Investigating vehicle characteristics behaviour for roundabout cornering

The allowable range of speed that a vehicle can tolerate in a constant radius turn is crucial for the development of smart assistance systems. Although the development of advanced system observers has been grown since early days of its introduction, extensive study is required in monitoring the vehicle’s behaviour in the conditions such as variation of vehicle dynamic parameters and terrain type. Autonomous vehicles will fail to judge the parameter of the road cornering due to the safety constraints of the vehicle. Thus, the primary concern of this paper is to study the vehicle’s behaviour for different curvature profiles. A real-time simulation for a typical Sedan is presented to test a constant roundabout turning with a radius of 50 m for this measure. In prior to that, a detailed analysis on the vehicle stability and handling responses are discussed. The vehicle is found to be traveling in a stable region at a speed from 10 to 74 km/h. The vehicle enters a critical area when speed is more than 74 km/h. Therefore, that the allowable range of speed that the vehicle can travel in a 50 m radius turn lies between 10 to 74 km/h. The stability is evaluated by two criterions which are the yaw rate and sideslip angle

Estimation of electric vehicle turning radius through machine learning for roundabout cornering

This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred using machine learning (ML) approaches based on the collected data. A compact electric vehicle model is used to obtain data and measurements of the vehicle states for different sets of road radius. The augmented basic measurements is fed to an Extra Tree Regression to predict the turning radius of the vehicle. The feasibility of the developed algorithm was tested and validated using performance metrics. The results show that the regression accuracy for the turning radius is 99% and can be obtained with sufficient vehicle dynamics information