All datasets have their strengths and weaknesses. While we'd all love to have a single, perfect dataset that enables us to make confident and accurate decisions, in practice, weaknesses are only an issue if we've used the wrong dataset for the wrong purpose.
This article provides a breakdown of common use cases and the appropriate datasets. With this knowledge, you will be able to make informed decisions beyond this list, applying the same logic.
Use Case | Recommended Dataset | Why |
I need traffic volume to inform road design | Tube counts (or similar hardware-based survey) | Tube counts provide a cost-effective way to get the count in a fixed location.
You already know the location of interest.
Crowdsourced traffic information from TomTom only provides a sample of the total volume, and scaling these values is difficult to do accurately. |
I want to understand where and when congestion occurs | Real-time traffic monitoring with floating vehicle data | Capture rich traffic data on journey times, delays and speeds via a floating vehicle provider like TomTom or Google gives you the ability to monitor a large area constantly, unlike manual traffic surveys.
Continuous monitoring of a wider area captures information on:
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I need to understand where and when queuing is occurring around my worksite | Queue monitoring with floating vehicle data | This approach provides an accurate estimate of queue lengths and can be run 24/7 on many routes cost-effectively.
The data produced will help those who understand when, where and how significant queuing issues are.
A similar deployment with hardware is typically cost-prohibitive, as each device is likely to cost $10-20k installed and can only capture queue information for approximately 50 meters. |
I have a hard contractual queue limit as part of a content process | Queue monitoring using machine vision or hardware | In this scenario, you know the exact location that needs to be captured, and it is important to have high-fidelity data on exact queuing instances and duration.
For this use case, machine vision cameras should be used.
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I need to know volumes/journey times for a period no monitoring was set up | SCATS/TomTom or other historical data | Where signals data like SCATS is present, it provides an effective record of volumes through a site.
If journey time is needed, or no volume history is available, other data services like TomTom can help fill the gap:
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I need to understand speeds that drivers travel through a road segment | Tube/camera surveys or TomTom | Traffic surveys can capture speeds that drivers travel through an area. If cost or time constraints rule this option out, TomTom can provide historic speeds that a representative sample have travelled through an area. Mooven can support your team with speed profiles to understand driver behaviour and safety risks in your next worksite. |