and encourage greater use of freight transport services outside congested periods. This would assist with fleet optimisation, with trucks spending less time in congestion. Further consultation with industry will help refine the 'congestion measures'.
Feedback
The NFDH is working to increase its partnership with industry to collect and include more varied truck telematics data. Please Contact the NFDH team If you are interested in being a part of our project, have any questions or suggestions for improving this interactive. All feedback is appreciated.