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Optimal planning of Maintenance and Rehabilitation (M&R) treatments due to limited resources and funding is vital. A pavement performance function formula is needed to model the M&R optimisation problem. By considering important features, a pavement deterioration function was developed with an R2 of 0.897. The essence of pavement deterioration is uncertain. Hence, disregarding the uncertainty may result in sub-optimal solutions. Therefore, two approaches were employed to optimise M&R treatments in a large-scale pavement network, including deterministic and risk-based. Both approaches aimed to minimise the required budget in the planning period constrained to acceptable pavement condition. A novel and robust metaheuristic algorithm was adjusted to solve the M&R planning problem deterministically. In the risk-based method, appropriate probability distribution functions were fitted to historical data of uncertain parameters. Monte Carlo simulation was performed to generate probability distributions of the required budget and condition of pavement sections. By using a risk-based strategy instead of the deterministic one, the required budget was reduced by 30%. Fault tree analysis was performed on the solutions obtained from the risk-based method to increase the pavement network's reliability. The results of the mentioned analysis represented that only by spending 2.5% more budget network's reliability could be significantly increased. [ABSTRACT FROM AUTHOR]

Developing an accurate pavement prediction model plays a dominant role in pavement M&R optimization. Despite employing different robust machine learning techniques to predict pavement conditions, these methods have some weaknesses in synchronising with exact optimization algorithms. The main contribution of this study is to propose a novel method for optimizing the pavement M&R plan with high accuracy. Contrary to conventional approaches, a robust prediction algorithm, Random Forest Regression (RFR), is applied to predict the pavement International Roughness Index (IRI). In addition, Multiple Linear Regression (MLR) is employed to assess the performance of the proposed technique in terms of IRI prediction accuracy. Whale Optimization Algorithm (WOA), as a powerful metaheuristic optimization algorithm, is utilised to obtain the optimal solution to the pavement M&R optimization problem. RFR is run as an internal part of the WOA in the introduced method. Furthermore, Genetic Algorithm (GA) is used to examine the performance of the proposed approach in finding the optimal solution. The RFR results conclude a more accurate prediction of IRI than MLR based on all machine learning performance indicators. Furthermore, the newly developed hybrid model significantly outperforms GA in finding the optimal and cost-effective solution to the M&R optimization problem. [ABSTRACT FROM AUTHOR]

Maintenance and Rehabilitation (M&R) scheduling is one of the vital aspects of a pavement management system (PMS). This study aims to establish accurate M&R plans for a large-scale pavement network. To this intent, parameters affecting pavement deterioration were identified from the literature, then Random Forest Regression was employed to determine the effective features for pavement deterioration modelling. An accurate pavement deterioration function was generated by applying significant features. The most robust metaheuristic and evolutionary algorithms were selected and adjusted to solve the M&R scheduling optimisation problem, including the Water Cycle Algorithm (WCA), Arithmetic Optimisation Algorithm (AOA), Differential Evolutionary (DE), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), and Genetic Algorithm (GA). The performance of the mentioned algorithms was compared to help researchers and decision-makers to select the appropriate algorithm for M&R scheduling optimisation. WCA and AOA showed to have the best performance among the adapted algorithms. Compared to AOA, DE, ACO, PSO, and GA, WCA's objective function was calculated to be 45%, 74%, 74%, 77% and 83% less, while its M&R cost was cheaper by 13%, 16%, 27%, 19%, and 18%, respectively. [ABSTRACT FROM AUTHOR]

CO2 emission reduction in large-scale pavement network maintenance planning has been an immense concern. The conventional single-objective optimisation modelsoverlook environmental issues such as CO2 emission. However, the introduced multi-objective optimisation aims to enhance the network condition and minimise CO2 emissions simultaneously. Two single-objective (coyote optimisation algorithm and genetic algorithm) and two multi-objective metaheuristic algorithms (multi-objective coyote optimisation algorithm and non-dominated sorting genetic algorithm) are employed to assess the effectiveness of the introduced environmental approach. Pavement maintenance planning optimisation requires the deterioration function formula and treatment improvement equation to be modelled. Hence, a new machine learning method called 'differential evolutionary programming' is introduced, which can provide the output-input formula. Differential evolutionary programming predicts the pavement deterioration value and overlay improvement with R2 of 0.992 and 0.970, respectively. The results indicate that the coyote optimisation algorithm's objective function is 66% lower than that of the genetic algorithm. Likewise, the multi-objective coyote optimisation algorithm reduces the first objective function by 72% on average compared to the non-dominated sorting genetic algorithm. The grey relational analysis is performed to compare single-objective and multi-objective optimal solutions. All optimal solutions presented by multi-objective modelling dominates the single-objective optimisation optimal solution based on the grey relational grade. [ABSTRACT FROM AUTHOR]

This study approaches a multi-stage stochastic mixed-integer programming model for the high-level complexity of large-scale pavement maintenance scheduling problems. The substance of some parameters in the mentioned problems is uncertain. Ignoring the uncertainty of these parameters in the pavement maintenance scheduling problems may lead to suboptimal solutions and unstable pavement conditions. In this study, annual budget and pavement deterioration rate are considered uncertain parameters. On the other hand, pavement agencies generally face large-scale pavement networks. The complexity of the proposed stochastic model increases exponentially with the number of network sections and scenarios. The problem is solved using the Progressive Hedging Algorithm (PHA), which is suitable for large-scale stochastic programming problems, by achieving an effective decomposition over scenarios. A modified adaptive strategy for choosing the penalty parameter value is applied that aims to improve the solution process. A pavement network including 251 sections is considered the case study for this investigation, and the current study seeks optimal maintenance scheduling over a finite analysis period. The performance of the stochastic model is compared with that of the deterministic model. The results indicate that the introduced approach is competent to address uncertainty in maintenance and rehabilitation problems. [ABSTRACT FROM AUTHOR]

This study examines the applicability to developing countries of a pavement management system (PMS) with less data (two-point) requirement to complement current practice. Due to limited capacity, many developing countries like Uganda have adopted a PMS after specified intervals regardless of deterioration rate (i.e. time-dependent policy). Maintenance planning based on deterioration rate (i.e. condition-dependent policy), as proposed, would be more ideal because pavement deterioration is stochastic. A PMS was developed using the Markov hazard model and then an empirical study was conducted for surveyed Ugandan national road network comparing both policies considering a basic plan and a fixed budget. A greedy algorithm was used to select sections for repair based on worst condition first (for time-dependent) or fastest deterioration first (for condition-dependent). A shift to the condition-dependent policy increased percentages of network in good and fair condition by 8.6% and 2.5%, respectively, and reduced percentages in poor and bad condition by 8.5% and 2.6%, respectively. Additionally, maintenance plans with and without preventive maintenance were compared considering a fixed budget. Preventive maintenance further increased percentage in good condition by 27.4% and reduced percentages in poor and bad condition by 11.6% and 4.2%, respectively, with a 53.5% reduction in life cycle costs. [ABSTRACT FROM AUTHOR]

Appropriate pavement maintenance is of great importance due to the increasing deterioration of pavements and limited resources. Nowadays, highway agencies face large-scale networks. The management of large-scale networks is a challenge concerning the computational complexity, which typically increases exponentially with the dimension of the network. Water cycle and genetic algorithms are utilised in this paper to find the optimal maintenance schedule of large-scale pavement networks. A new practical constraint is introduced in the mathematical formulation that the total annual costs should not fluctuate more than a predefined limit over the planning horizon. Moreover, a novel index is developed to calculate the equity level in pavement maintenance scheduling, and the outcomes of the algorithms are compared based on this equation. A real road network with 103 pavement sections is the case study of this paper. The results show that 'Equity index' is reduced by 94% and 48% during the analysis period by WCA and GA, respectively. Drawing on WCA and GA optimal solutions, the average international roughness index of the network is decreased by 35% and 31% respectively in a 5-year horizon. Moreover, the variance of the maximum and minimum allocated budget in the analysis period is less than 15%. [ABSTRACT FROM AUTHOR]

Decision Support Systems (DSS) are now an established part of the information systems mainstream, both in research and in practice. The DSS development approach differs from traditional systems development not only with regard to its associated paradigms and orientation, but also in the methods of requirements analysis it employs. This paper surveys the major methodologies used for DSS development. It analyzes them by structure, paradigm, and orientation, and discusses their underlying assumptions. A research model is then developed and used to relate the functions of DSS methodology to decision-making environments and the relevant processes within them. Finally, a contingency theory is presented to show how each of the surveyed methodologies reduces the lack of structure in the decision-making environment, and bow this may be used by DSS developers for selecting a DSS methodology. Other components of the research model are discussed, to identify further prerequisites for improved understanding of the DSS role and application. [ABSTRACT FROM AUTHOR]

Multifaceted characteristics of urban travel have an impact on the passengers' overall satisfaction with the transport system. In this study, we investigate the interrelationships among traveler satisfaction, travel and traveler characteristics, and service performance in a multimodal network that comprises of a trunk line and its feeder lines. We analyze the factors influencing the choices of access to rail transit stations and the satisfaction of transit travelers with the rapid rail transit systems. We quantitatively study these relationships and demonstrate the complexity of evaluating transit service performance. Since the interrelationships among variables affecting this system are mainly stochastic, we analyze the satisfaction with transit system problem using a Bayesian Belief Network (BBN), which helps capture the causality among variables with inherent uncertainty. Using the case of Istanbul, we employ the BBN as a decision support tool for policy-makers to analyze the rapid rail transit services and determine policies for improving the quality and the level of service to increase the satisfaction with transit system. In the case study, satisfaction with accessibility and access mode variables are found to be more effective variables than total travel time for travel time satisfaction, confirming the significant role of access in multimodal travels. [ABSTRACT FROM AUTHOR]

Pavement roughness is a key parameter for controlling pavement construction processes and for assessing ride quality during the life of a pavement system. This paper describes algorithms used in processing three-dimensional (3D) stationary terrestrial laser scanning (STLS) point clouds to obtain surface maps of point wise indices that characterise pavement roughness. The backbone of the analysis is a quarter-car model simulation over a spatial 3D mesh grid representing the pavement surface. With the rich data-set obtained by 3D scanning, the algorithms identify several dynamic responses and inferences (suspension, acceleration and jerk) at each point in the domain. Variability in the indices is compared for a ‘rough’ pavement and a ‘smooth’ pavement in the spatial domain for different speed simulations of the quarter-car model. Results show high spatial variability in the various roughness indices both longitudinally and transversely (i.e. different wheel path positions). It is proposed that pavement roughness characterisation using a spatial framework coupled with univariate statistics provides more details on the severity and location of pavement roughness features compared to the (1D) one-dimensional methods. This paper describes approaches that provide an algorithmic framework for others collecting similar STLS 3D spatial data to be used in advanced pavement roughness characterisation. [ABSTRACT FROM AUTHOR]

The incidence of road crash deaths is high in Iran. Seat belts can reduce the risk of death or serious injury. This study aimed to estimate the rate of seat belt use and its related factors for car drivers in Tehran, Iran after proclamation of the 2011 legislation. A roadside observational study was conducted in 2012 and 10,752 cars and taxis commuting in different streets of Tehran were screened in regard to drivers' seat belt wearing. Other variables including gender, age range, type of street, district, time of day and day of week were also collected. The rate of seat belt use was 70.9%, and was significantly higher in females, elders and on freeways and significantly less in afternoon hours, side streets and in taxi drivers. The rate of seat belt use in Tehran (a representative of Iran) is still low despite the implementation of new legislations. More initiatives are needed to increase this rate especially in certain groups and areas. [ABSTRACT FROM AUTHOR]

This article addresses a general class of infrastructure management problems raised in maintenance and rehabilitation scheduling. Infrastructure agencies usually face budget uncertainties that eventually lead to suboptimal scheduling planning if maintenance decisions are made without taking the uncertainty into consideration. It is important for decision makers to adopt maintenance and rehabilitation scheduling policies that consider all budget scenarios. The authors propose a multistage, stochastic programming model to address this problem. The authors also develop a solution procedure using the augmented Lagrangian decomposition algorithm. A case study exploring the computational characteristics of the proposed algorithm is conducted and the benefit ofusing the stochastic programming approach is discussed. [ABSTRACT FROM PUBLISHER]

This paper presents a methodology for maintenance optimisation for heterogeneous infrastructure systems, i.e., systems composed of multiple facilities with different characteristics such as environments, materials, and deterioration processes. We present a bottom-up approach: facility-level optimal maintenance policies are first found; these policies are then combined with budget constraints in the system-level optimisation. In the first step, optimal and near-optimal maintenance policies for each facility are found and used as inputs for the system-level optimisation. In the second step, the problem is formulated as a constrained combinatorial optimisation problem, where the best combination of facility-level optimal and near-optimal solutions is identified. Two heuristics, pattern search heuristic (PSH) and evolutionary algorithm (EA), are adopted to solve the combinatorial optimisation problem. Their performance is evaluated using a hypothetical system of pavement sections. Comparison result with real optimal solutions for 20 facilities showed that both algorithms give near-optimal solutions (within less than 0.1% difference from the optimal solution) in 978 (PSH) and 966 (EA) cases out of 1000 executions. The EA performs better in terms of processing time than the PSH. Numerical experiments show the potential of the proposed algorithms to solve the maintenance optimisation problem for realistic heterogeneous systems. [ABSTRACT FROM AUTHOR]

This paper computes the cost of traffic congestion in the city of Antofagasta in Chile. A microsimulation is implemented where all the agents of the system travel across the transport network. The congestion cost is computed through the aggregation of the opportunity cost of people waiting within the transport system, as a consequence of traffic congestion. Monte Carlo experiments produced an approximated congestion cost of US$1.02 million during a typical working day. Moreover, the simulation provides useful information about the average traveling time for the 14 districts of the city. [ABSTRACT FROM PUBLISHER]

Pedestrian injuries are a significant health risk to children, particularly those 5–9 years of age. Surprisingly, few studies have explored parent-related factors that may moderate this risk. We examined parental supervision choices in the context of child pedestrian experience, parent perceptual factors and varying levels of environmental risk. A series of street crossing scenarios were used to examine the roles of child, parent and environmental factors in determining parents’ supervision choices. Parents recognised differing levels of risk across environmental conditions and altered their supervision choices accordingly. Child age and parental risk perception were significantly predictive of supervision choices. Our results demonstrate that parents assess multiple factors when determining the intensity of supervision necessary for their children. Notably, parents adjust their supervision in direct relation to changes in the physical environment. Implications of these findings for injury prevention and future research are discussed. [ABSTRACT FROM AUTHOR]

This article presents a framework and an illustrative example for identifying the optimal pavement maintenance and rehabilitation (M&R) strategy using a mixed-integer nonlinear programming model. The objective function is to maximize the cost-effectiveness expressed as the ratio of the effectiveness to the cost. The constraints for the optimization problem are related to performance, budget, and choice. Two different formulations of effectiveness are derived using treatment-specific performance models for each constituent treatment of the strategy; and cost is expressed in terms of the agency and user costs over the life cycle. The proposed methodology is demonstrated using a case study. Probability distributions are established for the optimization input variables and Monte Carlo simulations are carried out to yield optimal solutions. Using the results of these simulations, M&R strategy contours are developed as a novel tool that can help pavement managers quickly identify the optimal M&R strategy for a given pavement section. [ABSTRACT FROM AUTHOR]

We hypothesise that intra-household interaction influences home departure time and mode choice for the morning commute. In Indonesia, over 71% of vehicles on the road are motorcycles. This fact increases the significance of household interaction in influencing transport mode choice since the simplicity of the motorcycle allows a great degree of versatility in regard to multiple family member transport. To emphasise this point, our study focuses on the unique travel behaviour of adolescents during the school morning commute which, due to the use of the motorcycle, is a combination of the travel behaviour of accompanied children and escorting adults. Our study discovers that adolescents are likely to shift their school arrival time very early or close to the designated starting time in relation to motorcycle-based parental escort to school. In regard to mode choice, adolescent students prefer to be escorted by motorcycle rather than take public transport. [ABSTRACT FROM AUTHOR]

The present research examines the design of the public neighborhoods in the United Arab Emirates in terms of social sustainability, especially in the city of Al Ain. Based on the relevant principles and indicators of social sustainability in neighborhoods both globally and locally, the research began with an evaluation of the dimensions of social sustainability by adopting a qualitative research method. The research tools included conducting face-to-face interviews with representatives of Emirati families living in public neighborhoods, analyses of the design patterns of some selected neighborhoods, field observations and spatial syntactic analyses. Through this multi-phase analysis, a clearer understanding of the level of social sustainability achieved in the design of public neighborhoods in Al Ain has been realized, and some neighborhood design guidelines have been proposed. [ABSTRACT FROM PUBLISHER]

Pedestrian and cyclist injuries are significant public health issues, together accounting for 11-30% of road deaths in highly motorised countries. Children are particularly at risk. In Australia in 2009 11.4% of pedestrian deaths and 6.4% of cyclist deaths comprised children aged 0-16 years. Parental attitudes and level of supervision are important to children's road safety. Results from a telephone survey with parents of children 5-9 years (N = 147) are reported. Questions addressed beliefs about preventability of injury, appropriate ages for children to cross the road or cycle independently and the frequency of holding 5-9 year old children's hands while crossing the road. Results suggest that parents believe most injuries are preventable and that they personally can act to improve their own safety in the home, on the road, at work, as well as in or on the water. Most parents (68%) indicated children should be 10 years or older before crossing the road or cycling independently. Parents were more likely to report holding younger children's hands (5-6 years) when crossing the road and less likely to do so for 7- to 9-year olds. There was a small effect of child gender, with parents more likely to hold a boy's hand than that of a girl. [ABSTRACT FROM AUTHOR]

This study measures pedestrian walking speeds in New Zealand to estimate the influences on mean walking speeds as these concern urban planning and pedestrian facility design. Research was conducted using field observations of walking speeds under different conditions: gradient and urban/rural townships. The data show complex interrelationships between environment, personal characteristics of pedestrian and physical factors. Mean walking speeds between 80-95 m/min are observed. These results do not support the idea that walking speeds are indicative of pace of life. Rather, walking speeds are proposed as being an indicator of the environment's 'walkability', as a walking speed that closely reflects that of the mean population is a key indicator of the successful design of pedestrian facilities. [ABSTRACT FROM AUTHOR]

The article examines the childhood injury prevention study, which states that the essential cause of children's trauma was due to insufficient parental supervision. The purpose of the study was to determine the role of caregivers and parents for the safety of children, that was conducted to the group of primary school children aged 5-12 years old in Australia in 2006. Accordingly, the research was funded by the national health and medical research council of the country.

In the past decade, there has been significant investment in Intelligent Transportation Systems (ITS) technologies that provide information to both en-route and pre-trip travelers. However, there is no definitive evidence that en-route travelers actually use the information and alter their travel patterns. Previous research employed surveys that relied on motorists' written or spoken responses to questions involving travel information and hypothetical roadway scenarios. This research examines travel behavior on freeways equipped with ITS technologies in Connecticut using collected real-time traffic count data from the diversionary roadways. Results find that more travel is occurring on the diversionary routes during periods of variable message sign (VMS) messages than during equivalent periods having no messages, indicating a motorist travel response to these messages. [ABSTRACT FROM AUTHOR]

The ADVANCE Project, conducted from 1990 through 1997, was one of the first attempts to undertake a large-scale field test of an emerging technology in the ITS field, specifically in the area of in-vehicle dynamic route guidance. It was also an early example of a public-private partnership involving a large corporation, two university research centers, state and federal governments, and other participants in more specific or minor roles. This memoir, initially written at the close of my involvement in the Project in early 1996, seeks to describe the many institutional difficulties of this undertaking, as well as some of the lessons I learned. [ABSTRACT FROM AUTHOR]

The spatial configuration of cities and its relationship to the urban environment has recently been the subject of empirical, theoretical and policy research. Because of the disciplines involved, relevant articles are scattered over a large number of journals. The objective of this paper is to put the issues in perspective by reviewing the basic concepts and relationships involved, and to evaluate critically the current state of knowledge about urban form, energy utilisation and the environment. The scope of the paper is limited to urban transport energy use and the associated emissions. Suggestions for further progress in the field are offered, with emphasis placed on integrated urban models as useful and policy-sensitive analytical tools. [ABSTRACT FROM AUTHOR]