Energy efficient driving in dynamic environment: Considering other traffic participants and overtaking possibility

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

This chapter studies energy efficient driving of (semi)autonomous electric vehicles operating in a dynamic environment with other traffic participants on a unidirectional, multi-lane road. This scenario is considered to be a so called hard problem, as constraints imposed are varying in time and space. Neglecting the constraints imposed from the surrounding traffic, the generation of an energy optimal speed trajectory may lead to bad results, with the risk of low driver acceptance when applied in a real driving environment. An existing approach satisfies constraints from surrounding traffic by modifying an existing unconstrained trajectory. In contrast to this, the proposed approach incorporates a leading vehicle’s motion as constraint in order to generate a new optimal speed trajectory in a global optimal sense. First simulation results show that energy optimal driving considering other vehicle participants is important. Even in simple setups significantly (8%) less energy is consumed at only 1.3% travelling time prolongation compared to the best constant speed driving strategy. Additionally, the proposed driving strategy is using 4.5% less energy and leads to 1.6% shorter travelling time compared to the existing overtaking approach. Using simulation studies, the proposed energy optimal driving strategy is analyzed in different scenarios.
Original languageEnglish
Title of host publicationComprehensive Energy Management – Eco Routing & Velocity Profiles
Place of PublicationCham
PublisherSpringer International Publishing AG
Pages61
Number of pages20
Volume1
Edition1
ISBN (Electronic)978-3-319-53165-6
ISBN (Print)978-3-319-53164-9
Publication statusPublished - 2017

Publication series

NameSpringerBriefs in Applied Sciences and Technology
PublisherSpringer
ISSN (Print)2191-530X

Fingerprint

Trajectories
Electric vehicles

Keywords

  • Car following
  • Ecodriving
  • Optimal speed trajectory
  • Overtaking

Cite this

Ajanovic, Z., Stolz, M., & Horn, M. (2017). Energy efficient driving in dynamic environment: Considering other traffic participants and overtaking possibility. In Comprehensive Energy Management – Eco Routing & Velocity Profiles (1 ed., Vol. 1, pp. 61). [4] (SpringerBriefs in Applied Sciences and Technology). Cham: Springer International Publishing AG .

Energy efficient driving in dynamic environment: Considering other traffic participants and overtaking possibility. / Ajanovic, Zlatan; Stolz, Michael; Horn, Martin.

Comprehensive Energy Management – Eco Routing & Velocity Profiles. Vol. 1 1. ed. Cham : Springer International Publishing AG , 2017. p. 61 4 (SpringerBriefs in Applied Sciences and Technology).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Ajanovic, Z, Stolz, M & Horn, M 2017, Energy efficient driving in dynamic environment: Considering other traffic participants and overtaking possibility. in Comprehensive Energy Management – Eco Routing & Velocity Profiles. 1 edn, vol. 1, 4, SpringerBriefs in Applied Sciences and Technology, Springer International Publishing AG , Cham, pp. 61.
Ajanovic Z, Stolz M, Horn M. Energy efficient driving in dynamic environment: Considering other traffic participants and overtaking possibility. In Comprehensive Energy Management – Eco Routing & Velocity Profiles. 1 ed. Vol. 1. Cham: Springer International Publishing AG . 2017. p. 61. 4. (SpringerBriefs in Applied Sciences and Technology).
Ajanovic, Zlatan ; Stolz, Michael ; Horn, Martin. / Energy efficient driving in dynamic environment: Considering other traffic participants and overtaking possibility. Comprehensive Energy Management – Eco Routing & Velocity Profiles. Vol. 1 1. ed. Cham : Springer International Publishing AG , 2017. pp. 61 (SpringerBriefs in Applied Sciences and Technology).
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AB - This chapter studies energy efficient driving of (semi)autonomous electric vehicles operating in a dynamic environment with other traffic participants on a unidirectional, multi-lane road. This scenario is considered to be a so called hard problem, as constraints imposed are varying in time and space. Neglecting the constraints imposed from the surrounding traffic, the generation of an energy optimal speed trajectory may lead to bad results, with the risk of low driver acceptance when applied in a real driving environment. An existing approach satisfies constraints from surrounding traffic by modifying an existing unconstrained trajectory. In contrast to this, the proposed approach incorporates a leading vehicle’s motion as constraint in order to generate a new optimal speed trajectory in a global optimal sense. First simulation results show that energy optimal driving considering other vehicle participants is important. Even in simple setups significantly (8%) less energy is consumed at only 1.3% travelling time prolongation compared to the best constant speed driving strategy. Additionally, the proposed driving strategy is using 4.5% less energy and leads to 1.6% shorter travelling time compared to the existing overtaking approach. Using simulation studies, the proposed energy optimal driving strategy is analyzed in different scenarios.

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