Dynamic Route Flow Estimation in Road Networks Using Data from Automatic Number of Plate Recognition Sensors

Santos Sánchez-Cambronero, Fernando Álvarez-Bazo, Ana Rivas and Inmaculada Gallego
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Santos Sánchez-Cambronero: Department of Civil and Building Engineering, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
Fernando Álvarez-Bazo: Department of Civil and Building Engineering, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
Ana Rivas: Department of Civil and Building Engineering, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
Inmaculada Gallego: Department of Civil and Building Engineering, University of Castilla-La Mancha, 13071 Ciudad Real, Spain

Sustainability, 2021, vol. 13, issue 8, 1-30

Abstract: The traffic flow on road networks is dynamic in nature. Hence, a model for dynamic traffic flow estimation should be a very useful tool for administrations to make decisions aimed at better management of traffic. In fact, these decisions may in turn improve people’s quality of life and help to implement good sustainable policies to reduce the external transportation costs (congestion, accidents, travel time, etc.). Therefore, this paper deals with the problem of estimating dynamic traffic flows in road networks by proposing a model which is continuous in the time variable and that assumes the first-in-first-out (FIFO) hypothesis. In addition, the data used as model inputs come from Automatic Number of Plate Recognition (ANPR) sensors. This powerful data permits not only to directly reconstruct the route followed by each registered vehicle but also to evaluate its travel time, which in turn is also used for the flow estimation. In addition, the fundamental variable of the model is the route flow, which is a great advantage since the rest of the flows can be obtained using the conservation laws. A synthetic network is used to illustrate the proposed method, and then it is applied to the well-known Nguyen-Dupuis and Eastern Massachusetts networks to prove its usefulness and feasibility. The results on all the tested networks are very positive and the estimated flows reproduce the simulated real flows fairly well.

Keywords: continuous dynamic traffic model; ANPR sensor data; dynamic route flow estimation; FIFO rule (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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