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 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.

Integration of GPS and Accelerometer Uncertainties to Improve the Estimation of the Pose of Autonomous Vehicles

2010 ◽  
Author(s):  
Wilson O. Achicanoy M. ◽  
Carlos F. Rodriguez H.
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Sampling Rate ◽  
System A ◽  
Accelerometer Signal ◽  
Gps Measurement ◽  
Global Positioning ◽  
The Individual ◽  
Uncertainty Models

Uncertainty fusion techniques based on Kalman filtering are commonly used to provide a better estimation of the state of a system. A comparison between three different methods to combine the sensor information in order to improve the estimation of the pose of an autonomous vehicle is presented. Two sensors and their uncertainty models are used to measure the observables states of a process: a Global Positioning System (GPS) and an accelerometer. Given that GPS has low sampling rate and the uncertainty of the position, calculated by double integration from the accelerometer signal, increases with time, first a resetting of the estimator based on accelerometer by the GPS measurement is done. Next, a second method makes the fusion of both sensor uncertainties to calculate the estimation. Finally, a double estimation is done, one for each sensor, and a estimated state is calculated joining the individual estimations. These methods are explained by a case study of a guided bomb.

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 Soluciones de conducción para vehículos autónomos, y propuestas adaptativas para establecer los tiempos de semáforos y elegir rutas

2019 ◽  
Vol 20 (2) ◽  
Author(s):  
José Gerardo Carrillo González
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Traffic Lights ◽  
Linear Path ◽  
Time Cycle ◽  
Adaptive Solutions ◽  
The Times ◽  
The Right

Two objectives are pursued in this article: 1) with adaptive solutions, improve the traffic flow by setting the time cycle of traffic lights at intersections and reduce the travel time by selecting the vehicles route (treated as separated problems). 2) Avoid driving conflicts among autonomous vehicles (which have defined trajectories) and these with a non-autonomous vehicle (which follows a free path). The traffic lights times are set with formulas that continuously recalculate the times values according the number of vehicles on the intersecting streets. For selecting the vehicles route an algorithm was developed, this calculates different routes (connected streets that conform a solution from the origin to the destination) and selects a route with low density. The results of the article indicate that the adaptive solutions to set the traffic lights times and to select the vehicles path, present a greater traffic flow and a shorter travel time, respectively, than conventional solutions. To avoid collisions among autonomous vehicles which follow a linear path, an algorithm was developed, this was successfully tested in different scenarios through simulations, besides the algorithm allows the interaction of a vehicle manually controlled (circulating without restrictions) with the autonomous vehicles. The algorithm regulates the autonomous vehicles acceleration (deceleration) and assigns the right of way among these and with the human controlled vehicle.

SwiVR-Car-Seat

2021 ◽  
Vol 5 (4) ◽  
pp. 1-26
Author(s):  
Mark Colley ◽  
Pascal Jansen ◽  
Enrico Rukzio ◽  
Jan Gugenheimer
Keyword(s):  
Interface Design ◽  
Autonomous Vehicles ◽  
User Study ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
User Input ◽  
The Road ◽  
Car Seat ◽  
Perceived Realism ◽  
Vehicle Motion

Autonomous vehicles provide new input modalities to improve interaction with in-vehicle information systems. However, due to the road and driving conditions, the user input can be perturbed, resulting in reduced interaction quality. One challenge is assessing the vehicle motion effects on the interaction without an expensive high-fidelity simulator or a real vehicle. This work presents SwiVR-Car-Seat, a low-cost swivel seat to simulate vehicle motion using rotation. In an exploratory user study (N=18), participants sat in a virtual autonomous vehicle and performed interaction tasks using the input modalities touch, gesture, gaze, or speech. Results show that the simulation increased the perceived realism of vehicle motion in virtual reality and the feeling of presence. Task performance was not influenced uniformly across modalities; gesture and gaze were negatively affected while there was little impact on touch and speech. The findings can advise automotive user interface design to mitigate the adverse effects of vehicle motion on the interaction.

scholarly journals Hybrid Multi-Sensor Integration for Static or Dynamic Obstacle Detection, Tracking and Classification for Autonomous Vehicle

2021 ◽  
Vol 23 (06) ◽  
pp. 1288-1293
Author(s):  
Dr. S. Rajkumar ◽  
◽  
Aklilu Teklemariam ◽  
Addisalem Mekonnen ◽  
◽  
...  
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Autonomous Vehicles ◽  
Detection System ◽  
Autonomous Vehicle ◽  
Obstacle Detection ◽  
Multiple Sensors ◽  
Environment Perception ◽  
Hybrid Sensors ◽  
The Individual

Autonomous Vehicles (AV) reduces human intervention by perceiving the vehicle’s location with respect to the environment. In this regard, utilization of multiple sensors corresponding to various features of environment perception yields not only detection but also enables tracking and classification of the object leading to high security and reliability. Therefore, we propose to deploy hybrid multi-sensors such as Radar, LiDAR, and camera sensors. However, the data acquired with these hybrid sensors overlaps with the wide viewing angles of the individual sensors, and hence convolutional neural network and Kalman Filter (KF) based data fusion framework was implemented with a goal to facilitate a robust object detection system to avoid collisions inroads. The complete system tested over 1000 road scenarios for real-time environment perception showed that our hardware and software configurations outperformed numerous other conventional systems. Hence, this system could potentially find its application in object detection, tracking, and classification in a real-time environment.

Modeling and Characterization of Driving Styles for Adaptive Cruise Control in Personalized Autonomous Vehicles

2017 ◽  
Author(s):  
Drew Bolduc ◽  
Longxiang Guo ◽  
Yunyi Jia
Keyword(s):  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Research Effort ◽  
Autonomous Vehicle ◽  
Individual Preference ◽  
Driver Model ◽  
Cruise Control ◽  
Critical Function ◽  
Driving Style ◽  
Safety And Reliability

For autonomous vehicles to gain widespread customer acceptance, safety and reliability are not nearly enough. Comfort and familiarity of the ride is also of essential importance. Because these are highly subjective factors, autonomous vehicles must be able to adopt personal driving styles to meet individual preference. The adaptive cruise control (ACC) system is a critical function performed by the autonomous vehicle and much research effort has been devoted to the development of a system that acts as a human driver. However, studies which investigate ACC models capable of learning a driving style are limited. In this paper, we propose a method to extract quantifiable parameters which represent a drivers’ driving style and apply these parameters to personalize the longitudinal control of an autonomous vehicle. We then develop a longitudinal driver model that integrates those parameters to enable the ACC system to mimic the driving style of the driver. Finally, the effectiveness of the extraction method and the driver model are obtained through simulation.

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.

scholarly journals Individual Predictors of Autonomous Vehicle Public Acceptance and Intention to Use: A Systematic Review of the Literature

2020 ◽  
Vol 6 (4) ◽  
pp. 106 ◽  
Author(s):  
Fahimeh Golbabaei ◽  
Tan Yigitcanlar ◽  
Alexander Paz ◽  
Jonathan Bunker
Keyword(s):  
Systematic Review ◽  
Autonomous Vehicles ◽  
Public Attitudes ◽  
Autonomous Vehicle ◽  
Influential Factors ◽  
Public Acceptance ◽  
Adoption Process ◽  
Intention To Use ◽  
People’S Attitudes ◽  
The Individual

Fully autonomous vehicles (AV) would potentially be one of the most disruptive technologies of our time. The extent of the prospective benefits of AVs is strongly linked to how widely they will be accepted and adopted. Monitoring and tracking of individuals’ reactions and intentions to use AVs are critical. The current study aims to explore and classify individual predictors (i.e., influential factors or determinants) of public acceptance of, and intention to use AVs, by conducting a systematic literature review and developing a conceptual framework to map out the individual influential factors that shape public attitudes towards AVs, which influence user acceptance and adoption preferences. This framework contains the key factors identified in the systematic review—i.e., demographic, psychological, and mobility behavior characteristics. The findings of the review disclose that public perceptions and adoption intentions vary significantly among different socio-demographic cohorts. Commuters value different aspects concerning AVs, which shape their intentions on acceptance and adoption. Thus, direct experience with AVs along with education and communication would be helpful to change people’s attitudes towards AVs in a positive way. The study informs urban and transport policymakers, managers, and planners, and helps in planning for a healthy AV adoption process with minimal societal disruption.

scholarly journals Exploring Personalised Autonomous Vehicles to Influence User Trust

2020 ◽  
Vol 12 (6) ◽  
pp. 1170-1186
Author(s):  
Xu Sun ◽  
Jingpeng Li ◽  
Pinyan Tang ◽  
Siyuan Zhou ◽  
Xiangjun Peng ◽  
...  
Keyword(s):  
Experimental Study ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Major Determinant ◽  
Automated System ◽  
Driving Style ◽  
Novel Approach ◽  
The Impact ◽  
User Trust

AbstractTrust is a major determinant of acceptance of an autonomous vehicle (AV), and a lack of appropriate trust could prevent drivers and society in general from taking advantage of such technology. This paper makes a new attempt to explore the effects of personalised AVs as a novel approach to the cognitive underpinnings of drivers’ trust in AVs. The personalised AV system is able to identify the driving behaviours of users and thus adapt the driving style of the AV accordingly. A prototype of a personalised AV was designed and evaluated in a lab-based experimental study of 36 human drivers, which investigated the impact of the personalised AV on user trust when compared with manual human driving and non-personalised AVs. The findings show that a personalised AV appears to be significantly more reliable through accepting and understanding each driver’s behaviour, which could thereby increase a user’s willingness to trust the system. Furthermore, a personalised AV brings a sense of familiarity by making the system more recognisable and easier for users to estimate the quality of the automated system. Personalisation parameters were also explored and discussed to support the design of AV systems to be more socially acceptable and trustworthy.

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