Spatial Big Data and Moving Objects: A Comprehensive Survey <s> B. COST ISSUES <s> The majority of today's automated vehicle location (AVL) systems use Global Positioning System (GPS) technology, which can provide position information with an accuracy of approximately 15 m. Recently, low-cost Differential GPS (DGPS) receivers, which have a positioning accuracy of approximate 2-3 m, have become available. With this increased accuracy, it is now possible to perform AVL down to specific roadway lanes. In this paper, a vehicle-lane-determining system is described, consisting of an onboard DGPS receiver that is connected with a wireless communications channel, a unique lane-level digital roadway database, a developed lane-matching algorithm, and a real-time vehicle location display. Lane-level positioning opens up the door for a number of new intelligent transportation system applications such as better fleet management, lane-based traffic measurements from probe vehicles, and lane-level navigation. The developed low-cost system has been tested on a number of roadways and has performed very well when used with accurately surveyed map data. Based on more than 100 000 s, it has correctly determined the lane 97% of the time. <s> BIB001 </s> Spatial Big Data and Moving Objects: A Comprehensive Survey <s> B. COST ISSUES <s> This paper examines the usability of mobile cellular networks to obtain traffic information on a freeway. The question of whether a mobile station (cell phone) can play an acceptable role as a probe for collecting traffic information on a freeway is examined. A space-based approach, wherein the probe vehicles transmit information to roadside devices as they pass through reference points, is exploited rather than a time-based approach, wherein the probe vehicles report information for every specific instant of time. The latter has been of concern to most researchers interested in the use of a mobile cellular network for collecting traffic data. First, a simple analytical model is introduced to address the usability of cell phones as traffic probes and to pinpoint which factors affect the qualification of probe phones when the space-based approach is adopted. Second, simulation experiments are also employed to deal with more realistic traffic conditions as supplementary tools for the analytical model. Finally, the actual traffic data on a freeway was considered to validate the above two hypothesized traffic conditions. The findings show that there are three main factors that affect the qualification of cell phones as a traffic probe: (1) the speed profile of the probe phone in cell coverage; (2) the variability of handoff location where the probe phone switches its jurisdictional cell; and (3) the locational relationship between a reference point and a speed jump (or drop) point in cell coverage. <s> BIB002 </s> Spatial Big Data and Moving Objects: A Comprehensive Survey <s> B. COST ISSUES <s> The responsibility of a vision-based lane departure warning (LDW) system is to alert a driver of an unintended lane departure. Because these systems solely rely on the vision sensor's ability to detect the lane markings on the roadway, these systems are extremely sensitive to the roadway conditions. When a vehicle's LDW system fails to detect lane markers on the roadway, it loses its ability to alert the driver of an unintended lane departure. The goal of this research is to use GPS combined with inertial sensors and a high-accuracy map to assist a vision-based LDW system. GPS navigation systems are available in many automobiles, along with automotive-grade inertial sensors. The low accuracy of a typical GPS receiver found in an automotive navigation system is largely attributed to a position error. This error is too large to allow the GPS receiver to locate a vehicle in a particular lane on a roadway. A method to measure this error using a vision-based LDW system, together with a high-accuracy map, is presented in this paper. With the error known, the accuracy of the GPS receiver is increased to a high-enough level to localize the vehicle on a particular lane. Next, a method fusing GPS/inertial navigation sensor/vision and a high-accuracy map for highway lane tracking is presented. This method provides a backup lateral offset measurement that can be used for LDW when the LDW vision system loses track of the lane markings. <s> BIB003 </s> Spatial Big Data and Moving Objects: A Comprehensive Survey <s> B. COST ISSUES <s> Unlike other biometric authentication methods, gait recognition is noninvasive and effective from a distance. However, the performance of gait recognition will suffer in the low-resolution (LR) case. Furthermore, when gait sequences are projected onto a nonoptimal low-dimensional subspace to reduce the data complexity, the performance of gait recognition will also decline. To deal with these two issues, we propose a new algorithm called superresolution with manifold sampling and backprojection (SRMS), which learns the high-resolution (HR) counterparts of LR test images from a collection of HR/LR training gait image patch pairs. Then, we incorporate SRMS into a new algorithm called multilinear tensor-based learning without tuning parameters (MTP) for LR gait recognition. Our contributions include the following: 1) With manifold sampling, the redundancy of gait image patches is remarkably decreased; thus, the superresolution procedure is more efficient and reasonable. 2) Backprojection guarantees that the learned HR gait images and the corresponding LR gait images can be more consistent. 3) The optimal subspace dimension for dimension reduction is automatically determined without introducing extra parameters. 4) Theoretical analysis of the algorithm shows that MTP converges. Experiments on the USF human gait database and the CASIA gait database show the increased efficiency of the proposed algorithm, compared with previous algorithms. <s> BIB004
Cost is still a major concern for data analysis in moving objects. One of the major concerns in this regard is the data collection sources. It is possible to reduce the cost in BD routing by designing an efficient classifier for object recognition BIB001 , BIB004 . Another solution is to utilize low cost alternative devices while improving the performance of the algorithms. It is also possible to use the existing infrastructure deployed for other applications BIB004 , BIB002 . Clanton et al. BIB003 combine the high accuracy map and the navigation system to propose a lane departure system. Such system reduces the cost by eliminating the requirement for expensive GPS receivers. Similarly, the probe cell phones are used to estimate the travel time between two points. The advantage here is to use the already deployed infrastructure for acquiring the desired data BIB002 .