Development and Evaluation of a Cooperative Vehicle Intersection Control Algorithm Under the Connected Vehicles Environment

By Joyoung Lee, Byungkyu Brian Park. IEEE transactions on intelligent transportation systems (Print), 2012

735 citations recorded by the source corpus.

Subfields: Automotive Engineering, Control and Systems Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/f9bbc70f2c86bd0b18012a355f3a5127ce669b9e

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In Automotive Engineering

In Control and Systems Engineering

In Safety, Risk, Reliability and Quality

Citations in the corpus

Cooperative Collision Avoidance at Intersections: Algorithms and Experiments (2013, background): “More recently, work that employs job-scheduling techniques [8], [17] and optimal control [19] for ICA has appeared.”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, methodology): “For the optimal control methods, the total travel time [529], [530], the vehicle overlaps [531], [532] or multi-objective [533], [534] of all the vehicles within the control intersection is optimized to reduce the total vehicle travel time and fuel consumption.”
A Survey on the Coordination of Connected and Automated Vehicles at Intersections and Merging at Highway On-Ramps (2017, methodology): “Intersection coordination: This approach was first proposed by Lee and Park in [48] where they considered the case of a two-roads intersection with two lanes and turning capabilities using of a phase conflict map as a part of the problem formulation.”
Automated and Cooperative Vehicle Merging at Highway On-Ramps (2017, positive): “Dresner and Stone [9], Au and Stone [10], de la Fortelle [11], Huang et al. [12] and Zhang et al. [13] proposed the use of reservation schemes.”
A Survey of the Connected Vehicle Landscape—Architectures, Enabling Technologies, Applications, and Development Areas (2017, positive): “One study shows a 99% stop delay reduction, 33% total travel time reduction and 44% reduction in C O2 emission and fuel consumption relative to business as usual [133].”
Cooperative Intersection Management: A Survey (2016, background): “VRU detection and collision avoidance methods form one important issue while integration of VRUs into the CIM framework forms another challenging issue.”
A Review of Motion Planning Techniques for Automated Vehicles (2016, background): “Others consider the uncertainty in data acquisition [108], communications [109] and even future behavior prediction [110] to avoid situations like the MITCornell collision in the Darpa Urban Challenge [111].”
Urban traffic signal control with connected and automated vehicles: A survey (2019, neutral): “Readers who are interested in cooperative driving around non-signalized intersections may refer to some other surveys and papers (Chen and Englund, 2016; Lee et al., 2012, Li et al., 2014c; Meng et al., 2018; Qian et al., 2017; VanMiddlesworth et al., 2008; Xu et al., 2018) for detailed discussions.”