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Many vehicular and ITS applications require a highly accurate real-time vehicle position estimate for ensuring their safety and efficiency. The current limitation of vehicle positioning research is the lack of reliable position reference regardless of the surrounding environments. To mitigate this problem, we use the position estimate of three-dimensional simultaneous localization and mapping (3-D SLAM) as the ground truth. Then, we experimentally assess the positioning accuracy of three GPS receivers, i.e. the normal GPS, SBAS-GPS, and RTK- GPS, in two different geographical environments. From the numerical results, the RTK-GPS is shown to achieve the best positioning accuracy (with RMSE of 1.18 m) in the PNU campus with a good sky view, but surprisingly, its positioning accuracy in a high-rise apartment complex is the worst (with RMSE of 42.6 m) presumably due to the blocking and multi-path reflection of the GPS signals.

The highway junction point, where the ramp is merged with the mainstream, is the main traffic congestion point in the highway when handling transport demands. A vehicle driving on the ramp generally attempts to enter the highway without predicting the traffic condition, and commonly causes traffic congestion on highways. Traffic congestion in the highway junction is defined as the traffic situation that the transport demand in the conjunction point exceeds the bottleneck capacity and the accumulated demand remains to the bottleneck. Under traffic congestion, vehicles driving on the ramp cannot efficiently enter the highway. As a result, the waiting time of the vehicle on the ramp becomes long, and fuel consumption and CO2 emission increase due to the frequent acceleration and deceleration. In this paper, we propose a vehicular speed acceleration advisory algorithm for the vehicle on the ramp at the junction point. By recognizing the traffic condition on highways using V2V (Vehicle-to-Vehicle) communication, the proposed algorithm helps to reduce the frequent acceleration and deceleration by drivers. From the simulation results, compared to the conventional driving on the ramp, we show that the proposed algorithm can decrease fuel consumption, CO2 emission under various vehicle densities.

NASA's Soil Moisture Active Passive (SMAP) Project now has completed its prime-phase (three years) mission and has entered a new five-year extended phase. The global L-band radiometry from SMAP has enabled diverse scientific investigations in water, energy and carbon cycle research, terrestrial ecology and ocean science. These include eliciting the role of soil moisture control on the evaporation regime and vegetation gross primary productivity, observing soil-vegetation continuum water relations, analysis of flood and droughts, climate modeling and weather prediction, detecting ocean high-winds during tropical storms, and observing fresh-water outflow in coastal oceans. This paper highlights the recent enhancements to the SMAP suite of science products (from instrument level-1 to geophysical retrievals level-2 and level-3).

As BEOL pitch continues to aggressively scale, contributions from pattern dimension and edge placement constrict the available geometry of interconnects. In particular, the critical minimum insulator spacing which defines a technologies max operating voltage is now limited by Vx to Mx spacing. This spacing has historically been a challenge since the introduction of self-aligned vias due to the loss of CD and chamfer control in the non-self-aligned direction. As pitch continued to shrink from self-aligned via introduction around the 22 nm node, the fraction of via CD control and edge placement compared to the dielectric spacing between interconnects has continued to grow. Alone this trend could be combated by increasing the dielectric spacing, however, the exponential increase in Cu resistivity (under scaling) has forced BEOL technologies into strong line/space asymmetry to keep line resistance under control. At pitches below 32 nm these factors reach a tipping point, either design to exponentially increasing line resistance or lower the technology Vmax. Both approaches cause performance degradation to achieve pitch scaling

A fully aligned via (FAV) integration scheme is introduced and demonstrated at 36 nm metal pitch, with extendibility to beyond the 7 nm node. Selective chemistries were developed to recess Cu and W wires and their associated barrier liner materials, so as to create local topography with no adverse effects on these wiring levels or their dielectrics. Dielectric cap layers were optimized for excellent via RIE selectivity, to act as via guiding structures during subsequent level pattern definition. This combination mitigates via overlay and critical dimension (CD) errors. FAV integration can enable line/via area scaling for 70% lower line resistances and 30% larger via contact areas at the same node. Concurrently, FAV improves TDDB reliability through increased minimum insulator spacing, and EM reliability by maximizing via/wire contact area.

This paper proposes a novel method to graphically compute all feasible gain and phase margin specifications-oriented robust and optimal fractional PID controllers to stabilize time delay processes (TD) of any order. The gain-phase margin tester method is utilized to guarantee the concerned systems certain robust safety margins and test the constant gain margin boundary, constant phase margin boundary, and stability boundary in the parameter plane. The overlapping region of these plotted boundaries, which represents all feasible robust stabilizing PID controllers and allows the considered TD processes to retain pre-specified safety margins, is graphically determined as the gain and phase margin specifications-oriented region (GPMSOR). The variations of the GPMSOR and the stability region with respect to the variations of the noninteger orders of the integral and derivative terms have been investigated. According this, it is possible to slightly enlarge the GPMSOR by altering the noninterger order of the integral and derivative terms. This modifications in GPMSOR through altering the noninteger orders of the integral and derivative terms allows us to find the robust and optimal PID controller gain set for the considered TD systems. In other words, the selected fractional order PID controllers from the GPMSOR not only retain the prescribed GM and PM specifications but minimize the integral of the absolute error (IAE) or the integral of the squared error (ISE) performance criterion. Finally, an illustrative example cited from the literature with computer simulations is provided to demonstrate the effectiveness and confirm the validity of the proposed methodology.

For beyond 7 nm node BEOL, line resistance (R) is assessed among four metallization schemes: Ru; Co; Cu with TaN/Ru barrier, and Cu with through-cobalt self-forming barrier (tCoSFB) [1]. Line-R vs. linewidth of Cu fine wires with TaN/Ru barrier crosses over with barrier-less Ru and Co wires for beyond-7 nm node dimensions, whereas Cu with tCoSFB remains competitive, with the lowest line R for 7 nm and beyond. Our study suggests promise of this last scheme to meet requirements in line R and EM reliability.

Due to the increasing number of vehicles in recent years, traffic congestion problem is a common issue for residents of metropolises. For a better understanding of traffic congestion, the analyzed data from big data technology can be provided as timeline information. However, a scalability problem would occur when we convert raw traffic data into the timeline information due to the volume and complexity of traffic data. In this paper, we present two MapReduce-based approaches which extract the timeline information of road traffic data. By utilizing the distribute processing strategy, we can resolve the scalability problem. We propose an iterative approach of MapReduce as a baseline approach and a single iteration approach as an efficient solution. The single iteration easily extended to support various and/or complex analytic queries by providing proper codes at a reducer. We validate experimentally our MapReduce-based approaches on real traffic dataset from a Busan Intelligent Transport System (ITS) center.

Accurate vehicle tracking is a principal requirement of vehicle safety critical applications. In vehicle-to-vehicle communication, vehicle tracking is achieved by broadcasting beacon containing state information of the sending vehicle in dedicated short range communication (DSRC) channel. Frequent beacon broadcasting can enhance vehicle tracking accuracy, but also lead to channel congestion in high vehicle density. The state-of-the-art beaconing schemes adapt beacon rate to avoid channel congestion. In this paper, we analyze the impacts of event-driven traffic on the tracking accuracy of beaconing schemes. The simulation results show that tracking accuracy degrades with the increase of event-driven traffic load. Based on the results, we conclude that beacon rate should be carefully determined in order to maintain the tracking accuracy with the existence of event-driven traffic load.

With a rapid increase of automobiles and driver licenses, road traffic congestion (RTC) is becoming a more serious problem in many countries. In addition, continuing urbanization all around the world makes this problem more severe especially at urban intersections. In this paper, we present a new green light optimal speed advisory (GLOSA), called the driver-centric GLOSA (DC-GLOSA), which advises the degree of acceleration/braking by comparing the current vehicle mobility with several reference mobility models. We argue that the DC-GLOSA can achieve higher fuel efficiency, better driving comfort, and less driver's distraction. To validate our argument, we conduct a real experiments at an intersection in Pusan National University campus. From the numerical results, we demonstrate that the DC-GLOSA can reduce 23.9% of the intersection stopping time (IST) on average.

In vehicular localization, there is an increasing interest in the fusion algorithm between the relative local sensing estimate (LSE) of ranging sensors and the absolute remote sensing estimate (RSE) of a GPS receiver. A challenging issues of the fusion algorithm is to find a matched pair corresponding to the same vehicle between two sets of estimates. To aim this, we present a greedy data matching (GDM) that finds an optimal set of pairs, consisting of a sensing estimate and a GPS estimate, based on the closeness of these estimates. To represent the closeness in spatial domain, we employ the Mahalanobis distance metric based on the position and the speed estimates. To cope with the temporal randomness of these estimates, we also present a moving-average weighting factor which can provide a robustness to the random error of the estimates. From the numerical results, we show that the GDM outperforms the existing schemes in terms of the correct matching probability.

A key feature of the vehicular ad-hoc networks (VANETs) is to broadcast the beacon message containing the position, speed, heading, etc. However, the fixed-rate scheme in the current standards may incur too large traffic load to the DSRC channel leading to a significant degradation of the network performance. In this paper, we present a new beacon rate control algorithm that succeeds in tracking the movement of nearby vehicles until K consecutive losses of the beacon message. From the numerical results of the simulation, we show that the proposed scheme can achieve much better performance than the fixed-rate scheme in term of the DSRC channel utilization and the successful vehicle tracking probability.

In vehicular safety applications, a vehicular positioning algorithm plays a crucial role in preventing road accidents through the perception of a dangerous situation in advance. However, most of vehicular positioning devices, e.g. a low-cost GPS receiver, have too large position error to be used for these applications. To reduce this error, we present the vehicular positioning accuracy enhancement (VITAE) algorithm which reduces the position error of a vehicle by taking into account the GPS estimate and the sensing estimate of each nearby vehicle; A GPS estimate is obtained from vehicle-to-vehicle communications, whereas a sensing estimate is measured at local sensors, e.g. vehicular radar. We first present a greedy data-association (GDA) algorithm to find a minimal-weight matching between a GPS estimate and a sensing estimate based on an Euclidian distance. We next adjust the position estimate of the vehicle by using the difference in the mass center of GPS estimates and that of sensing estimates. From the law of large numbers, this adjustment leads to the reduction of the position error by 1/√N times, where N is the number of nearby vehicles. To further reduce the position error, we combine our positioning algorithm with the Kalman filter. From the numerical results, we demonstrate that our positioning algorithm can reduce the position error by 81.8% on average.

In many active safety applications, each vehicle must periodically disseminate a beacon message including the status information, such as position, speed, steering, etc., so that a neighbor vehicle can better perceive and predict the kinematics of the vehicle sending this message. However, a simple broadcasting of beacon message may lead to a low message reception as well as an excessive delay. To resolve this problem, we consider the requirements of an active safety application, a channel load and a vehicle mobility in a highway scenario of vehicular networks. Based on these requirements, we analyze the impact of the following three key parameters of the beacon dissemination on the performance of vehicular networks: beacon period, beacon transmission power, and contention window (CW) size. We first derive a beacon period which is inversely proportional to the vehicle speed. Next, we mathematically formulate the maximum beacon load to demonstrate the necessity of the transmission power control. We finally present an approximate closed-form solution of the optimal CW size that leads to the maximum throughput of beacon messages in vehicular networks.

With a proliferation of IEEE 802.11 WLAN technology, Wi-Fi mesh networks (WMNs) have received a considerable attention as a promising solution to provide a cost-efficient high-bandwidth Internet access to nomadic stations, such as lap-top computers and smartphones. However, the capacity of a WMN is still limited due to the frame collisions in its contention-based MAC protocols. In this paper, we present a distributed throughput-maximal scheduling (D-TMS) MAC protocol which overlays the distributed link-activation (DLA) algorithm over the IEEE 802.11 MAC protocol. The DLA algorithm activates a set of collision-free links by exchanging the control frames between neighbor mesh routers only. With an adaptive data-transmission period, the D-TMS MAC protocol attains a better throughput-delay performance for a wide range of traffic condition. The simulation results show that the D-TMS MAC protocol achieves much higher throughput than the IEEE 802.11 MAC protocols.

Data-parallel XML parsing has a crucial problem in partitioning XML documents. Existing approaches need a pre-parse step to determine the partitions. In this paper, we propose a direct parallel method to solve this problem without pre-parsing. In the direct parallel method, we directly start the parallel parsing by finding the "light tower", which is a particular character with some exceptions, called clues. We handle the exceptions by watching the clues and reparsing the partition if it is required in the parsing stage. We also propose a non-synchronized splitter approach to the parallel XML querying using XPath expressions. In the non-synchronized splitter approach, we split an XPath expression into pieces to be executed by threads and we use a data structure, called the ancestor table, to help each thread handle its part of XPath expression independently without communications between threads. Our experiments show that our approach scales well from small sized files to huge sized files.

Ship area networks (SANs) have lately attracted attention in order to guarantee the safety of sea travelers and marine transportation. The wireless sensor network (WSN) is one of the most important components of SAN because crew members must know any damage or malfunction of parts of ships promptly. The safety systems are mostly real-time applications, thus delay is the most important QoS requirement in SAN. Meanwhile, energy consumption is also a traditionally important metric in WSN. Therefore, the goal of this paper is to find the minimum possible transmission power of each sensor node on the condition that it can meet delay constraint. Assuming the uniformly distributed sensor nodes, the proposed method firstly suggests the way to compute the average per-hop advancement with a single transmission. The difference from the actual simulation is less than 1% although it uses only nodal density information. Based on this per-hop advancement, the minimum possible transmission power is calculated, which can guarantee delay QoS for the predetermined ratio of connections in WSNs. The error-prone channel is also considered since packet transmission may frequently fail due to many equipments and ship body made of steel.

Blocking probability is the most widely used performance metric for the design and the dimensioning of wavelength-routed WDM networks. In this paper, we study the blocking performance of such networks under two heterogeneities: traffic heterogeneity and configuration heterogeneity. The former means that different sessions may have different kinds of traffic, and the latter that different nodes and links may have different wavelength conversion capabilities and different number of optical fibers in use, respectively. We also investigate how these heterogeneities impact on the blocking performance of such networks. To achieve these goals, we present a dedicated analytical model for each heterogeneity. First, we present two single-link models for estimating the arrival-point wavelength occupancy distribution on a link with heterogeneous traffic: the FP model and the RP model. Both models are based on the BPP/M/C/C model in which the first two moments of an arbitrary session are matched by those of a birth-death process whose arrival rate linearly varies with the average number of busy wavelengths occupied by its own calls. Next, we derive two recurrence formulas to estimate the number of free wavelengths on a multi-fiber link and the number of free wavelengths after limited-range wavelength conversion. We also present a comprehensive analytical framework for estimating the blocking performance of WDM networks in the presence of both heterogeneities. From the numerical results, we demonstrate that our model is highly accurate in evaluating the blocking probability for a wide range of the heterogeneities discussed above.

In this paper, we investigate the core-switch mapping (CSM) problem that optimally maps cores onto an NoC architecture such that either the energy consumption or the congestion is minimized. We propose a many-to-many core-switch mapping (mCSM) that allows a switch (core) to have multiple connections to its adjacent cores (switches). We also present decomposition methods that can obtain the suboptimal solutions with enhanced computational efficiency. Our work is the first to provide an exact mixed-integer linear programming (MILP) formulation for the complete CSM problems, including the optimal choice of core placements, switches for each core, and network interfaces for communication flows. Experiments with four random benchmarks show that 4:4 mCSM achieves 81.2% of energy savings and 2.5% of bandwidth savings compared with one-to-one mapping. They also show that, for one-to-one mapping, our optimal solutions obtained by the full MILP save 34.8% of energy consumption and 34.4% of bandwidth requirement compared with those from the existing algorithms.

This paper presents a novel analytical redundancy technique for fault diagnostics of a differential brake control system. The proposed diagnostic algorithm builds upon open loop and closed loop state estimators to generate residuals and identify failures. By judiciously utilizing the residual information, it is possible to detect faults at the component level rather than at the system level. In addition, robust and adaptive estimators are shown to effectively combat with two perennial nuisances of fault diagnostic algorithms: sensitivity to disturbance and false alarms. Hardware-in-the-loop simulation studies show how reliably the proposed diagnostic algorithm detects faults in the differential brake control system that is expected to play a crucial role in active vehicle safety.

This paper deals with feedback control of a hydraulic unit for direct yaw moment control, which actively maintains the dynamic stability of an automobile. The uncertain parameters and complex structure naturally call for empirical modeling of the hydraulic unit, which lead to a high-fidelity input/output model. The identified model is cross-validated against experimental data under various conditions, which helps to establish a stringent model uncertainty. Then, the H/sub /spl infin// optimization technique is employed to synthesize a controller with guaranteed robust stability and performance against the model uncertainty. The superb performance of the synthesized controller is experimentally verified, which shows the viability of the proposed approach in a real-world vehicle safety application.

We design a new high performance ATM switch architecture based on a distributed network with O(N) hardware complexity. Considering various performance parameters such as average hop distance, adoptability of self routing, and flexibility on the number of nodes, we choose the generalized shuffle network (GSN) as a building block for the ATM switch design. To improve the throughput of the switch, a layering strategy called weaved GSN (WGSN) is adopted in our switch design. The performance of WGSN is studied under uniform and full load conditions through analytic modeling and simulation. The analysis and simulation results show that the proposed switch has better throughput and cell loss performance when compared with other banyan-based switch architectures known so far.

We propose a heuristic wavelength routing algorithm for IP datagrams in WDM networks which operates in a distributed manner. We first present an efficient construction method for a loose virtual topology with a required connectivity property, which reserves a few wavelengths to cope with dynamic traffic demands properly. We then develop a high-speed distributed wavelength routing algorithm adaptive to dynamic traffic demands and derive the general bounds on average wavelength utilization in distributed wavelength routing algorithms. Finally, through simulation, it is shown that our algorithm is efficient enough to be used in distributed WDM networks in terms of the blocking performance, control traffic overhead, and computational complexity.