Efficient minimum manoeuvre time optimisation of an oversteering vehicle at constant forward speed

A receding horizon steering controller is presented, capable of pushing an oversteering nonlinear vehicle model to its handling limit while travelling at constant forward speed. The controller is able to optimise the vehicle path, using a computationally efficient and robust technique, so that the vehicle progression along a track is maximised as a function of time. The resultant method forms part of the solution to the motor racing objective of minimising lap time. © 2011 AACC American Automatic Control Council.

Vehicle trajectory linearisation to enable efficient optimisation of the constant speed racing line

A driver model is presented capable of optimising the trajectory of a simple dynamic nonlinear vehicle, at constant forward speed, so that progression along a predefined track is maximised as a function of time. In doing so, the model is able to continually operate a vehicle at its lateral-handling limit, maximising vehicle performance. The technique used forms a part of the solution to the motor racing objective of minimising lap time. A new approach of formulating the minimum lap time problem is motivated by the need for a more computationally efficient and robust tool-set for understanding on-the-limit driving behaviour. This has been achieved through set point-dependent linearisation of the vehicle model and coupling the vehicle-track system using an intrinsic coordinate description. Through this, the geometric vehicle trajectory had been linearised relative to the track reference, leading to new path optimisation algorithm which can be formed as a computationally efficient convex quadratic programming problem. © 2012 Copyright Taylor and Francis Group, LLC.

Verification of periodically controlled hybrid systems: Application to an autonomous vehicle

This article introduces Periodically Controlled Hybrid Automata (PCHA) for modular specification of embedded control systems. In a PCHA, control actions that change the control input to the plant occur roughly periodically, while other actions that update the state of the controller may occur in the interim. Such actions could model, for example, sensor updates and information received from higher-level planning modules that change the set point of the controller. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariant properties of PCHAs is presented. For PCHAs with polynomial continuous vector fields, it is possible to check these conditions automatically using, for example, quantifier elimination or sum of squares decomposition. We examine the feasibility of this automatic approach on a small example. The proposed technique is also used to manually verify safety and progress properties of a fairly complex planner-controller subsystem of an autonomous ground vehicle. Geometric properties of planner-generated paths are derived which guarantee that such paths can be safely followed by the controller. © 2012 ACM.

Stability control of a railway vehicle using absolute stiffness and inerters

Work presented in this paper studies the potential of employing inerters -a novel mechanical device used successfully in racing cars- in active suspension configurations with the aim to enhance railway vehicle system performance. The particular element of research in this paper concerns railway wheelset lateral stability control. Controlled torques are applied to the wheelsets using the concept of absolute stiffness. The effects of a reduced set of arbitrary passive structures using springs, dampers and inerters integrated to the active solution are discussed. A multi-objective optimisation problem is defined for tuning the parameters of the proposed configurations. Finally, time domain simulations are assessed for the railway vehicle while negotiating a curved track. A simplification of the design problem for stability is attained with the integration of inerters to the active solutions. © 2012 IEEE.

Effects of ethanol on vehicle energy efficiency and implications on ethanol life-cycle greenhouse gas analysis.

Bioethanol is the world's largest-produced alternative to petroleum-derived transportation fuels due to its compatibility within existing spark-ignition engines and its relatively mature production technology. Despite its success, questions remain over the greenhouse gas (GHG) implications of fuel ethanol use with many studies showing significant impacts of differences in land use, feedstock, and refinery operation. While most efforts to quantify life-cycle GHG impacts have focused on the production stage, a few recent studies have acknowledged the effect of ethanol on engine performance and incorporated these effects into the fuel life cycle. These studies have broadly asserted that vehicle efficiency increases with ethanol use to justify reducing the GHG impact of ethanol. These results seem to conflict with the general notion that ethanol decreases the fuel efficiency (or increases the fuel consumption) of vehicles due to the lower volumetric energy content of ethanol when compared to gasoline. Here we argue that due to the increased emphasis on alternative fuels with drastically differing energy densities, vehicle efficiency should be evaluated based on energy rather than volume. When done so, we show that efficiency of existing vehicles can be affected by ethanol content, but these impacts can serve to have both positive and negative effects and are highly uncertain (ranging from -15% to +24%). As a result, uncertainties in the net GHG effect of ethanol, particularly when used in a low-level blend with gasoline, are considerably larger than previously estimated (standard deviations increase by >10% and >200% when used in high and low blends, respectively). Technical options exist to improve vehicle efficiency through smarter use of ethanol though changes to the vehicle fleets and fuel infrastructure would be required. Future biofuel policies should promote synergies between the vehicle and fuel industries in order to maximize the society-wise benefits or minimize the risks of adverse impacts of ethanol.

Optimisation of passive and semi-active heavy vehicle suspensions

An investigation into the potential for reducing road damage by optimising the design of heavy vehicle suspensions is described. In the first part of the paper two simple mathematical models are used to study the optimisation of conventional passive suspensions. Simple modifications are made to the steel spring suspension of a tandem axle trailer and it is found experimentally that RMS dynamic tyre forces can be reduced by 15% and theoretical road damage by 5.2%. A mathematical model of an air-sprung articulated vehicle is validated, and its suspension is optimised according to the simple models. This vehicle generates about 9% less damage than the leaf-sprung vehicle in the unmodified state and it is predicted that, for the operating conditions examined, the road damage caused by this vehicle can be reduced by a further 5.4%. Finally, it is shown experimentally that computer-controlled semi-active dampers have the potential to reduce road damage by a further 5-6%, compared to an air suspension with optimum passive damping. © Copyright 1994 Society of Automotive Engineers, Inc.

CO2Y the intelligent green solution: minimising carbon emissions by maximising shared travel opportunity.

It is in the interests of everybody that the environment is protected. In view of the recent leaps in environmental awareness it would seem timely and sensible, therefore, for people to pool vehicle resources to minimise the damaging impact of emissions. However, this is often contrary to how complex social systems behave – local decisions made by self-interested individuals often have emergent effects that are in the interests of nobody. For software engineers a major challenge is to help facilitate individual decision-making such that individual preferences can be met, which, when accumulated, minimise adverse effects at the level of the transport system. We introduce this general problem through a concrete example based on vehicle-sharing. Firstly, we outline the kind of complex transportation problem that is directly addressed by our technology (CO2y™ - pronounced “cosy”), and also show how this differs from other more basic software solutions. The CO2y™ architecture is then briefly introduced. We outline the practical advantages of the advanced, intelligent software technology that is designed to satisfy a number of individual preference criteria and thereby find appropriate matches within a population of vehicle-share users. An example scenario of use is put forward, i.e., minimisation of grey-fleets within a medium-sized company. Here we comment on some of the underlying assumptions of the scenario, and how in a detailed real-world situation such assumptions might differ between different companies, and individual users. Finally, we summarise the paper, and conclude by outlining how the problem of pooled transportation is likely to benefit from the further application of emergent, nature-inspired computing technologies. These technologies allow systems-level behaviour to be optimised with explicit representation of individual actors. With these techniques we hope to make real progress in facing the complexity challenges that transportation problems produce.

Time-dependent Hyperstar algorithm for robust vehicle navigation in time-dependent stochastic road networks.

The vehicle navigation problem studied in Bell (2009) is revisited and a time-dependent reverse Hyperstar algorithm is presented. This minimises the expected time of arrival at the destination, and all intermediate nodes, where expectation is based on a pessimistic (or risk-averse) view of unknown link delays. This may also be regarded as a hyperpath version of the Chabini and Lan (2002) algorithm, which itself is a time-dependent A* algorithm. Links are assigned undelayed travel times and maximum delays, both of which are potentially functions of the time of arrival at the respective link. The driver seeks probabilities for link use that minimise his/her maximum exposure to delay on the approach to each node, leading to the determination of the pessimistic expected time of arrival. Since the context considered is vehicle navigation where the driver is not making repeated trips, the probability of link use may be interpreted as a measure of link attractiveness, so a link with a zero probability of use is unattractive while a link with a probability of use equal to one will have no attractive alternatives. A solution algorithm is presented and proven to solve the problem provided the node potentials are feasible and a FIFO condition applies for undelayed link travel times. The paper concludes with a numerical example.