A method for defining a classifier for use in defining a vehicle way, which method being carried out by a traffic analytics system, the traffic analytics system comprising a processing resource, a data store and a network interface, the processing resource and the data store being communicatively coupled and arranged for carrying out the operations of the method, and the network interface being interoperable with a communication network and configured for obtaining historical vehicle data from network components, which historical vehicle data, once received, being stored as subsets of raw vehicle data by the data store in a database of the traffic analytics system; the method comprising: identifying a plurality of sample vehicle ways (802a - 802f); for each sample vehicle way of the plurality of sample vehicle ways (802a - 802f), defining a plurality of zones (908a - 908f; 1010a - 1010f), with each zone thereof comprising a corresponding sample vehicle way and each comprising a plurality of contiguous subzones (910a - 910f; 1011a - 1011f), with each subzone thereof having boundaries defined in accordance with a geographic coordinate system presenting a unique two-dimensional space on the Earth's surface; selecting from historical vehicle data indicative of vehicle operating conditions for a plurality of corresponding vehicles, a subset of raw vehicle data associated with each of the plurality of zones (908a - 908f; 1010a - 1010f); for each of the plurality of contiguous subzones (910a - 910f; 1011a - 1011f) of each zone of the plurality of zones (908a - 908f; 1010a - 1010f), extracting a plurality of features from the subset of raw vehicle data; for each of the plurality of contiguous subzones (910a - 910f; 1011a - 1011f) of each zone of the plurality of zones (908a - 908f; 1010a - 1010f), generating training data comprising the plurality of features for each contiguous subzone and an indication of the class of each subzone; and using at least one machine learning technique with the training data to define a classifier for classifying a subzone as one of a vehicle way class or not-vehicle way class. the traffic analytics system comprising a processing resource, a data store and a network interface, the processing resource and the data store being communicatively coupled and arranged for carrying out the operations of the method, and the network interface being interoperable with a communication network and configured for obtaining historical vehicle data from network components, which historical vehicle data, once received, being stored as subsets of raw vehicle data by the data store in a database of the traffic analytics system; the method comprising: identifying a plurality of sample vehicle ways (802a - 802f); for each sample vehicle way of the plurality of sample vehicle ways (802a - 802f), defining a plurality of zones (908a - 908f; 1010a - 1010f), with each zone thereof comprising a corresponding sample vehicle way and each comprising a plurality of contiguous subzones (910a - 910f; 1011a - 1011f), with each subzone thereof having boundaries defined in accordance with a geographic coordinate system presenting a unique two-dimensional space on the Earth's surface; selecting from historical vehicle data indicative of vehicle operating conditions for a plurality of corresponding vehicles, a subset of raw vehicle data associated with each of the plurality of zones (908a - 908f; 1010a - 1010f); for each of the plurality of contiguous subzones (910a - 910f; 1011a - 1011f) of each zone of the plurality of zones (908a - 908f; 1010a - 1010f), extracting a plurality of features from the subset of raw vehicle data; for each of the plurality of contiguous subzones (910a - 910f; 1011a - 1011f) of each zone of the plurality of zones (908a - 908f; 1010a - 1010f), generating training data comprising the plurality of features for each contiguous subzone and an indication of the class of each subzone; and using at least one machine learning technique with the training data to define a classifier for classifying a subzone as one of a vehicle way class or not-vehicle way class. identifying a plurality of sample vehicle ways (802a - 802f); for each sample vehicle way of the plurality of sample vehicle ways (802a - 802f), defining a plurality of zones (908a - 908f; 1010a - 1010f), with each zone thereof comprising a corresponding sample vehicle way and each comprising a plurality of contiguous subzones (910a - 910f; 1011a - 1011f), with each subzone thereof having boundaries defined in accordance with a geographic coordinate system presenting a unique two-dimensional space on the Earth's surface; selecting from historical vehicle data indicative of vehicle operating conditions for a plurality of corresponding vehicles, a subset of raw vehicle data associated with each of the plurality of zones (908a - 908f; 1010a - 1010f); for each of the plurality of contiguous subzones (910a - 910f; 1011a - 1011f) of each zone of the plurality of zones (908a - 908f; 1010a - 1010f), extracting a plurality of features from the subset of raw vehicle data; for each of the plurality of contiguous subzones (910a - 910f; 1011a - 1011f) of each zone of the plurality of zones (908a - 908f; 1010a - 1010f), generating training data comprising the plurality of features for each contiguous subzone and an indication of the class of each subzone; and using at least one machine learning technique with the training data to define a classifier for classifying a subzone as one of a vehicle way class or not-vehicle way class.