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Paper details
Number 2 - June 2021
Volume 31 - 2021
Dynamic location models of mobile sensors for travel time estimation on a freeway
Weiwei Sun, Liang Shen, Hu Shao, Pengjie Liu
Abstract
Travel time estimation for freeways has attracted much attention from researchers and traffic management departments.
Because of various uncertain factors, travel time on a freeway is stochastic. To obtain travel time estimates for a freeway
accurately, this paper proposes two traffic sensor location models that consider minimizing the error of travel time estimation
and maximizing the collected traffic flow. First, a dynamic optimal location model of the mobile sensor is proposed under
the assumption that there are no traffic sensors on a freeway. Next, a dynamic optimal combinatorial model of adding
mobile sensors taking account of fixed sensors on a freeway is presented. It should be pointed out that the technology of
data fusion will be adopted to tackle the collected data from multiple sensors in the second optimization model. Then,
a simulated annealing algorithm is established to find the solutions of the proposed two optimization models. Numerical
examples demonstrate that dynamic optimization of mobile sensor locations for the estimation of travel times on a freeway
is more accurate than the conventional location model.
Keywords
traffic mobile sensor, dynamic location model, travel time estimation, simulated annealing algorithm, data fusion