Performance Of Transportation Infrastructure Research Articles

Mobility Index Towards Heritage Tourism Area, Case Study: Borobudur, Prambanan, And Ratu Boko

Mobility has become a crucial factor in transportation management, especially in the tourism sector. It is a key indicator of the performance of transportation infrastructure and people's response to it. To evaluate mobility in tourist areas, there is a need for tools to represent its value. In this study, the concept of an index as a measure of performance is applied, gathering information into a simpler and more mutually agreeable form. The cultural heritage sites of Borobudur, Prambanan, and Ratu Boko are chosen as an ideal study location due to their popularity internationally. Given the limitations of previous research on mobility indexes in tourist areas, the Sustainable Urban Mobility Index (I_SUM) framework is used to develop the variables. To avoid bias, this study utilizes expert opinion methods to assess necessary and unnecessary variables in achieving the index. Eight individuals with expertise and experience in transportation and tourism are selected as respondents. Furthermore, the expert evaluation results are processed using the Content Validity Index (CVI). The outcome is 26 variables that meet the validation test out of a total of 32 previous variables, which are divided into five domains, covering accessibility, social aspects, transportation infrastructure, traffic cycle, and transportation systems.

Mobility has become a crucial factor in transportation management, especially in the tourism sector. It is a key indicator of the performance of transportation infrastructure and people's response to it. To evaluate mobility in tourist areas, there is a need for tools to represent its value. In this study, the concept of an index as a measure of performance is

Mobility has become a crucial factor in transportation management, especially in the tourism sector. It is a key indicator of the performance of transportation infrastructure and people's response to it. To evaluate mobility in tourist areas, there is a need for tools to represent its value. In this study, the concept of an index as a measure of performance is applied, gathering information into a simpler and more mutually agreeable form. The cultural heritage sites of Borobudur, Prambanan, and Ratu Boko are chosen as an ideal study location due to their popularity internationally. Given the limitations of previous research on mobility indexes in tourist areas, the Sustainable Urban Mobility Index (I_SUM) framework is used to develop the variables. To avoid bias, this study utilizes expert opinion methods to assess necessary and unnecessary variables in achieving the index. Eight individuals with expertise and experience in transportation and tourism are selected as respondents. Furthermore, the expert evaluation results are processed using the Content Validity Index (CVI). The outcome is 26 variables that meet the validation test out of a total of 32 previous variables, which are divided into five domains, covering accessibility, social aspects, transportation infrastructure, traffic cycle, and transportation systems.

Conditional seasonal markov-switching autoregressive model to simulate extreme events: Application to river flow

Extreme events have the potential to significantly impact transportation infrastructure performance. For example, in the case of bridges, climate change impacts the river discharge, hence scouring patterns, which in turn, affects the bridge foundation stability. Therefore, extreme events (river flow) forecasting is mandatory in bridge reliability analysis. This paper approaches this river flow forecasting problem by developing a Markov-Switching Autoregressive model coupled with a conditional hidden seasonal Markov component. In addition, the proposed model is also combined with the deep machine learning neural networks method to forecast river flow from a dataset or from simulations. The proposed method is illustrated by using realistic data: historic river flow values of the Thames River. The results indicate that the proposed model well represented the extreme events within the dataset. In terms of river flow forecasting, the results indicate that the forecasts improve when the training period changes from 20 years to 40 years.

THE EFFECTS OF ENVIRONMENTAL PECULIARITIES ON TRANSPORTATION INFRASTRUCTURE PERFORMANCE IN LAGOS METROPOLIS, NIGERIA: RESIDENTS' EXPERIENCES

Efficient transportation infrastructure is pivotal for the seamless functioning of global cities, with coastal cities facing unique challenges due to environmental peculiarities. This study delves into how Lagos' environmental peculiarities impact transportation infrastructure performance, shedding light on both positive and negative implications. A comprehensive survey involving 1284 residents within Lagos Metropolis was conducted using multistage sampling techniques. A combination of descriptive (percentage and mean-weighted analysis) and inferential (Fisher’s exact test and Phi Cramer's V Test) statistics was adopted for data analysis. Major findings revealed that the environmental peculiarities in Lagos foster the use of multimodal infrastructure options and concurrently exert adverse effects on various facets of transportation infrastructure performance, including travel cost, commuting time, fare charges, wear and tear of infrastructure, and the overall cost of maintenance and repairs. The results of the Fisher’s exact test underscore the undeniable impact of Lagos' environmental peculiarities on transportation infrastructure performance (p = 0.000 < 0.05). This study concludes that high water tables, as a representative environmental peculiarity, substantially influence transportation infrastructure performance, shaping the mobility needs of residents. In light of these findings, the study advocates for the full implementation of sustainable infrastructure solutions. Recommendations include establishing robust drainage systems, incorporating corrosion-resistant materials, and adopting innovative technologies to mitigate the repercussions of rising sea levels on critical transportation infrastructure, enhancing its resilience in the face of environmental challenges.

Transport infrastructure environmental performance: the role of stakeholders, technological integration, government policies and lean supply chain management

The recent past is characterized by heightened environmental awareness, enhancing the environmental performance of transportation infrastructure was of utmost importance. The central purpose of this study was to delve into and comprehend methods for improving the environmental performance of transportation infrastructure. It aimed to investigate three pivotal factors: engagement of stakeholders, integration of technology and formulation of government policies. Furthermore, the study emphasized exploring how Lean Supply Chain Management could act as a facilitator in accomplishing these enhancements. The study’s approach involved a mediation analysis, utilizing quantitative methods to collect data from 89 construction firms operating in Pakistan. The customized questionnaire was employed to gather the necessary data, and employed random sampling techniques to select participants. The hypotheses were tested through partial least squares (PLS 4) analysis. The findings of this study highlighted that stakeholder, including government entities, private enterprises, and local communities, significantly shape the environmental outcomes of transport projects. It explored how technological integration influences environmental performance and assesses the effectiveness of current government policies in promoting sustainability. The study also examined the role of lean supply chain management practices. Implications stressed the importance of stakeholder collaboration, the integration of innovative technologies and policies, refining regulations for sustainability goals and adopting a holistic approach for enhancing overall environmental performance in the transport sector.

Assessment of the impact of climate change and flooding on bridges and surrounding area

Climate change has the potential to significantly impact transportation infrastructure performance. Bridges crossing rivers are designed to withstand a maximum flood level (design flood) considering the expected frequencies and magnitudes of floods in the area. The design flood level ensures the safety of the bridge without being damaged against historical flooding levels. However, flood magnitude and/or frequency are expected to increase in some regions due to climate change, and therefore, bridges may not be able to maintain their serviceability and safety, resulting in significant risk to users and economic losses. This problem is approached in this paper by investigating the effects of flooding and climate change on bridges crossing rivers and surrounding areas. The input of the proposed methodology is the river flow for various climate change scenarios as well as the topography and bridge characteristics. Flood frequency analysis is used to provide information about the magnitude and frequency of annual maximum river discharges under a changing climate. Afterwards, several risk assessment indicators are computed for the bridge and its surrounding area. In addition, stochastic Poisson process is integrated to account for the randomness of floods arrivals and to investigate stochastically the probability of exceeding the design flood level. The proposed methodology is illustrated with a case study in the United Kingdom. The results indicate that the risk of flooding, and associated consequences, would increase for the case study when considering more pessimistic climate change scenarios. Findings from this study can be used to inform decision making for improving bridges’ resilience.

Modeling the dynamic performance of transportation infrastructure using panel data model in state-space specifications

Modeling the dynamic performance of transportation infrastructure using panel data model in state-space specifications

Sustainable Operations: A Systematic Operational Performance Evaluation Framework for Public–Private Partnership Transportation Infrastructure Projects

With the application of public–private partnership (PPP) model in urban transportation infrastructure projects, various participants have put forward multi-dimensional demands to the operation and maintenance of infrastructures. This study aims to establish a systematic operational performance evaluation framework for PPP transportation infrastructure projects. Based on a literature review, the balanced scorecard was improved, and a conceptual model of multidimensional performance assessment was constructed. The structure of the qualitative performance assessment system was quantified and analyzed by combining structural equation modeling with questionnaires to obtain causal relationships among the indicators. Subsequently, a system dynamics model was constructed to assess the performance dynamically, and a validation analysis was conducted. It finds that maintaining a low level of operational quality over an extended period can significantly reduce stakeholder satisfaction, consequently exacerbating the decline in project performance. In contrast, an improvement in the level of informatization is found to positively contribute to enhancing operational quality and facilitating the long-term sustainability of project operations. It innovatively integrates four dimensions of financial, multi-stakeholder satisfaction, operation and maintenance quality, and sustainability performance to enrich the theoretical system of PPP transportation infrastructure performance assessment. At the same time, it analyzes the influence mechanism among the indicators and its long-term dynamic performance, which provides an effective decision-making tool for operational performance management.

Analysis of Selection and Performance of Public Transport Mode In Tarakan City

<em>The problems of passenger transportation (TAP) in Tarakan City are multi-dimensional, such as, fares and routes that are less organized and uneven, inconvenience and less secure, excess passengers during peak hours and vice versa, condition of operator systems, increased pollution and noise and the number of accidents and traffic violations, and driver behavior. In short, the root of the problem is the incompatibility between the Regional Spatial Plan (RTRW) for the city of Tarakan and the TAP. This study aims to assess the performance of passenger transportation based on descriptive statistical methods to: see the demand for population movement; route performance and transport operations; and the performance of transportation infrastructure, as well as the level of road service in the form of the ratio of volume per road segment capacity. The results achieved found that the existing performance of TAP in Tarakan City was relatively not optimal, the level of main road service on secondary roads because the increase in vehicle volume was significantly influenced by the high population movement, land use, level of transportation service, transportation comfort, load factor, and road conditions.</em>

Scenario-Based Strategic Modeling of Road Transport Demand and Performance

Road infrastructure plays an important role in the economic and social development of societies. Thus, it requires effective and timely responses to cope with and embrace uncertain future changes. This study proposes an integrated, scenario-based strategic model which estimates transport demand, network performance, emission, and energy consumption. The model accounts for future economic, behavioral, policy, and technological developments by including four future scenarios and traces the possible changes in transport infrastructure performance. It primarily aims at supporting infrastructure decisions by quantifying a set of network and environmental performance indicators along their spatial–temporal dimension. Moreover, the effects of transport demand and energy transition policies on road performance are considered within each scenario. This model is applied in a case study region covering the main industrial and urban regions of the Netherlands. The discussed results provide insights into the possible infrastructure investments within each scenario and elaborate on the possible effects of policies.

Transport infrastructure and manufacturing sector: an energy perspective from India

PurposeThe purpose of this study is to dissect the transport infrastructure performance, public spending in transport infrastructure development and the manufacturing sector in determining the transport sector energy consumption.Design/methodology/approachAn analysis of transport energy consumption with the transport infrastructure performance, public spending in transport infrastructure and manufacturing sector output in India using annual data for the period 1987–2019. The study used the autoregressive distributed lag (ARDL) bounds test approach along with FMOLS, DOLS and canonical cointegration regression (CCR) methods.FindingsThe results of the ARDL bounds test provide evidence for the long- and short-run relationships among study variables. It evidenced that transport infrastructure performance reduces transport energy consumption by using FMOLS, DOLS and CCR methods. Furthermore, the inference of the positive impact of value added in the manufacturing sector on transport energy consumption validates the higher energy demand of the manufacturing sector from a mobility perspective.Practical implicationsThe estimated finding of this study is expected to be contributing to policy-making discussions on transport infrastructure and manufacturing sector development in an emerging economy like India with insights on energy consumption.Originality/valueTo the best of the authors’ knowledge, this is the first study that integrates the impact of manufacturing sector output on transport sector energy consumption along with transport infrastructure performance and public investment in the transport infrastructure.

Gaussian Process Regression for Transportation System Estimation and Prediction Problems: The Deformation and a Hat Kernel

Gaussian process regression (GPR) is an emerging machine learning model with potential in a wide range of transportation system estimation and prediction problems, especially those where the uncertainty of estimation needs to be measured, for instance, traffic flow analysis, the transportation infrastructure performance estimation problems and transportation simulation-based optimization problems. The kernel function is the core component of GPR, and the radial basis function (RBF) kernel is the most commonly used one, suitable for tasks without special knowledge about the patterns of data, like trend and periodicity. However, an inappropriate hyperparameter of the kernel function may lead to over-fitting or under-fitting of GPR. During hyperparameter optimization, the usage of the RBF kernel often suffers from the issue of failing to find the optimal hyperparameter. This paper aims to address this problem by promoting the use of the hat kernel, which can reduce the risk of under-fitting. Moreover, we propose the notion of deformation, corresponding to severe over-fitting of a GPR. To further address this issue, we investigate the connection between deformation and the Bayesian generalization error of GPR. Two lower bounds for the hyperparameter of the hat kernel are also proposed to avoid deformation of GPR.

Effect of Sustainable Infrastructure and Service Delivery on Sustainable Tourism: Application of Kruskal Wallis Test (Non-parametric)

This study examined the effect of sustainable infrastructure and service delivery on sustainable tourism in Kashmir Valley through the five main destinations by covering essential stakeholders. At present, tourism potential nations face destination sustainability issues in various junctures of the tourism sector. Therefore, international agencies and nations focus on sustainable tourism through sustainable transport infrastructure, other factors and improved service delivery. Few studies underlined the role of sustainable infrastructure in service quality and their collective impact on sustainability without empirical evidence at the destination level. At this juncture, the current study presents the summaries of empirical investigation of the effect of sustainable transport infrastructure and services delivery on sustainable tourism in Kashmir Valley. For analysis, the Kruskal-Wallis test (non-parametric) is applied to assess the variation in sustainable tourism based upon the performance of sustainable infrastructure and service delivery at destinations. The application of the Kruskal-Wallis independent samples tests duly confirmed the significant results. Sustainable tourism differs by transport infrastructure performance, other elements and service quality of the destinations. Therefore, it is to be stated that poor functioning of transport infrastructure and other basic structures adversely affects service delivery and raises sustainability issues at destinations. It asserts that the comprehensive sustainable transport infrastructure, water supply and drainage, health and sanitation, solid and liquid waste management are highly required to combat environmental issues and ensure sustainability at destinations. The findings of the study have significant policy implications to promote green infrastructure, quality services and development of sustainable tourism at destinations.

Deep reinforcement learning-based decision support system for transportation infrastructure management under hurricane events

The high wind, large surge/wave and heavy rainfall during a hurricane may significantly impact the performance of transportation infrastructure and associated traffic safety. Accordingly, stakeholders need to make a sequence of decisions to close (or restrict) the traffic of vulnerable components in the transportation network (e.g., aerodynamics-sensitive long-span bridges, hydrodynamics-sensitive coastal bridges and inundation-sensitive road segments) for the balance of safety and mobility. Due to large uncertainty involved in hurricane weather and traffic conditions, it is essentially a stochastic sequential decision problem and can be effectively formulated as a Markov decision process. This study proposes a deep reinforcement learning (RL)-based decision support system for stakeholders to optimally manage these critical components for the purpose of minimizing the network-level losses induced by hurricanes. Specifically, the RL policy (i.e., mapping from high-dimensional continuous traffic/weather information to management decisions) is represented by a deep neural network (DNN) and the optimal decision (corresponding to a set of DNN weights) is obtained using the deep Q learning algorithm. A case study based on a hypothetical traffic network is utilized to demonstrate the good performance of the developed deep RL-based decision support system in the application of transportation infrastructure management under hurricane conditions.

Artificial Intelligence Based Structural Assessment for Regional Short- and Medium-Span Concrete Beam Bridges with Inspection Information

The functional and structural characteristics of civil engineering works, in particular bridges, influence the performance of transport infrastructure. Remote sensing technology and other advanced technologies could help bridge managers review structural conditions and deteriorations through bridge inspection. This paper proposes an artificial intelligence-based methodology to solve the condition assessment of regional bridges and optimize their maintenance schemes. It includes data integration, condition assessment, and maintenance optimization. Data from bridge inspection reports is the main source of this data-driven approach, which could provide a substantial amount og condition-related information to reveal the time-variant bridge condition deterioration and effect of maintenance behaviors. The regional bridge condition deterioration model is established by neural networks, and the impact of the maintenance scheme on the future condition of bridges is quantified. Given the need to manage limited resources and ensure safety and functionality, adequate maintenance schemes for regional bridges are optimized with genetic algorithms. The proposed data-driven methodology is applied to real regional highway bridges. The regional inspection information is obtained with the help of emerging technologies. The established structural deterioration models achieve up to 85% prediction accuracy. The obtained optimal maintenance schemes could be chosen according to actual structural conditions, maintenance requirements, and total budget. Data-driven decision support can substantially aid in smart and efficient maintenance planning of road bridges.

Transport Infrastructure and Regional Integration in the Middle East

AbstractThe soft aspects of the infrastructure of regionalism in the Middle East have previously been studied, while the impact of the region’s hard infrastructure, in particular transport infrastructure, has received little attention. This paper contributes to the study of regionalism in the Middle East by investigating the relationship between hard infrastructure and economic integration. It analyzes whether the state of domestic and cross‐border transport infrastructure in the region promotes regional trade. This is done by addressing the following sub‐questions: 1) What is the condition of domestic and cross‐border transport infrastructure in the Middle East? And 2) What is the relationship between domestic and cross‐border transport infrastructure and regional trade in the Middle East? These questions are answered by examining Egypt, Iraq, Israel, Jordan, Lebanon, Palestine, Syria, and Turkey as representative samples of the broader region. It is argued that regionalism relies on the development of domestic and cross‐border transport infrastructure and where the latter is limited, regionalism cannot deepen. The study concludes that domestic and cross‐border transport infrastructure performance is weak in several of the countries studied and that this weakness hinders regional economic integration regardless of the level of the region’s soft infrastructure.

METHODOLOGICAL APPROACH TO EVALUATING THE PERFORMANCE OF TRANSPORT INFRASTRUCTURE ENTERPRISES

Despite the significant number of discussions regarding the problems of evaluating the performance of enterprises, little attention has been paid to evaluating the performance of enterprises on the basis of a comprehensive approach that takes into account all factors. The article considers a methodological approach to evaluating the performance of transport infrastructure enterprises on the example of passenger road transport enterprises, formed using a balanced scorecard. The development of a methodological approach to evaluating the performance of enterprises is important both conceptually and operationally. Methodological approach to evaluating the performance of passenger road transport enterprises is improved in the work. It is determined that one of the modern approaches to evaluating the performance of enterprises is a balanced scorecard, which is a system of strategic management of an organization, based on the measurement and evaluation of its performance on a set of indicators. The proposed methodological approach for evaluating the performance of passenger road transport enterprises involves three main stages: preparation; evaluation of the performance of passenger transport enterprises; analysis of the results of evaluating the performance of passenger transport enterprises. In the work the list of indicators are determined by which the performance assessment and the procedure for their calculation are held. On the basis of a balanced scorecard for passenger transport enterprises the author selected 4 groups of indicators: “Finance”, “Staff”, “Clients”, “Main processes of an enterprise”. The algorithm of evaluation of the performance of passenger transport enterprises is formed. The proposed methodological approach will allow passenger road transport enterprises to improve the level of competitiveness and performance. The results obtained, which are an improved methodological approach to evaluating the performance of passenger road transport enterprises, allow for further researches on how to enhance the effective activity of transport infrastructure enterprises.

The Belt and Road Initiative as a tool for promoting EU-China trade. Poland’s case

The aim of the study is to evaluate the potential role of the Belt and Road Initiative (BRI) for promoting EU – China trade, and especially Poland – China trade. We test two hypotheses: 1) Non-tariff barriers (NTBs), particularly related to railway transport, are significant for Poland – China trade, and 2) Poland – China trade fits railway transport well. Therefore, we start with a study of the significance of tariff and non-tariff barriers in mutual trade relations, including transport-related barriers. NTBs are mainly derived from the EU Market Access database, and as for transport-related barriers – the logistics performance index (LPI) is used. As the next step, we study the composition of bilateral trade in static and dynamic terms using the OECD TiVA database. In the light of the significant increase in NTBs on EU manufacturing products exported to China and the railway transport infrastructure performance in Poland, the BRI could become an effective tool for improving the business environment for EU exporters. By contrast, the BRI project is more suitable for China and the EU as a whole than for Poland in terms of commodity structure of bilateral trade.

Characterizing and measuring transportation infrastructure diversity through linkages with ecological stability theory

Transportation infrastructure is critical to any community. Disturbances such as natural hazards can hinder transportation infrastructure performance impacting a community’s quality of life through disruptions in service and effects on interdependent systems. Ecological systems are robust and resilient and have similarities with infrastructure systems. Diversity is a fundamental element of ecological resilience and is recognized as an important factor in transportation resilience. However, measures of transportation diversity are not well-developed. Accordingly, this paper adapts the ecological diversity concepts of richness and evenness to develop an approach to characterize transportation system diversity and distinguishes the approach from existing methods. Measures of transportation functional richness and evenness are derived and applied to New York City at the zip code level. The results facilitate identification of zip codes in New York City with varying levels of transportation diversity. Those zip codes with low diversity generally have limited availability (low richness) and disproportionate distribution (low evenness) of alternative transportation modes. Further, these zip codes are potentially susceptible to system disturbances as a consequence of routine disruptions or natural hazards. For instance, many low diversity zip codes are in hurricane evacuation zones. Limited complementarity in the transportation system of these zip codes will likely impact evacuations during hurricanes and recovery to pre-disturbance performance levels. Ultimately, the transportation diversity approach presented should lead to better understanding of transportation system characteristics such as inherent and augmented complementarity, which will enhance transportation system performance in urban communities.

ANALISIS KINERJA INFRASTRUKTUR TRANSPORTASI KABUPATEN MUNA BARAT

The policy of providing road infrastructure that is right and effective, requires an instrument that can see the success rate of providing road infrastructure in balancing economic development, population and number of vehicles. The purpose of this study was to analyze the performance of transportation infrastructure in this case the condition of the West Muna Regency road network.This research was conducted in two ways, namely using the Road Infrastructure Index (IPJ) and Minimum Service Standards (SPM). The road infrastructure index uses four variables which are also indicators in the assessment of the availability of road infrastructure (Ktj), road network performance (KNJ), traffic load (BLN) and road infrastructure services (Pyp). While the Minimum ServiceStandards are viewed from the Accessibility Index and Mobility Index.The results of the study showed that the performance of transportation infrastructure based on the 2016 West Muna Regency Road Infrastructure Index (3.78) was said to be insufficient according to the national minimum value (6.00) and national average value (5.68). Based on the Minimum Service Standards of West Muna Regency, accessibility and mobility indices have met the existing requirements. Keywords: Transportation Infrastructure Performance, Road Network System, RoadInfrastructure Index (IPJ), Minimum Service Standards (SPM)