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Introduction. At present, numerical methods enjoy widespread use in construction practice. They enable performing and analyzing complex non-linear, multi-factor models without excessive analytical procedures. However, as a rule, the most complex tasks, performed in a three-dimensional setting with account taken of physical, geometric and other nonlinearities, are performed in deterministic formulations without the analysis of the stochastic nature of physical processes. This seems particularly strange, given that numerical methods are well-suited for modeling stochastic processes. Numerical probabilistic and statistical approaches (PSA) can be applied to simulate and take into consideration various spatiotemporal aspects of the probabilistic nature of loads and forces, structural system resistances, materials and geological terrains. Even the most advanced numerical models of deterministic physical systems are merely a specific case of probabilistic and statistical modeling: they enable obtaining only one value (point) on the whole field of possible implementations, being unable to demonstrate an objective and exhaustive variety of probable outcomes. This article presents a case study of numerical probabilistic and statistical analyses of loads and forces. Methods of research. Materials from different sources, such as reference books, regulatory documents, laboratory test results, as well as available experimental data, were used as input parameters. The principal calculation and analysis of the integral function of loads was performed using the Monte Carlo numerical method of probabilistic and statistical modeling and various theoretical (statistical) and empirical distributions, followed by the quantitative assessment of design loads at various confidence probability values. Results. This study provides an example of the probabilistic and statistical calculation (determination) of the integral function of loads and forces with account taken of different origins of loads and varied input parameter distribution patterns, including empirical distributions. It has proven great importance of accurate description of initial distributions of a random value for the determination of reliable design load values. Conclusions. Probabilistic and statistical approaches have the ability to objectively assess the performance of structural systems based on the quantitative assessment of the probabilistic nature of load factors. These approaches have huge potential for increasing the reliability of buildings and structures and the cost effectiveness of construction projects.

The performance function of many engineering structures and mechanisms is usually complex, highly nonlinear, and described in the implicit form. The reliability analysis of these structures using common methods requires high cost and time. In this paper, a new approach for reliability analysis of engineering structures and mechanisms by using the particle swarm optimization algorithm is presented. The advantages of this method in comparison with the conventional methods are its simplicity and accuracy. In addition, the limitations of the common previously presented methods are eliminated by the proposed method. This approach is based on a new redefinition of most probable point in the reliability analysis. To evaluate the performance and validity of the proposed method, some examples in the reliability analysis of various functions are employed. Finally, the superiority of the proposed method in performance and accuracy is demonstrated and compared to the conventional methods and it can be used for reliability analysis of complicated engineering structures.

In the foreseeable future, the traffic stream will be likely mixed with connected automated vehicles (CAVs) and regular vehicles (RVs). In the mixed traffic environment, when following a RV, due to the lack of vehicle-to-vehicle communications, it may take longer time for a CAV to sense and react than a human driver, which results in longer time headway and the loss of highway throughput. To address such a connectivity gap, this paper investigates an infrastructure-based solution, i.e., the deployment of roadside units to help CAVs in the heterogeneous traffic stream. Specifically, it is envisioned that these roadside units can sense vehicles in their coverage areas and provide the beyond-line-of-sight motion information to CAVs to empower them to react proactively, as they would do when following other CAVs. This paper is devoted to the analysis of the impacts of this type of roadside units at a strategic planning stage. In doing so, we first derive an analytical link performance function to capture their impact on the link capacity and travel time, and then develop a network equilibrium model to gauge their effect on travelers’ route choices and thus the flow distribution of both RVs and CAVs across the whole network. This modeling development will allow us to conduct a cost-benefit analysis for a given deployment plan of roadside units. For fair analyses, we further develop an optimization model to determine the optimal deployment plan for a given budget, while focusing on the worst case of its impact, because the flow distribution resulting from our network equilibrium model is not unique. Such a model provides a conservative estimate of the benefit brought by roadside units. Lastly, we offer case studies to demonstrate the models and unveil the potential of such an infrastructure-based solution.

This study evaluated the effects of three types of hybrid iterative reconstruction (IR) on image quality of pediatric body computed tomography images. The image quality components evaluated were noise power spectrum (NPS), task-based modulation transfer function (TTF), and system performance function (SPF). As the IR strength was increased while reducing the radiation dose, the NPS increased in a low-frequency range and the TTF decreased in low-contrast regions. In the low-contrast regions, the calculated SPF decreased over the entire frequency range. Alternatively, in the high-contrast regions, the SPF decreased in the low-frequency regions and increased in the high-frequency regions. The radiation dose reduction using the hybrid IR resulted in the deterioration of the image quality in the low-contrast regions and changes in the spatial frequency characteristics in the high-contrast regions.

This paper attempts to apply the resilience concept to the mining sector, especially to mining machinery and production systems. The quantitative analysis method using the linear recovery function has been applied. As the core part of the proposed method, it is assumed that in the mining machinery fleet, the performance function falls to a “zero” value immediately after the occurrence of a failure. Therefore, the resilience calculation process runs through the concept of time to repair and machine maintainability. As a case study for the proposed concept, the operation and failure data of the drum shearer machine in Parvadeh longwall mine in Iran is applied. The data pertains to a coal cutting operation in a whole longwall panel over the period of two years. In total, the calculations encompass over 2600 hours of actual operation and 171.8 hours of repair time, which reveals that the studied shearer has a resilience of 96.7 percent. Along with the case study results, it is confirmed by this paper that resilience as a developing concept could be adequately applied to coal mining systems as a support measure for production assurance and reliability., U radu je opisana primjena koncepta otpornosti u rudarstvu, tj. u radu strojeva koji se rabe kod iskapanja i proizvodnje. Uporabljena je linearna funkcija kao kvantitativna analitička metoda. Pretpostavljeno je kako performanse rudarske opreme padaju na nulu odmah nakon događaja koji označava kvar. Slijedom toga izračun otpornosti postupak je koji u obzir uzima vrijeme potrebno za popravak strojeva u prvobitno radno stanje. Studija slučaja načinjena je s podatcima o kvarovima utvrđenim na sjekačima korištenim u iranskome rudniku (s uzdužnim iskapanjem) Parvadeh i obuhvaćaju dvogodišnje razdoblje vađenja ugljena. Kroz to vrijeme obrađeni su podatci za više od 2600 radnih sati te 171,8 sati utrošenih na popravke. Obradom je izračunano kako otpornost promatranih sjekača iznosi 96,7 %. Potvrđeno je kako takva otpornost može biti primijenjena kod rudarenja ugljena kao dodatna varijabla kojom se opisuje stabilnost i pouzdanost vađenja rude.

The Ebeg Turangga Edan performance is one of the traditional folk art groups in Cilacap Regency which uses the Ebeg property which is turned into a horse. The research objective was to describe the form and function of the Turangga Edan Ebeg Performance in Tegalreja Village, Cilacap Selatan District, Cilacap Regency. This research uses qualitative methods, with a structure and function approach. Data collection techniques include observation, interviews, and documentation. The data validity technique used triangulation. Data analysis using data reduction, data presentation, and drawing conclusions. The results of the research reveal that the Ebeg show is patterned into several parts, namely the initial part of performing the rituals carried out by the penimbul (Pawang), the core part of the three-act presentation, the final part marked by a mass mendheman scene and the closing remarks from the pengimbul / elder / chairman of the Turangga Edan association. Ebeg show is formed from the relationship between elements of the show which includes themes, actors / dancers, movement, music, make-up and fashion, property / equipment, stage, lighting / light and sound, appreciators / audience. The function of the Ebeg Turangga Edan performance in the community of Cilacap Regency includes the functions of ceremonial facilities, self-expression, entertainment, shows / performing arts, educational media, therapy / treatment vehicles, and communication media / social interaction tools. The conclusion is that the Ebeg Turangga Edan show is patterned into parts that are united into one show. The Turangga Edan Ebeg show is used by the community as entertainment., Artikel ini bertujuan mendeskripsikan bentuk dan fungsi Pertunjukan EbegTurangga Edan di Kelurahan Tegalreja, Kecamatan Cilacap Selatan, Kabupaten Cilacap. Metode yang digunakan adalahmetode kualitatif, dengan pendekatan struktur dan fungsi. Teknik pengumpulan data meliputi observasi, wawancara, dan dokumentasi. Teknik keabsahan data menggunakan triangulasi. Analisis data dengan menggunakan cara reduksi data, penyajian data, dan menarik kesimpulan. Hasil penelitian mengungkapkan bahwa pertunjukan Ebeg terpola menjadi beberapa bagian yaitu bagian awal melakukan ritual yang dilakukan oleh penimbul(Pawang), bagian inti adanya sajian tiga babak, bagian akhir ditandai dengan adegan mendhemanmassal dan sambutan penutup dari penimbul/sesepuh/ketua paguyuban Turangga Edan. Pertunjukan Ebeg terbentuk dari tata hubungan antar elemen pertunjukan yang meliputi tema, pelaku/penari, gerak, musik, tata rias dan tata busana, property/perlengkapan, tempat pentas, tata lampu/cahaya dan suara, apresiator/penonton. Fungsi pertunjukan EbegTurangga Edan di masyarakat Kabupaten Cilacap meliputi fungsi sarana upacara, ekspresi diri, hiburan, tontonan/seni pertunjukan, media pendidikan, wahana terapi/pengobatan, dan media komunikasi/alat interaksi sosial. Kesimpulannya adalah bentuk pertunjukan Ebeg Turangga Edan terpola menjadi bagian-bagian yang menyatu menjadi satu pertunjukan. Pertunjukan Ebeg Turangga Edan digunakan masyarakat yang berfungsi sebagai hiburan.

Reliability analysis of complex geotechnical engineering is time-consuming since its performance function is highly nonlinear and implicit. In this paper, an adaptive sequential sampling m...

A safety performance function (SPF) is a statistical equation to predict the expected crash frequency for a certain roadway facility, mainly as a function of traffic exposure indicators. Ro...

An important challenge in structural reliability is to reduce the number of calls to evaluate the performance function, especially the complex implicit performance functions. To reduce the computational burden and improve the reliability analysis efficiency, a new active learning method is developed to consider the probability density function of samples based on the learning function U in an active learning reliability method that combines the kriging and Monte Carlo simulation. In the proposed method, the proposed active learning function contains two parts: part A is based on function U, and part B is based on the probability density function and function U. By changing the weights of parts A and B, the sample points close the limit-state function, and those in the region with a higher probability density function have more weight to be selected compared to the others. Subsequently, the kriging model can be constructed more effectively. The proposed method avoids a large number of time-consuming function evaluations, and the recommended weight is also reported. The performance of the proposed method is evaluated through three numerical examples and one engineering example. The results demonstrate the efficiency and accuracy of the proposed method.

The available robust and reliable topology optimization methods provide quick and efficient design output in an uncertain environment. However, the whole domain of performance function remains hidden during this design process. In the interest of the designer, it is required to know the overall behavior of performance functions in deterministic as well as uncertain/realistic environment. The current work achieves this by proposing an integrated methodology, which combines the design of experiments approach and reliability-based topology optimization. The proposed method enables the designer to simulate performance functions in a desired design-factors space, including uncertainties, via reliability value. For this analysis, compliance, maximum deflection, mechanical advantage, and von Mises stress values are selected as performance functions. Volume fraction, applied force, and dimensions or aspect ratio are chosen as design/control factors. The uncertainties of these design factors are captured using reliability-based topology optimization. The uncertainties due to noncontrollable factors such as material property, load direction, and magnitude are incorporated using the design of experiments approach. Under these uncertainties, the performance of topologically optimized problem is simulated for different experimental combinations of the design factors. The experimental combinations for uncertainties and design factors are generated using Taguchi's orthogonal array. Simulated results are analyzed using techniques such as analysis of mean and variance, signal-to-noise ratio, and response surface method. These analyses help in identifying statistical significance of factors and uncertainties, performance variations, and equivalence relation of performance vs. factor. The proposed methodology is illustrated by selecting monolithic structures such as, on MBB, cantilever beam, and force inverter mechanism.

For efficiently estimating the Profust failure probability based on probability input variables and fuzzy-state assumption, a General Performance Function (GPF) expression is established under the strict mathematical derivation for the Profust reliability model. By constructing the GPF, the calculation of the Profust failure probability can be transformed into the calculation of the traditional failure probability. Then various existing methods for the traditional failure probability can be used to estimate the Profust failure probability. Due to the high efficiency of the Adaptive Kriging (AK) model and the universality of the Monte Carlo Simulation (MCS), AK inserted MCS (abbreviated as AK-MCS) has been proven to be an efficient method for estimating the failure probability. Therefore, the AK-MCS combined with the GPF (abbreviated as AK-MCS + GPF) is proposed for estimating Profust failure probability. The proposed method greatly reduces the computational cost while ensuring the accuracy. Finally, four examples are given to validate the proposed AK-MCS + GPF. The results of the examples show the rationality and the efficiency of the proposed AK-MCS + GPF. Keywords: Failure probability, Fuzzy-state assumption, General performance function, Kriging model, Profust reliability, Reliability

This paper proposes an efficient Kriging-based subset simulation (KSS) method for hybrid reliability analysis under random and interval variables (HRA-RI) with small failure probability. In this method, Kriging metamodel is employed to replace the true performance function, and it is smartly updated based on the samples in the first and last levels of subset simulation (SS). To achieve the smart update, a new update strategy is developed to search out samples located around the projection outlines on the limit-state surface. Meanwhile, the number of samples in each level of SS is adaptively adjusted according to the coefficients of variation of estimated failure probabilities. Besides, to quantify the Kriging metamodel uncertainty in the estimation of the upper and lower bounds of the small failure probability, two uncertainty functions are defined and the corresponding termination conditions are developed to control Kriging update. The performance of KSS is tested by four examples. Results indicate that KSS is accurate and efficient for HRA-RI with small failure probability.

In reliability analysis for the practical engineering problems with the time-consuming model, it has become an important challenge that how to obtain accurate reliability assessment with a minimum number of calls. In order to reduce the computational cost, this paper develops a new sequential surrogate method combining adaptive kriging and Markov chain Monte Carlo simulation with a novel learning strategy for reliability analysis. The proposed method is named AK-MCMC, which takes full advantage of the classification feature of reliability analysis based on the surrogate models, and it can efficiently approximate the classification boundary of the performance function. First, the learning strategy is developed to sequentially pick out the informative samples for updating the experimental design samples. Then, a new stopping criterion is adopted to guarantee the classification accuracy of the constructed kriging model. In this way, the proposed method skillfully makes reliability evaluation independent of an adaptive iterative process, which greatly improves the efficiency of model refinement. Finally, the proposed method is applied to several examples, which contain small failure probability problem, non-linearity problem, and engineering problem with an implicit performance function. In particular, the efficiency of the proposed AK-MCMC method is proved for the problems with small failure probability.

This paper aims to propose a new analytical method of deriving the enveloping macroscopic fundamental diagram (MFD) in the light of the well-defined sufficient condition and the route choice criterion in a general network. The enveloping MFD is defined to describe the boundary of all scatter points relating the flow rate (vehicles per unit time) to the vehicle accumulation (vehicles) in a road network. The theoretical framework consists of two parts. The first part is a static congested traffic assignment model which is based on the congested link performance function and the deterministic user equilibrium principle under the entirely congested condition. The second part is the new analytical method which is proposed based on the static uncongested and congested traffic assignments with the deterministic user equilibrium, in which the well-defined sufficient condition is satisfied by employing the static traffic assignment models, and the route choice criterion is fulfilled by the deterministic user equilibrium condition (Wardrop's principle). The main findings of this paper are summarized as follows: 1) the enveloping MFD delimits a region where all scatter points are located; 2) the existence and reproducibility of the enveloping MFD in a general network are verified through numerical examples; 3) the proposed method is suggested to be applied to transportation planning for describing and evaluating the macro-characteristics and the performance of road networks and evaluating whether the OD pattern is congruous with the network topology.

Laser marking has been widely used in industrial processing. For different hatching methods, the operating efficiency and the clarity of the marking pattern are also different. Herein, we realize the zigzag parallel and contour parallel hatch of the single-layer and multi-layer contour pattern respectively based on different parameters, evaluate the algorithm, and give optimization strategies.

Motorcyclists account for more than 380 000 deaths annually worldwide from road traffic accidents. Motorcyclists are the most vulnerable road users worldwide to road safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% of deaths are from low- or middle-income countries. Colombia has a rate of 9.7 deaths per 100 000 inhabitants, which places it 10th in the world. Motorcycles in Colombia correspond to 57% of the fleet and generate an average of 51% of fatalities per year. This study aims to identify significant factors of the environment, traffic volume, and infrastructure to predict the number of accidents per year focused only on motorcyclists. The prediction model used a negative binomial regression for the definition of a Safety Performance Function (SPF) for motorcyclists. In the second stage, Bayes’ empirical approach is implemented to identify motorcycle crash-prone road sections. The study is applied in Cartagena, one of the capital cities with more traffic crashes and motorcyclists dedicated to informal transportation (motorcycle taxi riders) in Colombia. The data of 2884 motorcycle crashes between 2016 and 2017 are analyzed. The proposed model identifies that crashes of motorcyclists per kilometer have significant factors such as the average volume of daily motorcyclist traffic, the number of accesses (intersections) per kilometer, commercial areas, and the type of road and it identifies 55 critical accident-prone sections. The research evidences coherent and consistent results with previous studies and requires effective countermeasures for the benefit of road safety for motorcyclists.

The main objective of this study was to evaluate the safety effects caused by altering the lengths of deceleration and acceleration lanes at rest areas on expressways in Korea. Although general conclusions can be found through crash-based safety analysis, to examine more specific optimal conditions considering various traffic conditions, this study proposes a novel framework to explore and evaluate crash-based and simulation-based safety performances. For this purpose, the safety performance function (SPF) and crash modification factor (CMF) were developed to reflect real-world safety impacts. To consider nonlinear trends of the parameters, nonlinearizing link functions were introduced into the analysis. Two types of simulation analyses were conducted to (1) find the combination of surrogate safety measures (SSMs) that best fit with the crash-based safety performance results and (2) determine the optimal lengths of deceleration lane and acceleration lanes for different traffic conditions. The results showed that the best length of deceleration lane of a rest area is between 240 and 260 m, depending on the traffic conditions. The results also indicated that the optimal length of acceleration lane of a rest area is between 385 and 400 m, depending on the traffic parameters. The findings of this study could be used to determine the safety solutions with a micro-traffic simulator.

This article proposes a new fixed-time fuzzy adaptive fault-tolerant control methodology for the longitudinal dynamics of hypersonic flight vehicles (HFVs) in the presence of actuator faults, uncertain dynamics and external disturbances. In contrast with the conventional fixed-time control schemes that typically contain the fractional powers of errors in their designs, this work develops a low-complexity control structure in the sense of removing the dependence on the need of above-mentioned fractional power terms by means of prescribed performance control (PPC) method. Different from the most existing PPC approaches where the initial conditions of tracking errors are required to be known, the newly proposed prescribed performance function (PPF) can relax such restrictions through choosing properly small initial values of PPF. Fuzzy logic systems (FLSs) are employed to handle unknown dynamics and minimal learning parameter (MLP) technique is incorporated into the design for the purpose of alleviating computation burden. Closed-loop stability is rigorously proved via Lyapunov stability theory and simulation results are eventually given to validate the effectiveness of the proposed control strategy.

In this paper, a new analytical formula is proposed to determine the mean outcrossing rate of nonstationary non-Gaussian performance functions. The performance function is firstly transform...

Local reliability sensitivity methods aim at determining the partial derivatives of the failure probability or the reliability index with respect to model parameters. For efficient local reliability based sensitivity analysis, it is important to avoid repeated evaluations of the performance function. To this end, an extension of the moving particles method to local reliability based sensitivity analysis is presented that is completely based on the already evaluated samples for the reliability estimate and thus avoids repeated evaluations of the performance function. In order to further reduce the variance of the estimator and to increase the efficiency, a multilevel variant of the estimator is proposed. The method is discussed in detail and illustrated by means of examples.

The present work discusses an innovative approach to metamodeling in reliability that uses a field-transversal rationale. Adaptive metamodeling in reliability is characterized by its large spectra of models and techniques with different assumptions. As a result, the reliability engineer is frequently faced with the highly challenging task of selecting an appropriate model or technique with limited a priori knowledge about the performance function that defines the problem of reliability. To tackle this challenge, a complement-basis is proposed for adaptive metamodeling. It consists in using a batch of multiple metamodels or techniques that, accordingly to an activation criterion, are selected to solve the reliability analysis. This activation is set to depend on the model synergy with the problem in-hand. In the present work the leave-one-out loss is applied as evaluator of compatibility, and results show that the absolute loss successfully performs as an activator. A metamodel-independent learning approach and stopping criterion are implemented to study the proposed approach in five representative examples. Results show that the complement-basis allows to increase the efficiency of the reliability analysis through the selection of adequate metamodels, which is indicative of the untapped potential that further transversal research may add to metamodeling in reliability analysis.

The Probabilistic Seismic Demand Analysis (PSDA) which is frequently implemented in the first generation performance-based earthquake engineering quantifies seismic behavior of a structure by computing mean annual frequency of exceeding a specific value of a desired demand parameter given all anticipated earthquakes. This framework, based on the total probability integration formula, provides a technical basis on which aleatory uncertainties, uncertainties originated due to inherent randomness of the phenomena, are explicitly addressed. However, variability in the mean value of different model parameters, referred to as epistemic uncertainties and mainly due the finite-sample size of observations, is neglected. In this study, as an alternative to total probability integration, a reliability-based formulation tailored to effortlessly reflect both aleatory and epistemic uncertainties is put-forward to perform unified PSDA. Next, as an application of the proposed methodology, a reliability-based seismic demand curve of a 4-story example building is developed. Results demonstrate that the Second-Order Reliability Method (SORM) and important sampling method (ISM) along with multi-step Monte Carlo simulation (MSMCS) methods are appropriate candidates for computing reliability-based PSDA with differentiable and nondifferentiable performance functions, respectively.

Kriging-based surrogate model is widely adopted in the area of component reliability analysis, thanks to its computational efficiency. However, surrogate models employed in component reliability analysis can not be employed directly in system reliability analysis. In this paper, an effective krigingbased system reliability analysis approach is proposed based on AK-SYS. In the proposed method, the best next samples are selected from the safe region or failure region, and samples in the areas that have little contribution to the composite performance function are avoided. The efficiency and accuracy of the proposed method are illustrated via a numerical example.

Structural reliability analysis involving highly nonnormally distributed performance functions or relatively small failure probabilities is still a challenging problem in engineering practi...

The reliability of stay cables is critical to the safety of cable-stayed bridges. This paper investigates and compares reliability assessments of stay cables by using identified cable tens...

Cross-Industry Innovation is commonly understood as identification of analogies and interdisciplinary transfer or copying of technologies, processes, technical solutions, working principles or models between industrial sectors. In general, creative thinking in analogies belongs to the efficient ideation techniques. However, engineering graduates and specialists frequently lack the skills to think across the industry boundaries systematically. To overcome this drawback an easy-to-use method based on five analogies has been evaluated through its applications by students and engineers in numerous experiments and industrial case studies. The proposed analogies help to identify and resolve engineering contradictions and apply approaches of the Theory of Inventive Problem Solving TRIZ and biomimetics. The paper analyses the outcomes of the systematized analogies-based ideation and outlines that its performance continuously grows with the engineering experience. It defines metrics for ideation efficiency and ideation performance function. Finally, a comparison with other TRIZ inventive techniques, such as nine fields of the Substance-Field Analysis and 40 Inventive Principles is presented.

The existing step size methods aim to success in the convergence of searching the minimum performance target point in the reliability analysis. However, these methods cannot guarantee that the performance function value is smaller than that of previous point. This results in the redundant computation during the search process. In this paper, a new step method called hybrid directional step method is proposed to improve the efficiency of search process. The proposed method can keep the performance function values of iterations presenting a decreasing sequence and quickly converge to the minimum performance target point. The proposed method is compared with some existing methods through several numerical examples. The results show that the proposed hybrid directional step method presents good robustness and more efficient computation in practical application.

The focus of this paper is on an evaluation of negative consequences due to the installation of pedestrian hybrid beacon (PHB) signals and to identify associated characteristics to proactively plan and reduce danger at mid-block locations. Data for thirteen mid-block locations with a PHB signal in the city of Charlotte, North Carolina was gathered to conduct before-after analysis using Empirical Bayes (EB) method. Data for fifty-nine mid-block locations without a PHB signal or similar treatment was considered as control locations for developing a safety performance function (SPF). The on-network characteristics were considered as the predictor variables, while the number of all crashes from 2011 to 2013 was considered as the dependent variable. The SPF was validated using 2014 data. A calibration factor was applied to estimate the number of all crashes at each PHB location. The results obtained from before-after EB analysis showed that the actual number of all crashes are relatively higher after the installation of PHB signals at five out of the thirteen PHB signal locations when compared with the estimated number of all crashes, had the PHB signal not been installed. Pearson correlation coefficients were estimated and used to examine the relationship between the number of all crashes and predictor variables such as demographic, socio-economic, land use, and on-network characteristics within the vicinity of each PHB signal location. The findings indicate that installing PHB signals at mid-block locations along high traffic volume, high-speed and wide roads, and, near office, multi-family, retail, and vertical mixed land use areas will lead to an increase in the number of all crashes after its installation.