A Car2X Sensor Model for Virtual Development of Automated Driving

Research output: Contribution to specialist publicationArticleResearchpeer-review

Abstract

Automated driving requires a reliable digital representation of the environment, which is achieved by various vehicle sensors. Wireless devices for communication between vehicles and infrastructure (Car2X communication) provide additional data beyond the vehicle’s sensor range. In order to reduce the amount of on-road testing, there has been an increased use of numerical simulation in the development of automated driving functions, which demands accurate simulation models for the sensors involved. The present research deals with the development of Car2X sensor models for conceptual, automated driving investigations based on relatively simple yet computationally efficient mathematical models featuring parameters derived from on-road hardware testing. For analysis purposes, variations in range and reliability in different driving situations were measured and depicted in Google Earth. For the sensor model, a combination of geometric and stochastic models was chosen. The modeling is based on a link budget calculation that considers system and path losses, where wave propagation is described using Nakagami probability density functions. For intersections, an additional term is added to account for the path loss with geometric parameters of the intersection. After model parametrization, an evaluation was conducted. In addition, as a sample case, Car2X was added to an adaptive cruise control, and the improved functionality was demonstrated using vehicle dynamics simulation. This extended adaptive cruise control used information from the indicator of surrounding vehicles to react faster to lane changes by these vehicles.
Original languageEnglish
Number of pages12
Volume14
No.5
Specialist publicationInternational Journal of Advanced Robotic Systems
PublisherSAGE Publications Ltd
DOIs
Publication statusPublished - 7 Sep 2017

Fingerprint

Sensors
Adaptive cruise control
Communication
Computer simulation
Testing
Stochastic models
Wave propagation
Probability density function
Earth (planet)
Mathematical models
Hardware

Keywords

  • Car2X
  • sensor models
  • ADAS
  • automated driving
  • virtual development

ASJC Scopus subject areas

  • Automotive Engineering

Fields of Expertise

  • Mobility & Production

Treatment code (Nähere Zuordnung)

  • Application

Cite this

A Car2X Sensor Model for Virtual Development of Automated Driving. / Eichberger, Arno; Markovic, Gerald; Magosi, Zoltan Ferenc; Rogic, Branko; Lex, Cornelia; Samiee, Sajjad.

In: International Journal of Advanced Robotic Systems, Vol. 14, No. 5, 07.09.2017.

Research output: Contribution to specialist publicationArticleResearchpeer-review

@misc{dc960c3dd90945ba97b749ad78f49f5f,
title = "A Car2X Sensor Model for Virtual Development of Automated Driving",
abstract = "Automated driving requires a reliable digital representation of the environment, which is achieved by various vehicle sensors. Wireless devices for communication between vehicles and infrastructure (Car2X communication) provide additional data beyond the vehicle’s sensor range. In order to reduce the amount of on-road testing, there has been an increased use of numerical simulation in the development of automated driving functions, which demands accurate simulation models for the sensors involved. The present research deals with the development of Car2X sensor models for conceptual, automated driving investigations based on relatively simple yet computationally efficient mathematical models featuring parameters derived from on-road hardware testing. For analysis purposes, variations in range and reliability in different driving situations were measured and depicted in Google Earth. For the sensor model, a combination of geometric and stochastic models was chosen. The modeling is based on a link budget calculation that considers system and path losses, where wave propagation is described using Nakagami probability density functions. For intersections, an additional term is added to account for the path loss with geometric parameters of the intersection. After model parametrization, an evaluation was conducted. In addition, as a sample case, Car2X was added to an adaptive cruise control, and the improved functionality was demonstrated using vehicle dynamics simulation. This extended adaptive cruise control used information from the indicator of surrounding vehicles to react faster to lane changes by these vehicles.",
keywords = "Car2X, sensor models, ADAS, automated driving, virtual development, Car2X, sensor models, ADAS, automated driving, virtual development",
author = "Arno Eichberger and Gerald Markovic and Magosi, {Zoltan Ferenc} and Branko Rogic and Cornelia Lex and Sajjad Samiee",
year = "2017",
month = "9",
day = "7",
doi = "https://doi.org/10.1177/1729881417725625",
language = "English",
volume = "14",
journal = "International Journal of Advanced Robotic Systems",
issn = "1729-8806",
publisher = "SAGE Publications Ltd",
address = "United Kingdom",

}

TY - GEN

T1 - A Car2X Sensor Model for Virtual Development of Automated Driving

AU - Eichberger, Arno

AU - Markovic, Gerald

AU - Magosi, Zoltan Ferenc

AU - Rogic, Branko

AU - Lex, Cornelia

AU - Samiee, Sajjad

PY - 2017/9/7

Y1 - 2017/9/7

N2 - Automated driving requires a reliable digital representation of the environment, which is achieved by various vehicle sensors. Wireless devices for communication between vehicles and infrastructure (Car2X communication) provide additional data beyond the vehicle’s sensor range. In order to reduce the amount of on-road testing, there has been an increased use of numerical simulation in the development of automated driving functions, which demands accurate simulation models for the sensors involved. The present research deals with the development of Car2X sensor models for conceptual, automated driving investigations based on relatively simple yet computationally efficient mathematical models featuring parameters derived from on-road hardware testing. For analysis purposes, variations in range and reliability in different driving situations were measured and depicted in Google Earth. For the sensor model, a combination of geometric and stochastic models was chosen. The modeling is based on a link budget calculation that considers system and path losses, where wave propagation is described using Nakagami probability density functions. For intersections, an additional term is added to account for the path loss with geometric parameters of the intersection. After model parametrization, an evaluation was conducted. In addition, as a sample case, Car2X was added to an adaptive cruise control, and the improved functionality was demonstrated using vehicle dynamics simulation. This extended adaptive cruise control used information from the indicator of surrounding vehicles to react faster to lane changes by these vehicles.

AB - Automated driving requires a reliable digital representation of the environment, which is achieved by various vehicle sensors. Wireless devices for communication between vehicles and infrastructure (Car2X communication) provide additional data beyond the vehicle’s sensor range. In order to reduce the amount of on-road testing, there has been an increased use of numerical simulation in the development of automated driving functions, which demands accurate simulation models for the sensors involved. The present research deals with the development of Car2X sensor models for conceptual, automated driving investigations based on relatively simple yet computationally efficient mathematical models featuring parameters derived from on-road hardware testing. For analysis purposes, variations in range and reliability in different driving situations were measured and depicted in Google Earth. For the sensor model, a combination of geometric and stochastic models was chosen. The modeling is based on a link budget calculation that considers system and path losses, where wave propagation is described using Nakagami probability density functions. For intersections, an additional term is added to account for the path loss with geometric parameters of the intersection. After model parametrization, an evaluation was conducted. In addition, as a sample case, Car2X was added to an adaptive cruise control, and the improved functionality was demonstrated using vehicle dynamics simulation. This extended adaptive cruise control used information from the indicator of surrounding vehicles to react faster to lane changes by these vehicles.

KW - Car2X

KW - sensor models

KW - ADAS

KW - automated driving

KW - virtual development

KW - Car2X

KW - sensor models

KW - ADAS

KW - automated driving

KW - virtual development

UR - http://journals.sagepub.com/eprint/HGHjAtBXjnB4vSpjxZR4/full

U2 - https://doi.org/10.1177/1729881417725625

DO - https://doi.org/10.1177/1729881417725625

M3 - Article

VL - 14

JO - International Journal of Advanced Robotic Systems

JF - International Journal of Advanced Robotic Systems

SN - 1729-8806

PB - SAGE Publications Ltd

ER -