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

Schockenhoff, Ferdinand; Nehse, Hannes; Lienkamp, Markus

doi:10.3390/app10113946

Cited by 13 publications

(11 citation statements)

References 37 publications

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“…Furthermore, a comparison with driving data from BEV should be investigated to show to what extent the transferability of ICEV driving data to driving behavior in BEV can be guaranteed. Another future application of the method shown here is the representation of different driving styles for autonomous vehicles, which can be represented by changing acceleration rates and top speeds [18].…”

Section: Discussionmentioning

confidence: 99%

Compressed Driving Cycles Using Markov Chains for Vehicle Powertrain Design

Zähringer

Kalt

Lienkamp

2020

WEVJ

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In recent years, topics of digitalisation, urbanisation and sustainability are shaping future developments in the automotive industry and pose new challenges to the individual areas of vehicle development. In the design and simulation of multiple components in the vehicle, especially in powertrain, generically generated driving cycles play an important role since they reflect representative user behavior. Nowadays, driving cycles are mainly associated with the worldwide fuel consumption and emission tests, but they are nevertheless used in many fields of vehicle development. A design based on the currently used consumption and emission cycles proves to be unsuitable, especially for electric vehicles. This is reflected in the current discussion about the large discrepancy between the driving ranges achieved when using emission cycles and those under real driving conditions. In order to minimize the energy consumption of a vehicle, the main requirement is a good efficiency of the electric machine. Here, not the maximum efficiency of the machine is decisive, but the averaged overall system efficiency during real driving behavior. The electric machine must therefore be designed for the driving cycle. To optimize the use of electric machines in the future, the actual power requirements of future vehicle models must first be determined. In the course of this paper, a compressed vehicle class specific driving cycle will be created based on real driving data using Markov chains, which can be used for powertrain dimensioning.

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Section: Discussionmentioning

confidence: 99%

Compressed Driving Cycles Using Markov Chains for Vehicle Powertrain Design

Zähringer

Kalt

Lienkamp

2020

WEVJ

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“…The output variables represent the customer-relevant properties of an AV concept. Based on the overall vehicle properties defined by Schockenhoff et al [15], we proposed a total of 28 customer-relevant properties at the specification level by adapting existing customer-relevant properties [23,40,41] and adding new properties through studies and reports ( [42], p. 13), ( [43], p. 14), ( [44], p. 18), ( [45], p. 8), ( [46], p. 64). These are described inTable 3.…”

Section: Methodsmentioning

confidence: 99%

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

Schockenhoff

Zähringer

Brönner

et al. 2021

Systems

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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.

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“…The following three examples demonstrate how detailed research on subfunctions of an AVC can influence the VCD. Schockenhoff et al (2020b) deal with a new aspect of AVCs. Driving style is an important aspect to fulfill user needs in autonomous driven vehicles.…”

Section: Research On Specific Aspects Of Autonomous Drivingmentioning

confidence: 99%

User Need-Oriented Concept Development of Autonomous Vehicles

et al. 2021

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Vehicle 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.

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

Cited by 13 publications

References 37 publications

Compressed Driving Cycles Using Markov Chains for Vehicle Powertrain Design

Compressed Driving Cycles Using Markov Chains for Vehicle Powertrain Design

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

User Need-Oriented Concept Development of Autonomous Vehicles

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