Long-term path prediction in urban scenarios using circular distributions
作者：
Highlights：
• A stochastic model to predict future positions of humans is presented.
• Both static and dynamic aspects, based on circular distributions, are considered.
• The next agent's state is modeled as a Markov random process.
• A ray-launching procedure models environmental constraints.
• A nearly-constant velocity factor smooths rapidly velocity changes.
摘要
•A stochastic model to predict future positions of humans is presented.•Both static and dynamic aspects, based on circular distributions, are considered.•The next agent's state is modeled as a Markov random process.•A ray-launching procedure models environmental constraints.•A nearly-constant velocity factor smooths rapidly velocity changes.
论文关键词：Long-term path prediction,Circular distribution,Human-scene interaction,Stochastic model
论文评审过程：Received 6 February 2017, Revised 21 October 2017, Accepted 27 November 2017, Available online 5 December 2017, Version of Record 18 December 2017.
论文官网地址：https://doi.org/10.1016/j.imavis.2017.11.006
