Modelling vehicle interactions in microscopic simulation of merging and weaving
By P. Hidas. 2005
547 citations recorded by the source corpus.
Subfields: Building and Construction, Control and Systems Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/2e3b3cf13945f7f67e75dc809a43dcba97938320
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
In Control and Systems Engineering
- Arnaud de La Fortelle
- Ching-yao Chan
- Pin Wang
- Harry H. Cheng
- W. Jin
- Szilárd Aradi
- Praveen Palanisamy
- Edouard Leurent
In Transportation
Citations in the corpus
- A Review of the Applications of Agent Technology in Traffic and Transportation Systems (2010, background): “Personal agents for each individual traveler communicate with the driver and the system to provide optimal advice to the traveler and update stored traffic information in the system.”
- Generalized bathtub model of network trip flows (2019, background): “…or signalized); then travel times and traffic dynamics on each road and intersection can be described by the link performance function (e.g Sheffi, 1984), Webster’s delay function (e.g. Roess et al., 2010), kinematic wave theory (e.g. Jin, 2012), or car-following models (e.g. Hidas, 2005).”
- A kinematic wave theory of multi-commodity network traffic flow (2012, background): “In traffic operation studies, numerous simulators have been developed based on microscopic models of individual vehicles’ behaviors (e.g. Gazis et al., 1961; Gipps, 1986; Hidas, 2002; Hidas, 2005).”
- Continuous formulations and analytical properties of the link transmission model (2014, methodology): “Network traffic flow models have been proposed at various scales: microscopic models (Hidas, 2005), the LWR model (Lighthill and Whitham, 1955; Richards, 1956), the link queue model (Jin, 2012d), the neighborhood model (Daganzo and Geroliminis, 2008), and continuum network models (Beckmann, 1952; Ho”
- A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers (2018, background): “Research on automated lane changing maneuvers has been extensively conducted and the work can broadly be divided into two functional categories: a decision-making module and a control execution module [3].”