scholarly journals Evaluation of cell phone induced driver behavior at a type II dilemma zone

2018 ◽  
Vol 5 (1) ◽  
pp. 1436927 ◽  
Author(s):  
Ziaur Rahman ◽  
Diana Martinez ◽  
Nadia Martinez ◽  
Zirun Zhang ◽  
Arezoo Memarian ◽  
...  
Author(s):  
David S. Hurwitz ◽  
Haizhong Wang ◽  
Michael A. Knodler ◽  
Daiheng Ni ◽  
Derek Moore

2016 ◽  
Vol 96 ◽  
pp. 271-273 ◽  
Author(s):  
Linda Ng Boyle ◽  
Susan Chrysler ◽  
Matthew Karlaftis

Author(s):  
Joseph B. Claveria ◽  
Salvador Hernandez ◽  
Jason C. Anderson ◽  
Eric L. Jessup

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Zhaosheng Yang ◽  
Xiujuan Tian ◽  
Wei Wang ◽  
Xiyang Zhou ◽  
Hongmei Liang

Vehicles are often caught in dilemma zone when they approach signalized intersections in yellow interval. The existence of dilemma zone which is significantly influenced by driver behavior seriously affects the efficiency and safety of intersections. This paper proposes the driver behavior models in yellow interval by logistic regression and fuzzy decision tree modeling, respectively, based on camera image data. Vehicle’s speed and distance to stop line are considered in logistic regression model, which also brings in a dummy variable to describe installation of countdown timer display. Fuzzy decision tree model is generated by FID3 algorithm whose heuristic information is fuzzy information entropy based on membership functions. This paper concludes that fuzzy decision tree is more accurate to describe driver behavior at signalized intersection than logistic regression model.


PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247453
Author(s):  
Wenjun Li ◽  
Lidong Tan ◽  
Ciyun Lin

Driver behavior is considered one of the most important factors in the genesis of dilemma zones and the safety of driver-vehicle-environment systems. An accurate driver behavior model can improve the traffic signal control efficiency and decrease traffic accidents in signalized intersections. This paper uses a mathematical modeling method to study driver behavior in a dilemma zone based on stochastic model predictive control (SMPC), along with considering the dynamic characteristics of human cognition and execution, aiming to provide a feasible solution for modeling driver behavior more accurately and potentially improving the understanding of driver-vehicle-environment systems in dilemma zones. This paper explores the modeling framework of driver behavior, including the perception module, decision-making module, and operation module. The perception module is proposed to stimulate the ability to perceive uncertainty and select attention in the dilemma zone. An SMPC-based driver control modeling method is proposed to stimulate decision-making behavior in the dilemma zone. The operation module is proposed to stimulate the execution ability of the driver. Finally, CarSim, the well-known vehicle dynamics analysis software package, is used to verify the proposed models of this paper. The simulation results show that the SMPC-based driver behavior model can effectively and accurately reflect the vehicle motion and dynamics under driving in the dilemma zone.


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