Prediction of the meta-stability phase through analysis of driving behavior

Toshio Ito, Ryohei Kaneyasu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traffic jams are formed in three phases: the free travel phase, the meta-stability phase, in which allows unchanged travel speed with only vehicle density increased, and the traffic jam phase. Therefore, it can be considered that if the meta-stability phase can be detected, forecasting traffic jams becomes possible. Moreover, it can also be considered that drivers unconsciously change their driving behavior based on changes in the surrounding environment. This article proposes a driver model that forecasts traffic jams based on changes in driving behavior and that does not rely on traffic flow monitoring infrastructure. As a result of evaluation in driving simulators, it was understood that the distribution of steering and throttle input frequency changes based on changes in the travel phase. It is possible to distinguish these changes using neural networks, and it is possible to make this into a driver model that forecasts traffic jams. This article will discuss experiments regarding changes in driving behavior in each travel phase, and a driver model that forecasts traffic jams constructed based on analysis of the results of the experiments.

Original languageEnglish
Title of host publication21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World
PublisherIntelligent Transport Systems (ITS)
Publication statusPublished - 2014
Event21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014 - Detroit, United States
Duration: 2014 Sep 72014 Sep 11

Other

Other21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014
CountryUnited States
CityDetroit
Period14/9/714/9/11

Fingerprint

Phase stability
traffic behavior
traffic
driver
travel
Simulators
Experiments
Neural networks
Monitoring
experiment
neural network
infrastructure
monitoring
evaluation

Keywords

  • Congestion prediction
  • Driver behavior
  • Meta-stability phase

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Automotive Engineering
  • Transportation
  • Electrical and Electronic Engineering

Cite this

Ito, T., & Kaneyasu, R. (2014). Prediction of the meta-stability phase through analysis of driving behavior. In 21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World Intelligent Transport Systems (ITS).

Prediction of the meta-stability phase through analysis of driving behavior. / Ito, Toshio; Kaneyasu, Ryohei.

21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World. Intelligent Transport Systems (ITS), 2014.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ito, T & Kaneyasu, R 2014, Prediction of the meta-stability phase through analysis of driving behavior. in 21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World. Intelligent Transport Systems (ITS), 21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014, Detroit, United States, 14/9/7.
Ito T, Kaneyasu R. Prediction of the meta-stability phase through analysis of driving behavior. In 21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World. Intelligent Transport Systems (ITS). 2014
Ito, Toshio ; Kaneyasu, Ryohei. / Prediction of the meta-stability phase through analysis of driving behavior. 21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World. Intelligent Transport Systems (ITS), 2014.
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