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Until recently, most data about cars and traffic was collected solely using external hardware:
One of the most common forms of plug-in devices that collect vehicle analytics are OBD Devices.
Initially, most cars relied on the installation of On-Board Diagnostic Devices (OBDs). OBDs are plug-in diagnostic or telematics tools that gather information generated by the car’s sensors and Engine Control Unit; your car’s ‘brain’. It’s often used by car technicians to diagnose issues and analyse data that helps in the maintenance and repair of a vehicle. They were first introduced by Volkswagon in the 1960’s.
OBDs form an essential part of vehicle telematics and fleet management. They collected data relating to:
Native connect refers to vehicles that have their own ‘native’ connectivity (i.e. a connection through an embedded “SIM”, included during the manufacturing of the vehicle). It provides an alternative to other hardware-based approaches, including OBDs. It’s used to offer a broad range of online services that can be seamlessly ported inside and outside the vehicle, including streaming the information gathered from internal sensors via the cloud, back to the manufacturer. Native Connect leverages what is being termed ‘Software-defined vehicles’.
Software-Defined Vehicles are vehicles that are defined by their software rather than their hardware. Their features and functions are enabled via software or over-the-air updates that allow for the constant transformation of the car, without changing the exterior. That is, car manufacturers are increasingly becoming defined by their software and the capabilities this software enables rather than the physical car itself: driver assistance systems, infotainment, keyless entry, app control, and unique value offerings.
The biggest challenges facing hardware-based approaches to data collection are cost and scale. It’s impossible to cover every single road because the hardware requirements would be too great, too expensive, a lot of manual processing, and/or too difficult to scale outside of smaller privately owned vehicle fleets.
A natively connected vehicle overcomes these challenges because it does not require additional hardware such as cameras, phones, OBDs, or other telematics devices. The vehicle becomes a hub that is defined by it's software, supporting and communicating with several third-party services inside and outside the vehicle, including other vehicles and infrastructure.
Connected vehicles can provide a number of data variants depending on the make and model of a car and whether the data is anonymous aggregated data or identifiable data.
Most connected vehicle data is anonymised and aggregated to provide insights into trends and aggregate behavioural patterns. Aggregated data variants include:
Identifiable data is data that can be traced back to an individual, usually via their vehicle’s Vehicle Identification Number (VIN). A VIN is a unique identifier for each individual car, like a fingerprint. Data that can be linked back to a person’s identity, like a VIN, requires explicit unambiguous consent from the owner before organisations can access or use it.
You can explore more about these different data types and how they are applied on real-life projects on our Compass Learning Hub
Connected Vehicle data differs from data collected from mobile phones, cameras, and other methods in a few ways:
Each connected vehicle can have upwards of 60 sensors depending on the make and model. There can be more than 10 sensors inside the car’s engine alone. Most sensors fall under a few different categories, relating to the function they serve. Here are a few groups:
Some common sensors and their functions include:
Connected vehicle data can add value in a number of ways
Connected vehicle data can be used as leading indicators and identifying trends before they become severe or impact road users.
Connected vehicle data is incredibly granular. They collect data on everything from battery life, axel movements, location, speed, and heading, to whether the windows are opened or closed.
Connected vehicle data is passively collected as drivers drive around road networks, all the time, across virtually every road.
Connected Vehicles provide opportunities to scale. The number of connected vehicles on our roads globally is increasing every year. More connected vehicles on roads mean a greater number of vehicles across different locations to draw data from.
Data coverage is dynamic across different geographical areas. It varies based on a few factors, including:
Generally, only a subset of data is collected on any road at any given time as not all cars on the road are connected cars. A common myth is that you need 100% of all vehicles to gain any insight from connected car data. In reality, no method of traffic data collection will provide 100% coverage because even most hardware-based collection methods can only collect data during set periods of time, or are set up temporarily. For example, manual traffic counts will only count the number of cars at a specific location for a set period of time. Similarly, not all cars have OBD devices installed.