Evolving a rule system controller for automatic driving in a car racing competition

IEEE Symposium on Computational Intelligence and Games. Perth, Australia, 15-18 December 2008.The techniques and the technologies supporting Automatic Vehicle Guidance are important issues. Automobile manufacturers view automatic driving as a very interesting product with motivating key features which allow improvement of the car safety, reduction in emission or fuel consumption or optimization of driver comfort during long journeys. Car racing is an active research field where new advances in aerodynamics, consumption and engine power are critical each season. Our proposal is to research how evolutionary computation techniques can help in this field. For this work we have designed an automatic controller that learns rules with a genetic algorithm. This paper is a report of the results obtained by this controller during the car racing competition held in Hong Kong during the IEEE World Congress on Computational Intelligence (WCCI 2008).Publicad

Application of serious games to sport, health and exercise

Use of interactive entertainment has been exponentially expanded since the last decade. Throughout this 10+ year evolution there has been a concern about turning entertainment properties into serious applications, a.k.a "Serious Games". In this article we present two set of Serious Game applications, an Environment Visualising game which focuses solely on applying serious games to elite Olympic sport and another set of serious games that incorporate an in house developed proprietary input system that can detect most of the human movements which focuses on applying serious games to health and exercise

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competitio

Optimisation of racing car suspensions featuring inerters

Racing car suspensions are a critical system in the overall performance of the vehicle. They must be able to accurately control ride dynamics as well as influencing the handling characteristics of the vehicle and providing stability under the action of external forces. This work is a research study on the design and optimisation of high performance vehicle suspensions using inerters. The starting point is a theoretical investigation of the dynamics of a system fitted with an ideal inerter. This sets the foundation for developing a more complex and novel vehicle suspension model incorporating real inerters. The accuracy and predictability of this model has been assessed and validated against experimental data from 4- post rig testing. In order to maximise overall vehicle performance, a race car suspension must meet a large number of conflicting objectives. Hence, suspension design and optimisation is a complex task where a compromised solution among a set of objectives needs to be adopted. The first task in this process is to define a set of performance based objective functions. The approach taken was to relate the ride dynamic behaviour of the suspension to the overall performance of the race car. The second task of the optimisation process is to develop an efficient and robust optimisation methodology. To address this, a multi-stage optimisation algorithm has been developed. The algorithm is based on two stages, a hybrid surrogate model based multiobjective evolutionary algorithm to obtain a set of non-dominated optimal suspension solutions and a transient lap-time simulation tool to incorporate external factors to the decision process and provide a final optimal solution. A transient lap-time simulation tool has been developed. The minimum time manoeuvring problem has been defined as an Optimal Control problem. A novel solution method based on a multi-level algorithm and a closed-loop driver steering control has been proposed to find the optimal lap time. The results obtained suggest that performance gains can be obtained by incorporating inerters into the suspension system. The work suggests that the use of inerters provides the car with an optimised aerodynamic platform and the overall stability of the vehicle is improved

A Telemetry-driven Approach to Simulate Data-intensive Manufacturing Processes

Abstract Telemetry enables the collection of data from remote points to support monitoring, analysis and visualization. It is largely adopted in Formula One car racing, where streams of live data collected from hundreds of sensors installed on car components are transmitted to the pitwall to be used as input of real-time car performance simulations. The aim of this paper is to evaluate the potential of a telemetry-driven approach in a manufacturing environment, where researchers are still looking for efficient methods to perform valuable simulations of the production processes on the basis of real data coming from the factory. The telemetry could contribute to the implementation of a virtual image of the real factory, which in turn could be used to simulate the factory performance, allowing to predict failures or investigate problems, and to reduce costly downtime. This study addresses in particular the efforts to combine and adapt methods and techniques borrowed from the field of Formula One car racing. Moreover, the investigation of the exploitation possibilities of the factory telemetry is paired with the design of a software application supporting this technology, starting from the elicitation and specification of the functional requirements

Discontinuities handled with events in Assimulo

Often integrating ordinary differential equations or differential algebraic equations (DAE) do not constitute the problem alone. A common complement is finding the root of an algebraic function (an event function) that depends on the states of the problem. This formulation of a model enables the possibility of including discontinuities, an important part of the Functional Mock-up Interface standard which allows hybrid models of differential algebraic equations. The problem of root-finding during integration is however difficult. Both in a theoretical aspect and as a software problem. An implementation of software for root-finding is done in Assimulo, a Python/Cython wrapper for integrators. The implementation takes the Functional Mock-up Interface standard into consideration. The implementation is made usable for a wide variety of integration algorithms and is also verified and benchmarked with advanced industrial models, showing good indications of being robust and scaling well for large systems

er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using independently developed software on open-wheel racecars. This paper presents the complete software architecture used by team TII EuroRacing (TII-ER), covering all the modules needed to avoid static obstacles, perform active overtakes and reach speeds above 75 m/s (270 km/h). In addition to the most common modules related to perception, planning, and control, we discuss the approaches used for vehicle dynamics modelling, simulation, telemetry, and safety. Overall results and the performance of each module are described, as well as the lessons learned during the first two events of the competition on oval tracks, where the team placed respectively second and third.Comment: Preprint: Accepted to Field Robotics "Opportunities and Challenges with Autonomous Racing" Special Issu

FSAE aerodynamics and lap time simulator

Aerodynamic design of a Formula Student racing car using Solidworks Flow Simulation. The devices designed are compatible with the Vilanova Formula Team 2022 racing car. The project also contains the development of a deep learning tool to test the track efficiency of the car. This tool compares different aerodynamic configurations in a determined track before building the car