Improvement of traffic flux with introduction of a new lane-change protocol supported by Intelligent Traffic System
Creators
- 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.2019.03.007Additional 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.