Siyuan Gong

Prof. Siyuan Gong

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2018 in Transportation Research Part B: Methodological
Verified
Journal Article
Closed access
SGSiyuan Gong
Siyuan Gong
LDLili Du
Lili Du

1 December 2016 in Transportation Research Part B: Methodological
Verified
Journal Article
Closed access
SGSiyuan Gong
Siyuan Gong
JSJinglai Shen
Jinglai Shen
LDLili Du
Lili Du

1 April 2020 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Closed access
CWChaojie Wang
Chaojie Wang
SGSiyuan Gong
Siyuan Gong
AZAnye Zhou
Anye Zhou
TLTao Li
Tao Li
SPSrinivas Peeta
Srinivas Peeta

15 May 2019 in Transportation Research Record: Journal of the Transportation Research Board
Verified
Journal Article
Closed access
PDF file
SGSiyuan Gong
Siyuan Gong
AZAnye Zhou
Anye Zhou
SPSrinivas Peeta
Srinivas Peeta
Vehicle-to-vehicle communications can be unreliable as interference causes communication failures. Thereby, the information flow topology (IFT) for a platoon of connected autonomous vehicles (CAVs) can vary dynamically. This limits existing cooperative adaptive cruise control (CACC) strategies as most of them assume a fixed IFT. To address this problem, a CACC scheme is introduced that considers a dynamic information flow topology (CACC-DIFT) for CAV platoons. An adaptive proportional-derivative (PD) controller under a two-predecessor-following IFT is proposed to attenuate the negative effects when communication failures occur. The parameters of the PD controller are determined to ensure the string stability of the platoon. Furthermore, the proposed PD controller also factors the performance of individual vehicles. Hence, when communication failure occurs, the system will switch to a certain type of CACC instead of degenerating to adaptive cruise control, which improves the platoon control performance considerably. The effectiveness of the proposed CACC-DIFT is validated through numerical experiments based on Next Generation Simulation (NGSIM) field data. Simulation results indicate that the proposed CACC-DIFT design outperforms CACC based on a predetermined information flow topology.

1 October 2019 in Transportation Research Part B: Methodological
Verified
Journal Article
Closed access
JWJian Wang
Jian Wang
SGSiyuan Gong
Siyuan Gong
SPSrinivas Peeta
Srinivas Peeta
LLLili Lu
Lili Lu

7 December 2022 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Closed access
SSShuai Su
Shuai Su
JSJiangfeng She
Jiangfeng She
DWDi Wang
Di Wang
SGSiyuan Gong
Siyuan Gong
Yang ZhouYang Zhou
Yang Zhou