scholarly journals Combining a Genetic Algorithm and a Fuzzy System to Optimize User Centricity in Autonomous Vehicle Concept Development

Systems ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 25
Author(s):  
Ferdinand Schockenhoff ◽  
Maximilian Zähringer ◽  
Matthias Brönner ◽  
Markus Lienkamp
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy System ◽  
Autonomous Vehicles ◽  
Methodological Approach ◽  
Autonomous Vehicle ◽  
Concept Development ◽  
User Needs ◽  
Vehicle Concept ◽  
Entire Vehicle ◽  
User Centered

The megatrends of individualization and sharing will dramatically change our consumer behavior. The needs of a product’s users will be central input for its development. Current development processes are not suitable for this product development; thus, we propose a combination of a genetic algorithm and a fuzzy system for user-centered development. We execute our new methodological approach on the example of autonomous vehicle concepts to demonstrate its implementation and functionality. The genetic algorithm minimizes the required number of vehicle concepts to satisfy the mobility needs of a user group, and the fuzzy system transfers user needs into vehicle-related properties, which are currently input for vehicle concept development. To present this method, we use a typical family and their potential mobility behavior. Our method optimizes their minimal number of vehicle concepts to satisfy all mobility needs and derives the properties of the vehicle concepts. By integrating our method into the entire vehicle concept development process, autonomous vehicles can be designed user-centered in the context of the megatrends of individualization and sharing. In summary, our method enables us to derive an optimized number of products for qualitatively described, heterogeneous user needs and determine their product-related properties.

scholarly journals Maneuver-Based Objectification of User Comfort Affecting Aspects of Driving Style of Autonomous Vehicle Concepts

2020 ◽  
Vol 10 (11) ◽  
pp. 3946 ◽  
Author(s):  
Ferdinand Schockenhoff ◽  
Hannes Nehse ◽  
Markus Lienkamp
Keyword(s):  
Pilot Study ◽  
Travel Time ◽  
Autonomous Vehicles ◽  
User Study ◽  
Autonomous Vehicle ◽  
User Needs ◽  
Vehicle Concept ◽  
Driving Style ◽  
The Individual ◽  
User Comfort

Driving maneuvers try to objectify user needs regarding the driving dynamics for a vehicle concept. As autonomous vehicles will not be driven by people, the driving style that merges the individual aspects of driving dynamics, like user comfort, will be part of the vehicle concept itself. New driving maneuvers are, therefore, necessary to objectify the driving style of autonomous vehicle concepts with all its interdependencies relating to the individual aspects. This paper presents a methodology to design such driving maneuvers and includes a pilot study and a user study. As an example, the methodology was applied to the parameters of user comfort and travel time. The driven maneuvers resulted in statistical equations to objectify the interdependencies of these two aspects. Finally, this paper provides an outlook for needed maneuvers in order to tackle the entire driving style with its multidimensional facets.

scholarly journals USER NEED-ORIENTED CONCEPT DEVELOPMENT OF AUTONOMOUS VEHICLES

2021 ◽  
Vol 1 ◽  
pp. 3349-3358
Author(s):  
Ferdinand Schockenhoff ◽  
Adrian König ◽  
Maximilian Zähringer ◽  
Markus Lienkamp
Keyword(s):  
21St Century ◽  
Autonomous Vehicles ◽  
Development Process ◽  
Autonomous Vehicle ◽  
Concept Development ◽  
Vehicle Concept ◽  
Design Concepts ◽  
Starting Point ◽  
User Need ◽  
Input Variables

AbstractVehicle concept development is a domain that has applied and detailed its process over decades. The megatrends of the 21st century of “automation” and “sharing” influence the vehicle concept in such a manner that this well-running process needs an update. The vehicle itself and the customer of the vehicle are changing and therefore the components of the vehicle and the input variables of the useroriented design of the vehicle concept must be changed as well. We present a development process for autonomous vehicle concepts to address these challenges. We are therefore analyzing the current definition of a vehicle concept and its development process. Based on a literature review of a selection of common design methodologies, we update this definition for autonomous vehicle concepts and present a development process that presents design concepts of autonomous vehicle in a user need oriented way. This includes the sharing of models since user needs could be fulfilled by more than one vehicle concept. We believe that the presented process can be a starting point for vehicle concept development of the 21st century.

scholarly journals An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach

2013 ◽  
Vol 23 (1) ◽  
pp. 183-200 ◽  
Author(s):  
Fei Yan ◽  
Mahjoub Dridi ◽  
Abdellah El Moudni
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Control Methods ◽  
Traffic Condition ◽  
Sequencing Problem ◽  
Genetic Algorithm Approach ◽  
Short Time ◽  
Intersection Management

This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm.

scholarly journals CONCEPT DEVELOPMENT PROCESS FOR DOORS OF AUTONOMOUS VEHICLES

2021 ◽  
Vol 1 ◽  
pp. 701-710
Author(s):  
Adrian König ◽  
Patrick Neuhaus ◽  
Koch Alexander ◽  
Schockenhoff Ferdinand ◽  
Hafemann Philipp ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Early Phase ◽  
Development Process ◽  
User Study ◽  
Autonomous Driving ◽  
Concept Development ◽  
Vehicle Concept ◽  
Modular Architecture

AbstractVehicle doors have barely changed in recent decades, and nor has the car. Since autonomous driving will lead to changes in vehicles and how they are used, their doors will also have to be rethought. In the project UNICARagil, researchers from several universities in Germany design and build four prototypes of driverless and autonomous vehicles, which are developed based on a new and modular architecture. As part of this, we developed a concept including a prototype of an automated door system. In this paper, we present our concept development process adapted for door systems of autonomous vehicles. Based on the vehicle concept development process, it should help researchers and engineers to select and design new door concepts in an early phase. At the end, by means of an example, we present the prototype of our door concept as well as a boarding user study we carried out. This study helps evaluate and improve the boarding comfort of future door concepts.

scholarly journals PACKAGE PLANNING OF AUTONOMOUS VEHICLE CONCEPTS

2021 ◽  
Vol 1 ◽  
pp. 2369-2378
Author(s):  
Adrian König ◽  
Daniel Telschow ◽  
Lorenzo Nicoletti ◽  
Markus Lienkamp
Keyword(s):  
Autonomous Vehicles ◽  
Business Models ◽  
New Technologies ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Vehicle Concept ◽  
Passenger Cars ◽  
New Business ◽  
New Business Models ◽  
A Current

AbstractAutonomous driving will not just change vehicles themselves, but also the entire concept of mobility. New business models and the expansion of individual mobility to new groups of society are merely examples of possible impact. In order to create optimal vehicles for new technologies right from the start, vehicle concept optimization helps to find suitable solutions from numerous possible variations. The package as part of a vehicle concept is currently focused on passenger cars with steering wheels and pedals. Therefore, a new method is needed to plan the package of driverless and autonomous vehicles. In this paper, we present a possible method that separates the vehicle into the interior and the front and rear wagon. This way, different seating layouts can be considered and evaluated in terms of package efficiency. In the results, we check the plausibility by rebuilding a current battery electric vehicle (BEV) and, by way of example, show the variation of the gear angle and different seating layouts, and the resulting package efficiency.

Vision-Based Navigation of Autonomous Vehicles in Roadway Environments with Unexpected Hazards

2019 ◽  
Vol 2673 (12) ◽  
pp. 494-507 ◽  
Author(s):  
Mhafuzul Islam ◽  
Mashrur Chowdhury ◽  
Hongda Li ◽  
Hongxin Hu
Keyword(s):  
Object Detection ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Semantic Segmentation ◽  
Steering Wheel ◽  
Potential Hazard ◽  
Driving System ◽  
Hazardous Object ◽  
Vision Based Navigation ◽  
Navigational System

Vision-based navigation of autonomous vehicles primarily depends on the deep neural network (DNN) based systems in which the controller obtains input from sensors/detectors, such as cameras, and produces a vehicle control output, such as a steering wheel angle to navigate the vehicle safely in a roadway traffic environment. Typically, these DNN-based systems in the autonomous vehicle are trained through supervised learning; however, recent studies show that a trained DNN-based system can be compromised by perturbation or adverse inputs. Similarly, this perturbation can be introduced into the DNN-based systems of autonomous vehicles by unexpected roadway hazards, such as debris or roadblocks. In this study, we first introduce a hazardous roadway environment that can compromise the DNN-based navigational system of an autonomous vehicle, and produce an incorrect steering wheel angle, which could cause crashes resulting in fatality or injury. Then, we develop a DNN-based autonomous vehicle driving system using object detection and semantic segmentation to mitigate the adverse effect of this type of hazard, which helps the autonomous vehicle to navigate safely around such hazards. We find that our developed DNN-based autonomous vehicle driving system, including hazardous object detection and semantic segmentation, improves the navigational ability of an autonomous vehicle to avoid a potential hazard by 21% compared with the traditional DNN-based autonomous vehicle driving system.

The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

2021 ◽  
pp. 095440702110090
Author(s):  
Xing Xu ◽  
Minglei Li ◽  
Feng Wang ◽  
Ju Xie ◽  
Xiaohan Wu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Control Method ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Test Track ◽  
Optimal Control Method ◽  
The Future ◽  
On The Road

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

scholarly journals Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2244
Author(s):  
S. M. Yang ◽  
Y. A. Lin
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Random Trees ◽  
Average Deviation ◽  
Lane Changes ◽  
Path Smoothing ◽  
Rapidly Exploring Random Trees

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

scholarly journals Modelling of the system “driver - automation - autonomous vehicle - road”

2020 ◽  
Vol 10 (1) ◽  
pp. 175-182 ◽  
Author(s):  
Grzegorz Koralewski
Keyword(s):  
Autonomous Vehicles ◽  
Combustion Engine ◽  
Autonomous Vehicle ◽  
Application Software ◽  
Motion Simulation ◽  
Gear Shift ◽  
Shift Control ◽  
Driving Torque ◽  
Physical Quantities ◽  
Motion Quality

AbstractThe work presents a simulation model of a “driver–automation–autonomous vehicles–road” system which is the basis for synthesis of automatic gear shift control system. The mathematical description makes use of physical quantities which characterise driving torque transformation from the combustion engine to the car driven wheels. The basic components of the model are algorithms for the driver’s action logic in controlling motion velocity, logic of gear shift control functioning regarding direction and moment of switching, for determining right-hand side of differential equations and for motion quality indicators. The model is realised in a form of an application software package, comprising sub-programmes for input data, for computerised motion simulation of cars with mechanical and hydro-mechanical – automatically controlled – transmission systems and for models of characteristic car routes.

scholarly journals An Open-Source Scale Model Platform for Teaching Autonomous Vehicle Technologies

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3850
Author(s):  
Bastien Vincke ◽  
Sergio Rodriguez Rodriguez Florez ◽  
Pascal Aubert
Keyword(s):  
Open Source ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Constrained Systems ◽  
Scale Model ◽  
Technical Students ◽  
Vehicle Technologies ◽  
Model Platform ◽  
High Level ◽  
Time And Energy

Emerging technologies in the context of Autonomous Vehicles (AV) have drastically evolved the industry’s qualification requirements. AVs incorporate complex perception and control systems. Teaching the associated skills that are necessary for the analysis of such systems becomes a very difficult process and existing solutions do not facilitate learning. In this study, our efforts are devoted to proposingan open-source scale model vehicle platform that is designed for teaching the fundamental concepts of autonomous vehicles technologies that are adapted to undergraduate and technical students. The proposed platform is as realistic as possible in order to present and address all of the fundamental concepts that are associated with AV. It includes all on-board components of a stand-alone system, including low and high level functions. Such functionalities are detailed and a proof of concept prototype is presented. A set of experiments is carried out, and the results obtained using this prototype validate the usability of the model for the analysis of time- and energy-constrained systems, as well as distributed embedded perception systems.

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