## 3 Data Collection
### Field Speed and Flow Data  
As mentioned, the real-world traffic speed and traffic volume data used in this research were provided by Intelematics INSIGHT Studio, Australia [62]. The data were collected from sections on Hoddle Street, including traffic signals at intersections along the street in Melbourne, Australia (see Figure 1). The availability of signal control schemes at intersections in the study area makes it more challenging to provide accurate prediction results for both traffic volume and speed. This is because of the highly fluctuating traffic demands distributed at each section of the road for different time horizons.  
The study area included a 14-km section of Hoddle Street, an arterial road bounded by Citylink in Richmond (Northbound) and Eastern Freeway in Fitzroy (Southbound), that runs through a highly urbanised area with a speed limit of 70 km/h along the section. For this study, all sections of Hoddle Street along this corridor were analysed, as illustrated in Figure 2.  
The dataset used in this study included speed and volume observations collected for a period of 12 months. The data were aggregated in 15-min intervals across all lanes, covered 24-h durations, weekday and weekend traffic, and represented different traffic conditions (free flow and congested conditions).  
Hoddle Street is a major arterial road known as one of the busiest and most congested roads in Melbourne. The road consists of multiple lanes in each direction, with several signalised and non-signalised intersections. It serves as a key corridor connecting various inner and outer suburbs, and its traffic flow is influenced by varying conditions throughout the day, including peak-hour congestion and weekend traffic patterns. These road characteristics, including lane configurations and intersection types, were factored into the model to improve the accuracy of the traffic flow and speed predictions.  
For this study, traffic flow is defined as the number of vehicles passing a specific point per unit of time, averaged across all lanes within the study sections. This encompasses both peak and off-peak hours. The data collected for this study span from 12 AM on 1 June 2020 to 11:45 PM on 31 May 2021, with observations taken in 15-min intervals. While peak hours may vary depending on daily traffic patterns, especially given the fluctuating traffic conditions during and post-COVID, we did not specifically define peak hours in this study. The general categorisation of traffic flow as either peak or off-peak was based on observed patterns over the 12 months. Therefore, evaluating peak hours is not central to the focus of this research. For transparency, the raw data used in this study, including time, date, and traffic flow observations, can be made available if necessary.  
Machine learning models require large amounts of data that are needed for model development. The data are typically divided into a training dataset used for model calibration and a testing dataset used for model verification. The validity of the model is tested on an independent dataset not used in model training, referred to as the testing dataset. These data sets, as used in this study, are shown in Table 1.  
Figure 1: The Hoddle Street section used for collecting datasets [63]. Note: The red arrow represents the Northbound direction towards the Eastern Freeway and the yellow arrow represents the Southbound direction towards Citylink.