Vehicle game lane-changing mechanism and strategy evolution based on trajectory data.

Dayi Qu, Kedong Wang, Shouchen Dai, Yicheng Chen, Shanning Cui, Yuxiang Yang

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Safety evaluation in the weaving segment between minor roads and U-turns on arterial roadways.Scientific reports · 2025
Article

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

6 authors.

Dayi QuSchool of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China.

Kedong WangSchool of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China. 18661831717@163.com.

Shouchen DaiSchool of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China.

Yicheng ChenSchool of Civil Engineering, Qingdao University of Technology, Qingdao, 266520, China.

Shanning CuiSchool of Civil Engineering, Qingdao University of Technology, Qingdao, 266520, China.

Yuxiang YangSchool of Civil Engineering, Qingdao University of Technology, Qingdao, 266520, China.

Funding

National Natural Science Foundation of China 52272311Qingdao West Coast New District College President's Fund GXXZJJ202301

6 · The paper itself

Abstract

To improve the safety of ramp vehicles changing lane and to shorten the merging distance, this paper explores the dynamic game interaction properties of vehicles merging and the consistency of vehicles' decision-making behaviors at the macro-microscopic levels. Using the exiD dataset and evolutionary game theory, the merging behavior of ramp vehicles is modeled to explore the effects of different driving states on the evolutionary convergence of strategies. Based on the game cost theory, the lane choice behavior of mainline vehicles is modeled. Validated by SUMO software, the results show that the model in this paper can significantly improve the safety of vehicle merging and reduce the merging distance. The mainline vehicles are more inclined to change lane and cut out in advance when facing the ramp vehicles under the influence of the change of advantage in the subsequent game.

Indexed as

Autonomous vehicleGame interaction propertiesLane-changing behaviorTrajectory data

Identifiers

PMID39924545

DOI10.1038/s41598-025-89567-z

PMCPMC11808085

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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.