Reduction of driver stress using AmI technology while driving in motorway merging sections

Kashif Zia, Andreas Riener, Alois Ferscha

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

High average intensity of traffic and problems like traffic congestions, road safety, etc. are challenging problem striking highway operators in these days. With the broad application of intelligent transport systems (ITS), particularly for the most dense street sections, some of these problems can be minimized or even solved; supplementary great potential is attributed to applications based on state-of-the art technology like car-to-x communication, for instance by extending an individuals ``field of vision'' by observations taken from all the vehicles in front. In this work we present a simulation-based approach for improving driving experience and increasing road safety in merging sections by redirecting vehicles in advance according to a negotiation of requirements and desires of the flowing traffic on the main road and cars merging from the entrance lane. The simulation experiments performed in a cellular automaton based environment were data driven and on real scale, using traffic flow data on a minute-by-minute basis from a large urban motorway in a main city of the European Union. Our results have shown that the application of AmI technology has potential to influence driver's behavior (seamlessly invoking for a lane change well before an abrupt merging point) resulting in reduction in panic, particularly for sections with limited range of view.
Original languageEnglish
Title of host publicationFirst International Joint Conference on Ambient Intelligence (AmI-10), November 10-12, 2010, Malaga, Spain
Editors Boris de Ruyter, Reiner Wichert, David V. Keyson, Panos Markopoulos, Norbert Streitz, Monica Divitini, Nikolaos Georgantas, Antonio Mana Gomez
Place of PublicationHeidelberg
PublisherSpringer
Pages127-137
Number of pages11
Volume6439
ISBN (Print)3642169163, 9783642169168
DOIs
Publication statusPublished - Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6439 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fields of science

  • 102 Computer Sciences
  • 102009 Computer simulation
  • 102013 Human-computer interaction
  • 102019 Machine learning
  • 102020 Medical informatics
  • 102021 Pervasive computing
  • 102022 Software development
  • 102025 Distributed systems
  • 202017 Embedded systems
  • 211902 Assistive technologies
  • 211912 Product design

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