MOTORWAY TRAFFIC MANAGEMENT AND TRAFFIC PARAMETERS ESTIMATION FROM MOBILE PHONE COUNTS (original) (raw)

Motorway traffic parameter estimation from mobile phone counts

European Journal of Operational Research, 2006

In this paper a new method for real time estimation of vehicular flows and densities on motorways is proposed. This method is based on fusing traffic counts with mobile phone counts. The procedure used for the estimation of traffic flow parameters is based on the hypothesis that "instrumented" vehicles can be counted on specific motorway sections and traffic flow can be measured on entrance and exit ramps. The motorway is subdivided into cells, assuming that mobile phones entering and exiting every cell can be counted during the observation period. An estimate of "instrumented" vehicle concentration is obtained and propagated on the network in time and space. This allows one to estimate traffic flow parameters by sampling "instrumented" traffic flow parameters using a "concentration" (the ratio of the densities of instrumented vehicles to the density of overall traffic) propagation mechanism.

Review of traffic data estimations extracted from cellular networks

IET Intelligent Transport Systems, 2008

One of the main characteristics of modern society is the never-ending increase in mobility. This leads to a series of problems such as congestion and increased pollution. To resolve these problems, it is imperative to have a good road network management and planning. To efficiently identify the characteristics of traffic in the road network, it would be necessary to perform a permanent monitorisation of all roadway links. This would involve an excessive cost of installation and maintenance of road infrastructure. Hence, new alternatives are required which can characterise traffic in a real time with good accuracy at an acceptable price. Mobile telephone systems are considered as a promising technology for the traffic data collection system. Its extensive use in converting its subscribers in a broad sample to draw information from phones becomes anonymous probes to monitor traffic. It is reviewed how to obtain parameters related to traffic from cellular-network-based data, describing methods used in existing simulation works as well as field tests in the academic and industrial field. 2 Mobility management in mobile phone networks The mobility required today is modifying the life style both at an individual and collective level. The result is the need for

Traffic density estimation with the cell transmission model

Proceedings of the 2003 American Control Conference, 2003., 2003

A macroscopic traffic flow model, called the switchingmode model (SMM), has been derived from the cell transmission model (CTM) and then applied to the estimation of traffic densities at unmonitored locations along a highway. The SMM is a hybrid system that switches among different sets of linear difference equations, or modes, depending on the mainline boundary data and the congestion status of the cells in a highway section. Using standard linear systems techniques, the observability and controllability properties of the SMM modes have been determined. Both the SMM and a density-based version of the CTM have been simulated over a section of I-210 West in Southern California, using several days of loop detector data collected during the morning rush-hour period. The simulation results show that the SMM and CTM produce density estimates that are both similar to one another and in good agreement with measured densities on I-210. The mean percentage error averaged over all the test days was approximately 13% for both models.

Traffic Flow Estimation Models Using Cellular Phone Data

IEEE Transactions on Intelligent Transportation Systems, 2000

Traffic volume is a parameter used to quantify demand in transportation studies, and it is commonly collected by using on-road (fixed) sensors such as inductive loops, cameras, etc. The installation of fixed sensors to cover all roads is neither practical nor economically feasible; therefore, they are only installed on a subset of links. Cellular phone tracking has been an emerging topic developed and investigated during the last few years to extract traffic information. Cellular systems provide alternative methods to detect phones in motion without the cost and coverage limitations associated with those infrastructure-based solutions. Utilizing existing cellular systems to capture traffic volume has a major advantage compared with other solutions, since it avoids new and expensive hardware installations of sensors, with a large number of cellular phones acting as probes. This paper proposes a set of models for inferring the number of vehicles moving from one cell to another by means of anonymous call data of phones. The models contain, in their functional form, terms related to the users' calling behavior and other characteristics of the phenomenon such as hourly intensity in calls and vehicles. A set of intercell boundaries with different traffic background and characteristics were selected for the field test. The experiment results show that reasonable estimates are achieved by comparison with volume measurements collected by detectors located in the same study area. The motion of phones while being involved in calls can be used as an easily accessible, fast, and low-cost alternative to deriving volume data on intercell boundaries.

Traffic parameter estimation on motorway networks by combination of filtering techniques

2009 IEEE International Conference on Systems, Man and Cybernetics, 2009

In order to perform road traffic control, it is very important to estimate the traffic parameters which can not be measured directly from sensors. In this paper, we will focus on turn fraction estimation based on a new road network representation which is used in traffic control software at the Dutch traffic management company Trinité Automatisering B.V. The common approach for the turn fraction estimation is by applying Kalman filter. However, the sensor information for motorways is not always available due to the fact that there are no physical sensors or detector failure on some parts of motorways. In this case, Kalman filter can not be applied to estimate turn fraction. A new approach by combining of Kalman filter and a low pass data filtering technology called Treiber-Helbing-filter is presented. This approach can contribute solving the problem by using Treiber-Helbing-filter to complete the missing data firstly. Then, turn fraction is able to estimate by using Kalman filter and visualize in traffic control software.

Measuring traffic flow using real-time data

… Research Board. Paper presented to the …, 2008

The theory of traffic flow based upon speed, flow and density that vary only slowly in space and time is well established. However, matching field observations up to this theory and extracting estimates of quantities of interest is not always straightforward. Spatial density of traffic is not measured readily, and inductive loops are often used instead to measure the proportion of a sampling period for which a vehicle is present, which is known as occupancy: the relationship between occupancy and density k is k = / L , where L is the mean effective length of a vehicle at the detector. According to this, correct interpretation of occupancy depends on the composition of the traffic that is measured, which will affect the value of L. Estimates of the capacity of a road are most useful when they are expressed in units that are independent of traffic composition. In this paper, we show how the value of L can be estimated from the 1-minute point observations of a kind that are available from the Highways Agency MIDAS data that are collected on the U.K. motorway network. The value of this quantity was found to vary substantially over time during the day, between lanes on the road, and according to the control status of the road thus reflecting variations in traffic composition, and variations in lane usage. The consequences of this are discussed for interpretation and use of traffic data of this kind in estimating the speeddensity relationship, capacity and related properties of a road section.

Density and Velocity Estimation in Traffic Flow

IFAC Proceedings Volumes, 2005

An estimation scheme that allows to recover vehicle density and velocity in a stretch of highway is presented. The design is based on a non-linear switching model, inspired by the cell transmission traffic flow model, that has a distinctive behavior for free flow or congested traffic. Lyapunov and linear matrix inequalities techniques are used to prove the stability of the estimation and observer schemes. The algorithm is applied to a set of data traffic collected in a stretch of highway in Pasadena, California, showing good performance.

Algebraic Methods for Traffic Flow Densities Estimation

An estimation approach that allows recovering of the traffic state is proposed in this paper. The method used is based on numerical differentiation, which does not need any integration of differential equations and turns out to be quite robust with respect to perturbations and measurements noises. Numerical simulations, carried-out by using the so-called Cell Transmission Model (CTM) demonstrate the relevance of the proposed on-line estimation scheme.