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Accurate and energy-efficient GPS-less outdoor localization
Aly H., Basalamah A., Youssef M. ACM Transactions on Spatial Algorithms and Systems3 (2):1-31,2017.Type:Article
Date Reviewed: Jan 19 2018

Location identification has become a central issue within the fields that are related to autonomous driving and autonomous vehicles. Smartphones (and maybe other mobile devices) offer the chance to create an integrated solution for location-based services with high accuracy. It is anticipated that an enormous integrated information system with the most modern communication technology (5G) will be a must to realize the imagined transportation future. The paper is an extended version of a conference paper that expands the basic ideas on location identification more thoroughly. The analysis in the paper highlights several problems on location identification that originate out of the constraints of the technology; thereby, the paper proposes a solution for stepping beyond the recent approaches.

Naturally, commercial navigation software products are utilized, and the road maps contained within them are used for fitting the sensed objects to the objects on the road map. The usual solution is that GPS and cellular mobile phone information (location of base stations of several service providers) are used for localization. The authors propose a complementary extension to the recent practice, namely defining physical and virtual anchors (PANs and VANs). The basic mechanism is that the moving objects (either vehicles or pedestrians) can be traced by some simple calculation grounded in kinematics. This method is called dead-reckoning: the velocity and acceleration as they are detected by sensors can be taken into account and can be used to calculate the movement of the object. However, this method is error prone; naturally, there is lots of noise in the environment. The correction may happen using the road maps of navigation software, exploiting the GPS and location data of the cellular mobile phone. However, these technologies have limitations: buildings, tunnels, outage of the systems, and so on may mean various obstacles for reliable operation.

The authors developed a system called Dejavu that incorporates the concept of PANs and VANs that are stored in a geographical information system (GIS) beside the maps that are built into the navigational software. The map-matching technology can be extended with these two concepts to be integrated into the navigational system and to provide high accuracy in cities and motorways. The proposed system contains modules that dynamically enhance the information base of the system with the assistance of specific machine learning methods; for example, the system through sensors may discern new base stations and new WiFi stations. In the case of vehicles, physical anchors could be bridges, tunnels, turns, curves, railway crossings, and so on, which can be used to correct the data and filter the erroneous information. The authors carried out systematic investigation and data analysis in two geographically distinct areas to prove that the approach is viable.

The authors’ proposal is interesting for the future world of autonomous vehicles when the real-time, continuous operation of the supporting navigational system will be of critical importance. The GIS system enhanced by anchors and maintained to be up to date provides an opportunity for temporal, local, and standalone operation in a serious outage of vital systems such as GPS, cellular mobile phone service providers, mobile Internet, and navigational service providers (in case there is a local backup system). In normal operations, the integrated system yields capabilities for forecasting traffic with high accuracy.

The paper is worth reading for researchers and developers involved in the autonomous driving and vehicles fields.

Reviewer:  Bálint Molnár Review #: CR145796 (1805-0245)
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