assessment of freeway work zone safety with improved cellular automata model

Clicks: 97
ID: 252321
2014
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #19 of 22 articles by views in macworld-boulder

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
To accurately assess the safety of freeway work zones, this paper investigates the safety of vehicle lane change maneuvers with improved cellular automata model. Taking the traffic conflict and standard deviation of operating speed as the evaluation indexes, the study evaluates the freeway work zone safety. With improved deceleration probability in car-following raies and the addition of lanechanging rules under critical state, the lane-changing behavior under critical state is defined as a conflict count. Through 72 schemes of simulation runs, the possible states of the traffic flow are carefully studied. The results show that under the condition of constant saturation traffic conflict count and vehicle speed standard deviation reach their maximums when the mixed rate of heave vehicles is 40%. Meanwhile, in the case of constant heavy vehicles mix, traffic conflict count and vehicle speed standard deviation reach maximum values when saturation rate is 0. 75. Integrating ail simulation results, it is known the traffic safety in freeway work zones is classified into four levels : safe, relatively safe, relatively dangerous, and dangerous.
Reference Key
liang2014journalassessment Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Guohua Liang;Fengjing Wang;Wei Wang;Xiaoduan Sun;Wugong Wang
Journal macworld-boulder
Year 2014
DOI
10.1016/S2095-7564(15)30271-3
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.