On optimal recovery from terminal understeer

Klomp, Matthijs; Lidberg, Mathias R; Gordon, Timothy

doi:10.1177/0954407013511796

Cited by 23 publications

(33 citation statements)

References 7 publications

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“…Depending on the type of path constraint under consideration, different options exist to ensure path constraints are satisfied. If the vehicle is at risk of violating the outer road boundary, the method presented in [29] can be used to minimise off-tracking. On the other hand, if the vehicle is close to violating the inner road boundary, a constraint can be added in the MHA optimisation that limits the maximum lateral force that can be generated by the tyres.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Note that in the case of offtracking, it might be infeasible in some cases to stay within the outer road edge while crossing the bullet vehicle path due to overspeeding or low friction or both. The feasibility of staying within the road boundary can be checked using a similar optimal control based approach as outlined in [29]. If it is seen that staying within the road boundaries is infeasible, then either the intervention can be stopped/not started or the objective of the intervention can be changed to minimising offtracking instead.…”

Section: Dealing With Path Constraintsmentioning

confidence: 99%

“…If it is seen that staying within the road boundaries is infeasible, then either the intervention can be stopped/not started or the objective of the intervention can be changed to minimising offtracking instead. The derivation of an optimal global force angle reference to minimise offtracking is outlined in [29].…”

Section: Dealing With Path Constraintsmentioning

confidence: 99%

See 2 more Smart Citations

Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion

Arikere

Yang

Klomp

2018

Vehicle System Dynamics

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Vehicle System Dynamics paperV5 Collision avoidance at intersections involving a host vehicle turning left across the path of an oncoming vehicle (Left Turn Across Path/Opposite Direction or LTAP/OD) have been studied in the past, but mostly using simplified interventions and rarely considering the possibility of crossing the intersection ahead of a bullet vehicle. Such a scenario where the driver preference is to avoid a collision by crossing the intersection ahead of a bullet vehicle is considered in this work. The optimal vehicle motion for collision avoidance in this scenario is determined analytically using a particle model within an optimal control framework. The optimal manoeuvres are then verified through numerical optimisations using a two-track vehicle model, where it was seen that the wheel forces followed the analytical global force angle result independently of the other wheels. A Modified Hamiltonian Algorithm (MHA) controller for collision avoidance that uses the analytical optimal control solution is then implemented and tested in CarMaker simulations using a validated Volvo XC90 vehicle model. Simulation results showed that collision risk can be significantly reduced in this scenario using the proposed controller, and that more benefit can be expected in scenarios that require larger speed changes.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Dealing With Path Constraintsmentioning

confidence: 99%

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Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion

Arikere

Yang

Klomp

2018

Vehicle System Dynamics

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“…Though MPC have been proven to be effective in many non-critical applications, it is interesting to consider how MPC performs in vehicle control at the limits of friction. In the application of road departure prevention, the problem is close to earlier investigations mentioned above [8][9][10] ; here we propose using MPC to address the same scenario. This is based on the understanding that MPC, once tested in the situation of quasi-static braking and cornering, it may be easily extended to other, more complex scenarios.…”

Section: Incorporating a Receding Horizon Technique Mpc Canmentioning

confidence: 78%

“…Equations (9) and (10) represent the system dynamics while equation (11) defines the incremental inputs to be used in the MPC scheme. Then equations (12), (13) and (14) capture the input and state constraints.…”

Section: The Mpc Formulationmentioning

confidence: 99%

Vehicle optimal road departure prevention via model predictive control

Yuan

Gao

Gordon

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

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This article addresses the problem of road departure prevention using integrated brake control. The scenario\ud considered is when a high speed vehicle leaves the highway on a curve and enters the shoulder or another lane,\ud due to excessive speed, or where the friction of the road drops due to adverse weather conditions. In such a scenario,\ud the vehicle speed is too high for the available tyre-road friction and road departure is inevitable; however, its effect can\ud be minimized with an optimal braking strategy. To achieve online implementation, the task is formulated as a receding\ud horizon optimization problem and solved in a linear model predictive control (MPC) framework. In this formulation, a\ud nonlinear tire model is adopted in order to work properly at the friction limits. The optimization results are close to\ud those obtained previously using a particle model optimization, PPR, coupled to a control algorithm, MHA, specifically\ud designed to operate at the vehicle friction limits. This shows the MPC formulation may equally be effective for vehicle\ud control at the friction limits. The major difference here, compared to the earlier PPR/MHA control formulation, is that\ud the proposed MPC strategy directly generates an optimal brake sequence, while PPR provides an optimal reference\ud first, then MHA responds to the reference to give closed-loop actuator control. The presented MPC approach has the\ud potential to be used in futur

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