Published May 2019 | Version v1
Journal article

Improvement of traffic flux with introduction of a new lane-change protocol supported by Intelligent Traffic System

  • 1. Faculty of Engineering Sciences, Kyushu University (Japan)
  • 2. Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580 (Japan)

Description

A new Cellular Automata traffic model based on Revised S-NFS model was established, which considers traffic density ahead of a car in next 50 [m] and also accounts for a decision making process of whether a lane change should be tried or not so as to diminish the frequency of meaningless lane-changes. It intends to be applied as one of the protocols to improve traffic efficiency in premise with Intelligence Traffic System (ITS) that is able to provide information on traffic density next hundred meters in front of a focal vehicle. A series of systematic simulations reveals that the presented lane changing protocol enhances traffic flux vis-à-vis the conventional lane change rule based on the traditional incentive criterion and safe criterion. Social dilemma analysis suggests our new protocol mitigates a strong social dilemma encouraged by a competition between a cooperator; not intending any lane-changes and a defector; trying to lane-changes to minimize his own travel time.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2019.03.007

Additional details

Identifiers

DOI
10.1016/j.chaos.2019.03.007;
PII
S0960077919300670;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
122
Journal Page Range
p. 1-5
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54120496
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
AUTOMOBILES; COMPUTERIZED SIMULATION; DENSITY; METERS
Descriptors DEC
MEASURING INSTRUMENTS; PHYSICAL PROPERTIES; SIMULATION; VEHICLES

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.