Evidence map›Paper›PMID 40388501›Full record

ArticlePloS one2025

A bi-level dynamic emergency route planning system considering signal preemption control using CV technology.

Yulu Dai, Liang Hu, Shutong Zhou, Yanbin Liu, Aixi Yang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yulu DaiHangzhou Vocational and Technical College, Hangzhou, Zhejiang, China.ORCID https://orcid.org/0009-0002-2578-4377
Liang HuJiangsu Provincial Department of Transportation Planning and Research Center, Nanjing, Jiangsu, China.
Shutong ZhouHohai University, Nanjing, Jiangsu, China.ORCID https://orcid.org/0009-0005-5852-9091
Yanbin LiuTsinghua University, Beijing, Beijing, China.
Aixi YangHangzhou Vocational and Technical College, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emergency Vehicles (EVs) are of considerable significance in saving human lives and property damages. To promote the efficiency of emergency operation, signal preemption control could give priority to EVs heading toward the incident location. On the other hand, providing dynamic and precise route planning for EVs plays an important role in emergency rescue since traffic changes constantly. Furthermore, connected vehicle (CV) technology that incorporates advanced wireless communication technologies, offers a huge potential to promote the efficiency of EVs and maintain smooth traffic flow via collaborative optimization of routes and signals. This study presents a bi-level dynamic emergency route planning system considering signal preemption control, which builds on traffic flow combined with hierarchical bi-layer model predictive control (MPC), for more than one EV under partial CV environment. In this approach, the mobility of EVs is prioritized before decreasing the impact of EVs operation on normal traffic. In the upper layer, a road-level emergency route would be dynamically planned and updated after each time horizon, according to the network-wide traffic flow estimation under diverse CV market penetration ratios through loop detectors and Cellular-Vehicle-to-Everything (C-V2X) communication. In the lower layer, a lane-level emergency route that combined with signal preemption control would be planned to ensure the efficiency of EVs and reduce the adverse impact of signal preemption on normal traffic. In the end, a microscopic simulation environment for a real traffic network is carried out to test the effectiveness of the proposed system. The simulation results indicate that the proposed system provides reliable and practical emergency route planning and signal control services for EVs under different traffic flow conditions.

Indexed as

Accidents, TrafficEmergenciesWireless TechnologyAlgorithmsHumansModels, Theoretical

Identifiers

PMID40388501
PMCPMC12088061

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.