A Generic Fuzzy Pilot and Path Planning for Vehicle Handling Dynamics Simulation Studies

Uzunsoy, Erdem; Olatunbosun, Oluremi

doi:10.4271/2003-01-2263

Cited by 5 publications

(1 citation statement)

References 5 publications

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“…The artificial potential field method simulates the spatial environment to generate repulsive poles and gravitational poles for obstacles and target points without the need for specific modeling of individuals. Our method is different from related algorithms, such as fuzzy logic [38], rolling window-based method [39], and other intelligence algorithms [40]. The fuzzy logic method needs more human experience, however, the reproducibility of applications for different environments is somewhat poorer.…”

Section: ) Vehicle Navigation and Path Planningmentioning

confidence: 95%

Design and Performance Evaluation of a Simple Semi-Physical Human-Vehicle Collaborative Driving Simulation System

Duan

2019

IEEE Access

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Human-vehicle collaborative driving (HVCD) has a novel concept of an intermediate stage from the development of a normal smart vehicle to self-driving vehicle, requires the vehicle's decisionmaking authority equivalent to the human driver's operation. As the self-driving vehicle cannot achieve full-condition driving without human driver yet and still have a long time to go, the collaborative driving can exploit both machine and human specialties, which requires human and vehicle intelligence to control the vehicle simultaneously and work together. However, there were a few studies focusing on the HVCD that experimental environment and evaluation methods are rarely discussed, even under the simulation conditions, which limits the development of collaborative driving. To bridge the significant gaps, this paper designed simple semi-physical simulation system architecture for the HVCD. First, the simple designed system can achieve basic functions, including human control input as the normal driver, vehicle intelligence with local and global sensor data process and decision fusion. The presented system can use and process this multisource information to achieve the HVCD in the simulated environment. Second, the evaluation method based on vehicle driving safety, stability, and rapidity is proposed and discussed, which matters most for system performance test and feasibility verification. In addition, experiments with different decision fusion conditions were presented and the experimental results show that the proposed simple semi-physical HVCD simulation system can work smoothly and reflect the practical scenario. Furthermore, the performance of different fusion weights experiments shows the advantages of both human driver and vehicle intelligence, which provides a reference for the HVCD related research improvement. INDEX TERMS Human-vehicle collaborative driving, simulation system design, vehicle driving performance evaluation.

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Section: ) Vehicle Navigation and Path Planningmentioning

confidence: 95%

Design and Performance Evaluation of a Simple Semi-Physical Human-Vehicle Collaborative Driving Simulation System

Duan

2019

IEEE Access

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Development of a trajectory following vehicle control model

Uzunsoy

Erkilic

2016

Advances in Mechanical Engineering

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Determination of the handling properties of a vehicle may be restrictive in some situations. A vehicle model coupled with a driver model may be necessary and even unavoidable to analyse the real road behaviour in the most basic form. Therefore, a fuzzy logic–based controller has been investigated for potential application in modelling driver. Using some particular and limited number of information from characteristics of human driving operation, the model aims to provide any flexible vehicle path reliably. It generates the vehicle’s trajectory through a number of specified points through which the vehicle must pass. The controller was modified to account for peripheral vision characteristic of human eye, as an input. The simulation is carried out in the MATLAB© programming environment using a Simulink© vehicle model. Both longitudinal and lateral controls were applied in the study. This article adds novel approaches to the limited existing published work on driver steering model using fuzzy logic.

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A study of the effect of rear suspension auxiliary roll damping on vehicle-handling dynamics

Uzunsoy

Olatunbosun

2005

Proceedings of the Institution of Mechanical Engineers, Part D:

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The handling dynamics of a University of Birmingham Racing Formula Student racing car, incorporating a novel rear suspension load transfer system which provides auxiliary roll damping, is modelled using a simulation tool, HANDSIM, developed for vehicle-handling studies, and the effect of the system on the vehicle's handling performance is discussed by considering the results obtained from the simulation. The aim of implementing this suspension load transfer system is to improve the handling characteristics of the vehicle in severe cornering manoeuvres.able by any vehicle model regardless of its complexity. Edgbaston, Birmingham, B15 2TT, UK. email: o.a.olatunbosun@ The path that the vehicle is supposed to follow is pre-mapped on the Earth fixed coordinates [1-3].bham.ac.uk D08004

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A Generic Fuzzy Pilot and Path Planning for Vehicle Handling Dynamics Simulation Studies

Cited by 5 publications

References 5 publications

Design and Performance Evaluation of a Simple Semi-Physical Human-Vehicle Collaborative Driving Simulation System

Design and Performance Evaluation of a Simple Semi-Physical Human-Vehicle Collaborative Driving Simulation System

Development of a trajectory following vehicle control model

A study of the effect of rear suspension auxiliary roll damping on vehicle-handling dynamics

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