This paper reports a novel intersection support (IS) system for motorcycles developed through the SAFERIDER project (www.saferider-eu.org). The IS function described is built on a receding horizon approach that is designed for a set of predefined intersection scenarios. In the receding horizon scheme, a nonlinear optimal control problem is repetitively solved in real time, yielding a reference motion plan. The initial value of the longitudinal jerk (control input) of each plan is used as a measure of the correction that the rider has to apply to conform to an optimal-safe maneuver. This technique has the advantage of yielding a homogenous measure of the threat independent of the scenario, and it is directly linked with the control variable that the rider should use to accordingly change the vehicle’s longitudinal dynamics. Additionally, the receding horizon approach naturally accommodates road geometry and constraint attributes, motorcycle dynamics, rider input, and riding styles. Warning feedback is given to the rider by an appropriate combination of human–machine interface elements, such as the haptic throttle, the vibrating glove, and the visual display. This paper explains the IS concept, discusses the implementation aspects of the proposed receding horizon approach, and presents the results of pilot tests conducted on a top-of-the-range riding simulator.

Intersection Support System for Powered Two-Wheeled Vehicles: Threat Assessment Based on a Receding Horizon Approach

LOT, ROBERTO;ROTA, STEFANO;
2012

Abstract

This paper reports a novel intersection support (IS) system for motorcycles developed through the SAFERIDER project (www.saferider-eu.org). The IS function described is built on a receding horizon approach that is designed for a set of predefined intersection scenarios. In the receding horizon scheme, a nonlinear optimal control problem is repetitively solved in real time, yielding a reference motion plan. The initial value of the longitudinal jerk (control input) of each plan is used as a measure of the correction that the rider has to apply to conform to an optimal-safe maneuver. This technique has the advantage of yielding a homogenous measure of the threat independent of the scenario, and it is directly linked with the control variable that the rider should use to accordingly change the vehicle’s longitudinal dynamics. Additionally, the receding horizon approach naturally accommodates road geometry and constraint attributes, motorcycle dynamics, rider input, and riding styles. Warning feedback is given to the rider by an appropriate combination of human–machine interface elements, such as the haptic throttle, the vibrating glove, and the visual display. This paper explains the IS concept, discusses the implementation aspects of the proposed receding horizon approach, and presents the results of pilot tests conducted on a top-of-the-range riding simulator.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2518078
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