The University of Queensland

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

Sun, Jie and Kim, Jiwon (2021). Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks. Transportation Research. Part C: Emerging Technologies, 128 103114, 103114. doi: 10.1016/j.trc.2021.103114

Integrated simulation platform for conventional, connected and automated driving: a design from cyber–physical systems perspective

Jia, Dongyao, Sun, Jie, Sharma, Anshuman, Zheng, Zuduo and Liu, Bingyi (2021). Integrated simulation platform for conventional, connected and automated driving: a design from cyber–physical systems perspective. Transportation Research Part C: Emerging Technologies, 124 102984, 1-19. doi: 10.1016/j.trc.2021.102984

The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based controller

Sun, Jie, Zheng, Zuduo and Sun, Jian (2020). The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based controller. Transportation Research Part B: Methodological, 142, 58-83. doi: 10.1016/j.trb.2020.10.004

Investigating the long- and short-term driving characteristics and incorporating them into car-following models

Chen, Xiaoyun, Sun, Jian, Ma, Zian, Sun, Jie and Zheng, Zuduo (2020). Investigating the long- and short-term driving characteristics and incorporating them into car-following models. Transportation Research Part C: Emerging Technologies, 117 102698, 102698. doi: 10.1016/j.trc.2020.102698

Simultaneous modeling of car-following and lane-changing behaviors using deep learning

Zhang, Xiaohui, Sun, Jie, Qi, Xiao and Sun, Jian (2019). Simultaneous modeling of car-following and lane-changing behaviors using deep learning. Transportation Research Part C: Emerging Technologies, 104, 287-304. doi: 10.1016/j.trc.2019.05.021

A car-following model considering asymmetric driving behavior based on long short-term memory neural networks

Huang, Xiuling, Sun, Jie and Sun, Jian (2018). A car-following model considering asymmetric driving behavior based on long short-term memory neural networks. Transportation Research Part C: Emerging Technologies, 95, 346-362. doi: 10.1016/j.trc.2018.07.022

Stability analysis methods and their application to car-following models in conventional and connected environments

Sun, Jie, Zheng, Zuduo and Sun, Jian (2018). Stability analysis methods and their application to car-following models in conventional and connected environments. Transportation Research Part B: Methodological, 109 (2018), 212-237. doi: 10.1016/j.trb.2018.01.013

Real-time crash prediction on urban expressways: identification of key variables and a hybrid support vector machine model

Sun, Jie and Sun, Jian (2016). Real-time crash prediction on urban expressways: identification of key variables and a hybrid support vector machine model. IET Intelligent Transport Systems, 10 (5), 331-337. doi: 10.1049/iet-its.2014.0288

Capacity estimation model on weaving segments of urban expressway

Sun, Jian, Hu, Jia-Qi and Sun, Jie (2016). Capacity estimation model on weaving segments of urban expressway. Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, 29 (4), 114-122.

Study on traffic characteristics for a typical expressway on-ramp bottleneck considering various merging behaviors

Sun, Jian, Sun, Jie and Li, Zhipeng (2015). Study on traffic characteristics for a typical expressway on-ramp bottleneck considering various merging behaviors. Physica A: Statistical Mechanics and its Applications, 440, 57-67. doi: 10.1016/j.physa.2015.08.007

A dynamic Bayesian network model for real-time crash prediction using traffic speed conditions data

Sun, Jie and Sun, Jian (2015). A dynamic Bayesian network model for real-time crash prediction using traffic speed conditions data. Transportation Research Part C: Emerging Technologies, 54, 176-186. doi: 10.1016/j.trc.2015.03.006

Key variables identification and proactive assessment of real-time traffic flow accident risk on urban expressway

Jia, Fengyuan, Sun, Jie and Sun, Jian (2015). Key variables identification and proactive assessment of real-time traffic flow accident risk on urban expressway. Tongji Daxue Xuebao/Journal of Tongji University, 43 (2). doi: 10.11908/j.issn.0253-374x.2015.02.009

Proactive assessment of real-time traffic flow accident risk on urban expressway

Sun, Jian and Sun, Jie (2014). Proactive assessment of real-time traffic flow accident risk on urban expressway. Tongji Daxue Xuebao/Journal of Tongji University, 42 (6), 873-879. doi: 10.3969/j.issn.0253-374x.2014.06.008

Use of support vector machine models for real-time prediction of crash risk on urban expressways

Sun, Jian, Sun, Jie and Chen, Peng (2014). Use of support vector machine models for real-time prediction of crash risk on urban expressways. Transportation Research Record: Journal of the Transportation Research Board, 2432 (1), 91-98. doi: 10.3141/2432-11

Understanding the trigger of breakdown at tunnel sag section and exploring the cause with an improved car-following model

Ye, Yingjun, Sun, Jie and Sun, Jian (2020). Understanding the trigger of breakdown at tunnel sag section and exploring the cause with an improved car-following model. COTA International Conference of Transportation Professionals, Xi'an, China, 14-16 August 2020. Reston, VA, United States: American Society of Civil Engineers (ASCE). doi: 10.1061/9780784483053.375

Investigating the oscillation characteristics and mitigating its impact with low-penetration connected and automated vehicles

Sun, Jie and Sun, Jian (2018). Investigating the oscillation characteristics and mitigating its impact with low-penetration connected and automated vehicles. 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, United States, 4 - 7 November 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ITSC.2018.8569492

Queuing analysis at toll stations under the toll-free policy in holidays in Shanghai

He, Qing, Li, Ye, Li, Jian, Liang, Xiucheng, Shen, Jianfneg and Sun, Jie (2018). Queuing analysis at toll stations under the toll-free policy in holidays in Shanghai. 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, United States, 4 - 7 November 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ITSC.2018.8569390