Stochastic programming model for oversaturated intersection signal timing

By Yue Tong, Lei Zhao, Li Li, Yi Zhang. 2015

60 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/bc3e15843507046dba80f3846e844f967f3f61e9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Li Li
2. Xuegang (Jeff) Ban
3. Qiangqiang Guo
4. Yisheng Lv

In Control and Systems Engineering

1. Li Li
2. Xuegang (Jeff) Ban
3. Qiangqiang Guo
4. Yisheng Lv
5. Li Li

In Transportation

1. Li Li
2. Xuegang (Jeff) Ban
3. Qiangqiang Guo
4. Yisheng Lv

Citations in the corpus

• Traffic signal timing via deep reinforcement learning (2016, background): “As indicated in [25] and [26], a larger R2 value indicates more balanced queues.”
• Urban traffic signal control with connected and automated vehicles: A survey (2019, background): “The optimal solutions are speed guidances dedicated for certain objectives, such as to avoid being caught by red lights (Li et al., 2012) or save fuel by driving in economic modes (Katsaros et al., 2011; Schuricht et al., 2011; Tang et al., 2018; Ubiergo and Jin, 2016; Wu et al., 2010).”