Search

Despite the abundance of studies on signal progression for arterial roads, most existing models for bandwidth maximization cannot concurrently ensure that the resulting delays will be at a desirable level, especially for urban arterials accommodating high turning volume at some major intersections or constrained by limited turning bay length. Extending from those models that aim to address delay minimization in the progression design, this study provides two enhanced progression maximization models for arterials with high turning volumes. The first model aims to select the signal plan that can produce the lowest total signal delays for all movements from the set of non-inferior offsets produced by MAXBAND. Failing to address the impact of potential turning bay spillback at some critical intersections under such a design may significantly degrade the quality of through progression and increase the overall delay. For this reason, the second model proposed in this study offers the flexibility to trade the progression bandwidths within a pre-specified level for the target delay reduction, especially for turning traffic. The evaluation results from both numerical analyses and simulation experiments have shown that both proposed models can produce the desirable level of performance when compared with the two benchmark models, MAXBAND and TRANSYT 16. The second model yielded the lowest average network delay of 117.2 seconds per vehicle (s/veh), compared with 121.7 s/veh with TRANSYT. Moreover, even its average delay of 141.8 s/veh for through vehicles is comparable with that of 141.2 s/veh by MAXBAND, which is designed mainly to benefit through-traffic flows.

To minimize the likelihood of having rear-end collisions at signalized intersections, this study presents two algorithms for use with an actuated signal controller and the wide-ranger senso...

Contending with congestion on major urban arterials by providing progression bands has long been a priority task for the traffic community. However, on an arterial experiencing heavy left-turn volumes at major intersections, the left-turn queue may spill back rapidly and further degrade the effectiveness of the through progression band if the left-turn volume and the limited bay length have not been accounted for in the optimization of signal coordination plan. Such negative impact from left-turn queues also justifies the need to take into account the concurrent progression of through and left-turn flows on major arterials. To address these two issues, this paper presents a three-staged signal optimization model that can circumvent or minimize the impact of left-turn spillback to the through movements and concurrently minimize the delay of left-turn flows. The proposed model firstly obtains an initial maximized bandwidth from an existing state-of-the-art method and then maximizes the portion of through bandwidth not impeded by the left-turn overflows. The delay of left-turn flows at each intersection will also be minimized under the obtained effective through bandwidth. The results from the numerical analyses have confirmed the benefits and need of including the left-turn volume and its bay length in the design of dual progression for through and left-turn movements. The simulation experiments further show a reduction in the average delay and the number of stops, by 6.4% and 5.5%, respectively, for vehicles traversing an arterial segment of six intersections, compared with the state-of-the-art model, MULTIBAND.

Fluid-coupled Lamb waves (LWs) were proposed to facilitate the self-assembling of three-dimensional (3D) photonic crystals (PCs) in this work. Numerical models were constructed for proof-of-concept, and a fabrication set-up was developed for experimental demonstration. LWs were initially generated by a piezoelectric substrate. A couplant altered the propagating direction of these LWs to form the fluid-coupled LWs at a superstrate. The coffee-ring effect (CRE) of a suspension droplet on the superstrate was thus suppressed. The suspended nanospheres formed 3D PCs after the droplet dried out. Diversified PCs were fabricated using the developed set-up. Their transmittance spectra demonstrated the corresponding bandgap clearly. Advantages of utilizing fluid-coupled LWs for self-assembling 3D PCs include flexibility in excitation frequency, fabrication cost-effectiveness, acceptance for a passively oscillating substrate, and enlargement of sample area.

This work set up a Lamb wave excitation device for assembling polystyrene nanospheres into 3D photonic crystals (PCs) of face-centered cubic structures. The optical property of fabricated PCs was verified by transmittance spectra measurements.

This work investigated the phenomena and cause of photonic band gap (PBG) shift under an open environment at −10 °C ∼ 20 °C for the three-dimensional (3D) photonic crystals (PCs). The 3D PCs were composed of polystyrene spheres using the self-assembly method. The reflective gloss of 3D PC sample underwent non-monotonous color change within the temperature region. PBG of PCs first red-shifted during the cooling from room temperature. Later, the PBG blue-shifted when the temperature decreased from about 0 °C. The average transmittance through the PC sample within the visible range also increased first and then decreased with ambient temperature reduction. Influences from structure dimension, optical constants of involved materials, condensation and its phase change on PBG were all quantitatively investigated.

Most congested urban arterials, connecting multiple major intersections with heavy turning flows, are likely to comprise multiple high-volume path flows in addition to its through traffic. Hence, such arterials, if designed with state-of-the-art models for progressing mainly through traffic flows, cannot achieve the expected level of performance, because those heavy path flows involving turning movements will inevitably suffer from overflows at their turning bays and consequently trigger a mutual blockage between the turning and through traffic flows. Although some recent advances on multi-path signal progression (Yang et al., 2015; Arsava et al., 2016) offer a viable design alternative for arterials accommodating such traffic patterns, their required data such as the arterial’s O-Ds or path volume information cannot be collected with state-of-the-practice traffic sensors, or mathematically estimated at the accuracy level sufficient for design of control strategies. As such, this study proposes a model with the optimized phase sequence and offsets to produce a progression band for each candidate path along the target arterial with only each intersection's volume counts, based on the set of “local bands” for all local paths constituted by each link’s upstream flow-in and downstream flow-out movements. Such identified local progression bands are then optimally connected between two neighboring links to form the progression band for traffic flows on each path to progress over multiple arterial links under the objective of maximizing the total weighted progression bands. To ensure the effectiveness of the produced progression bands, the proposed model has accounted for all factors and geometric constraints that may cause their mutual impedance in design of the offsets and phase sequences. The results of extensive numerical experiments with respect to delay and the number of stops per vehicle (reduced by 5.8% and 9.9%, respectively, compared to the benchmark model) within the entire network have shown the effectiveness of the proposed model.

This work both numerically and experimentally investigates hemispherical radiative properties (absorptance, reflectance, and transmittance) of complex gratings. Crystal silicon is employed to generate samples. One is a double-sided polished 520-μm-thick substrate, and the other is a substrate with complex gratings on its top. The incidence wavelength λ ranges from 0.5 μm to 1.7 μm, containing the intrinsic band gap wavelength λbg = 1.09 μm. Wavelength-selective and polarization-sensitive features are exhibited in spectra of properties for complex gratings. The wavelength-selectivity and polarization-sensitivity are elaborated using near-field electromagnetic patterns at three representative wavelengths (λ λbg).

This study presents an integrated off-ramp control model that incorporates the impact of ramp queue spillback on the freeway mainline in design of the off-ramp intersection’s signal plan. The proposed model consists of a mesoscopic traffic module to capture the complex interrelations between the freeway mainline’s traffic state and the lane-changing maneuvers triggered by off-ramp queue spillback, and a local signal optimization module to maximize the total benefit for both the freeway and intersection in the vicinity of an interchange. Using the simulation–optimization solution logic, the proposed model will first estimate the off-ramp queue length, produced from the signal module, to assess the resulting impacts on the freeway mainline, and then feed such impacts back to the control objective to iteratively search for the optimal cycle length and phase durations with the genetic algorithm. To assess the effectiveness of the proposed model, this study has conducted a two-stage evaluation, where the first stage uses the extensive field data to confirm the reliability of its freeway queue impact module and the second stage focuses on evaluating the benefits of accounting for the queue impacts on the freeway in design of the off-ramp signal plan under various traffic scenarios. The results from extensive tests have confirmed that the proposed model can effectively minimize the likelihood of causing off-ramp queues to spill back to the freeway mainline, and the failing to incorporate such impacts in design of the off-ramp signal will contribute significantly to the formation of freeway bottlenecks in the interchange area.

This work developed a type of energy-saving glass for regions undergoing sun glare and high temperature. Its functions cost zero energy and negligible weight increment (1.81 g/m2). The key to its success was two-dimensionally periodic nanostructures composed of single material. These nanostructures were arranged in a hexagonal way and added on a commonly-seen glass substrate. The area of these structures was scalable, and their fabrication was cost-effective using nanoimprint lithography technology. The glass was able to exhibit broadband wavelength-selective transmittance. Measured spectra confirmed transparency in the visible and approximate opaqueness in the near-infrared regions. The power for indoor illumination and air conditioner could thus be simultaneously saved. This work also utilized numerical modeling to obtain electromagnetic field patterns in the near-field. The patterns explained the broadband wavelength-selectivity and influences from an adhesive layer existing in real samples.

InGaN/GaN-based green light-emitting diodes (LEDs) with high-density ultra-small In-rich quantum dots (QDs) embedded in InGaN multiple quantum wells via spinodal decomposition are grown by metal organic chemical vapor deposition. The density and average size of In-rich QDs increased from 1 × 1011 cm−2 to 2 × 1012 cm−2 and decreased from 8.4 nm to 2.3 nm, respectively, when the NH3 flow rate was reduced during the growth of InGaN active layers. The associated growth mechanism of QDs is discussed. High-density ultra-small QDs with improved internal quantum efficiency due to good carrier confinement and a small number of defects are obtained. The proposed approach improves the light emission efficiency of InGaN QD-based LEDs and a 10% enhancement in light output power for packaged lamp-form LEDs is demonstrated in this work.

Obtaining the horizontal variation of temperature and current fields of a water column usually requires travel-time measurements of acoustic signals traveling along different paths between several horizontally distributed transceivers. This study explores the possibility of using a pair of transceivers deployed in a highly-reverberant harbor environment to extract spatial information of the water. Multipath acoustic propagation of two main arrival groups, i.e., direct arrivals and arrivals reflecting off the harbor side, was observed in the pulse responses measured in the harbor environment during the flood tide. Compared with the direct point measurements of temperature and current, the path-averaged measurements show a similar temporal variation during the experiment, demonstrating the possibility of estimating the spatial variation of the currents and temperatures using the multipath acoustic propagation.

Over the last few years, human computer interaction has become an active research area, which releases people from inactive, inconvenient communication with machine. In this paper, an automotive infotainment system with intelligent applications is presented. The proposed system combines the interactive gesture control for controlling in-car applications which can enhance safety and driving performace, as well as increase the level of comfort in modern vehicles.

Wiener filter is one of the most fundamental noise-reduction approaches among numerous techniques. The speech recognition in an in-vehicle environment needs a non-stationary noise cancellation to eliminate the background noise. However, few efforts have been reported to show the effectiveness of Wiener filter. Not much has been evaluated how the Wiener filter really works for reducing the non-stationary noise in real-time. In this paper, a real-time adaptive Wiener filter with two microphones is implemented to reduce noisy speech when noise signals and desired speech are incoming simultaneously. Furthermore, in order to build a real-time noise canceller, this paper also gives an analysis of different matrix sizes of the Wiener filter so as to enable the possibility of real-time implementation. The performance of the proposed design is measured by as much as 20dB noise reduction, and the proposed adaptive Wiener matrix update speed achieves a 28.6 ms/frame, with a matrix size of 200.

Image binarization involves converting gray-level images into binary ones, which has significantly impacted on intelligent portable devices in recent years. Given the limited memory space and computational power of portable devices, reducing the computational complexity of algorithms which work on embedded systems is of priority concern. This paper proposes a 2-D intelligent block detection algorithm with more accurate region segmentation for document image binarization. by combining merits of global and local algorithms, the proposed approach provides an effective outcome and a low computational cost. as demonstrated by the experimental results, the proposed algorithm is slower than Otsui¦s method but 275 times faster than local methods.

This paper presents the architecture and implementation of a real-time adaptive Wiener filter for non-stationary noise cancellation in a car environment. The Wiener filter has been implemented in a Xilinx Virtex-5 chip and the target device is chosen as xc5vlx110t. The proposed design can filter each 32 samples within 918 micro seconds. The peak sampling rate is estimated to be 88.6KHz. The performance of proposed design is measured as 15.85dB noise reduction.

License plate recognition system (LPR) plays an important role in many applications such as access control, traffic control, and the detection of stolen vehicles. A LPR system can be classified into the detection and recognition parts. Improvement of the detection part will be discussed in this paper. Binarization of plate images is one of the major tasks of detection which consumes huge processing time and impacts on the recognition rate. This paper proposes an efficient binarization algorithm with intelligent block size detection. Based on image characteristics, the plate image is automatically divided into several blocks with various sizes. Then, a threshold surface is constructed to derive the binary image. Experimental results show that the proposed method not only provides promising binarization result, but also low computation cost.

Skin color is an important feature for face detection and recognition in color images. In order to obtain the possible face regions in color images, the skin color models are always constructed by statistical analysis. Owing to low accuracy of the static models, researches have discussed several dynamic models to correct input image such as illumination compensation, white balance, edge points addition, etc. Unfortunately, it is possible that some objects whose color is the same as the definition exist, and the previous methods can not separate real skin item from skin color background. Thus, to enhance skin color separation, this paper presents a honeycomb model to recognize the real human skin and the skin color items. First, the possible skin color is estimated from the pixels of database, and the honeycomb structure is built in HSV color space according to the training samples. Then, the personal skin is captured in one of the honeycomb cells. The performance of the new skin color detector technique has been tested under complex lighting source and background environments. It is observed that the proposed model can effectively improve the segmentation results. Especially, the honeycomb model is capable of separating the human face which connected with other face or skin color background.

Recently, VNC (virtual network computing) has become one of the popular remote access techniques for Internet applications such as remote distant learning and collaborative application systems. However, there is no any multimedia functions have been implemented to enhance the performance. In this paper, we presents a framework based on remote frame buffer (RFB) and real-time protocol (RTP) to provide real-time video and audio transmissions for multimedia applications. The framework can be applied to build distance collaborative environments with multimedia and RTP (real-time transport) features efficiently.

In this paper, given a set of timing-driven routing trees for all the interconnection nets, a new multilevel timing-constrained full-chip routing (MTFR) in a dynamic hierarchical quad-grid model is proposed to complete full-chip routing in reasonable time. The experimental results show that the proposed MTFR approach uses less CPU time to obtain 100% timing-constrained routing results for all the tested benchmark circuits.

A probabilistic congestion prediction approach in a dynamic hierarchical quad-grid model is proposed to be applied in timing-constrained congestion-driven global routing (TCGR). Experimental results show that the TCGR algorithm (Yan, J.T. and Lin, S.H., Asia-Pacific Design Automation Conf., p.683-6, 2004) with the proposed probabilistic congestion prediction can use less CPU time to obtain a better timing-constrained congestion-driven global routing result for the tested benchmark circuits.

As the complexity of VLSI circuits increases, the routability problem becomes more and more important in modern VLSI design. In general, the flexibility improvement of the edges in one routing tree has been exploited to release the routing congestion and increase the routability in the routing stage. In this paper, given an initial routing tree, based on the definition of the routing flexibility in a SRT and the timing-constrained location flexibility of the Steiner-point in one Y-type wire, the simulated-annealing-based approach is proposed to obtain a better timing-constrained flexibility-driven SRT by reassigning the feasible locations of the Steiner-points in a SRT. The experimental results show that our proposed STFSRT algorithm can obtain 43%/spl sim/173% improvement on the measure of total routing flexibility for the tested benchmark circuits.

Skin colour is an important feature for face detection and recognition in colour images. To obtain the possible face regions in colour images, skin colour models are always constructed by statistical analysis. Owing to low accuracy of the static models, researchers have discussed several dynamic models to correct input images. Unfortunately, it is possible that some objects whose colour is the same as the definition exist, and the previous methods cannot separate real skin item from skin colour background. Thus, this paper presents a honeycomb model to recognise the real human skin colour. The performance of the new skin colour detector technique has been tested under complex lighting source and background environments. It is observed that the proposed model can effectively improve the segmentation results. Especially, the honeycomb model is capable of separating the human face which connected with other face or skin colour background.

In this paper, given a set of parallel wires between a pair of adjacent P/G lines, according to the definition and computation of the inductive noise and the classification of violation wires, an O(n) optimal approach is proposed to insert shields into these parallel wires for the avoidance of inductive noise, where n is the number of a set of given parallel wires. The experimental results show that our proposed approach can use less CPU time to minimize the number of inserted shields for the avoidance of inductive noise.