Against the backdrop of comprehensive urbanisation, Shanghai Shikumen Lane Housing (SLH), as a typical heritage community, is confronted with multiple dilemmas, including an imbalance between conservation and development, ambiguous property rights, and the erosion of community identity. Existing studies have predominantly focused on physical transformation while overlooking the underlying institutional logic. Using institutional economics, this paper analyzes property rights evolution and regeneration contradictions by way of historical, dual-track, and matrix analyses. Findings show that the separation of rights and responsibilities, along with dual-track misalignment, underlies building decay, community disintegration, and spatial degradation. It constructs a two-dimensional matrix and proposes four models with 11 pathways for collaborative governance. Transcending morphological perspectives, this study uncovers the institutional logic of heritage community regeneration and provides both theoretical support and practical strategies for SLH conservation and identity reorientation in stock-based urban renewal. Furthermore, it offers actionable institutional design and multi-stakeholder mechanisms, giving municipal engineering practitioners and policymakers clear tools to achieve synergies between heritage conservation, community governance, and livelihood improvement.
The growing urbanisation-induced impacts of climate change on coastal communities and ecosystems call for engineers to adopt more holistic sustainable, adaptive, and ecologically conscious approaches when developing coastal infrastructure. This paper presents a systematised review of literature on nature-aligned engineering (NAE) in coastal infrastructure development, synthesising existing evidence to highlight the state of knowledge, current implementation approaches, performance outcomes, and emerging opportunities and barriers. The review applies structured inclusion criteria and a PRISMA-guided search to identify key design practices, performance outcomes, and policy actions that support integration of natural processes into engineered coastal systems. Three databases were selected for the review process: Scopus, Web of Science, and Google Scholar. The latter was chosen to facilitate access to policy documents and technical reports. The study reveals key strategic actions needed, namely, advancement of skills and knowledge on NAE, policy support, establishment of standardised performance evaluation metrics, targeted research to fill data gaps, and greater coordination and collaboration of ecological, planning, and engineering experts to realise technical feasibility, environmental sustainability, social acceptance, and economic viability of NAE solutions. The insights generated provide practical guidance for engineers, planners, and policymakers seeking to enhance coastal resilience through sustainable, nature-aligned design practices.
This study develops a locally calibrated safety performance function () using a negative binomial () model to estimate crash frequency on NH-44 and NH-334B corridors in Sonepat, Haryana. Crash data from 2018-2022 comprising 1230 cases were integrated with traffic, roadway, and pavement condition variables. Mixed models were not adopted due to the absence of significant unobserved heterogeneity after inclusion of key explanatory factors. Results indicate that annual average daily traffic is the most influential variable, with an elasticity of 1.387, implying that a 1% increase in traffic leads to similar to 1.39% rise in crashes. Heavy-vehicle proportion also showed a significant positive effect, increasing crashes by 2.3% for every 1% increase. Pavement roughness (International Roughness Index) increased crash frequency by 9.3% per 1 m/km rise, while each additional metre of shoulder width reduced crashes by 13.2%. Earthen medians and absence of medians increased crash risk by 60% and 170%, respectively, compared to concrete barriers. Model validation demonstrated improved predictive accuracy over the national SPF, with reductions of 20.3% in mean absolute error, 26.2% in root mean squared error, and 25% in mean absolute percentage. The findings highlight the importance of incorporating local roadway and traffic characteristics for effective highway safety planning.
Travel time and ridership growth are two indicators of how interconnectivity affects the effectiveness of public transportation. Using a comparison of Extreme Gradient Boosting, polynomial regression (Degree 2), and the semi-linear regression approach, this research report attempts to determine the impact of interconnectivity and identify the most effective technique for estimating ridership demand for multi-modal transport systems. The influence of several factors on ridership demand is evaluated in three cities where the metro and bus rapid transit system () are operational. The results show that ridership is impacted by interconnectedness. The metro-BRTS transfer sites and the number of boardings in Ahmedabad show a strong correlation, indicating well-established multimodal integration (R-2 = 0.974). According to Jaipur, route length was the most important feature, indicating that transfers are more efficient over longer routes with fewer interchanges. Pune showed moderate predictability, indicating changes in intermodal connections and increased variability in passenger behaviour. The (Shapley Additive exPlanations) and (Local Interpretable Model-agnostic Explanations) analyses found that the number of interchange locations and metro alighting volumes had the greatest positive impact on ridership. However, long travel times and frequent stops discourage ridership and deter commuters.
The necessity for four-dimensional (4D) cadastral studies arises from the need for historical real estate information, the determination of the vertical positions of infrastructure elements located above and below immovable properties, and the management of complex urban and rural land use scenarios. The proposed model was tested in a pilot study area located in the Golhisar district of Burdur province, comprising 10 cadastral parcels. In this study, a relational database was developed to integrate two-dimensional (2D), three-dimensional (3D), and 4D cadastral data within a geographic information system environment. Within the study area, three types of registered objects, namely, drinking water lines, sewer lines, and building structures, were modelled together with parcel data. A 4D cadastral data model was created using the unified modelling language, and a desktop application was developed based on this model. Temporal changes related to cadastral processes, including initial registration, subdivision, and subsequent geometric and legal alterations, were incorporated into the system to represent the fourth dimension. This application enables users to query and analyse 2D, 3D, and 4D cadastral information for any parcel in a chronological manner. The results demonstrate that integrating time enhances the usability of cadastral systems in the pilot region.
Trip generation is the first step of traffic demand estimation, providing essential estimates of trips produced and attracted by each traffic analysis zone. This study examines the effects of land use type, built-up area, and spatial location on trip generation rates within urban municipal areas, drawing from empirical data and established literature. The analysis distinguishes between residential and non-residential land uses. Residential trip rates are disaggregated by housing type, dwelling size, and their location within core, middle, and outer zones. Non-residential categories commercial, industrial, logistics, and public/semi-public are assessed by built-up area and spatial placement to evaluate their trip-generating potential. Findings indicate that residential trip rates increase with dwelling size, ranging from 1.33 (1BHK) to 1.42 (4BHK), with statistically significant differences (H = 70.72, p < 0.001). Trip rates also rise with built-up area, from 1.33 (<50 sq. m) to 1.57 (>150 sq. m) (H = 49.87, p < 0.001). In non-residential areas, commercial zones exhibit the highest trip rate (78 trips/100 sq. m), with significant variation across land use types (H = 1055.98, p < 0.001). Spatial location shows limited effect on residential trip rates but does effect non-residential trip behaviour.
Public transport accessibility is a key component of inclusive and sustainable urban development, particularly in developing-country contexts, where infrastructural and operational barriers may intensify social exclusion. This study evaluates the transferability of a validated accessibility assessment model originally developed in Spain to Durban, South Africa. The research examines 71 bus stops within the Durban People Mover network, focusing on accessibility conditions for persons with reduced mobility. The methodology combines field observation, geolocation, and photographic documentation within a structured framework based on technical requirements classified as critical and non-critical, enabling a systematic assessment across the travel chain. The findings indicate high levels of compliance in basic pedestrian infrastructure, exceeding 90% for ramps, gradients, and pavement conditions. However, accessibility is constrained by operational and informational deficiencies, including the occupation of boarding areas by private vehicles (32.26% non-compliance) and the absence of inclusive information systems, with 0% compliance for Braille signage, real-time information, and audible systems. The study demonstrates that accessibility gaps are primarily linked to management and information systems rather than to infrastructural deficits. It confirms the model’s value as a transferable and replicable tool for evaluating accessibility under limited data conditions, thereby supporting evidence-based interventions aligned with Sustainable Development Goal 11.2.
The Planning and Infrastructure Act 2025 represents one of the most significant reforms to the English planning system in recent decades, with profound implications for infrastructure delivery. This paper critically examines the Act, focusing on how legislative reform reshapes governance arrangements, professional practice, and infrastructure outcomes. Using a qualitative doctrinal and comparative methodology, the study analyses the Act alongside previous UK planning reforms and selected European planning systems, highlighting how legislative change influences infrastructure delivery through governance arrangements and professional practice. The paper develops a conceptual framework linking law, governance mechanisms, and built environment outcomes, demonstrating that legislative change influences infrastructure performance indirectly through institutional structures and professional practice. The analysis identifies key opportunities arising from the Act, including accelerated infrastructure delivery, improved project certainty, enhanced investment confidence, and the potential for strategic environmental mitigation. However, it also highlights significant challenges relating to environmental integrity, public trust, and skills and capacity constraints within local authorities. While the Act may improve delivery efficiency, its success will depend on complementary governance reforms, sustained investment in professional capacity, and the ethical engagement of engineers in balancing efficiency with sustainability. The findings offer practical insights for engineers, policymakers, and regulators navigating planning reform.
Community-based adaptation (CBA) is widely promoted as a participatory approach to climate resilience, yet it often assumes that communities operate as cohesive units. Drawing on qualitative research from an Ethiopian village, this paper examines how local power relations shape the implementation and outcomes of a CBA project centred on forest enclosure and land rehabilitation. Based on semi-structured interviews with farmers, local leaders, and government officials, the findings show that adaptation processes unfold within 'politicised communities' characterised by unequal access to land, authority, and decision-making power. While project reports emphasised technical success in ecological restoration, local accounts revealed contested resource access, uneven participation, and social non-compliance. The study further demonstrates that adaptation infrastructure durability depends not only on technical design but also on its perceived legitimacy among differently positioned community groups. In this context, indigenous knowledge and environmental narratives were mobilised as governance tools to justify project interventions. The paper argues that effective adaptation requires sustained engagement with local governance systems, stakeholder differentiation, and participatory monitoring beyond initial consultation to ensure both environmental effectiveness and social durability.
In the post-COVID-19 era, economic uncertainty and restricted budgets have made countries more cautious about investing in construction. While building information modelling (BIM) has transformed building projects, its application to infrastructure remains difficult. This study investigates whether BIM’s long-standing philosophy can be effectively adapted for infrastructure through a tri-axial model based on the policy-technology-process framework. A competency structure was developed, including five core meta categories and 26 sub-variables. A structured questionnaire was distributed in the USA and Turkey, chosen for their contrasting BIM maturity levels. Domain competency analysis introduced the total number of meta-variables factor at three levels to assess readiness. Findings identified meta managerial (MM) as the most impactful, meta contractual (MC) as the most uncertain, and meta financial (MF) and meta public authority (MP) as major barriers. Turkish respondents rated MM and MC 15%–28% lower than Americans, with larger gaps for MF and MP. Execution competency was assessed using Light Gradient Boosting Machine (LightGBM), with Q-factor and E-factor metrics used to test and validate the data. The final framework delivers a data-driven benchmark for guiding BIM integration in infrastructure-focused projects.
The study focuses on identifying and analysing the barriers encountered by individuals with disabilities when accessing urban public buildings in India. Present research establishes an association between the likelihood of difficulties faced by the disabled in accessing public buildings and the determinants affecting these difficulties. The National Sample Survey dataset covering the nationwide data of 31 948 collected through the stratified random sampling method was analysed to examine public building usage and barriers faced by persons with disabilities. A Binary Logistic Regression model was used to analyse the difficulties faced by disabled people in public buildings in the Indian urban context. The major findings are as follows: (a) In the Indian urban built environment, veterans with disabilities feel fewer barriers than novices; thus, with age, ease increases to some extent. (b) Living arrangements with close or other relatives do not alleviate the difficulties faced in daily life. (c) The religious perspective on disability is crucial in facing urban challenges. (d) Vertical transportation is critical factor in facing difficulties in urban India. This approach allows for a comprehensive understanding of the factors contributing to accessibility challenges, potentially informing future policy decisions and architectural design practices to create inclusive public spaces.
This paper aims to explore carbon emissions and determine corresponding improvement methods based on road access conditions, thereby achieving the 'dual carbon' goal based on road traffic. In this study, models of access conditions and traffic carbon emissions are first determined, and the desired speed model is further determined based on the minimum growth rate of traffic carbon emissions, while the speed limit control model is constructed. Then, based on the actual confluence area of expressways, statistical methods, and simulation methods, the relationship between road access conditions and traffic carbon emissions is explored, and the desired speed is also determined; meanwhile, changes in traffic efficiency, speed, and traffic carbon emissions under speed limit control are analysed. Finally, the reasons for synchronous changes in traffic carbon emissions and traffic efficiency are discussed, and the effectiveness of speed limit control is compared and analysed. The results show that speed and the number of vehicles per unit of time are the main factors of synchronous changes, and the essence lies in the change in traffic states. In addition, speed limit control plays a certain role in improving traffic conditions in the confluence area.
Demand-responsive transport (DRT) can expand urban accessibility. However, pickup-point design is often guided by user convenience while neglecting system costs, including detour delays for onboard passengers and additional road congestion. This paper develops a decision-support framework for DRT pickup-point siting that explicitly internalises these externalities. The problem is formulated as a Stackelberg bi-level optimisation model. At the upper level, a planner selects feasible pickup-point locations within a predefined search area to minimise total social cost, defined as the sum of network travel time and detour-related passenger delay. At the lower level, travellers' demand response is represented by a utility-based logit model that updates mode shares. The proposed framework translates welfare objectives into implementable siting rules and supports the specification of service standards, such as bounds on detours for existing riders and thresholds for acceptable congestion impacts. It further enables systematic evaluation of trade-offs among ridership, equity, and network performance under budget and operating constraints. A case study using real-world network and demand data indicates that the approach provides evidence-based guidance on pickup-point spacing and placement while maintaining DRT competitiveness.
Autonomous mobile robots (AMRs) are increasingly recognised as a sustainable solution to urban challenges such as environmental pollution and labour shortages. However, dynamic obstacles in urban areas with high pedestrian density hinder their safe and efficient operation, making it increasingly important to identify favourable segments and routes for them to navigate. This study proposes the construction of a robot-specific network that incorporates link-level resistance factors, including sidewalk width and obstacle locations, as weighted attributes. Within the study area, origin–destination pairs were defined, and urban network analysis was applied to identify high-activity pedestrian segments and derive potential paths. The applicability of the proposed network was validated through field experiments using AMRs under real-world pedestrian conditions. The results confirmed that segments with frequent pedestrian robot conflicts were associated with significant travel delays, whereas paths with fewer conflicts demonstrated superior travel performance. Overall, the study provides empirical evidence supporting the necessity of robot-specific networks that explicitly incorporate pedestrian density and congestion.
As autonomous vehicles enter urban traffic systems, the allocation of Dedicated Autonomous Vehicle Lanes (DAVLs) becomes a strategic concern for transport operations and long-term infrastructure planning. This study develops a reinforcement learning framework that formulates DAVL management as a Markov Decision Process and applies Proximal Policy Optimisation to minimise congestion, energy consumption, and pollutant emissions on Seoul's Naebu Ringway under varying AV market penetration rates. The results reveal non-linear and threshold-dependent responses: at low penetration (10%), premature DAVL allocation increases emissions and delays, whereas measurable benefits emerge only beyond 30-50%. At high penetration (>= 50%), DAVL allocation improves traffic flow, increases average speed, reduces density, and lowers emissions by up to 33%. The study reframes DAVLs as both an operational tool and a planning instrument, providing insights for aligning automation readiness with sustainability goals, indicating that DAVL allocation is conditionally effective rather than universally beneficial.
The paper selected Tianjin urban rail transit and conventional bus as the research object and used ArcGIS spatial evaluation and DepthMap integration analysis to analyse the spatial characteristics of all coordination characteristics of the evaluation system based on the data of 174 stations on 8 subway lines in Tianjin. First, an evaluation system with 9 indicators (e.g. station kernel density and line repetition coefficient) is built across three dimensions. Second, the entropy weight method and analytic hierarchy process are used to determine the comprehensive weight of the evaluation index. The coordination comprehensive evaluation method with the grey correlation degree as the core is established. According to the coordination scores of urban rail transit and conventional public transportation within four types of station areas: commercial centre, residential service, suburban area to be built, and transportation hub, it is found that the residential service type has the largest number, and the suburban area to be built has the highest imbalance rate. The imbalance rate of commercial centre-type stations is 11.1%, and there are only two imbalance stations in the transportation hub type. The findings aid optimisation of coordination and address public transport imbalance.
Bus transportation holds the primary position of public transportation in Indian cities after introducing Jawaharlal Nehru National Urban and Rural Mission scheme. The significant rise in passenger demand over recent decades has increased the need for improved vehicular and passenger facilities at bus stations. This study analysed the factors affecting the performance of Arapalayam Bus Station in Madurai, which serves both intercity and local bus services. The field investigations revealed that current service intensity is insufficient to accommodate the bus arrival rate, leading to queuing outside the station premises. This results in traffic congestion on city roads, develop conflicts between vehicles-pedestrians and increased delay in bus services. To evaluate the impact of each factor, a questionnaire survey was conducted and responses were ranked using a statistical method known as principal component analysis. The results indicated that absence of bay optimisation, separate bay facilities, streamlined passenger movement and bus queuing significantly affects station operations. In addition, absence of dedicated feeder service leads to passenger pick-up and drop-off near the adjacent carriageways, further contributing to blockages and congestion. The study designed an integrated bus terminal layout with improved feeder facilities to achieve multi-modal traffic operations in practice.
Water management systems in many developing countries, including Malaysia, face persistent and interlinked challenges such as high non-revenue water, ageing infrastructure, and fragmented monitoring processes. These issues compromise service delivery, sustainability, and long-term resilience. This paper applies a systems thinking approach to map the interdependencies and root causes within Malaysia's municipal water management ecosystem. Through this diagnostic lens, this study proposes the adoption of Digital Twin (DT) technology to enable real-time monitoring, data-driven decision making, and predictive maintenance. Drawing on international case studies, the research highlights how DT solutions can bridge data silos, optimise maintenance schedules, and extend infrastructure lifespan. A tailored framework is developed, offering a practical roadmap for the integration of DT into Malaysia's urban water systems. This study contributes to achieving the United Nations Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action), by supporting context-specific strategies for improving municipal water services through sustainable and technology-driven water management practices in Malaysia.
Although fixed chargers have been installed on motorways, they often fail to meet the charging demand of electric vehicles (EV) on peak days. The battery-less truck mobile charging station (BL-TMCS) is a truck that carries chargers for EV and can be moved along motorways to provide additional energy. Based on a detailed analysis of the feasibility of using BL-TMCS, this paper proposed a solution to the problem. By integrating traffic simulation, the Monte Carlo method, the EV energy consumption model, and the user decision model for charging, a comprehensive simulation-based framework was established to estimate the spatio-temporal distribution of charging demand on motorways. A precise method was developed to calculate waiting time of users based on the real-time status of chargers. To minimise the average waiting time of users, an optimal deployment model for BL-TMCS was formulated considering constraints such as the number, operating costs and transfer times, and solved using a genetic algorithm. The numerical study shows that with a 50% increase in traffic volume on the test motorway, the deployment of two BL-TMCSs reduces the average waiting time from 21.76 to 0.75 min. These results highlight the effectiveness of the proposed solution and method.
