Human-Centered Design of an Acc-With-Braking and Forward-Crash-Warning System

This paper addresses the development of driver assistance systems whose functional purposes are to provide both adaptive cruise control (ACC) and forward collision warning (FCW). The purpose of the paper is to combine concepts from human factors psychology, vehicle-dynamics, and control theory, thereby contributing to the body of knowledge and understanding concerning human-centered approaches for designing and evaluating driver assistance systems. Conceptual and experimental results pertaining to driving manually and with the assistance of ACC and FCW are presented. The following human-centered aspects of driver-assistance systems are analyzed and presented: the looming effect; including rule-based and skill-based behavior in the design of ACC systems; using desired dynamics in controlling the driving process; braking rules that trade headway range for deceleration level; and collision-warning rules based on two different stress indicators. Field-test data are examined to justify and verify the parametric values selected for use in human-centered ACC systems. Measured data from on-road driving are used to evaluate the performance of proposed FCW systems in braking situations. The paper concludes with observations concerning the difficulty of developing a clear understanding of when and why drivers brake.     

Fueling Control of Spark Ignition Engines

Presented in this paper is an adaptive, model based, fueling control system for spark ignition-internal combustion engines. Since the fueling control system is model based, the engine maps currently used in engine fueling control are eliminated. This proposed fueling control system is modular and can therefore accommodate changes in the engine sensor set such as replacing the mass-air flow sensor with a manifold air pressure sensor. The fueling algorithm can operate with either a switching type O 2 sensor or a linear O 2 sensor. The fueling control system is also parceled into steady state fueling compensation and transient fueling compensation. This feature provides the distinction between fueling control adaptation for transient fueling and steady state fueling. The steady state fueling compensation utilizes a feedforward controller which determines the necessary fuel pulsewidth after a throttle transient to achieve stoichiometry. This feedforward controller is comprised of two nonlinear models capturing the steady state characteristics of the fueling process. These models are identified from an input-output testing procedure where the inputs are fuel pulsewidth and mass-air flow signal and the output is a lambda signal. These models are adapted via a recursive least squares method to accommodate product variability, engine aging, and changes in the operating environment. The transient fueling compensation also utilizes a feedforward controller that captures the essential dynamic characteristics of the transient fueling operation. This controller is measured using a frequency domain system identification approach. This proposed fueling control system is demonstrated on a Ford 4.6L V-8 fuel injected engine.     

Modal Controllers for Active Steering of Railway Vehicles with Solid Axle Wheelsets

This paper presents the development of a modal control strategy for the active steering of solid axle railway vehicles and reveals benefits of actively stabilising the wheelsets of a railway vehicle. A modal decomposition is applied to a 2-axle railway vehicle to de-couple its body lateral and yaw motions and hence to allow more detailed analysis of the vehicle behaviour and more robust design of active controllers. Independent controllers for the two motions are developed based on the two de-coupled modes. Parameter variations such as creep coefficients and wheelset conicity are taken into account in the design process to guarantee a robust design. The study shows that, compared to a passive vehicle, the vehicles with actively steered wheelsets not only perform much better on a curved track, but also improve the ride quality on straight track. Computer simulations are used in the study to verify the development of the controllers and assess the system performance with the control scheme proposed.     

The opening of the Amsterdam Ring Road

This paper presents the results of a major before-and-after study carried out to establish the short term effects of the removal of a severe bottleneck in the road network around Amsterdam. An important focus in the study was on measuring changes in the timing of travel, as well as changes in route choice, mode choice, destination choice and frequency of travel. The results of the study indicated that, in the short run, there was little or no change in mode choice, nor was there significant emergence of new induced trips. On the other hand, large shifts in time of travel as well as route choice were reported, emphasising the importance of alterations to the timing and routes of existing trips when congestion is relieved, and the need to consider the benefits these bring in evaluating the impact of any road investment.     

Analytical extension of the effective axle characteristics concept for the development of a structured chassis design process

The lateral vehicle dynamics is defined by the effects of side forces at the front and rear axle. These forces are caused by the slip and camber angle at the individual tyres, which are results of the kinematics and compliances of the chassis. This paper extends the approach of the effective axle characteristics by Paceyka to the analytical expression of the axle cornering stiffness and the axle relaxation behaviour with the aim of the development of a chassis design process as it applies in the early design stage. The obtained expression is integrated into a single track model and validated against a full nonlinear two-track model. By this means of these analytical expressions for the axle cornering stiffness and the axle relaxation behaviour it is possible to directly calculate and analyse the effective slip angles for linear quasi-static and dynamic driving manoeuvres.     

Wheel slip control with torque blending using linear and nonlinear model predictive control

Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.     

New methodology for fast prediction of wheel wear evolution

In railway applications wear prediction in the wheel–rail interface is a fundamental matter in order to study problems such as wheel lifespan and the evolution of vehicle dynamic characteristic with time. However, one of the principal drawbacks of the existing methodologies for calculating the wear evolution is the computational cost. This paper proposes a new wear prediction methodology with a reduced computational cost. This methodology is based on two main steps: the first one is the substitution of the calculations over the whole network by the calculation of the contact conditions in certain characteristic point from whose result the wheel wear evolution can be inferred. The second one is the substitution of the dynamic calculation (time integration calculations) by the quasi-static calculation (the solution of the quasi-static situation of a vehicle at a certain point which is the same that neglecting the acceleration terms in the dynamic equations). These simplifications allow a significant reduction of computational cost to be obtained while maintaining an acceptable level of accuracy (error order of 5–10%). Several case studies are analysed along the paper with the objective of assessing the proposed methodology. The results obtained in the case studies allow concluding that the proposed methodology is valid for an arbitrary vehicle running through an arbitrary track layout.     

Semi-active control of tracked vehicle suspension incorporating magnetorheological dampers

In past years, the application of magnetorheological (MR) and electrorheological dampers in vehicle suspension has been widely studied, mainly for the purpose of vibration control. This paper presents theoretical study to identify an appropriate semi-active control method for MR-tracked vehicle suspension. Three representative control algorithms are simulated including the skyhook, hybrid and fuzzy-hybrid controllers. A seven degrees-of-freedom tracked vehicle suspension model incorporating MR dampers has been adopted for comparison between the performance of the three controllers. The model differential equations are derived based on Newton's second law of motion and the proposed control methods are developed. The performance of each control method under bump and sinusoidal road profiles for different vehicle speeds is simulated and compared with the performance of the conventional suspension system in time and frequency domains. The results show that the performance of tracked vehicle suspension with MR dampers is substantially improved. Moreover, the fuzzy-hybrid controller offers an excellent integrated performance in reducing the body accelerations as well as wheel bounce responses compared with the classical skyhook and hybrid controllers.     

A fast implementation of MPC-based motion cueing algorithms for mid-size road vehicle motion simulators

The use of dynamic driving simulators is constantly increasing in the automotive community, with applications ranging from vehicle development to rehab and driver training. The effectiveness of such devices is related to their capabilities of well reproducing the driving sensations, hence it is crucial that the motion control strategies generate both realistic and feasible inputs to the platform. Such strategies are called motion cueing algorithms (MCAs). In recent years several MCAs based on model predictive control (MPC) techniques have been proposed. The main drawback associated with the use of MPC is its computational burden, that may limit their application to high performance dynamic simulators. In the paper, a fast, real-time implementation of an MPC-based MCA for 9 DOF, high performance platform is proposed. Effectiveness of the approach in managing the available working area is illustrated by presenting experimental results from an implementation on a real device with a 200?Hz control frequency.     

Real-time weighted multi-objective model predictive controller for adaptive cruise control systems

In this paper, a novel spacing control law is developed for vehicles with adaptive cruise control (ACC) systems to perform spacing control mode. Rather than establishing a steady-state following distance behind a newly encountered vehicle to avoid collision, the proposed spacing control law based on model predictive control (MPC) further considers fuel economy and ride comfort. Firstly, a hierarchical control architecture is utilized in which a lower controller compensates for nonlinear longitudinal vehicle dynamics and enables to track the desired acceleration. The upper controller based on the proposed spacing control law is designed to compute the desired acceleration to maintain the control objectives. Moreover, the control objectives are then formulated into the model predictive control problem using acceleration and jerk limits as constrains. Furthermore, due to the complex driving conditions during in the transitional state, the traditional model predictive control algorithm with constant weight matrix cannot meet the requirement of improvement in the fuel economy and ride comfort. Therefore, a real-time weight tuning strategy is proposed to solve time-varying multi-objective control problems, where the weight of each objective can be adjusted with respect to different operating conditions. In addition, simulation results demonstrate that the ACC system with the proposed real-time weighted MPC (RW-MPC) can provide better performance than that using constant weight MPC (CW-MPC) in terms of fuel economy and ride comfort.