Estimating road traffic parameters from mobile communications

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.

Proceedings of the 2012 ACM Conference on Ubiquitous Computing - UbiComp '12, 2012

Road traffic can be monitored by means of static sensors and derived from floating car data, i.e., reports from a sub-set of vehicles. These approaches suffer from a number of technical and economical limitations. Alternatively, we propose to leverage the mobile cellular network as a ubiquitous mobility sensor. We show how vehicle travel times and road congestion can be inferred from anonymized signaling data collected from a cellular mobile network. While other previous studies have considered data only from active devices, e.g., engaged in voice calls, our approach exploits also data from idle users resulting in an enormous gain in coverage and estimation accuracy. By validating our approach against four different traffic monitoring datasets collected on a sample highway over one month, we show that our method can detect congestions very accurately and in a timely manner.

In the area of Intelligent Transportation Systems the introduction of wireless communications is reshaping the information distribution concept, and is one of the most important enabling technologies. The distribution of real-time traffic information, scheduling and route-guidance information is helping the transportation management systems in their strive to optimize the system. The communication required to transfer all this information is rather expensive in terms of transmission power, use of the scarce resources of frequencies and also the building of an infrastructure to support the transceivers. By using information that already exists and is exchanged within the infrastructures of the GSM and UMTS networks, a lot of the resource problems are solved. The information that could be extracted from these cellular networks could be used to obtain accurate road traffic information to support real-time traffic information. In this way the cellular networks not only becomes the means to distribute information but also a source of road traffic information. From the analysis made it is obvious that the potential of retrieving valuable road traffic information from cellular systems in a cost efficient way, i.e. by using already existing signaling data, is very high. It has however not been clear what to expect from these systems in terms of accuracy, availability and coverage. In this chapter the basics for this is laid out and discussed in detail. A practical trial has also been performed and the results show clearly the potential as well as the differences in using the GSM compared to the UMTS network. The advantages and drawbacks are discussed and backed up by real measurements in two different road environments. The main advantages of using the existing signaling data, i.e., passive monitoring compared to active monitoring where the terminal sends extra data is discussed and could be summarized in three components, no user acceptance is necessary, no extra signaling is necessary and it does not drain the terminal battery.

2006

Acquiring high quality origin destination information for the vehicle traffic in a geographic area is a tedious and costly task. Traditional methods are expensive, time-consuming and generally only present a snapshot of the traffic situation at a certain time. The technique developed in this paper exploits the use of data already at hand in a GSM network. Instead of monitoring vehicles flows, mobile phones flows are measured and are correlated to the traffic flow. This methodology is based on the fact that a GSM network always knows an estimated position of each terminal, referred to the location area of the base station that provides services to it. For a pilot study a GSM network simulator has been designed to generate a synthetic database with location registers, which is then processed mathematically and transformed into traffic data. Primary results show great potential of this method.

… Proceedings, 2006 6th …, 2006

This paper summarizes different approaches to collecting road traffic information from second-generation cellular systems (GSM) and point out the possibilities that arise when third generation systems (UMTS) are used. Cell breathing is a potential problem, but smaller cells, soft handover and flexible measurements have the potential to increase the usage area and information quality when road traffic information is extracted from the UMTS network compared to using the GSM network.

IEEE Transactions on Intelligent Transportation Systems, 2015

Mobile cellular networks can serve as ubiquitous sensors for physical mobility. We propose a method to infer vehicle travel times on highways and to detect road congestion in real-time, based solely on anonymized signaling data collected from a mobile cellular network. Most previous studies have considered data generated from mobile devices active in calls, namely Call Detail Records (CDR), an approach that limits the number of observable devices to a small fraction of the whole population. Our approach overcomes this drawback by exploiting the whole set of signaling events generated by both idle and active devices. While idle devices contribute with a large volume of spatially coarse-grained mobility data, active devices provide finer-grained spatial accuracy for a limited subset of devices. The combined use of data from idle and active devices improves congestion detection performance in terms of coverage, accuracy, and timeliness. We apply our method to real mobile signaling data obtained from an operational network during a one-month period on a sample highway segment in the proximity of a European city, and present an extensive validation study based on groundtruth obtained from a rich set of reference datasources -road sensor data, toll data, taxi floating car data, and radio broadcast messages.

Vodafone proposes to offer road traffic information services to its mobile phone customers. Such systems usually require some sort of static infrastructure to measure traffic flow (e.g. magnetic inductance loops buried in the surface of the road, or cameras combined with number plate recognition technology). In contrast, Vodafone intends to generate traffic flow and velocity data by using the signalling information that is already generated by the standard operation of its mobile phone network. This report investigates the feasibility of this idea by analysing a data set provided by a pilot project on the autobahn network in Southern Germany. The initial aim is to design filters that operate on the mobile phone signalling data and whose output is a low-dimensional description of road traffic conditions. The eventual aim is to develop filters which give short-term forecasts of future traffic conditions.

Signaling data of cellular phones can be used as valuable information for state-of-the-art traffic applications especially in urban areas. The traces of mobiles like handovers and location area updates may be efficiently utilized in the field of road traffic measurement and forecasting or even traffic control. By detecting and processing the locomotion of anonymous mobile phones, origin-destination flows and trip distribution can be inferred. This information may serve as important basis for transportation planning, and even for realtime applications, such as traffic control or route guidance. The proposed method apply only passive signaling events generated by the user and captured by the cellular system operator. Therefore, it does not require additional infrastructure on the operator-side or the use of any active application on the client-side such as GPS. Moreover, it can be applied in 2G as well as 3G cellular systems.

2001

In this paper some of the new possibilities in monitoring traffic and in deploying new control strategies with the use of mobile phones localization data are discussed. The possibilities open to these new applications are enormous given: -the extraordinary diffusion of mobile phones ; -the new technological developments in the field of mobile phone data transmission; -The implementation of E-911 in USA and the potential economic interest of mobile phone producers and mobile phone network operators towards mobile phone localization systems. Mobile phone based toll collection is discussed and a new traffic monitoring system is introduced that can produce estimates for dynamic o/d matrices and the evaluation of travel times. The idea of the system (which is covered in Italy by an industrial patent), is to use all the localization data that the mobile network operators already have to obtain estimates of o/d traffic matrices. The methodology is analyzed in order to establish statistical properties and calibration methodologies.

2012

The worldwide proliferation of cellphones has created numerous opportunities for new and powerful applications that contribute towards improving the quality of life. Traffic problems due to traffic congestions, especially in cities with high population density, is one of the areas that need attention. GPS-enabled cellphones can contribute towards alleviating some of these traffic problems. A GPS-enabled cellphone can be a source of useful information pertaining to traffic congestions. The velocity and location information that are transmitted by GPSs on the road can be gathered and analyzed at run-time to determine traffic status. In addition, a cellphone can receive area maps with overplayed traffic information to help drivers select optimal routes for their trips. In this paper we describe a prototype system that enables passengers who are carrying cellphones to know, in advance, the best route that a taxi needs to take by providing them with distance information, taxi fare estima...

The need for increased individual mobility has resulted in a significant and continuous increase of road traffic density. More and more, the roads are getting congested. Modern Intelligent Transportation Systems (ITS) are offering methods to avoid these congestions. However, this requires a dense surveillance system of sensors that is very costly. Thus, due to financial constraints, not all roads are equipped with such sensors. Especially the secondary and tertiary roads are generally sacrificed. Thus, a complete real-time traffic monitoring of all available road systems is not guaranteed. This calls for new and flexible tracking systems which offer full coverage, high flexibility, synergy with available or already implemented systems and all this at a very high performance to cost ratio. Such a novel solution is presented in this paper. It uses location management data from wireless cellular networks and doesn't require external sensors. The mobile phones, which have become ubiquitous devices carried by people moving inside the cars, are implicitly used as sensors. The key contribution of this paper is to show how cellular networks can perform a sensing task, in this case of road traffic information, while using functions they need for their normal operation, in this case the mobility management ones. Thus, the cellular network can be seen as a type of sensor network (even if not an ad-hoc one). This new service concept opens new revenue opportunities for cellular operators. The concept presented in this paper is named TTLM (an abbreviation for Traffic Tracking using Location Management functions of cellular networks).

IEICE Transactions on Communications, 2011

This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called "3R" philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The "3R" philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions. key words: mobile probes, "3R" philosophy, vehicle classification, pedestrian recognition, traffic state quantification model

2010

The growing need of the driving public for accurate traffic information has spurred the deployment of large scale dedicated monitoring infrastructure systems, which mainly consist in the use of inductive loop detectors and video cameras. On-board electronic devices have been proposed as an alternative traffic sensing infrastructure, as they usually provide a cost-effective way to collect traffic data, leveraging existing communication infrastructure such as the cellular phone network. A traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network. This article presents a field experiment nicknamed Mobile Century, which was conceived as a proof of concept of such a system. Mobile Century included 100 vehicles carrying a GPS-enabled Nokia N95 phone driving loops on a 10-mile stretch of I-880 near Union City, California, for 8 hours. Data were collected using virtual trip lines, which are geographical markers stored in the handset that probabilistically trigger position and speed updates when the handset crosses them. The proposed prototype system provided sufficient data for traffic monitoring purposes while managing the privacy of participants. The data obtained in the experiment were processed in real-time and successfully broadcast on the internet, demonstrating the feasibility of the proposed system for real-time traffic monitoring. Results suggest that a 2-3% penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow.

2010

This paper introduces an algorithm that estimates the speed of a mobile phone by matching time-series signal strength data to a known signal strength trace from the same road. Knowing a mobile phone's speed is useful, for example, to estimate traffic congestion or other transportation performance metrics. The proposed algorithm can be implemented in the carrier's infrastructure with Network Measurement Reports obtained by a base station or on a mobile phone with signal strength readings obtained by the handset and depending on implementation choices, promises lower energy consumption than Global Positioning System (GPS) receivers. We evaluate the effectiveness of our algorithm on highway and arterial roads using GSM signal strength traces obtained from several phones over a one month period. The results show that the Correlation algorithm is significantly more accurate than existing techniques based on handoffs or phone localization.

Transportation Research Part C: Emerging Technologies, 2007

The purpose of this paper is to examine the performance of a new operational system for measuring traffic speeds and travel times which is based on information from a cellular phone service provider. Cellular measurements are compared with those obtained by dual magnetic loop detectors. The comparison uses data for a busy 14 km freeway with 10 interchanges, in both directions, during January-March of 2005. The dataset contains 1 284 587 valid loop detector speed measurements and 440 331 valid measurements from the cellular system, each measurement referring to a 5 min interval. During one week in this period, 25 floating car measurements were conducted as additional comparison observations. The analyses include visual, graphical, and statistical techniques; focusing in particular on comparisons of speed patterns in the time-space domain. The main finding is that there is a good match between the two measurement methods, indicating that the cellular phone-based system can be useful for various practical applications such as advanced traveler information systems and evaluating system performance for modeling and planning.