PMID- 38489329
OWN - NLM
STAT- MEDLINE
DCOM- 20240318
LR  - 20240318
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 19
IP  - 3
DP  - 2024
TI  - A dynamic traffic signal scheduling system based on improved greedy algorithm.
PG  - e0298417
LID - 10.1371/journal.pone.0298417 [doi]
LID - e0298417
AB  - Urbanization has led to accelerated traffic congestion, posing a significant 
      obstacle to urban development. Traditional traffic signal scheduling methods are 
      often inefficient and cumbersome, resulting in unnecessary waiting times for 
      vehicles and pedestrians, exacerbating the traffic situation. To address this 
      issue, this article proposes a dynamic traffic signal scheduling system based on 
      an improved greedy algorithm. Unlike conventional approaches, we introduce a 
      reward function and a cost model to ensure fair scheduling plans. A constraint 
      function is also established, and the traffic signal scheduling is iterated 
      through the feasible matrix using the greedy algorithm to simplify the 
      decision-making process and enhance solution efficiency. Moreover, an emergency 
      module is integrated to prioritize special emergency vehicles, reducing their 
      response time during emergencies. To validate the effectiveness of our dynamic 
      traffic signal scheduling system, we conducted simulation experiments using the 
      Simulation of Urban Mobility (SUMO) traffic simulation suite and the SUMO traffic 
      control interface Traci. The results indicate that our system significantly 
      improves intersection throughput and adapts well to various traffic conditions, 
      effectively resolving urban traffic congestion while ensuring fair scheduling 
      plans.
CI  - Copyright: (c) 2024 Sun et al. This is an open access article distributed under the 
      terms of the Creative Commons Attribution License, which permits unrestricted 
      use, distribution, and reproduction in any medium, provided the original author 
      and source are credited.
FAU - Sun, Guangling
AU  - Sun G
AD  - School of Electronic and Information Engineering, Anhui Jianzhu University, 
      Hefei, China.
AD  - Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei University 
      of Technology, Hefei, China.
FAU - Qi, Rui
AU  - Qi R
AUID- ORCID: 0009-0009-4162-7452
AD  - School of Electronic and Information Engineering, Anhui Jianzhu University, 
      Hefei, China.
FAU - Liu, Yulong
AU  - Liu Y
AD  - School of Electronic and Information Engineering, Anhui Jianzhu University, 
      Hefei, China.
FAU - Xu, Feng
AU  - Xu F
AD  - School of Electronic and Information Engineering, Anhui Jianzhu University, 
      Hefei, China.
LA  - eng
PT  - Journal Article
DEP - 20240315
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Humans
MH  - *Algorithms
MH  - Computer Simulation
MH  - Ambulances
MH  - *Pedestrians
PMC - PMC10942090
COIS- The authors have declared that no competing interests exist.
EDAT- 2024/03/15 18:42
MHDA- 2024/03/18 06:42
PMCR- 2024/03/15
CRDT- 2024/03/15 13:53
PHST- 2023/08/11 00:00 [received]
PHST- 2024/01/24 00:00 [accepted]
PHST- 2024/03/18 06:42 [medline]
PHST- 2024/03/15 18:42 [pubmed]
PHST- 2024/03/15 13:53 [entrez]
PHST- 2024/03/15 00:00 [pmc-release]
AID - PONE-D-23-25729 [pii]
AID - 10.1371/journal.pone.0298417 [doi]
PST - epublish
SO  - PLoS One. 2024 Mar 15;19(3):e0298417. doi: 10.1371/journal.pone.0298417. 
      eCollection 2024.