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Celikoglu, H. and Silgu, M. (2016) Extension of Traffic Flow Pattern Dynamic Classification by a Macroscopic Model Using Multivariate Clustering. Transportation Science, 50, 966-981.
https://doi.org/10.1287/trsc.2015.0653

has been cited by the following article:

• TITLE: The Effect of Self-Driving Car on Urban Traffic

  AUTHORS: Zaiqiang Ku, Ting Liao

  KEYWORDS: Self-Driving Car, Least Square Method, Mixing Speed, Traffic Flow

  JOURNAL NAME: American Journal of Computational Mathematics, Vol.7 No.2, June 14, 2017

  ABSTRACT: Based on the idea of infinitesimal analysis, we establish the basic model of relation between speed and flow. Since putting a certain amount of self-driving car will affect the average speed of mixed traffic flow, we choose the proportion of self-driving car to be a variable, denoted by k. Based on the least square method, we find two critical values of k that are 38.63% and 68.26%. When k 38.63%, the self-driving cars have a negative influence to the traffic. When 38.63% 68.26%, they have significant improvement to the traffic capacity of the road.