Vehicle Rollover Stability And Path Planning In Adas Using Model Predictive Control

Advanced Driver Assistance Systems (ADAS) have been developed in recent years to significantly improve safety in driving and assist driver’s response in extreme situations in which quick decisions and maneuvers are required. Common features of ADAS in modern vehicles include automatic emergency braking (AEB), lane keeping assistance (LKA), electric stability control (ESC), and adaptive cruise control (ACC). While these features are developed primarily based on sensor fusion, image processing and vehicle kinematics, the importance of vehicle dynamics must not be overlooked to ensure that the vehicle can follow the desired trajectory without inducing any instability. In many extreme situations such as object avoidance, fast maneuvering of vehicles with high center of gravity might result in rollover instability, an event with a high fatality rate. It is thus necessary to incorporate vehicle dynamics into ADAS to improve the robustness of the system in the path planning to avoid collision with other vehicles or objects and prevent vehicle instability. The objectives of this thesis are to examine the efficacy of a vehicle dynamics model in ADAS to simulate rollover and to develop an active controller using Model Predictive Control (MPC) to manipulate the front-wheel steering and four-wheel differential braking forces, which are related to active steering as well as dynamic stability control for collision avoidance. The controller is designed using the model predictive control approach. A four degree-of-freedom vehicle model is simulated and tested in various scenarios. According to simulation results, the vehicle controller by the MPC controller can track the predicted path within error tolerance. The trajectories used in different simulation scenarios are generated by the MPC controller

Rollover prevention and path following of a scaled autonomous vehicle using nonlinear model predictive control

Vehicle safety remains an important topic in the automotive industry due to the large number of vehicle accidents each year. One of the causes of vehicle accidents is due to vehicle instability phenomena. Vehicle instability can occur due to unexpected road profile changes, during full braking, obstacle avoidance or severe manoeuvring. Three main instability phenomena can be distinguished: the yaw-rate instability, the rollover and the jack-knife phenomenon. The main goal of this study is to develop a yaw-rate and rollover stability controller of an Autonomous Scaled Ground Vehicle (ASGV) using Nonlinear Model Predictive Control (NMPC). Open Source Software (OSS) known as Automatic Control and Dynamic Optimisation (ACADO) is used to design and simulate the NMPC controller based on an eight Degree of Freedom (8 DOF) nonlinear vehicle model with Pacejka tire model. Vehicle stability limit were determined using load transfer ratio (LTR). Double lane change (DLC) steering manoeuvres were used to calculate the LTR. The simulation results show that the designed NMPC controller is able to track a given trajectory while preventing the vehicle from rolling over and spinning out by respecting given constraints. A maximum trajectory tracking error of 0.1 meters (on average) is reported. To test robustness of the designed NMPC controller to model mismatch, four simulation scenarios are done. Simulation results show that the controller is robust to model mismatch. To test disturbance rejection capability of the controller, two simulations are performed, with pulse disturbances of 0.02 radians and 0.05 radians. Simulations results show that the controller is able to reject the 0.02 radians disturbance. The controller is not able to reject the 0.05 radians disturbance

An Intelligent Predictive Algorithm for the Anti-Rollover Prevention of Heavy Vehicles for Off-Road Applications

Rollover detection and prevention are among the most critical aspects affecting the stability and safety assessment of heavy vehicles, especially for off-road driving applications. This topic has been studied in the past and analyzed in depth in terms of vehicle modelling and control algorithms design able to prevent the rollover risk. However, it still represents a serious problem for automotive carmakers due to the huge counts among the main causes for traffic accidents. The risk also becomes more challenging to predict for off-road heavy vehicles, for which the incipient rollover might be triggered by external factors, i.e., road irregularities, bank angles as well as by aggressive input from the driver. The recent advances in road profile measurement and estimation systems make road-preview-based algorithms a viable solution for the rollover detection. This paper describes a model-based formulation to analytically evaluate the load transfer dynamics and its variation due to the presence of road perturbations, i.e., road bank angle and irregularities. An algorithm to detect and predict the rollover risk for heavy vehicles is also presented, even in presence of irregular road profiles, with the calculation of the ISO-LTR Predictive Time through the Phase-Plane analysis. Furthermore, the artificial intelligence techniques, based on the recurrent neural network approach, is also presented as a preliminary solution for a realistic implementation of the methodology. The paper finally assess the efficacy of the proposed rollover predictive algorithm by providing numerical results from the simulation of the most severe maneuvers in realistic off-road driving scenarios, also demonstrating its promising predictive capabilities

Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicles Based on Model Predictive Control

Four-wheel independent drive electric vehicle was used as the research object to discuss the lateral stability control algorithm, thus improving vehicle stability under limit conditions. After establishing hierarchical integrated control structure, we designed the yaw moment decision controller based on model predictive control (MPC) theory. Meanwhile, the wheel torque was assigned by minimizing the sum of consumption rates of adhesion coefficients of four tires according to the tire friction ellipse theory. The integrated simulation platform of Carsim and Simulink was established for simulation verification of yaw/rollover stability control algorithm. Then, we finished road experiment verification of real vehicle by integrated control algorithm. The result showed that this control method can achieve the expectation of effective vehicle tracking, significantly improving the lateral stability of vehicle

Multi-Actuated Vehicle Control and Path Planning/Tracking at Handling Limits

The increasing requirements for vehicle safety along with the impressive progress in vehicle actuation technologies have motivated manufacturers to equip vehicles with multiple control actuations that enhance handling and stability. Moreover, multiple control objectives arise in vehicle dynamics control problems, such as yaw rate control and rollover prevention, therefore, vehicle control problems can be defined as multi-actuation multi-objective vehicle control problems. Recently, the importance of integrating vehicle control systems has been highlighted in the literature. This integration allows us to prevent the potential conflicting control commands that could be generated by individual controllers. Existing studies on multi-actuated vehicle control offer a coordinated control design that shares the required control effort between the actuations. However, they mostly lack an appropriate strategy for considering the differences among vehicle actuations in their energy usage, capabilities, and effectiveness in any given vehicle states. Therefore, it is very important to develop a cost-performance strategy for optimally controlling multi-actuated vehicles. In this thesis, a prioritization model predictive control design is proposed for multi-actuated vehicles with multiple control objectives. The designed controller prioritizes the control actuations and control objectives based on, respectively, their advantages and their importance, and then combines the priorities such that a low priority actuation will not kick in unless a high priority objective demands it. The proposed controller is employed for several actuations, including electronic limited slip differential (ELSD), front/rear torque shifting, and differential braking. In this design, differential braking is engaged only when it is necessary, thus limiting or avoiding its disadvantages such as speed reduction and maintenance. In addition, the proposed control design includes a detailed analysis of the above-mentioned actuations in terms of modelling, control, and constraints. A new vehicle prediction model is designed for integrated lateral and roll dynamics that considers the force coupling effect and allows for the optimal control of front/rear torque distribution. The existing methods for ELSD control may result in chattering or unwanted oversteering yaw moments. To resolve this problem, a dynamic model is first designed for the ELSD clutch to properly estimate the clutch torque. This ELSD model is then used to design an intelligent ELSD controller that resolves the issues mentioned above. Experimental tests with two different vehicles are also carried out to evaluate the performance of the prioritization MPC controller in real-time. The results verify the capability of the controller in properly activating the control actuations with the designed priorities to improve vehicle handling and stability in different driving maneuvers. In addition, the test results confirm the performance of the designed ELSD model in ELSD clutch torque estimation and in enabling the controller to prevent unwanted oversteering yaw moments. The designed stability controller is extended to use for emergency collision avoidance in autonomous vehicles. This extension in fact addresses a local path planning/tracking problem with control objectives prioritized as: 1) collision avoidance, 2) vehicle stability, and 3) tracking the desired path. The controller combines a conservative form of torque/brake vectoring with front steering to improve the lateral agility and responsiveness of the vehicle in emergency collision avoidance scenarios. In addition, a contingency MPC controller is designed with two parallel prediction horizons - a nominal horizon and a contingency horizon - to maintain avoidance in identified road condition uncertainties. The performance of the model predictive controllers is evaluated in software simulations with high fidelity CarSim models, in which different sets of actuation configurations in various driving and road conditions are assessed. In addition, the effectiveness of the local path planning/tracking controller is evaluated in several emergency and contingency collision avoidance scenarios

Optimal Vehicle Motion Control to Mitigate Secondary Crashes after an Initial Impact.

Statistical data of road traffic fatalities show that fatalities in multiple-event crashes are higher than in single-event crashes. Most vehicle safety systems were developed to mitigate first crash events. Few active safety systems can deal with subsequent crash events. After a first crash event, drivers may not react in a timely or correct manner, which can have devastating consequences. Production active safety systems such as Electronic Stability Control (ESC) may not react to a first crash event properly unless such events are within their design specifications. The goal of this thesis is to propose control strategies that bring the vehicle state back to regions where drivers and ESC can easily take over the control, so that the severity of possible subsequent (secondary) crashes can be reduced. Because the most contributing causes of fatal secondary crashes are large lateral deviations and heading angle changes, the proposed algorithms consider both lateral displacement and heading of the vehicle. To characterize the vehicle motion after a crash event, a collision force estimation method and a vehicle motion prediction scheme are proposed. The model-based algorithm uses sensing information from the early stage of a collision process, so that the collision force can be predicted and the desired vehicle state can be determined promptly. The final heading angles are determined off-line and results are stored in a look-up table for faster implementation. Linear Time Varying Model Predictive Control (LTV-MPC) method is used to obtain the control signals, with the key tire nonlinearities captured through linearization. This algorithm considers tire force constraints based on the combined-slip tire model. The computed high-level control signals are realized through a control allocation problem which maps vehicle motion commands to tire braking forces. For real-time implementation, a rule-based control strategy is obtained. Several rules were constructed, and results under the rule-based control are similar to those under the optimal control (LTV-MPC) method while avoiding heavy on-board computations. Lastly, this thesis proposes a preemptive steering control concept. By assessing the expected strength of an imminent collision force from another vehicle, a preemptive steering control is applied to mitigate the imminent impact.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111343/1/bjukim_1.pd

Reconfigurable Integrated Control for Urban Vehicles with Different Types of Control Actuation

Urban vehicles are designed to deal with traffic problems, air pollution, energy consumption, and parking limitations in large cities. They are smaller and narrower than conventional vehicles, and thus more susceptible to rollover and stability issues. This thesis explores the unique dynamic behavior of narrow urban vehicles and different control actuation for vehicle stability to develop new reconfigurable and integrated control strategies for safe and reliable operations of urban vehicles. A novel reconfigurable vehicle model is introduced for the analysis and design of any urban vehicle configuration and also its stability control with any actuation arrangement. The proposed vehicle model provides modeling of four-wheeled (4W) vehicles and three- wheeled (3W) vehicles in Tadpole and Delta configurations in one set of equations. The vehicle model is also reconfigurable in the sense that different configurations of control actuation can be accommodated for controller design. To develop the reconfigurable vehicle model, two reconfiguration matrices are introduced; the corner and actuator reconfiguration matrices that are responsible for wheel and actuator configurations, respectively. Simulation results show that the proposed model properly matches the high-fidelity CarSim models for 3W and 4W vehicles. Rollover stability is particularly important for narrow urban vehicles. This thesis investigates the rollover stability of three-wheeled vehicles including the effects of road angles and road bumps. A new rollover index (RI) is introduced, which works for various road conditions including tripped and un-tripped rollovers on flat and sloped roads. The proposed RI is expressed in terms of measurable vehicle parameters and state variables. In addition to the effects of the lateral acceleration and roll angle, the proposed RI accounts for the effects of the longitudinal acceleration and the pitch angle, as well as the effects of road angles. Lateral and vertical road inputs are also considered since they can represent the effects of curbs, soft soil, and road bumps as the main causes of tripped rollovers. Sensitivity analysis is provided to evaluate and compare the effects of different vehicle parameters and state variables on rollover stability of 3W vehicles. A high-fidelity CarSim model for a 3W vehicle has been used for simulation and evaluation of the proposed RI accuracy. As a potentially useful mechanism for urban vehicles, wheel cambering is also investigated in this study to improve both lateral and rollover stability of narrow vehicles. A suspension system with active camber has an additional degree of freedom for changing the camber angle through which vehicle handling and stability can be improved. Conventionally, camber has been known for its ability to increase lateral forces. In this thesis, the benefits of cambering for rollover stability of narrow vehicles are also investigated and compared with a vehicle tilt mechanism. The simulation results indicate that active camber systems can improve vehicle lateral stability and rollover behavior. Furthermore, by utilizing more friction forces near the limits, the active camber system provides more improvement in maneuverability and lateral stability than the active front steering does. The proposed reconfigurable vehicle model leads us to the development of a general integrated reconfigurable control structure. The reconfigurable integrated controller can be used to meet different stability objectives of 4W and 3W vehicles with flexible combinations of control actuation. Employing the reconfigurable vehicle model, the proposed unified controller renders reconfigurability and can be easily adapted to Tadpole and Delta configurations of 3W as well as 4W vehicles without reformulating the problem. Different types and combinations of actuators can be selected for the control design including or combination of differential braking, torque vectoring, active front steering, active rear steering, and active camber system. The proposed structure provides integrated control of the main stability objectives including handling improvement, lateral stability, traction/braking control, and rollover prevention. The Model Predictive Control (MPC) approach is used to develop the reconfigurable controller. The performance of the introduced controller has been evaluated through CarSim simulations for different vehicles and control actuation configurations

Vehicle Dynamics Control for Rollover Prevention

Vehicle rollover accidents are a particularly dangerous form of road accident. Existing vehicle dynamics controllers primarily deal with yaw stability, and are of limited use for dealing with problems of roll instability. This thesis deals with the development of a new type of vehicle dynamics control system, capable of preventing rollover accidents caused by extreme maneuvering. A control strategy based on limitation of the roll angle while following a yaw rate reference is presented. Methods for rollover detection are investigated. A new computationally–efficient control allocation strategy based on convex optimization is used to map the controller commands to the individual braking forces, taking into account actuator constraints. Simulations show that the strategy is capable of preventing rollover of a commercial van during various standard test maneuvers

Narrow Urban Vehicles with an Integrated Suspension Tilting System: Design, Modeling, and Control

Narrow urban vehicles are proposed to alleviate urban transportation challenges like congestion, parking, fuel consumption, and pollution. They are designed to seat one or two people in tandem, which saves space in road infrastructures as well as improves the fuel efficiency. However, to overcome the high rollover tendency which comes as a consequence of reduced track-width ratio, tilting systems for vehicle roll motion control are suggested. Existing tilting solutions, which mechanically connect the wheel modules on both sides for motion synchronization, are not space-friendly for the narrow vehicle footprint. The mechanical linkages also add extra weight to those urban vehicles initially designed to be light-weighted. A novel integrated suspension tilting system (ISTS) is proposed in this thesis, which replaces rigid mechanical linkages with flexible hydraulic pipes and cylinders. In addition, combining the suspension and tilting into an integrated system will result in even more compact, light-weighted, and spacious urban vehicles. The concept is examined, and the suspension mechanism for the tilting application is proposed after examining various mechanisms for their complexity and space requirements. Kinematic and dynamic properties of the tilting vehicle under large suspension strokes are analyzed to optimize the mechanism design. Control of the active tilting systems for vehicle roll stability improvement is then discussed. Rather than tilting the vehicle to entirely eliminate the lateral load transfer during cornering, an integrated envelope approach considering both lateral and roll motion is proposed to improve the energy efficiency while maintaining the vehicle stability. A re-configurable integrated control structure is also developed for various vehicle configurations as well as enhancing the system robustness against actuator failures. The model predictive control (MPC) scheme is adopted considering the non-minimum phase nature of active tilting systems. The predictive feature along with the proposed roll envelope formulation provides a framework to balance the transient and steady-state performances using the tilting actuators. The suggested controller is firstly demonstrated on a vehicle roll model, and then applied to high-fidelity full vehicle models in CarSim including a four-wheeled SUV as well as a three-wheeled narrow urban vehicle. The SUV simulation results indicate the potential of using the developed envelope controller on conventional vehicles with active suspensions, while the narrow urban vehicle simulations demonstrate the feasibility of using the suggested ISTS on narrow tilting vehicles. By adopting the integrated envelope control approach, actuation effort is reduced and the vehicle handling, along with the stability in both lateral and roll, can be further improved