With inaccurate data, road users, traffic professionals, and agencies suffer.
When your data is inaccurate, your agency is reactive, instead of proactive. Since your data isn’t actually showing where your roadways are congested and unsafe, you don’t know where your biggest problems are. Instead of being able to identify these conditions immediately and addressing them before they impact road users, you’re only aware of these pain points after they cause an issue, and you’re relying on citizen complaints and time-consuming fieldwork.
When your data is inaccurate, it’s impossible to track your project’s ROI and to manage traffic at scale. You have no way of knowing whether the changes you made worked, and, if they did, why.
When your data is inaccurate, your AI and automated solutions won’t work. Even a perfect model won’t produce usable results if the data input into it isn’t usable.
When your data is inaccurate, your road users will continue to encounter congested and unsafe roadways, causing massive liabilities for agencies. Preventable crashes, fatalities, delays, emissions, and inequities will keep occurring.