Yuan Liao

Doktorand vid Fysisk resursteori

I am currently a postdoc in mobility data science at Chalmers University of Technology. I received my B.E. and M.S. degree in automotive engineering from Tsinghua Univ., Beijing, China, in 2013 and 2016, respectively. I received the Excellent Graduate Student Award and the Excellent Master Thesis Award in July 2016. I received Ph.D. degree from Chalmers University of Technology, Gothenburg, Sweden in 2021. My research vision is data-driven understanding of humans to empower future intelligent transportation. My active research interests include mobility patterns, sustainable mobility, transportation, and geographic data science.

Källa: orcid.org
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Visar 18 publikationer

2021

A Mobility Model for Synthetic Travel Demand from Sparse Individual Traces

Yuan Liao, Kristoffer Ek, Eric Wennerberg et al
Preprint
2021

Traffic Crash Characteristics in Shenzhen, China from 2014 to 2016

Guofa Li, Yuan Liao, Qiangqiang Guo et al
International Journal of Environmental Research and Public Health. Vol. 18 (3), p. 1-24
Artikel i vetenskaplig tidskrift
2021

Feasibility of estimating travel demand using geolocations of social media data

Yuan Liao, Sonia Yeh, Jorge Gil
Transportation. Vol. In Press
Artikel i vetenskaplig tidskrift
2020

Disparities in travel times between car and transit: Spatiotemporal patterns in cities

Yuan Liao, Jorge Gil, Rafael H. M. Pereira et al
Scientific Reports. Vol. 10 (1)
Artikel i vetenskaplig tidskrift
2020

How drivers respond to visual vs. auditory information in advisory traffic information systems

Minjuan Wang, Yuan Liao, Sus Lyckvi et al
Behaviour and Information Technology. Vol. 39 (12), p. 1308-1319
Artikel i vetenskaplig tidskrift
2019

Detection of road traffic participants using cost-effective arrayed ultrasonic sensors in low-speed traffic situations

Guofa Li, Shengbo Li, Ruobing Zou et al
Mechanical Systems and Signal Processing. Vol. 132 (1), p. 535-545
Artikel i vetenskaplig tidskrift
2019

From individual to collective behaviours: exploring population heterogeneity of human mobility based on social media data

Yuan Liao, Sonia Yeh, Gustavo S. Jeuken
EPJ Data Science. Vol. 8 (1)
Artikel i vetenskaplig tidskrift
2018

Understanding Driver Response Patterns to Mental Workload Increase in Typical Driving Scenarios

Yuan Liao, Guofa Li, Shengbo Li et al
IEEE Access
Artikel i vetenskaplig tidskrift
2018

Cross-regional driver-vehicle interaction design: An interview study on driving risk perceptions, decisions, and ADAS function preferences

Yuan Liao, Minjuan Wang, Lian Duan et al
IET Intelligent Transport Systems. Vol. 12 (8), p. 801-808
Artikel i vetenskaplig tidskrift
2018

Predictability in Human Mobility based on Geographical-boundary-free and Long-time Social Media Data

Yuan Liao, Sonia Yeh
2018 21st International Conference on Intelligent Transportation Systems (ITSC), p. 2068-2073
Paper i proceeding
2017

Decision Tree-Based Maneuver Prediction for Driver Rear-End Risk-Avoidance Behaviors in Cut-In Scenarios

M. Hu, Yuan Liao, W. Wang et al
Journal of Advanced Transportation, p. 1-12
Artikel i vetenskaplig tidskrift
2017

Context-Adaptive support information for truck drivers: An interview study on its contents priority

Yuan Liao, G. Li, Fang Chen
28th IEEE Intelligent Vehicles Symposium, IV 2017, Redondo Beach, United States, 11-14 June 2017, p. 1268-1273
Paper i proceeding
2017

Cross-regional Study on Driver Response Behaviour Patterns and System Acceptance with Triggered Forward Collision Warning

Yuan Liao, Lian Duan, Minjuan Wang et al
2017 IEEE Intelligent Vehicles Symposium, p. 565-570
Paper i proceeding
2016

Detection of Driver Cognitive Distraction: A Comparison Study of Stop-Controlled Intersection and Speed-Limited Highway

Yuan Liao, S.E. Li, W. Wang et al
IEEE Transactions on Intelligent Transportation Systems. Vol. 17 (6), p. 1628-1637
Artikel i vetenskaplig tidskrift
2016

Detection of driver cognitive distraction: An SVM based real-time algorithm and its comparison study in typical driving scenarios

Yuan Liao, Shengbo Li, G. Li et al
IEEE Intelligent Vehicles Symposium, Proceedings. 2016 IEEE Intelligent Vehicles Symposium, IV 2016; Gotenburg; Sweden; 19-22 June 2016. Vol. 2016-August (Art no 7535416), p. 394-399
Paper i proceeding

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Visar 1 forskningsprojekt

2017–2019

Hållbara städer: användande av stora datamängder för att förstå och hantera rörelsemönster och trafikstockningar

Sonia Yeh Fysisk resursteori
Yuan Liao Fysisk resursteori 2
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