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Lean construction (LC) targets the reduction and eventual removal of non-value adding activities (otherwise known as waste) in construction projects to increase value to stakeholders. The applicati...

Several cities around the world have announced strategies to extend and (or) upgrade their bikeway networks in response to the rapid increase of bicycle users. However, there is a disconnection between these strategies and management systems, often used for the scheduling of maintenance and rehabilitation of roads. Traditional pavement management systems fail to incorporate bicycle pathways considering bicycling demand, along with pavement condition, as a driving element to budget for improvements. More convenient and safer bicycling facilities can encourage more individuals to shift their daily commuting habits to bicycling. In this study, we incorporate bicycling demand into pavement management systems to produce strategic plans for the maintenance and improvement of the bicycle networks. Furthermore, here we employ smartphones to represent bicycling demand using GPS trajectories of bicycles. In addition, goal optimization is applied to schedule interventions and improvements. Two scenarios are investigated with different annual budgets.

Urban railways play a critical role in the daily life of citizens. However, extensive deterioration of mostly aged systems complicates the management of this type of infrastructure in copin...

Roads in poor road condition disrupt emergency operations in disaster-prone areas during emergency periods. Prolonged inundation of pavements from storm surge accelerates deterioration of pavements and increases maintenance cost. The objective of this study is to propose an optimized decision support system for pavement maintenance and rehabilitation (MR community, structure and infrastructure vulnerabilities; and damage indices. Linear programming was applied to optimize M&R strategies to ensure good pavement condition for all roads at a minimum M&R budget. Lifecycle optimization of M&R operations estimated that USD 2.49 million is the minimum annual budget that ensures having good average road’s condition in the study area. Most of the annual M&R budget will be invested for overlay and resealing treatments on the roads at high and medium GEOPHRIV areas. This study helps transportation authorities to identify deteriorated pavement sections, maintain the pavement periodically to prevent or minimize damage before storm surge, and allocate resources for M&R operations.

Metro systems play a crucial role in the movement of millions of passengers worldwide as commuters rely on a fast, reliable, and convenient underground railway for their daily transportation. Howev...

The objective of this study is to apply the Backpropagation Neural (BPN) network with Generalised Delta Rule learning algorithm for reducing the measurement errors of pavement performance modelling. The Multi-Layer Perceptron network and sigmoid activation function are applied to build the BPN network of Pavement Condition Index (PCI). Collector and arterial roads of both flexible and rigid pavements in Montreal City are taken as a case study. The input variables of the PCI are Average Annual Daily Traffic (AADT), Equivalent Single Axle Loads (ESALs), Structural Number (SN), pavement age, slab thickness and difference in the PCI between the current and preceding year (ΔPCI). The BPN networks estimate that the PCI has inverse relationships with AADT, ESALs and pavement age. The PCI has positive relationships with these variables for roads that have recent treatment operations. The PCI has positive relationships with SN and slab thickness that imply the increase in pavement condition with increasing structu...

This study improves the pavement management system by developing a linear programming optimization for the road network of the City of Montreal with simulated traffic for a period of 50 years and deals with the uncertainty of pavement performance modeling. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. A backpropagation neural network (BPN) with a generalized delta rule learning algorithm is applied to develop pavement performance models without uncertainties. Linear programming of life-cycle optimization is applied to develop maintenance and rehabilitation strategies to ensure the achievement of good levels of pavement condition subject to a given maintenance budget. The BPN network estimated that PCI values were predominantly determined by the differences in pavement condition index, AADT, and equivalent single axle loads. Dynamic linear programming optimization estimated that CAD$150 million is the minimum annual budget required to keep most of the arterial and local roads in good condition in Montreal.

Traditional pavement management system uses historical data on traffic volume or traffic growth rate to develop the pavement deterioration curves. This study simulates the traffic loads on regional and urban road networks to estimate the pavement deterioration curves applying travel demand models at urban and regional scales during the period of 2013–2062. Highways 1, 2, 7, 15, 16, 102, and 104 connecting the Atlantic Provinces of Canada are considered as the case study at regional scale. Arterial and local roads of both rigid and flexible pavement types in the city of Montreal are considered as the case study at urban scale. The TRANUS model integrates spatial input-output and transportation models to simulate interprovincial freight movement on the regional road network. Urban transportation planning system simulates the urban traffic on the road network of the city of Montreal. The accumulated traffic loads are calculated based on the predicted annual average daily traffic and locally observed truck di...

Canada's railway industry has invested more than $20 billion since 1999 to improve the safety of users as a top priority. Although the accident rates have decreased, the users' safety and comfort could still be impacted by vehicle's vibration, air quality, and noise levels. In this regard, comfort and safety are mutually related aspects; worsening of air quality could compromise users' safety from a respiratory health perspective. Further, noise, level of lighting, thermal condition and movement could contribute to hearing problems, visual impairments, bacteria growth, and nausea, respectively. Management of urban transit systems should ensure a convenient transit service with adequate levels of ride and quality (time and cost) as well as users' comfort and safety. This article proposes an approach for measurement of riders' comfort (as it relates to safety) in terms of humidity, temperature, vibration, concentration of CO2, noise, and lighting level based on a set of maximum thresholds identified with respect to public health guidelines. This enables the use of a weighting method to establish an overall network comfort level. Such an index can be used to direct the allocation of investments for improvement of comfort as well as ridership. A case study of several lines in Sydney trains network is presented to illustrate the applicability and usefulness of the proposed approach. Data were collected and analyzed using low-cost technologies such as smart phones and mobile sensors. The comfort factors are measured and reported per train line and then combined to generate an overall comfort index.

Transit agencies concentrate their efforts to satisfy most commuters and convince them to abandon the use of the private car in daily trips, which is a key element in promoting environmentally sustainable cities. Travel time and cost have been widely investigated as travelers’ satisfaction factors, while human aspects such as comfort are mostly neglected. Management of urban transit systems should ensure a convenient transit service with adequate levels of ride and quality (time and cost) as well as users’ comfort, health and safety to achieve sustainable societies. This study proposes an approach to quantitatively measure railway riders’ comfort in terms of humidity, temperature, vibration, the concentration of CO2, noise, and lighting. Such indexes can be used to direct the allocation of investments for improvement of comfort in urban transit infrastructures as well as capture reality in demand prediction modeling. A case study of several lines in the Montreal metro network is presented to illustrate the applicability and usefulness of the proposed approach. The newer trains in the Montreal metro are an improvement over older trains when it comes to rider comfort; however, they could still be better, especially when it comes to auditory comfort.

The literature is rich in pavement deterioration modeling; however, classical frameworks for decay predication mostly rely on time series data for deterioration trends while several hidden ...

This paper presents a performance-based optimisation approach for conducting trade-off analysis between safety (roads) and condition (bridges and roads). Safety was based on potential for improvement (PFI). Road condition was based on surface distresses and bridge condition was based on apparent age per subcomponent. The analysis uses a non-monetised optimisation that expanded upon classical Pareto optimality by observing performance across time. It was found that achievement of good results was conditioned by the availability of early age treatments and impacted by a frontier effect preventing the optimisation algorithm from realising of the long-term benefits of deploying actions when approaching the end of the analysis period. A disaggregated bridge condition index proved capable of improving levels of service in bridge subcomponents.

Traffic loading for pavement deterioration should be modeled as a dynamic indicator based on trip distribution derived from spatial economics. The estimation of modal distribution of trips and land development has been the main focus of integrated land use and transport models. However, no connection with transportation asset management has been established. This paper proposes the use of spatial economic simulation to forecast freight-traffic distribution to improve pavement-deterioration modeling. A case study of trade flows between Canada’s Atlantic Provinces and Quebec is used to show the pitfall of current management models in estimating rates of deterioration, underfunding maintenance, and rehabilitation strategies. It was found that a total cost of $25 million could maintain adequate levels of condition under the current performance modeling; however, such a budget is inadequate when performance is based on forecasted truck traffic. It was also found that aggregation of pavements in a few homogeneous groups resulted in the inability to prioritize investments considering the economic relevance of the road in the region. This study suggests the use of individual deterioration models for strategic roads.

Transportation asset management systems are concerned with the daunting task of maintenance and upgrade of infrastructure within the restrictions of an annual budget. Consideration of environmental impacts is normally left out of the analysis. This paper considers the incorporation into strategic planning of environmental impacts resulting from maintenance and rehabilitation of pavements. The energy use of such activities and resulting greenhouse gas (GHG) emissions are explicitly considered, and the results of a performance-based optimization are discussed. The study followed a three-step trade-off process: (a) finding the minimum requirement for the annual budget, (b) maximizing pavement condition, and (c) reducing environmental impacts. The results showed that considering environmental impacts in the strategic planning process returned a substantial gain in energy savings and reduction of GHG emissions, although a small sacrifice in pavement performance was required. The consideration of environmental impacts reduced energy use and GHG emissions by 19% and 24%, respectively, but pavement condition dropped slightly to 98.5% of the optimal solution.

The objectives of this study are to simulate the Thornthwaite moisture index (TMI) for zones within the Atlantic provinces of Canada (APC) during three 30-year periods in the 21st century and to estimate the interactive effect of TMI and simulated freight traffic loads on the deterioration of pavement structure during the same period. Regional Highways 1, 2, 7, 15, 16, 102, and 104 connecting the APC are considered as the case study. Integration of spatial input-output and transportation models simulates freight movements on the selected regional highways during the period of 2012–2100. TMI is estimated using downscaled average monthly precipitation and temperature at 34 stations within the APC. Simulated traffic loads and TMI are applied to mechanistic modeling of roughness progression on the pavement structure. The findings of this study show that an increase in TMI can cause 11–68% increase of roughness progress rate on pavement structure.

This paper demonstrates a correlation between the extensiveness of infrastructure and national development. This was achieved by considering kilometres of paved roads, kilometres of rail, kilometres of paved runways, quality of shipping ports and quality of urban infrastructure. Data were collected from a variety of sources including the World Bank and the United Nations databases. Measures of the quantity or extensiveness of the infrastructures were normalized based on the populations of the various countries, transforming them into per capita measures, which were then logarithmically transformed to produce indices of the extensiveness of the infrastructures. These indices were then plotted against the national development indicator, the human development index (HDI). Of the infrastructures considered, paved roads per capita index showed the strongest correlation with HDI, while quality of port infrastructure index showed the weakest correlation. When the indices for the different infrastructures were co...

This paper presents an approach for incorporating reliability on initial performance prediction models developed from as little as two time series predictors. It employs a novel methodology to provide apparent ages as surrogate of condition and, in addition, applies multilevel Bayesian regression to calibrate mechanistic empirical models to local conditions. This paper develops an international roughness index deterministic performance model for the Costa Rica road network and, further shows the procedure for obtaining a probabilistic multilevel Bayesian model which includes distributions of the mechanistic parameters and confidence intervals for the predicted performance. Bayesian statistics are also deployed for calibrating pavement strength coefficients to local observations.

This paper proposes the use of multi-level Bayesian modeling for calibrating mechanistic model parameters from historical data while capturing reliability by estimating a desired confidence interval of the predictions. The model is capable of estimating the parameters from the observed data and expert criteria even in cases of missing data points. This approach allows rapid generation of several deterioration models without the need to partition the data into pavement families. It estimates posterior distributions for model coefficients and predicts values of the response for unobserved levels of the causal factors. A case study from the New Brunswick Department of Transportation is used to calibrate a simplified mechanistic pavement roughness progression model based on 6-year international roughness index (IRI) observations. The model incorporates the effects of pavement structural capacity in terms of deflection basin parameter (AREA) in place of the modified structural number, traffic loading (ESAL) and environmental factors. The results of the model showed that, as expected, chipseal roads have higher as built roughness and deteriorate faster than asphalt roads. Sensitivity analysis of the deterministic (the mean predictions) part of the model showed that in New Brunswick where traffic is relatively low the environment is the most important factor.

Acquiring detailed knowledge of surface treatments effectiveness is required to improve performance-based decisions for allocating resources to preserve and maintain pavements on any road network. Measurement of treatment effectiveness is a complex task that requires historical records of treatments with observations of before and after performance trends. Lack of data is often an obstacle that impedes development and incorporation of surface maintenance treatments into pavement management. This paper analyzes the effect of surface treatments on asphalt paved arterial roads for several control sections of New Brunswick. The method uses a Transition Probability Matrix to capture main effects by mapping mean trends of surface improvement and pavement structure decay. It was found that surface treatments have an immediate effect reducing the rate of loss of structural capacity. Pavements with international roughness index (IRI) smaller than 1.4 m/km did not seem to benefit from surface treatments. Those with IRI higher than 1.66 m/km gained from 6 to 8 years of additional life. Reset value for surface treatments fall between 1.18 and 1.29 m/km. This paper aims to serve to practitioners seeking to capture and incorporate effectiveness of surface treatments (i.e., crack-sealing) into Pavement Management.

Background We investigate the specification of roadway lighting for safety to understand the elements needed in statistical analysis of road collisions during night time. Several goals were targeted. First, which type of response is best, or whether both responses should be used. Second, which indicator of lighting should we favour? Third, which other factors should be included in the analysis and fourth, how effective is lighting in reducing nigh-time collision. Methods The case study comprised illuminance and luminance measurements collected for the Arthabaska region in Quebec, along with available operational and geometric variables expected to explain roadway collisions. A zero-inflated negative-binomial model was used to analyse the impact of predictors on collision frequency and severity using classical maximum likelihood validated by a Full Bayesian regression Results It was found that collision severity is best, resulting in more factors being significant in the expected sense of contribution. Luminance was the best indicator for road lighting. A correlation matrix aided in the identification of linearly dependencies between factors and the response or other factors. The last goal was investigated by comparing daytime with night-time collision analysis. The night time analysis included luminance and glare. The results were very close between day and night, with luminance proving to be an effective countermeasure for night collisions. A three-times difference on the coefficient for traffic volume was found. The use of a dummy variable related to standard levels of illumination is presented and will be key in future research for the estimation of effective levels of lighting. Conclusions A connexion between roadway lighting and crash history can be used to support the warrant of lighting and identification of levels by using the statistical methods herein proposed adapted to test effectiveness of lighting levels and explanatory power of variables surviving co-linearity and significance tests.

Increasing computing capacity has made possible the use of advanced simulation and optimization methods to solve complex problems in transportation and urban planning. Methods such as linear programming and heuristic optimization have made it possible to find the most cost-effective solution for allocating resources among competing alternatives. Agent based approaches and regional econometric models have succeeded to simulate urban development, economic growth and their impacts across modes of transportation. This paper examines the advantages of incorporating Land Use and Transport Modeling into Asset Management and presents a framework for accomplishing such an objective; especially for timing maintenance, rehabilitation and capital projects to improve safety, mobility and condition. It suggests that decisions for scheduling rehabilitation of existing links and construction of new projects should be based on user impacts and expected gains in terms of regional economic benefits. CE Database subject headings: transportation asset management; integrated land use and transportation; decision making analytical tools, capital projects; mobility; safety; condition.