Dataset for onboard road-type classification using Machine-Learning Clustering models in a Renault Clio III vehicle

Data repository with the raw and synthesized data of a journal paper under review. The dataset provided is obtained from a Renault Clio III vehicle (model year 2007) by accessing the CAN bus through the OBD‑II port. Table 1 lists all the parameters extracted from the CAN bus, comprising approximately 40,000 data records collected during driving sessions that covered different types of roads, including urban roads, conventional roads, and highways, along a route from the city of Malaga to Cártama in southern Spain, spanning a total distance of 56.8 km. The weather conditions during the data acquisition period featured temperatures ranging between 22 °C and 25 °C and no precipitation in the spring of 2025. Table 1. Extracted signals from the CAN bus of a Renault Clio III vehicle included in the dataset. Description Parameter Value Unit Steering wheel angle SWA 27,545 (left) – 38,116 (right) deg Steering wheel angular velocity SWAV 0 – 32,767 deg/s Revolutions per minute RPM 0 – 8,192 rpm Throttle position Accel 16 (idle) - 252 (full pressed) - Vehicle speed Speed 0 – 655 km/h Travelled distance since ignition Distance 0 – 65,535 m Engine temperature EngTemp 0 – 255 ºC Since the data processing is carried out using clustering algorithms within the framework of Machine Learning (ML) techniques, computed values are incorporated into the dataset to describe the micro‑clusters formed from all points stored in the point buffer retrieved from the CAN bus, together with the macro‑clusters subsequently generated to update the centroid using the information contained in the micro‑cluster buffer. However, the data provided can also be used with other processing techniques in alternative lines of research. The dataset includes the following data files, which contain the parameters listed in Table 1 and incorporate the parameter Time as a sample index to indicate the arrival order of the data samples. Training data is composed of 12 comma-separated values (CSV) files with data collected during the driving sessions, as described in Table 2. Each file includes records for nine parameters that describe their state at each time instant, and whose identifiers are provided in the first row, such as Time, SWA, SWAV, RPM, Accel, Speed, Distance, and EngTemp. Table 2. Training data files used in the study. Name of the data file Number of data records Range of the parameter Time training_s1.csv 706 11 – 363.5 training_s2.csv 1,168 5.5 – 589.99 training_s3.csv 6,137 631.5 – 3,699.5 training_s4.csv 8,668 6.5 – 4,340 training_s5.csv 1,423 103.5 – 814.5 training_s6.csv 2,210 503.5 – 1,608 training_s7.csv 181 11 - 101 training_s8.csv 413 10 – 216 training_s9.csv 5,306 5 – 2657.5 training_s10.csv 1,402 8.5 – 709 training_s11.csv 3,650 13.5 – 1,923 training_s12.csv 5,505 1,679.5 – 4,431.5 Testing data is composed of 11 CSV files with the results of the micro-clustering and macro-clustering processes obtained during the driving sessions using different damping coefficients (DC) of between 36 and 48, as described in Table 3, where the identifiers of the parameters are provided in the first row of each file. The micro-clustering records include the parameter Time, the computed values of each CAN-bus signal for each micro-cluster (Speed, Accel, and SWAV), the assigned macro-cluster (AssignedCluster), and the label applied to the micro-cluster by the experimenter (Label). The same files also contain the macro-clustering results, which consist of the computed centroid position for each macro-cluster (Speed_MC, Accel_MC, and SWAV_MC) and their corresponding identifier (MacroCluster). Table 3. Testing data files used in the study. Name of the data file Number of data records Range of the parameter Time testing_dc_36_s1.csv 454 1 – 426 testing_dc_36_s2.csv 562 2 – 93 testing_dc_36_s3.csv 272 2 – 169 testing_dc_36_s4.csv 219 2 – 136 testing_dc_36_s5.csv 414 4 – 253 testing_dc_48_s1.csv 625 4 – 380 testing_dc_48_s2.csv 278 27 – 196 testing_dc_48_s3.csv 178 12 – 117 testing_dc_48_s4.csv 211 5 – 131 testing_dc_48_s5.csv 126 4 – 81 testing_dc_48_s6.csv 132 2 – 81 “Init.txt” is a configuration file that contains the initial values of the macro-clusters prior to each driving session. Each macro-cluster is initialized with the following values: “C=0” for the identifier, “S=00023” for speed, “A=033” for acceleration, and “SWAV=00359” for steering wheel rotation velocity.