Detecting accidents in motorsports by using anomaly detection

A system for detecting accidents in motorsports, the system comprising at least one processor configured to:

• obtain, in real-time, measurement data from measurement units incorporated in or attached to a plurality of vehicles, the measurement data comprising a plurality of data points, each of the plurality of data points comprising a value for each of a plurality of variables,
• recursively partition the plurality of data points into a set of binary trees by determining a plurality of random subsets of the plurality of data points and building a binary tree for each respective subset of the plurality of random subsets, the data points of the respective subset being included as external nodes in a respective binary tree corresponding to the respective subset, each of the binary trees further including internal nodes, each of the internal nodes having a first subtree and a second subtree,
• wherein each remaining data point of a set of remaining data points of the respective subset is assigned to the first subtree or the second subtree based on which side of a hyperplane the remaining data point lies, the hyperplane being a hyperplane in an N-dimensional representation of the plurality of data points, each of the N dimensions corresponding to one of the plurality of variables, an N-dimensional slope vector of the hyperplane being randomly selected and each coordinate value of an N-dimensional intercept point of the hyperplane being determined by selecting a variable corresponding to a respective coordinate, determining an interval where a distance between values of the variable of consecutive data points of the remaining data points is maximal, and selecting a value for the respective coordinate on the interval,
• determine an average tree depth of the set of binary trees,
• determine, for each respective data point of the plurality of data points, a path length between an external node of a binary tree of the set of binary trees and a root node of the binary tree, the external node being associated with the respective data point,
• determine, for each respective data point, an anomaly score based on the path length determined for the respective data point and further based on the average tree depth,
• detect, in real-time, based on the anomaly scores, whether any of the plurality of data points corresponds to an anomaly, and
• generating an output signal reflecting a detected accident based on one or more detected anomalies by transmitting a control signal to one or more vehicles to activate a steering-assist function and/or a brake-assist function in the one or more vehicles to assist one or more drivers of the one or more vehicles to avoid the detected accident.

A method of detecting accidents in motorsports, the method comprising:

• obtaining measurement data from measurement units incorporated in or attached to a plurality of vehicles in real-time, the measurement data comprising a plurality of data points, each of the plurality of data points comprising a value for each of a plurality of variables;
• recursively partitioning the plurality of data points into a set of binary trees by determining a plurality of random subsets of the plurality of data points and building a binary tree for each respective subset of the plurality of random subsets, the data points of the respective subset being included as external nodes in a respective binary tree corresponding to the respective subset, each of the binary trees further including internal nodes, each of the internal nodes having a first subtree and a second subtree,
• wherein each remaining data point of a set of remaining data points of the respective subset is assigned to the first subtree or the second subtree based on which side of a hyperplane the remaining data point lies, the hyperplane being a hyperplane in an N-dimensional representation of the plurality of data points, each of the N dimensions corresponding to one of the plurality of variables, an N-dimensional slope vector of the hyperplane being randomly selected and each coordinate value of an N-dimensional intercept point of the hyperplane being determined by selecting a variable corresponding to a respective coordinate, determining an interval where a distance between values of the variable of consecutive data points of the remaining data points is maximal, and selecting a value for the respective coordinate on the interval;
• determining an average tree depth of the set of binary trees;
• determining, for each respective data point of the plurality of data points, a path length between an external node of a binary tree of the set of binary trees and a root node of the binary tree, the external node being associated with the respective data point;
• determining, for each respective data point, an anomaly score based on the path length determined for the respective data point and further based on the average tree depth;
• detecting, in real-time, based on the anomaly scores, whether any of the plurality of data points corresponds to an anomaly;
• and
• generating an output signal reflecting a detected accident based on one or more detected anomalies by transmitting a control signal to one or more vehicles to activate a steering-assist function and/or a brake-assist function in the one or more vehicles to assist the or more drivers of the one or more vehicles to avoid the detected accident.