Sean J. Barbeau

Positional Accuracy of Assisted GPS Data from High-Sensitivity GPS-enabled Mobile Phones

Utilizing both Assisted GPS (A-GPS) techniques and new high-sensitivity embedded GPS hardware, mobile phones are now able to achieve positioning in harsh environments such as urban canyons and indoor locations where older embedded GPS chips could not. This paper presents an empirical analysis of the positional accuracy of location data gathered using a high-sensitivity GPS-enabled mobile phone. The performance of the mobile phone is compared to that of regular recreational grade GPS receivers. Availability of valid GPS position fixes on the mobile phones tested was consistently close to 100% both outdoors and indoors. During static outdoor testing, positions provided by the mobile phones revealed a median horizontal error of between 5·0 and 8·5 m, substantially larger than those for regular autonomous GPS units by a factor of 2 to 3. Horizontal errors during static indoor testing were larger compared to outdoors, but the difference in accuracy between mobile phones and regular GPS receivers was reduced. Despite the modest performance of A-GPS on mobile phones, testing under various conditions revealed that very large errors are not very common. The maximum horizontal error during outdoor testing never exceeded 30 metres and during indoor testing never exceeded 100 metres. Combined with the relatively consistent availability of valid GPS position fixes under varying conditions, the current study has confirmed the reliability of A-GPS on mobiles phones as a source of location information for a range of different LBS applications.

G-Sense: a scalable architecture for global sensing and monitoring

The pervasiveness of cellular phones combined with Internet connectivity, GPS embedded chips, location information, and integrated sensors provide an excellent platform to collect data about the individual and its surrounding environment. As a result, new applications have recently appeared to address large-scale societal problems as well as improve the quality of life of the individual. However, these new applications, recently called location-based services, participatory sensing, and human-centric sensing, bring many new challenges, one of them being the management of the huge amount of traffic (data) they generate. This article presents G-Sense, for Global-Sense, an architecture that integrates mobile and static wireless sensor networks in support of location-based services, participatory sensing, and human-centric sensing applications. G-Sense includes specific mechanisms to control the amount of data generated by these applications while meeting the application requirements. Furthermore, it creates a network of servers organized in a peer-to-peer architecture to address scalability and reliability issues. An example prototype application is presented along with some basic results and open research issues.

A general architecture in support of interactive, multimedia, location-based mobile applications

The widespread use of cellular telephones and the availability of user-location information are facilitating the development of new personalized, location-based applications. However, as of today, most of these applications are unidirectional and text-based where the user subscribes and the system sends a text message when appropriate. This article describes a modular and general architecture that supports the development of interactive, multimedia, location-based applications, providing an extra level of service to the users. The flexibility of the architecture is demonstrated by presenting the wireless safety security system (Wi-Via) and other potential applications

Dynamic Management of Real-Time Location Data on GPS-Enabled Mobile Phones

Advanced location based services have the ability to track users with Global Positioning System (GPS)-enabled cell phones in real-time. These applications share a common problem; the continuous calculation and transmission of GPS fixes from the mobile phone to a server consumes a considerable amount of energy and increases data transmission costs. Therefore, an application-level algorithm is necessary to reduce the number of GPS fixes calculated and transmitted, while continuing to track the user in real-time and record an accurate representation of his or her travel path. In this paper, two complementary algorithms are presented: the critical point (CP) algorithm, which filters data points to be transmitted to the server, and the location-aware state machine, which dynamically manages the frequency of the location re-calculation update rate. Both algorithms were implemented in TRAC-IT, a Java Micro Edition (Java ME) application designed to automatically collect user travel behavior; the proposed algorithms allow TRAC-IT to build an accurate representation of the users path with a considerably reduced number of fixes while significantly extending mobile device battery life.

A location-aware framework for intelligent real-time mobile applications

The Location-Aware Information Systems Client (LAISYC) supports intelligent, real-time, mobile applications for GPS-enabled mobile phones by dynamically adjusting platform parameters for application performance while conserving device resources such as battery life.

OneBusAway multi-region – Rapidly expanding mobile transit apps to new cities

Real-time transit information offers many benefits to transit riders, including reduced wait times and increased customer satisfaction. However, offering real-time transit services has been challenging for many transit agencies. While mobile applications (apps) have emerged as a preferred dissemination method for real-time information, it is typically cost-prohibitive for transit agencies to fund custom development of native mobile apps for all popular smartphone platforms. Third-party developers can offer services if an agency openly shares real-time data, but these individuals are volunteers whose priorities and deadlines may not be the same as the agency’s. As a result, few cities have full app portfolios that cover all smartphone platforms. This paper presents the OneBusAway multi-region project, a collaborative effort that is enabling the rapid expansion of native mobile transit apps to new cities. OneBusAway is an open-source transit information system that has provided real-time transit services to the Puget Sound (Washington) area since 2008. The new OneBu sAway multi-region feature expands the coverage of the existing Android, iPhone, Windows Phone, and Windows 8 apps for OneBusAway to new cities, including Tampa and Atlanta. The multi-region system architecture, collaborative design and development process, and lessons learned from this ground-breaking project are discussed. The fundamental shift from proprietary to open-source software in the transit industry that has made this type of project possible also is examined.

Quantifying Position Accuracy of Multimodal Data from Global Positioning System–Enabled Cell Phones

The emergence of cell phones with embedded Global Positioning System (GPS) chips provides opportunities to push personalized real-time travel information subject to an individuals current location. One such application, a travel assistant device, notifies cognitively disabled public transportation users when it is time to request a stop and exit the vehicle. GPS-enabled cell phones must provide highly accurate real-time location data for this type of service. The components used in the data-collection process are identified, and a quantitative analysis of real-time GPS data obtained with a cell phone while walking, driving a vehicle, and riding public transportation is provided. The expectation was that position accuracy would suffer when the GPS signal was obstructed by a vehicle or the users clothing. The obtained data demonstrate the results of location fix attempts over different transportation modes in an urban environment. The highest percentage of GPS fixes (79.0%) was obtained by users walking with the cell phone open and unobstructed; walking also produced valid GPS data (i.e., location data estimated to be accurate within 30 m of the true position) 66.2% of the time. For bus trips, GPS and valid fix percentages were 71.7% and 66.1%, respectively, when the phone was held near the window; when the phone was placed in the travelers lap, these numbers fell to 51.3% and 27.8%, respectively. Car trips provided higher numbers: 77.7% and 71.6%, respectively. Location-based transportation applications are feasible using current technology, but predictive algorithms may be required to deliver highly accurate and timely location-aware services to cell phone users in highly obstructed environments.

Global Positioning System Integrated with Personalized Real-Time Transit Information from Automatic Vehicle Location

Navigation of a transit system can be a major obstacle to new riders, especially special-needs populations and tourists. For those with cognitive disabilities (approximately 14.3 million Americans, or 6% of the population), it is challenging to plan and execute a trip without assistance. A travel assistance device (TAD) software prototype for Global Positioning System–enabled phones was developed to aid new transit riders, especially those who are cognitively disabled. When riders approach their stops, the TAD vibrates and delivers audio and visual messages to the riders to request a stop and exit the vehicle. This paper reports the results of a study that integrated communication with an automatic vehicle location (AVL) system on transit vehicles into TAD, with new features, including personalized notices of estimated vehicle arrival time and of vehicle arrival. Implementation issues addressed include the limitations of accessing AVL data for real-time consumer use, integration of different transit agency data sources, and consideration of the effects of software applications (e.g., wireless data communication) on mobile phone functionality (e.g., battery life).

GO_Sync — A Framework to Synchronize Crowd-Sourced Mapping Contributors from Online Communities and Transit Agency Bus Stop Inventories

Proprietary formats and licensing restrictions limit individuals from sharing, viewing, or updating geographic (e.g., map) datasets and also restrict the use of these data to create innovative location-based services. Open geographic data repositories are now emerging that do not have these restrictions. The General Transit Feed Specification (GTFS) is a common open format for public transportation agencies’ schedules, routes, and geographic bus stop information. However, transit agencies struggle to internally maintain and update these very large official datasets. Meanwhile, OpenStreetMap.org (OSM), an online free-content “Wikipedia-like” repository of geographic data, currently has little information about U.S. public transportation, but does have a large number of users willing to freely contribute their efforts to improve geographic data for their communities. This paper presents GO_Sync, a framework and open-source software tool for synchronizing transit data between the transit agency’s official GTFS dataset and OSM. GO_Sync connects the wealth of data from GTFS datasets with the ability of the OSM community to contribute crowd-sourced improvements to large datasets. The GO_Sync tool therefore enables public transportation agencies to upload GTFS data to OSM and retrieve crowd-sourced data back, while the online community can edit and correct the bus stop locations and amenities based on existing GTFS data. Successfully translating GTFS data into the OSM format will enable over 125 transit agencies across the U.S. to share their public-domain data with the OSM community.

Closing the Loop: Improving Transit through Crowdsourced Information

Offering real-time arrival information to riders via mobile applications has been shown to improve the rider’s perception of transit, and even increase ridership. This direct connection to riders also offers the transit agency an opportunity to collect feedback on how transit service and infrastructure can be improved, including pedestrian and bike access to transit. These improvements will lead to an enhanced customer experience and can potentially help address Title VI access equity concerns. However, managing the sheer volume of this rider feedback can be very challenging, especially when various departments and agencies (e.g., city/county government) are involved (e.g., who owns the bench by the bus stop?). This paper discusses the design and deployment of a pilot project in Tampa, Florida, which focused on the improvement of the feedback loop from riders back to transit agencies, local government, and departments of transportation. This project made enhancements to the open-source OneBusAway mobile app, originally deployed in Tampa in 2013, to include support for the Open311 standard for issue reporting. Open311 support gives agencies the option of selecting a hosted issue management solution such as SeeClickFix.com and PublicStuff.com, or the option to utilize existing open-source Open311-compliant software. Lessons learned from regional collaboration surrounding issue reporting and infrastructure improvements are discussed, as are the technical design and challenges behind implementing such a system. The results of the first 6 months of system deployment covering 677 issue reports are presented, including specific examples of cross-jurisdictional and multimodal issues reported by the public.