Critical review and methodological issues in integrated life-cycle analysis on road networks

Life-cycle management of road network projects traditionally emphasise material production and construction stages, with less attention given to usage stage and functionality improvement. Increasingly there is a need to address: inconsistencies in cost attribute selection; adjusting for uncertainties and costs; clarifying system boundaries; data sources; functional units and regional or temporal applicability of life-cycle frameworks. The current study focuses on a critical literature review of life-cycle cost analysis (LCCA) and life-cycle assessment (LCA) research published in the last decade (post 2008) towards identification of research gaps. Accurately analysing all life-cycle stages, feedback loops, future cash and resource flows, and interlinking performance with overall sustainability can aid the decision-making process towards sustainable alternatives for constructing new, or rehabilitating existing roads. This review finds that the use of recycled materials, base/sub-base stabilisers and asphalt binder replacement has the potential of energy saving (=34% or 3.1 TJ), mitigating landfill disposal issues, and greenhouse gas load reduction (=34.5% CDE). Lack of real world LCCA-LCA application and stakeholder prejudice against recycled material usage are addressable by better stakeholder (decision-makers and road users) engagement via a social component. The proposed enhancements identified in this study can increase LCA/LCCA attraction to policy-makers, planners and users and ultimately ensure a more sustainable asset

Life-cycle asset management in residential developments building on transport system critical attributes via a data-mining algorithm

Public transport can discourage individual car usage as a life-cycle asset management strategy towards carbon neutrality. An effective public transport system contributes greatly to the wider goal of a sustainable built environment, provided the critical transit system attributes are measured and addressed to (continue to) improve commuter uptake of public systems by residents living and working in local communities. Travel data from intra-city travellers can advise discrete policy recommendations based on a residential area or development's public transport demand. Commuter segments related to travelling frequency, satisfaction from service level, and its value for money are evaluated to extract econometric models/association rules. A data mining algorithm with minimum confidence, support, interest, syntactic constraints and meaningfulness measure as inputs is designed to exploit a large set of 31 variables collected for 1,520 respondents, generating 72 models. This methodology presents an alternative to multivariate analyses to find correlations in bigger databases of categorical variables. Results here augment literature by highlighting traveller perceptions related to frequency of buses, journey time, and capacity, as a net positive effect of frequent buses operating on rapid transit routes. Policymakers can address public transport uptake through service frequency variation during peak-hours with resultant reduced car dependence apt to reduce induced life-cycle environmental burdens of buildings by altering residents' mode choices, and a potential design change of buildings towards a public transit-based, compact, and shared space urban built environment

FishEye8K: A Benchmark and Dataset for Fisheye Camera Object Detection

With the advance of AI, road object detection has been a prominent topic in computer vision, mostly using perspective cameras. Fisheye lens provides omnidirectional wide coverage for using fewer cameras to monitor road intersections, however with view distortions. To our knowledge, there is no existing open dataset prepared for traffic surveillance on fisheye cameras. This paper introduces an open FishEye8K benchmark dataset for road object detection tasks, which comprises 157K bounding boxes across five classes (Pedestrian, Bike, Car, Bus, and Truck). In addition, we present benchmark results of State-of-The-Art (SoTA) models, including variations of YOLOv5, YOLOR, YOLO7, and YOLOv8. The dataset comprises 8,000 images recorded in 22 videos using 18 fisheye cameras for traffic monitoring in Hsinchu, Taiwan, at resolutions of 1080$\times$1080 and 1280$\times$1280. The data annotation and validation process were arduous and time-consuming, due to the ultra-wide panoramic and hemispherical fisheye camera images with large distortion and numerous road participants, particularly people riding scooters. To avoid bias, frames from a particular camera were assigned to either the training or test sets, maintaining a ratio of about 70:30 for both the number of images and bounding boxes in each class. Experimental results show that YOLOv8 and YOLOR outperform on input sizes 640$\times$640 and 1280$\times$1280, respectively. The dataset will be available on GitHub with PASCAL VOC, MS COCO, and YOLO annotation formats. The FishEye8K benchmark will provide significant contributions to the fisheye video analytics and smart city applications.Comment: CVPR Workshops 202

Childhood acute lymphoblastic leukemia in the Middle East and neighboring countries: A prospective multi-institutional international collaborative study (CALLME1) by the Middle East Childhood Cancer Alliance (MECCA)

Background: Little is known about childhood ALL in the Middle East. This study was undertaken by MECCA as initial efforts in collaborative data collection to provide clinical and demographic information on children with ALL in the Middle East. Procedure: Clinical and laboratory data for patients with ALL between January 2008 and April 2012 were prospectively collected from institutions in 14 Middle East countries and entered into a custom-built-database during induction phase. All laboratory studies including cytogenetics were done at local institutions. Results: The 1,171 voluntarily enrolled patients had a mean age of 6.1±3.9 years and 59.2 were boys. T-ALL represented 14.8 and 84.2 had B-precursor ALL. At diagnosis, 5.6 had CNS disease. The distribution of common genetic abnormalities reflected a similar percentage of hyperdiploidy (25.6), but a lower percentage of ETV6-RUNX1 translocation (14.7) compared to large series reported from Western populations. By clinical criteria, 47.1 were low/standard risk, 16.9 were intermediate risk, and 36 were high risk. Most patients received all their care at the same unit (96.9). Patients had excellent induction response to chemotherapy with an overall complete remission rate of 96. Induction toxicities were acceptable. Conclusions: This first collaborative study has established a process for prospective data collection and future multinational collaborative research in the Middle East. Despite the limitations of an incomplete population-based study, it provides the first comprehensive baseline data on clinical characteristics, laboratory evaluation, induction outcome, and toxicity. Further work is planned to uncover possible biologic differences of ALL in the region and to improve diagnosis and management. Pediatr Blood Cancer 2014; 61:1403-1410. © 2014 Wiley Periodicals, Inc

A Bayesian Approach towards Modelling the Interrelationships of Pavement Deterioration Factors

In this study, Bayesian Belief Networks (BBN) are proposed to model the relationships between factors contributing to pavement deterioration, where their values are probabilistically estimated based on their interdependencies. Such probabilistic inferences are deemed to provide a reasonable alternative over costly data collection campaigns and assist in road condition diagnoses and assessment efforts in cases where data are only partially available. The BBN models examined in this study are based on a vast database of pavement deterioration factors including road distress data, namely cracking, deflection, the International Roughness Index (IRI) and rutting, from major road sections in the United Arab Emirates (UAE) along with the corresponding traffic and climatic factors. The dataset for the analysis consisted of 3272 road sections, each of 10 m length. The test results showed that the most critical parameter representing the whole process of road deterioration is the IRI with the highest nodal force. Additionally, IRI is strongly correlated with rutting and deflection, with mutual information of 0.147 and 0.143, respectively. Furthermore, a Bayesian network structure with a contingency table fit of over 90% illustrates how the road distress parameters change in the presence of external factors, such as traffic and climatic conditions

Life cycle assessment of roadworks in United Arab Emirates: Recycled construction waste, reclaimed asphalt pavement, warm-mix asphalt and blast furnace slag use against traditional approach

© 2020 Elsevier Ltd Life cycle assessment methodology was applied in this study to calculate environmental impacts of a 3.5-km-long dual carriageway asphalt highway section case study in Abu Dhabi across following life cycle stages: material extraction and production, material and equipment transport, construction, maintenance and rehabilitation; assuming a 30 years lifetime. Environmental impact assessment for air emissions and energy consumption generated by complete roadworks, namely: earthworks; pavement courses; concrete works for traffic barriers, kerbs, parapets, traffic signs, and light systems. A comprehensive analysis of environmental impact reduction was performed using recycled construction waste; reclaimed asphalt pavement; warm-mix asphalt with synthetic zeolite additives; and, slag as alternate material and production options. Actual field data for the road section using virgin materials and traditional asphalt production mix for pavement works and Portland cement concrete for the complete concrete works were used as the baseline case. Routine maintenance and periodic rehabilitation by milling and repaving wearing course (<4.5 cm depth) every 5 years was also analysed from an environmental impact reduction perspective. Environmental assessment considered all indicators from ReCiPe midpoint method. Results show that earthworks account for a significant portion (26% of CO2eq.) of the environmental impacts for complete roadworks. The life cycle impact results of hot-mix asphalt and warm-mix asphalt were almost equal due to addition of synthetic zeolites. Results showed significant environmental impact reduction across all indicators, after coupling all alternate options as: 34% in CO2eq.; 48% in energy consumption; 24.4% in NOxeq.; 21.53% in PM2.5eq.; 21.2% in acidification; and, 10.4% in land use. Monte Carlo simulations confirm these results and the sensitivity of environmental benefits to the allocation methodology was also investigated, which showed that the results were only marginally sensitive to the allocation approach. This study noted higher environmental benefits than reported in roadworks literature due to alternate material and asphalt production options

Lifecycle Cost Analysis of Recycled Asphalt Pavements: Determining Cost of Recycled Materials for an Urban Highway Section

Growing demand for road infrastructures and accompanying environmental footprint calls for the replacement of pavement materials with recycled options. The complexities in real-world usability are dependent upon project-specific characteristics and are affected by budgetary constraints of local governmental agencies, material applicability, and climatical conditions. This study conducts a comprehensive lifecycle cost analysis (LCCA) of an urban highway section “E10” in the hot Middle Eastern climate of Abu Dhabi, where virgin asphalt usage is dominant, using actual cost data under multiple scenarios and recycled construction waste (RCW) usage across aggregate layers and recycled asphalt pavement (RAP) across wearing, binder, and asphalt base courses. Blast furnace slag as partial cement replacement for road concrete works is also analysed. Impacts across all lifecycle stages from initial earthworks and construction to routine maintenance and operation were compared. Results found that cost of sustainable construction is lower. Cost reduction was highest for RAP and RCW usage, particularly when the usage was accumulated. The optimum cost scenario used 25% RCW in the sub-base, 80% RCW in the unbound base, 25% warm-mix asphalt (WMA) RAP in the asphalt base, 15% warm-mix RAP in the binder and wearing courses, and 65% slag for concrete roadworks and resulted in USD 2.6 million (15%) cost reduction over 30 years from 2015 to 2045

Lifecycle Cost Analysis of Recycled Asphalt Pavements: Determining Cost of Recycled Materials for an Urban Highway Section

Growing demand for road infrastructures and accompanying environmental footprint calls for the replacement of pavement materials with recycled options. The complexities in real-world usability are dependent upon project-specific characteristics and are affected by budgetary constraints of local governmental agencies, material applicability, and climatical conditions. This study conducts a comprehensive lifecycle cost analysis (LCCA) of an urban highway section &ldquo;E10&rdquo; in the hot Middle Eastern climate of Abu Dhabi, where virgin asphalt usage is dominant, using actual cost data under multiple scenarios and recycled construction waste (RCW) usage across aggregate layers and recycled asphalt pavement (RAP) across wearing, binder, and asphalt base courses. Blast furnace slag as partial cement replacement for road concrete works is also analysed. Impacts across all lifecycle stages from initial earthworks and construction to routine maintenance and operation were compared. Results found that cost of sustainable construction is lower. Cost reduction was highest for RAP and RCW usage, particularly when the usage was accumulated. The optimum cost scenario used 25% RCW in the sub-base, 80% RCW in the unbound base, 25% warm-mix asphalt (WMA) RAP in the asphalt base, 15% warm-mix RAP in the binder and wearing courses, and 65% slag for concrete roadworks and resulted in USD 2.6 million (15%) cost reduction over 30 years from 2015 to 2045

Crack45K: Integration of Vision Transformer with Tubularity Flow Field (TuFF) and Sliding-Window Approach for Crack-Segmentation in Pavement Structures

Recently, deep-learning (DL)-based crack-detection systems have proven to be the method of choice for image processing-based inspection systems. However, human-like generalization remains challenging, owing to a wide variety of factors such as crack type and size. Additionally, because of their localized receptive fields, CNNs have a high false-detection rate and perform poorly when attempting to capture the relevant areas of an image. This study aims to propose a vision-transformer-based crack-detection framework that treats image data as a succession of small patches, to retrieve global contextual information (GCI) through self-attention (SA) methods, and which addresses the CNNs’ problem of inductive biases, including the locally constrained receptive-fields and translation-invariance. The vision-transformer (ViT) classifier was tested to enhance crack classification, localization, and segmentation performance by blending with a sliding-window and tubularity-flow-field (TuFF) algorithm. Firstly, the ViT framework was trained on a custom dataset consisting of 45K images with 224 × 224 pixels resolution, and achieved accuracy, precision, recall, and F1 scores of 0.960, 0.971, 0.950, and 0.960, respectively. Secondly, the trained ViT was integrated with the sliding-window (SW) approach, to obtain a crack-localization map from large images. The SW-based ViT classifier was then merged with the TuFF algorithm, to acquire efficient crack-mapping by suppressing the unwanted regions in the last step. The robustness and adaptability of the proposed integrated-architecture were tested on new data acquired under different conditions and which were not utilized during the training and validation of the model. The proposed ViT-architecture performance was evaluated and compared with that of various state-of-the-art (SOTA) deep-learning approaches. The experimental results show that ViT equipped with a sliding-window and the TuFF algorithm can enhance real-world crack classification, localization, and segmentation performance

Lifecycle Analysis of Recycled Asphalt Pavements: Case Study Scenario Analyses of an Urban Highway Section

Roads account for a major part of energy/resource consumption and emission of GHGs, such as CO2, PM, NOx, O3, etc., due to high demand for virgin materials, specifically in developing regions. The applicability of recycled materials, such as recycled asphalt pavement (RAP) and other alternative approaches for, e.g., warm-mix asphalt (WMA), in developed countries is hindered by project-specific constraints and lack of empirical studies in these regions. Lifecycle assessment studies on the usage of these road options from actual projects in the developing countries can aid decision makers choose sustainable material approaches by providing case study examples as guidelines. To that end, this study analyses environmental in/out-flows for a traditional approach and multiple green approaches (RAP and WMA) for a major highway section in Abu Dhabi through a 30-year (2015–2045) lifecycle approach. Roadworks were modelled in SimaPro according to real-world conditions, and the expected burden mitigation in each stage is calculated. Benefits of using optimum RAP-based options and a virgin-material-based WMA case against the baseline virgin material case were also investigated. Results showed benefits of WMA as higher than replacing virgin asphalt with recycled asphalt (25% RAP asphalt base, 15% RAP binder and wearing courses). Land use (19%) and energy consumption (16%) showed the highest reduction, followed by ozone depletion (14%), ionizing radiation (11%), PM (8%), acidification (7%) and global warming potential (6%) across all pavement lifecycle stages and environmental indicators. Similar results were obtained for other scenarios with lesser degrees of reduction, which show the significance of replacing HMA with WMA for real-world projects, specifically in mega road projects in Abu Dhabi and the Middle East towards cutting the significant carbon footprint of asphalt pavements