Demand for intelligent vehicle safety systems in Europe

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

The demand for four intelligent vehicle safety systems (IVSSs) - emergency braking, speed alert, blind spot monitoring and lane keeping support - is analysed by constructing their demand curves (demand as a function of product price) based on data available from user interviews and a literature study. The study also provides a method for constructing linear and exponential demand curves of the systems from data gathered from user interviews. The estimated linear and exponential demand curves were tested by least-squares fitting to the data collected from user interviews. The mean absolute error was consistently larger for all of the systems studied here when using the linear instead of exponential model. This suggests that the exponential model reflects more accurately the demand for IVSSs than does the linear model.
Original languageEnglish
Pages (from-to)916-923
JournalIET Intelligent Transport Systems
Volume9
Issue number10
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

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Intelligent vehicle highway systems
Security systems
demand
Braking
interview
Monitoring
linear model
safety system
vehicle
Europe
monitoring

Keywords

  • Europe
  • emergency braking
  • exponential model
  • least-squares fitting
  • blind spot monitoring
  • speed alert
  • intelligent vehicle safety system demand
  • mean absolute error
  • lane keeping support

Cite this

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title = "Demand for intelligent vehicle safety systems in Europe",
abstract = "The demand for four intelligent vehicle safety systems (IVSSs) - emergency braking, speed alert, blind spot monitoring and lane keeping support - is analysed by constructing their demand curves (demand as a function of product price) based on data available from user interviews and a literature study. The study also provides a method for constructing linear and exponential demand curves of the systems from data gathered from user interviews. The estimated linear and exponential demand curves were tested by least-squares fitting to the data collected from user interviews. The mean absolute error was consistently larger for all of the systems studied here when using the linear instead of exponential model. This suggests that the exponential model reflects more accurately the demand for IVSSs than does the linear model.",
keywords = "Europe, emergency braking, exponential model, least-squares fitting, blind spot monitoring, speed alert, intelligent vehicle safety system demand, mean absolute error, lane keeping support",
author = "Risto {\"O}{\"o}rni",
note = "SDA: SHP:TransSmart Project code: 100624",
year = "2015",
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language = "English",
volume = "9",
pages = "916--923",
journal = "IET Intelligent Transport Systems",
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}

Demand for intelligent vehicle safety systems in Europe. / Öörni, Risto.

In: IET Intelligent Transport Systems, Vol. 9, No. 10, 2015, p. 916-923.

Research output: Contribution to journalArticleScientificpeer-review

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AB - The demand for four intelligent vehicle safety systems (IVSSs) - emergency braking, speed alert, blind spot monitoring and lane keeping support - is analysed by constructing their demand curves (demand as a function of product price) based on data available from user interviews and a literature study. The study also provides a method for constructing linear and exponential demand curves of the systems from data gathered from user interviews. The estimated linear and exponential demand curves were tested by least-squares fitting to the data collected from user interviews. The mean absolute error was consistently larger for all of the systems studied here when using the linear instead of exponential model. This suggests that the exponential model reflects more accurately the demand for IVSSs than does the linear model.

KW - Europe

KW - emergency braking

KW - exponential model

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KW - blind spot monitoring

KW - speed alert

KW - intelligent vehicle safety system demand

KW - mean absolute error

KW - lane keeping support

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