thesis on transportation problems

A Comprehensive Literature Review on Transportation Problems

• Review Article
• Published: 24 September 2021
• Volume 7 , article number  206 , ( 2021 )

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• Yadvendra Kacher 1 &
• Pitam Singh 1  

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A systematic and organized overview of various existing transportation problems and their extensions developed by different researchers is offered in the review article. The article has gone through different research papers and books available in Google scholar, Sciencedirect, Z-library Asia, Springer.com, Research-gate, shodhganga, and many other E-learning platforms. The main purpose of the review paper is to recapitulate the existing form of various types of transportation problems and their systematic developments for the guidance of future researchers to help them classify the varieties of problems to be solved and select the criteria to be optimized.

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Acknowledgements

First author (Yadvendra Kacher) acknowledges the financial support as Junior research fellowship (JRF) received from CSIR (Govt. of India) through HRDG(CSIR) senction Letter No./File No.: 09/1032(0019)/2019-EMR-I.

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Kacher, Y., Singh, P. A Comprehensive Literature Review on Transportation Problems. Int. J. Appl. Comput. Math 7 , 206 (2021). https://doi.org/10.1007/s40819-021-01134-y

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The Impacts of Transportation Infrastructure on Sustainable Development: Emerging Trends and Challenges

1 School of Management, Harbin Institute of Technology, Harbin 150001, China; nc.ude.tih@gnawiqul (L.W.); nc.ude.tih@euxlx (X.X.)

Xiaolong Xue

2 School of Management, Guangzhou University, Guangzhou 510006, China; nc.ude.uhzg@uyezgnaw

Transportation infrastructure has an enormous impact on sustainable development. To identify multiple impacts of transportation infrastructure and show emerging trends and challenges, this paper presents a scientometric review based on 2543 published articles from 2000 to 2017 through co-author, co-occurring and co-citation analysis. In addition, the hierarchy of key concepts was analyzed to show emerging research objects, methods and levels according to the clustering information, which includes title, keyword and abstract. The results expressed by visual graphs compared high-impact authors, collaborative relationships among institutions in developed and developing countries. In addition, representative research issues related to the economy, society and environment were identified such as cost overrun, spatial economy, prioritizing structure, local development and land value. Additionally, two future directions, integrated research of various effects and structure analysis of transportation network, are recommended. The findings of this study provide researchers and practitioners with an in-depth understanding of transportation infrastructure’s impacts on sustainable development by visual expression.

1. Introduction

Transportation infrastructure, as a complex network, connects cities and accommodates human activities coupling the social, economic and environmental systems with the urbanization and population growth. Additionally, the transportation network contributes to the socioeconomic development and the increased quality of life through generating inter- or intra-city connections during urbanization [ 1 , 2 ]. In addition, goals such as low-carbon, resilient and sustainable development should not be ignored when the transportation network is expanded [ 3 ]. In detail, transportation infrastructure among cities leads to urban aggregation and diffusion, greatly boosting the regional and national economic development [ 4 , 5 ]. However, the irrational planning of transportation infrastructure also generates negative effects, such as the ecological destruction, increased traffic accidents, climate change, CO 2 emissions and lower transport efficiency [ 6 , 7 , 8 , 9 , 10 , 11 ]. Therefore, it is necessary to identify multiple impacts of transportation infrastructure from existing studies.

Recently, the impact of transportation infrastructure has been a hot topic, and the economic effect of transportation infrastructure has been receiving more attention and debate [ 12 ] because of the pursuit to direct economic growth of both regions and sectors [ 13 ]. To review multiple impacts of transportation infrastructure, scientometric studies have been used to analyze the literature and reveal trends in some specific topics such as transport phenomenon [ 14 ] and public transport [ 15 ]. However, in the field of transportation, existing scientometric studies mainly focus on statistical results, lacking the exploration of visual and network structure analysis. Therefore, this paper analyzed the co-author, co-occurring and co-citation network based on the collected literature expressed by visual graphs. The software Citespace was used to build the author and literature collaboration network and the co-citation analysis based on the expanded data from the citation dimension. This expansion increases the potential data source and improves the accuracy of review analysis. More importantly, scientometric study based on network visualization is an effective way to identify representative researches in the network structure and find the phenomenon and regularity compared with traditional literature analysis.

In this paper, we present a scientometric and systematic review that explores the literature related to the impact of transportation infrastructure in the database of Web of Science from 2000 to 2017. The aims of this study are identifying the research trends in the field of the transportation infrastructure and finding the hot research topics through the visualization map built by the literature. This paper is divided into three main parts. Section 2 introduces the basic concepts, characteristics and multiple impacts of the transportation. Theoretical analysis provides an in-depth understanding of the impact mechanism of transportation infrastructure according to existing studies. Section 3 introduces the scientometric method in this paper. This method provides a means of visualization to identify the information in the map based on the software Citespace. Section 4 analyzes the scientometric results, including co-author, co-occurring and co-citation analysis. Finally, according to the identified cluster data, this paper systematically summarizes representative studies and important categories related to the effect of transportation infrastructure. Multiple analysis greatly increases the accuracy of the results.

2. Transportation Infrastructure

2.1. the definition and characteristics of transportation infrastructure.

As one of the main urban elements, transportation infrastructures such as roads, highways, railways, airports, bridges, waterways, canals and terminals play important roles in the transmission of materials and the flow of population during urban agglomeration and diffusion [ 16 , 17 , 18 ]. Just as stated in the definition given by OECD (2013), transportation infrastructure is a critical ingredient in the economic development at all levels of the income, supporting personal well-being and economic growth. From the perspective of function, transportation infrastructure is a kind of large-scale public work which has the importation influence on countries’ politics, economy, society, science, technology development, environmental protection, public health and national security. Besides, as a part of transportation system apart from the operating system and transport vehicles, the plan and construction of transportation infrastructure are complex. Grimsey and Lewis think it is easier and more meaningful to identify infrastructure than to define the infrastructure, and the key to identifying the infrastructure is indicating its characteristics [ 19 ]. For example, during construction, it has characteristics of large investment scale, long construction period, complicated risk, and many stakeholders [ 20 ].

Transportation infrastructure has the fundamental features of general infrastructure, such as high risk, high investment, complex organization and low income [ 21 ]. Additionally, it has another two special characteristics: geographic network and spatial externality [ 22 ]. On the one hand, transport infrastructure is a network infrastructure that constitutes the channel between nodes, regions or node-region. This promotes the spatial transfer of production factors and mobility of goods. On the other hand, the externality means that positive or negative effects on external subjects are generated when one economic entity produces or consumes. In terms of positive externalities, transport infrastructure as a public investment could directly promote economic growth and also indirectly increase the economy through spillover effects such as knowledge spillover effect and technology spillover effect. Meanwhile, environmental pollution and urban noise often happen because of the building of transport infrastructures, driving the generation of negative spillover effects. The existence of complex characteristics and significant roles drives the generation of multiple impacts of transportation infrastructures on the economy, society and environment.

2.2. The Multiple Impact of Transportation Infrastructure

The transportation infrastructure represents the motivator of economic growth and social welfare [ 23 ] through improving production performances and investment performances for the private sectors [ 24 ]. More specifically, the construction of transportation infrastructure could reduce the travel cost, attract foreign investment and expand trade of shared resources [ 25 ]. In terms of the social overhead capital, transport infrastructure plays a decisive role in industrialization and has obvious spillover effects on regional innovation, factor reallocation and manufacturing productivity [ 26 ], which promote the aggregation of industries, population and economy [ 16 ]; this is often called the economic distributional effect. However, some empirical studies have shown that the expansion of high-speed railway networks promotes the development of central cities but causes the economic growth rate of prefecture-level cities along the rail line to decline, which is referred to as the siphon effect [ 27 ]. Although different results were found based on various data sources or research objects, the empirical study is the most common and effective method to identify the positive or negative effects of transportation infrastructures.

Meanwhile, excessive infrastructure construction could put huge pressure on the natural and ecological environment when meeting the need for economic development and social improvement [ 28 ]. Transportation infrastructure provides the fundamental conditions for economic activities, while some spillover effects happen concomitantly [ 29 ], such as CO 2 emission generated via domestic and global production networks [ 30 ], ecological destruction because of the biological habitat fragmentation [ 11 ] and the change of water flow and declining water quality [ 31 , 32 ]. Since the United States published the Environmental Impact Assessment (EIA) in 1969 [ 33 ], environmental problems have become a significant part of the law, and many topics have received wide attention. For the transport sector, apart from cost-benefit, design and investment analyses, environmental impacts such as CO 2 emission and air quality are the main evaluation criteria [ 34 ]. In addition, some universal and systematic methods have been used to evaluate environmental performances, such as the multi-criteria model, meta-analysis [ 35 ], ecological footprint index [ 36 ], and value equilibrium analysis [ 37 ]. From the perspective of the environment, the effects of the transportation infrastructure are almost all negative, so minimizing the environmental impact has been the main research topic. Additionally, transport infrastructure assumes important social responsibility [ 38 , 39 ]. Although more jobs and optimized income distribution occurs after huge capital investments in infrastructure projects, health hazards, land expropriation and wildlife damage problems should not be neglected.

The multiple impacts of transportation infrastructures have received huge attention. However, the economic externality is still the most important and popular topic, which often ignores the environmental and social aspects [ 40 ]. Since the sustainable development topic has been a point of focus, the sustainable evaluation of transportation infrastructure has been increasingly valued. Based on the traditional cost-duration-quality decision model [ 41 ], plenty of indicators and methods have been extended to identify and assess transportation sustainability. For example, some multi-criteria models based on panel data have been extended, such as the multivariate co-integration approach [ 23 ], fuzzy logic evaluation [ 42 ] and the decoupling model [ 43 ]. In addition, optimizing the network structure and analyzing the spatial relationships of infrastructure operation are the key ways to promote the urban sustainability [ 44 ]. The complex characteristics and multiple impacts of transportation infrastructures have promoted studies on the identification and modelling of transportation sustainability. However, existing studies have mainly depended on experience to review the published articles. In addition, systematic and scientometric analysis could show complete and clear research status in this field.

In the field of transportation, many reviews have been published to identify the research status, while most reviews have mainly depended on researchers’ backgrounds and experiences. To build an overview of existing studies with a relatively complete literature, the scientometrics method was used to find out the scientific regularity related to the effects of transportation research based on mathematical statistics and computing techniques [ 45 ]. In addition, scientometric analysis mainly depends on bibliographic data to identify the research trends and literature relationships [ 46 ]. The scientometric method was used in this study to build a visual information graph for further data mining using the software Citespace ( http://cluster.cis.drexel.edu/~cchen/citespace/ ). The visualization process of the bibliography is meaningful for discovering the potential information based on the graphical representation of data using shapes, colors and images [ 47 ]. This method reduces the difficulty in analyzing a large literature, and effectively finds the regularity and the hidden information in existing studies. In this section, the data overview and research path of the scientometric method are presented.

3.1. Data Overview

The Web of Science (WOS) database was used to collect published literature data related to the transportation infrastructure. Apart from WOS, Google Scholar’s database is extensive, but its citation information is incomplete and inconsistent [ 48 ]. Therefore, it is difficult to use for scientometric analysis. In addition, WOS contains the most important and influential journals in the world [ 49 , 50 ]. The impact of transportation infrastructure includes many categories, such as human, economic and environmental. Therefore, in this section, a comprehensive data overview is presented to show the trend of existing studies. In addition, “transport infrastructure” and “transportation infrastructure” were used as keywords to collect the data, initially.

This paper analyzed all collected literature in the WOS core database from 2000 to 2017. The search code SS = (transport* infrastructure*) was used in the WOS core collection. Here, “*” denotes a fuzzy search and “SS” means an article subject search. A total of 2543 bibliographic records were collected in October, 2017, and there are 14 related records filtered by being highly cited in the field, as shown in Table 1 . Highly cited papers are the top one percent in each of the 22 Essential Science Indicators (ESI) subject areas per year, which indicates scientific excellence. We can see that this literature is distributed over recent years, and almost all records are related to the environmental dimensions. It is notable that the highest cited article was published in 2012 and is about biofuel application in transportation vehicles. Additionally, Figure 1 shows the top 20 research fields related to transportation infrastructure, including engineering, transportation, business economics, environmental sciences, computer science, geography, public administration, urban studies, and so on. This means the studies related to transportation infrastructure range from the technological level to the management level, providing more challenges and opportunities to interdisciplinary research.

The top 20 research fields of the transportation infrastructure.

Top highly cited research categories.

The data overview above shows the overall research trends and fields. According to the research scope and objects, some keywords are chosen to filter the results that are more related to the spillover effects of the transportation infrastructure network. Then the words (SS’ = effect* or affect* or influence* or impact*) were selected to refine the results, and a total of 1568 bibliographic records were searched. This step refined the records referring to the impact of transportation infrastructures or other effects on transportation infrastructure. Finally, the main keywords (SS’’ = railway* or rail* or road* or highway* or expressway* or freeway*) were used to further refine these results in accordance with the specific research objects of this paper, and got 764 records. Figure 2 shows the distribution of 1568 bibliographic records related to the two-way influence of transportation infrastructure and the records related to the influence of railway or road. In addition, the final 531 papers were used for further review analysis. Multi-step data filtering benefits a narrow data range, promoting study depth and guaranteeing the data integrity. It is clear that the distribution trend of is similar between the original data and the filtered data, which means the impact of railway and road could follow the path of the development of transportation infrastructure. In addition, research about the impact of railways and roads accounts for around 20–40% of research on transportation infrastructure during the timespan. In other words, the analysis of railways and roads partially represents the transportation infrastructure.

The number of articles on impact of transportation infrastructure.

3.2. Scientometric Method

Scientometric analysis is a systematic method to identify and analyze the published literature, and it has become increasingly frequently used to obtain a deeper understanding of a research area [ 51 ]. In addition, this analysis has been recognized as an efficient method to identify the hidden information in published bibliographies [ 52 ]. In the field of transportation, scientometric analysis has been used as a quantitative approach to identify research phenomena and trends [ 14 , 15 ], but these previous studies did not systematically analyze the research network or recognize the hidden research trends and relations. The software CiteSpace can visualize the emerging trends, transient patterns, substantial theoretical and methodological contributions in scientific literature from the perspective of a social network [ 53 , 54 ]. The accessible graphs based on network analysis and clustering algorithms are able to show the knowledge more logically and systematically [ 55 ]. Therefore, CiteSpace was used to identify and analyze the main effects of transportation infrastructure on sustainable development based on the literature. In this study, some scientometric techniques were used, such as fundamental information analysis (author, institution and country) and network analysis (subject, keywords and co-citation). According to these analysis results, the research challenges and trends were further systematically analyzed.

In detail, the research procedure of this study includes three main parts, according to the collected bibliographic data, as shown in Figure 3 . Firstly, 2543 records were collected to perform the data overview, including the highly cited analysis and the top 20 research fields. After the filtering, 2056 records were analyzed by CiteSpace software to show representative people, institutions, countries and relationships among them. Then the dual-map overlay and keyword network of the literature were analyzed to show representative research subjects and issues. Additionally, references in the collected literature were analyzed to build the co-citation network, which generates the clustering information to expand the data source. Finally, according to the clustered information, the research status and trend were summarized systematically to generate the hierarchy of key concepts. All of these steps reviewed the bibliographic information from different dimensions to find the respective research issues.

Research procedure of this study.

4. Results and Discussion

4.1. co-authorship analysis.

According to the author collaboration analysis, the domain authors have a relatively large number of links to other authors in the network, which means the domain authors have higher academic relevance [ 56 ]. In this study, 2056 valid bibliographic records were collected from 2000 to 2017. The co-authorship network is shown in Figure 4 , where each node represents an author and links between authors denote collaboration established through co-authorship of articles. In this network, excessive links were removed by Pathfinder using network pruning [ 57 ], and eventually 189 nodes and 173 links were identified. In addition, the node size represents the frequency of published references and the node color accounts for different collaboration modularity.

Comparison of author collaboration networks.

According to the cluster information from 2000 to 2017, the network density is 0.0097 and the cluster modularity Q is 0.8626, which means the network of co-authors is fragmented. Only a few closed circuits exist in the network, such as the Mulley C group, Flyvbjerg B group and Ogilvie D group. As shown in the left-bottom graph of Figure 4 , many authors collaborated with one or two productive authors. For example, Flyvbjerg Band Van Wee B were both productive and central authors in the community. All centralities of these groups are small, which indicates that in the timespan 2000–2010, important collaboration groups were not formed by author centrality. In order to determine the timeliness of the study, the research period was limited to 2010–2017. In addition, the right-bottom graph of Figure 4 shows the author collaboration network during this period. In this network, 1899 valid records are included and there are 185 nodes and 172 links. The network density is 0.0101, which is similar to the left graph. The network modularity and network structure only change slightly. It is notable that the author clusters change slightly, which means these central authors play significant roles in this field. Overall, from the perspective of timespan, author collaboration groups remained stable and relatively separate from the increased cumulative number of works in the published literature.

Apart from the collaboration analysis, author productivity is an important criterion to show the roles of authors or teams. Based on the 2056 collected bibliographic records, the top 10 most productive authors were identified in Table 2 . This shows that the main research fields of the hot authors include transportation, business economics and environmental management. More importantly, the collaboration links among most productive authors were more frequent and the productive authors generally led to modularity. For example, the productive author Flyvbjerg Bent cooperated with another productive author Van Wee Bert and the productive authors Ogilvie David, Flyvbjerg Bent and Mulley Corinne generated co-author modularity, as shown in Figure 4 , which means that the productive authors were often cited and focused upon.

Top ten most productive authors.

4.2. Co-Author’s Institution and Country Analysis

As shown in Figure 5 , the institution network includes 280 nodes and 236 links from 2000 to 2017. The node size represents the amount of published literature from one institution. According to the collected information, the studies related to transportation infrastructure were rich at institutions such as Delft University of Technology (50 records), University of Sydney (33 records), Universidad Politécnica de Madrid (29 records), University College London (28 records), University of Oxford (28 records) and Chinese Academy of Sciences (25 records). This indicates that transportation infrastructure research was active and advanced. In addition, institution nodes with high betweenness centrality are shown in Figure 5 . The size of the colored circle represents the amount of published literature in one institution, and different colors show the number in different years. Institutions with high centrality play important roles in the institution network, such as Delft University of Technology (centrality = 0.24), University of Illinois (centrality = 0.17), Georgia Institute of Technology (centrality = 0.14), Shanghai Jiao Tong University (centrality = 0.12) and University of Florida (centrality = 0.10), and they drove the research collaborations among different institutions. Apart from the Delft University of Technology, the top productive institutions did not have higher relative centrality. This means that institutions that published more articles did not play an equally important role in the collaboration network. The institutions with higher centrality would have greater potential.

Institution collaboration network.

Furthermore, Figure 6 shows the country collaboration network in 2000–2010 and 2010–2017; clusters are displayed in different colored circles and they are arranged vertically in the order of their size. In addition, the colored lines represent co-citation links among different countries. During 2000 to 2010, as shown in the left graph, the top 5 countries with the highest centrality include USA (centrality = 0.65), England (centrality = 0.4), Sweden (centrality = 0.36), Italy (centrality = 0.21) and Japan (centrality = 0.14), which means that they occupied key positions in the collaboration network. During 2010 to 2017, as shown in the right graph, the top 5 countries with the highest centrality include USA (centrality = 0.53), England (centrality = 0.31), Germany (centrality = 0.17), Australia (centrality = 0.15) and the People’s Republic of China (centrality = 0.1). We can see the centralities of USA and England experienced a decrease and the roles of Germany, Australia and the People’s Republic of China became increasingly significant. Additionally, apart from the top central countries, Spain, Netherlands and Canada had higher published frequencies, which indicates their higher relative potentials. According to the clustering results, we can see the change of research interests. The labels of clusters were generated by log-likelihood ratio method in the software. It is notable that during 2000–2010, an overview of popular topics included infrastructure surveillance, local development and evidence; during 2010–2017 those consisted of transportation decision, regional development and infrastructure surveillance. In addition, the clustering members experienced an increase and transfer.

Comparison of country collaboration network.

4.3. Co-Occurring ANALYSIS

4.3.1. discipline analysis.

Every citation and cited work was assigned to a specific research discipline according to the journals in a global map of science generated from over 10,000 journals indexed in the WOS [ 58 ]. Therefore, this study built an overlay map to show the dual-map of the science sketch database that perfectly described the interdisciplinary research. Figure 7 shows the main disciplines of collected citing articles and cited articles. The left part of the graph shows the distributed disciplines of citing articles and the right part describes that of cited articles. In addition, the color curves represent the fluctuant relations. It is clear that the journals of citing articles related to transportation infrastructure are mainly distributed in disciplines such as mathematics, systems, economics and physics. Cited articles’ journals are mainly distributed in the areas of ecology, computer, social education and economics. The distribution of cited articles indicates the application fields and research foundations. More importantly, transportation infrastructure papers are published in almost all major disciplines, which means transportation infrastructure studies play important roles in multidisciplinary research. Additionally, the dual-map overlay shows the information about the field studies more macro compared with article clustering analysis. Thus, Figure 8 shows the interdisciplinary co-occurring network of the literature based on the WOS discipline categories. We can see that the top frequent disciplines include Engineering, Transportation and Business & Economics. The links among different nodes mean the existence of collaboration among different disciplines. Interdisciplinary research is quite obvious in the field of transportation infrastructure.

A dual-map overlay of the literature’s journals.

Inter-disciplinary co-occurring network of the literature.

4.3.2. Co-Occurring Keyword Analysis

Keywords catch the core content of a paper, and in this section, the collected keywords show the situation and development of research using the software CiteSpace. According to the 2056 valid records collected, the keyword co-occurring network includes 225 nodes and 1092 links shown in Figure 9 . The node size represents the frequency of a keyword in all records and links among nodes indicate different keywords occurring in the same record. The t-SNE view was used to lay out the keyword map. The t-SNE technique is a perfect visual method for this map, and gave a complete and clear description. Among the top 50 hot keywords, the most frequent keywords include model (frequency = 176), impact (frequency = 120), system (frequency = 109), growth (frequency = 94), investment (frequency = 86), network (frequency = 85), accessibility (frequency = 80), city (frequency = 74) and policy (frequency = 72), in addition to transportation infrastructure (frequency = 225). More importantly, China (frequency = 86) and the United States (frequency = 52) are two representative country keywords, which means that in these two countries, studies related to transportation infrastructure attracted more attention. In addition, some keywords with high frequency had a relatively high centrality, such as city (centrality = 0.15), network (centrality = 0.14), investment (centrality = 0.12) and impact (centrality = 0.09). To indicate the change of hot topics, we divided the timespan into 2010–2010 and 2010–2017, as shown in Figure 9 . The top three keywords are model, infrastructure and impact. The related keywords experienced a significant increase; in particular, keyword impact-related topics included climate, urban studies, land use, resilience and accessibility, which indicated this role. However, this network only shows information based on the collected records, and its difference from the co-citation network is the limitation of this relatively incomplete data. Therefore, the co-citation analysis further solves the data incompleteness in the next section.

Keyword co-occurring network diffusion.

4.4. Co-Citation Analysis

Co-citation analysis has been defined as the frequency with which two articles are cited together in another article [ 59 ]. In this section, co-citation analysis identifies the underlying intellectual structures of the knowledge in the field of transportation infrastructure according to references. The co-citation network was generated based on 2047 valid records between 2000 and 2017, and the top 50 most cited publications in each year were used to construct a network of references cited in that year. As shown in Figure 10 , the synthesized network contains 879 references and 174 co-citation clusters after the clustering process. This network has a modularity of 0.8934, which is considered to be very high, suggesting that the specialties in science mapping are clearly defined in terms of co-citation clusters. The mean silhouette is 0.3855, which is relatively low, mainly because of the numerous small clusters. The major clusters that we focus on in this paper were sufficiently high. The areas in different colors indicate the time at which co-citation links in those areas appeared for the first time. Areas in green were generated earlier than areas in yellow. Each cluster can be labeled by title terms, keywords, and abstract terms of articles citing the cluster. We can see that studies related to new application, cost overruns and case study appeared earlier, and urban transportation and public-private partnerships appeared more recently. In addition, cluster areas of new transport infrastructure, cost overruns and evidence study are relatively bigger, which means that these studies received more attention. According to the LLR, labels of the largest 62 clusters were summarized as shown in Appendix A and the most active citer can be checked in Appendix B .

A landscape view of the co-citation network.

In addition, the timeline visualization in CiteSpace depicted clusters along horizontal timelines. As shown in Figure 11 , each cluster was displayed from left to right and clusters were arranged vertically in descending order of their size. The colored curves represent co-citation links added in the year of the corresponding color. Large-sized nodes or nodes with red tree rings received particular attention because they were either highly cited or had citation bursts, or both. We can see that the three most-cited references in a particular year are displayed. The labels of these references were placed in the lowest position. The cluster labels were generated based on terms identified by Latent Semantic Indexing (LSI) [ 60 ]. Figure 11 shows the top 2 largest clusters, listed as cluster#0 and cluster#1. The periods in which the clusters were sustained were different, which means that the difference of topic activity. For example, topic #0 (cost overrun) was active during the period from 2008 to 2017 and most of the top active topics were active about 20 years. Furthermore, the top ten largest clusters include cost overrun, quantitative spatial economics, prioritizing highway defragmentation location, local development, land value, regional economic growth, new transportation infrastructure, public-private partnerships, infrastructure change region, recent laboratory research and microbial engineering. All of these clusters have relative network sub-structures and research status, and trends hide in these references. For example, for the cluster around spatial economics, 2011 to 2012 was the most active timespan for citers.

A timeline visualization of the largest clusters.

The analysis above shows the research base and fronts that mine the potential research challenges and trends. In addition, main research topics were further analyzed according to the selected and filtered data above. Table 3 shows the temporal properties of major clusters. We can see that most of the representative references are related to the spillover effect of the transportation infrastructure. For example, Cluster #0 (cost overrun) is the largest cluster, containing 94 references from 2011 to 2017. The mean year of all references is 2008 and the year of the most representative cited articles in this cluster is 2008, too. The timeline visualization reveals the top three cited references from the period of 2000 to 2017. As shown in Figure 11 , the three most representative cited references (Priemus Hugo, Banister David and Khadaroo Jameel) occur in 2008. We can see that the period 2008 to 2016 was full of high-impact contributions—large colored citation circles and red citation bursts. We chose the top three cited circles and nine references to analyze the main research topics. Similarly, in the other five clusters, the top three circles and nine representative references were chosen to further analyze the hot research status and research trends. Appendix C shows the high-impact members of the other clusters. These authors may be not the most highly cited authors, but they play important roles in the corresponding fields.

Temporal properties of the major 6 clusters.

4.5. Hierarchy Analysis of Key Concepts

The co-citation network above was divided into 174 co-citation clusters. These clusters were labeled by index terms from their own citers. These keywords show the most representative research topics related to transportation infrastructure. The left part of Figure 12 shows the word cloud based on cluster labels filtered by the same or similar labels of clusters. In this figure, the keyword size represents the frequency of cluster labels. It is clear that the main research topics include economic, region or urban development and spatial effect analysis. However, the cluster data only analyzed the label information, and did not identify other potentially relevant information. Therefore, a report of automatically generated narratives was used to analyze the word cloud distribution further, as shown in the right part of Figure 12 . The narratives include the main subjects in the titles and abstracts of the top references in the top 62 clusters that are relatively complete. We can see that hot research topics consist of urban development, project, economic, cost and policies. In particular, we identified some potential topics that were excluded in the left graph, such as land, risk, panel data and policies. By means of the two-step summary, potential keywords could be easily identified.

Word cloud distribution of co-citation cluster results. (Tool: Tagxedo ( www.tagxedo.com ). Data source: Labels of the top 62 clusters, narrative summary report of the co-citation network.)

Additionally, key concepts identified from the titles of citing articles in Cluster #0 were algorithmically organized according to hierarchical relations derived from co-occurring concepts. Figure 13 shows the main concept tree of Cluster #0. The largest branch of such a hierarchy typically reflects the main concepts of scholarly publications produced by the specialty behind the cluster. The main logical categories include transport infrastructure, projects, cost overruns and impact. The category “Transportation Infrastructure” mainly focuses on improving the project performance separately from the traditional and important problem “Cost Overrun”. In particular, the category “impact” emerged gradually as an independent branch, which was driven by the increasing quantity and complexity of transportation infrastructure. It is notable that the transportation infrastructure branch highlights the characteristics (large, resilience, spatial and complexity), research methods (modeling, econometric and network mapping) and research questions (quality, risk, performance and PPP). In other words, sub-categories in this figure indicate the characteristics, questions, objects, dimensions and methods related to transportation infrastructure. The identity of category labels based on the title data obeys the logical tree algorithm of the software Citespace. This figure not only shows the main research topics but the logical relationships among these topics.

A hierarchy of key concepts in Cluster #0.

To understand the hierarchy better, the key concepts in the top 7 Clusters (#0–#6) were identified in one hierarchy. Figure 14 summarizes the concept tree generated by Citespace according to the reference titles in Cluster #0–#6. The categories colored blue were identified automatically. For the systematic expression of the hierarchy, some branches colored green are used to conclude the fragmented research questions. In addition, this hierarchy filtered the repeating keywords and deleted words which cannot indicate the main research questions, such as “analysis”. However, the sub-category concepts of the branch “analysis” were distributed in other branches. Meanwhile, some sub-categories of the branch “transportation infrastructure” were distributed in the summative branches such as the “objects” and “methods”. We can see from Figure 14 that the main branch is “impacts”, in which the “spillover effects” and “countries” are listed separately. This means the topic of spillover effect is the intensive research issue, and there are many countries analyzing the impacts of transportation infrastructure on the national scale. In addition, the “impact” category summarized some detailed topics such as land use, urban development and spatial effect. Compared with Figure 13 , this hierarchy identified more specific topics, such as rail and road research. Although the amount of data in Figure 14 is about seven times greater than in Figure 13 , the hierarchy framework becomes more clear and systematic after filtering out repeated data. More importantly, this systematic hierarchy can help to identify the hottest and most representative research issues quickly.

A hierarchy of key concepts in Cluster #0–#6.

5. Conclusions

This scientometric review based on over 2500 publications from 2000 to 2017 presented the systematic knowledge structure related to impacts of transportation infrastructure on sustainable development. Due to the complex impact mechanism, the identification process needs an in-depth understanding and clear expression. Although reviews related to transportation infrastructure have received attention, the scientometric review with visual expression provides a better way to explore the potential information hidden in knowledge network compared with the traditional review. In this paper, the presentation of scientometric and systematic reviews includes four main steps. Firstly, co-author analysis was used to identify the highly productive authors, institutions and countries to show the overall research status. Then, the co-occurring analysis was used to identify and visualize the overall research trends based on discipline and keyword information. Next, citing articles and cited references were modulated to find co-citation relationships and modularity labels by timeline visualization. Finally, after the modularity, the cluster information was analyzed further to conclude the hierarchy concepts of the main clusters, which accurately identified key points. These four steps analyzed the research status and emerging trends of transportation infrastructure’s impacts on sustainable development from multiple perspectives, such as author information, collaborative relationships and reference relationships. In addition, compared with the traditional literature review, this scientometric analysis shows the representative information clearly based on a visual map. Importantly, this visual expression provides an easier way to understand the complex collaboration network of literature.

The main research findings are as follows. First, collaboration links among the most productive authors were more frequent than other authors. Moreover, the productive authors generally led to modularity. Second, institutions with high centrality play important roles in the institution network, such as Delft University of Technology, University of Illinois and Georgia Institute of Technology. In addition, countries occupying key positions include USA, England and China. Third, the hot topics related to transportation infrastructure include cost, performance, quality and investment issues from the project level. In addition, from a more macro perspective, economic, social and environmental effects of transportation infrastructure were all caught. Fourth, according to the hierarchy analysis, specific research objects, methods and multiple effects of transportation infrastructure were identified. It is noticeable that spillover effects of transportation infrastructure include some dependent sub-categories, such as spatial, regional, economic and environmental effects. These more macro keywords indicate the complexity of impact mechanisms. In addition, transportation infrastructure has huge impacts on land, urban development, human life and city networks.

However, there are also some limitations that need further improvement in this study. A limitation of using bibliographic databases is that the WOS lacks the information of books and reports in public sources, thus necessitating the integration of multiple data resources. In addition, due to the limitations of the analysis tool, our study could not analyze the information hidden in the references’ context. Additionally, the determination of search keywords mainly relies on the subjective judgment of the authors, which might lead to data being missing or incomplete. Given these limitations, multiple analysis was exerted in this work to make up for the data limitations. In this study, the titles, keywords and abstracts could be credibly representative of the main context. Our findings not only reveal research trends, but future research directions. In the future, two directions—integrated study of various spillover effects and network effects of mega transportation infrastructures such as railway and road—will be valuable research issues. By conducting further research in these directions, an improved understanding of the significance of the transportation infrastructure will be obtained, and the planning of transport networks will be conducted under proper advice. In conclusion, this study provides valuable information for both researchers and practitioners to understand the significant and complex impact of transportation infrastructure. It is clear that in both technological issues and management issues, the impact assessment is the key step to justifying the research in the field of transportation infrastructure. This scientometric review will lead to the construction of a theoretical framework to guide this practice.

Acknowledgments

This work was funded by the National Natural Science Foundation of China (NSFC) (Grant No. 71390522, No. 71671053, No. 71271065, No. 71771067). This research was also supported by the National Key R&D Program of China (No. 2016YFC0701800 and No. 2016YFC0701808).

Appendix C. High-Impact Number in Top 10 Clusters

Author contributions.

Luqi Wang and Xiaolong Xue contributed to the conceptualization and methodology. Luqi Wang and Zebin Zhao analyzed the data and results. Luqi Wang and Zeyu Wang wrote and edited the draft. Xiaolong Xue and Zebin Zhao contributed to the project administration and funding acquisition.

Conflicts of Interest

The authors declare no conflict of interest.

Home > Centers > TREC > ETDs

TREC Theses and Dissertations

Theses/dissertations from 2019 2019.

Social Equity in Transit Service: Toward Social and Environmental Justice in Transportation , Torrey Lyons (Dissertation)

Theses/Dissertations from 2016 2016

Travel Mode Choice Framework Incorporating Realistic Bike and Walk Routes , Joseph Broach (Dissertation)

Cyclist Path Choices Through Shared Space Intersections in England , Allison Boyce Duncan (Dissertation)

Improving the Roadside Environment through Integrating Air Quality and Traffic-Related Data , Christine M. Kendrick (Dissertation)

Theses/Dissertations from 2015 2015

An Exploration of Bicyclist Comfort Levels Utilizing Crowdsourced Data , Bryan Philip Blanc (Thesis)

Safety at Half-Signal Intersections in Portland, Oregon , Todd Robert Johnson (Thesis)

The Effects of Urban Containment Policies on Commuting Patterns , Sung Moon Kwon (Dissertation)

Bicyclist Compliance at Signalized Intersections , Samson Ray Riley Thompson (Thesis)

Theses/Dissertations from 2014 2014

Determinants of Recent Mover Non-work Travel Mode Choice , Arlie Steven Adkins (Dissertation)

Bicyclists' Uptake of Traffic-Related Air Pollution: Effects of the Urban Transportation System , Alexander Y. Bigazzi (Dissertation)

Analyses of Bus Travel Time Reliability and Transit Signal Priority at the Stop-To-Stop Segment Level , Wei Feng (Dissertation)

Predicting Bicyclist Comfort in Protected Bike Lanes , Nicholas Mark-Andrew Foster (Thesis)

Participation, Information, Values, and Community Interests Within Health Impact Assessments , Nicole Iroz-Elardo (Dissertation)

Bicycle Level of Service: Where are the Gaps in Bicycle Flow Measures? , Pamela Christine Johnson (Thesis)

Exploring Pedestrian Responsive Traffic Signal Timing Strategies in Urban Areas , Sirisha Murthy Kothuri (Dissertation)

The Objective vs. the Perceived Environment: What Matters for Active Travel , Liang Ma (Dissertation)

Theses/Dissertations from 2013 2013

Improving Vehicle Trip Generation Estimations for Urban Contexts: A Method Using Household Travel Surveys to Adjust ITE Trip Generation Rates , Kristina Marie Currans (Thesis)

Exploring Data Quality of Weigh-In-Motion Systems , Chengxin Dai (Thesis)

Understanding Travel Modes to Non-work Destinations: Analysis of an Establishment Survey in Portland, Oregon , Christopher D. Muhs (Thesis)

Bicycle Traffic Count Factoring: An Examination of National, State and Locally Derived Daily Extrapolation Factors , Josh Frank Roll (Thesis)

A Theory of Travel Decision-Making with Applications for Modeling Active Travel Demand , Patrick Allen Singleton (Thesis)

The Relationship Between Traffic Signals and Pedestrian, Bicyclist and Transit User Exposure in Urban Areas , Courtney Natasha Slavin (Thesis)

Peak of the Day or the Daily Grind: Commuting and Subjective Well-Being , Oliver Blair Smith (Dissertation)

Skateboarding as Transportation: Findings from an Exploratory Study , Tessa Walker (Thesis)

Theses/Dissertations from 2012 2012

An Empirical Study of Particulate Matter Exposure for Transit Users at Bus Stop Shelters , Adam Moore (Thesis)

Safety Effectiveness of Red Light Treatments for Red Light Running , Carl Scott Olson (Thesis)

Theses/Dissertations from 2011 2011

Leveraging Weigh-In-Motion (WIM) Data to Estimate Link-Based Heavy-Duty Vehicle Emissions , Heba Naguib Alwakiel (Thesis)

Traffic Congestion Mitigation as an Emissions Reduction Strategy , Alexander York Bigazzi (Thesis)

Bus Replacement Modeling and the Impacts of Budget Constraints, Fleet Cost Variability, and Market Changes on Fleet Costs and Optimal Bus Replacement Age, A Case Study , Jesse Alexander Boudart (Thesis)

Exploration of Weather Impacts on Freeway Traffic Operations and Safety Using High-Resolution Weather Data , Chengyu Dai (Thesis)

Exploring Traffic Safety and Urban Form in Portland, Oregon , Kristie Werner Gladhill (Thesis)

Assessment of an Optimal Bus Stop Spacing Model Using High Resolution Archived Stop-Level Data , Huan Li (Thesis)

Theses/Dissertations from 2010 2010

Investigating Freeway Speed-Flow Relationships for Traffic Assignment Applications , Meead Saberi Kalaee (Thesis)

Modeling the Role of Operational Characteristics in Safety Performance of PublicTransportation Systems: The Case of TriMet Bus Collision and Non-collision Incidents. , Paul Herman Wachana (Dissertation)

Multi-Criteria Trucking Freeway Performance Measures for Congested Corridors , Nicole Marie Wheeler (Thesis)

Theses/Dissertations from 1994 1994

A Simultaneous Route-level Transit Patronage Model: Demand, Supply, and Inter-route Relationship , Zhongren Peng (Dissertation)

Theses/Dissertations from 1991 1991

The Effect of Road Investment on Economic Development: A Case Study of the Oregon Counties , Ameer Mohammed Al-Alwan (Dissertation)

Theses/Dissertations from 1990 1990

Exurban Commuting Patterns: A Case Study of the Portland Oregon Region , Judy Seppanen Davis (Dissertation)

Theses/Dissertations from 1985 1985

Women's labor force supply and commuting behavior: a time-budget analysis , Ta-Win Lin (Dissertation)

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How to Write an Essay on Transportation Problems

Examples of Proposal Arguments

Writing an essay on transportation problems is a generally easy and simple task. When writing your essay, it is very important to be clear about what your transportation problem is and what suggestions and/or solutions that you may have. Providing a good example of your transportation problem is also a must, as it will help your reader understand your frustrations. An essay that has clarity and examples makes a convincing read.

Writing an Essay on Transportation Problems

Construct and develop your thesis for your essay on transportation problems. You can place the thesis in the beginning of your opening paragraph, in the middle or use it as your last sentence. Your thesis should be the main emphasis of your essay and reflect its main idea. For instance, if your essay is dealing with transportation problems at a busy intersection, your thesis could be that the busy intersection is dangerous and that a traffic light needs to be installed for safety concerns. Your thesis can really be anything you want it to be, as long as it is relevant to your transportation problems essay.

Write the body paragraphs of your transportation essay using pertinent examples regarding your transportation problems. There is no better way to help convince your reader of your point than by providing relevant examples, especially regarding transportation problems. Most drivers have been annoyed by transportation issues, whether they were construction delays, dangerous intersections, heavy traffic or bad drivers. It is important to provide good examples in your essay so you can illustrate your perspective. You might want to support your thesis with information from your local, state or federal transportation departments.

Write the conclusion of your essay using your suggestions for improving the transportation problems highlighted in your essay. The conclusion is important, as you want to leave the reader with a good impression. By incorporating your ideas into the conclusion, the reader will be impressed with your proposed transportation improvements, which will help make your essay stand out. The conclusion will, ideally, be supportive of your thesis and help tie the essay together.

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Kevin Irons graduated in May 2008 from Saint Leo University with a bachelor's degree in creative writing. He's been writing professionally since 2008 and is pursuing his Master of Fine Arts in creative writing. He has expertise in surfing, playing music and sports.

20 Thesis topics related to Transportation

In today’s fast-paced world where everybody is constantly on the move, there is an increasing requirement for better and safer transportation facilities. This includes planning of the roadways and rail tracks, terminals and parking infrastructure. Walkability is also a growing concern among citizens with the heavy automobile traffic rendering the streets and squares abandoned. 

Transportation , as a topic, can never go out of fashion as there is a constant need for development to keep up with the growing population and needs of the people. Let us look at 20 Thesis topics related to transportation.

1. Airports

Airplanes have practically blurred the borders worldwide, opening up a multitude of opportunities for travel and business expansion. The added comfort and services provided by airports have made them an increasingly popular mode of transport in today’s fast-paced world. Airports are strategic in terms of economy, providing freight and cargo facilities. 

Apart from globalisation, tourism and commerce, airports are integral in case of emergency evacuations, for instance, the 1990 airlift of Indians from Kuwait or the Vande Bharat flights more recently. 

2. Railway Stations

From the Delhi Metro and Mumbai Local to the London Tube and the New York City Subway, trains form a crucial part of the public transport scenario in modern times. Train services, be it inter or intrastate, are cheap, convenient and quick, hence preferred by the masses. 

Additionally, the interstate train network is far more widespread than the air network, connecting to the smaller towns and villages with no air connectivity, transporting both goods and people. 

3. International Cruise Terminal 

Waterways were the mode of transport before the airplanes for international travel. With the likes of Titanic, cruises were developed into a whole new tourism sector. 

The terminals are integral with respect to the transport of cargo as well as acting as a mixed-use space incorporating commercial and entertainment services amongst others.

4. Inland Water Transport

A domestic means of transportation, they house ferries to transport people to nearby islands or simply for a joy ride in the sea. For instance, the coracle is a small boat used traditionally in countries like Ireland, Scotland, India, Vietnam, Iraq and Tibet. 

Sometimes, these may also be houseboats like those in Alleppey in Kerala or the shikara in Dal Lake. 

5. Bus Terminal

The most common mode of transport among the general public are the buses which result in the need for proper infrastructure for bus terminals as well as bus stops. Bus terminals, in particular, require planning in terms of the spaces allotted for the bus parking and ticketing counters to segregate the inter and intra city bus services. 

Considering the popularity of buses as a mode of transport, each bus stop is a significant social hub.  

6. Rickshaw Stands

Developing countries provide local public transport for 2-8 people which may be called by different names like tuk-tuk, pousse-pousse or simply a rickshaw. Rickshaw services may be motor operated, a cycle rickshaw or hand-pulled. Faring along with the motor vehicles, it may be a bit unsafe keeping in mind the lightweight of these rickshaws. 

This mode of transport has no developed infrastructure in place but there is a requirement for rickshaw stands to avoid congestion of traffic. 

7. Cycle Stands

Cycling for short distances is an increasingly growing trend among people today, particularly in modern cities, while in smaller towns and villages, cycles are the most common means of transportation. Separate cycling lanes are provided alongside the wide roads for automobiles. However, cyclists require a safer environment and larger spaces. 

Today, a lot of cities offer rental cycles which can be boarded and dropped off at fixed locations. Infrastructure needs to be developed to create more pick up and drop off locations that are easily accessible and at the same time connect to other modes of transport as well.

8. Electric Motor Vehicle Station 

Fuel-based vehicles are at the threshold of being replaced by electric motor vehicles all over the world, thanks to popularisation by the likes of Tesla. An eco-friendly alternative to meet the transportation requirements, EMVs generate an additional need for charging stations that must be widespread and easily accessible. 

Moving a few years ahead in time, this will be the most sought after amenity, requiring suitable infrastructure. 

9. Urban Transport Planning 

With an increase in urbanisation, cities today are experiencing a large influx of population. For this, cities need to be planned in a manner that accommodates the facility and transportation requirements of the current population while also leaving some scope for future expansion. 

The rising concerns of the harmful effects of the automobile have resulted in a need to balance the spaces allotted for automobiles and pedestrians while attempting to improve the public transport experience. 

10. Transit Oriented Development

Transit-oriented development translates to urban development integrating housing, retail and commercial spaces into a walkable neighbourhood with easily accessible public transport facilities. 

According to the Institute for Transportation and Development Policy, “It means inclusive access for all to local and citywide opportunities and resources by the most efficient and healthful combination of mobility modes, at the lowest financial and environmental cost, and with the highest resilience to disruptive events. Inclusive TOD is a necessary foundation for long-term sustainability, equity, shared prosperity, and civil peace in cities.”

Saisha is a student of architecture who believes that buildings are an integral part of civilization, affectinghumans in more ways than can be commonly comprehended. Born and brought up in Delhi, she has a keen interest in architectural writing and photography and aspires to promote sustainable development while preserving heritage.

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Solving Linear Programming's Transportation Problem

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A special case of the linear programming problem, the transportation problem, is the subject of this thesis. The development of a solution to the transportation problem is based on fundamental concepts from the theory of linear algebra and matrices.

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iii, 44 leaves

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Culp, William E. May 1968.

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• Culp, William E.
• Bilyeu, Russell Gene Major Professor

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• Crawford, Robert H. Minor Professor
• North Texas State University Place of Publication: Denton, Texas

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• Level: Master's
• Grantor: North Texas State University
• Name: Master of Arts
• Department: Department of Mathematics
• Discipline: Mathematics
• linear programming
• transportation problem
• Thesis or Dissertation

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• Call Number : 379 N81 no.3664
• Accession or Local Control No : n_03664
• UNT Catalog No. : b2490689 | View in Discover
• Archival Resource Key : ark:/67531/metadc130938

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• Dec. 27, 2012, 10:03 p.m.

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Culp, William E. Solving Linear Programming's Transportation Problem , thesis , May 1968; Denton, Texas . ( https://digital.library.unt.edu/ark:/67531/metadc130938/ : accessed April 1, 2024 ), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu ; .

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The Dali, the ship that brought down the Baltimore bridge, ran into a problem with its propulsion system months before the crash

• The ship that struck a key bridge on Tuesday was reported to have an issue with its propulsion in June.
• Records don't say exactly what the problem was, but a note mentioned gauges and thermometers.
• The Dali lost propulsion on Tuesday, but it's unclear if this was related to the June issue.

The 984-foot container vessel that lost power and crashed into the Francis Scott Key Bridge on Tuesday had issues with its propulsion system just months before, records show.

The Singapore-flagged Dali suffered a power outage as it bore down on the I-695 bridge, before ramming into a vital support beam that gave way and caused part of the structure to collapse into the Patapsco River in Baltimore.

"We can confirm that the crew notified authorities of a power issue," Maryland Gov. Wes Moore said in a press conference on Tuesday.

During the blackout, the Dali "experienced momentary loss of propulsion," the Maritime and Port Authority of Singapore said in a statement , citing a report from Synergy Marine, the ship's manager.

The same ship was flagged in June for an issue related to its propulsion system, according to records from an international database of port controls in Asia Pacific.

However, it's still unclear if the deficiency found in June was at all related to what caused the crash on Tuesday.

The issue was reported in San Antonio, Chile on June 27, and listed as a propulsion and auxiliary system deficiency. An attached note reads: "Gauges, thermometers, etc."

Per the records, this problem was not deemed as grounds for the ship to be detained in Chile.

Clay Diamond, the executive director of the American Pilots' Association, told The Washington Post that the Dali lost power at around 1:20 a.m., around eight minutes before the crash.

Pilots on board tried to start an emergency diesel generator to repower the ship and restart electrical systems, he said.

Related stories

But Diamond told USA TODAY that the propulsion didn't appear to kick back in.

"There was still some steerage left when they initially lost power," he said, per the outlet. "We've been told the ship never recovered propulsion."

Authorities and Synergy Marine, headquartered in Singapore, are investigating the cause of the power failure and allision.

The Dali was previously involved in a separate mishap. In 2016, it scraped its hull against a quay in Antwerp , an incident that was attributed to a pilot error.

On Wednesday, Singapore's maritime officials said the Dali had passed previous port inspections and that the June incident was "a faulty monitor gauge for fuel pressure," which was fixed before the ship left port.

When reached for comment, a representative for Synergy Marine referred Business Insider to the Singapore authorities' statement.

The bridge's collapse has triggered a state of emergency in Baltimore, and six members of a small construction crew working on the bridge during the crash are presumed dead. Authorities say officials managed to stop traffic on the bridge before it collapsed.

The Francis Scott Key Bridge was Baltimore's biggest bridge, and the loss of such critical infrastructure will likely cause supply chain issues across multiple industries. Around 11.3 million vehicles use the bridge annually, per the Maryland Transport Authority.

The nearby Port of Baltimore has also been closed to vessels until further notice, with experts telling BI's Dominic Reuter that the closure could halt about $15 million worth of economic activity daily .

This port is also particularly important for the automotive industry because it's a special terminal for wheeled cargo like vehicles and heavy farming equipment.

Coal, gypsum, sugar, paper, chocolate, and ice cream are commonly moved through the Port of Baltimore, BI's Erin Snodgrass reported.

Meanwhile, shares of Maersk , the Danish shipping company that chartered the Dali, dropped as much as 8% in Copenhagen on Tuesday. The firm has declared that its lanes through Baltimore are closed, for now.

March 27, 2023: This story was updated to reflect a response from Synergy Marine and a new MPA statement on the Dali's reported issue with its propulsion system in June.

Watch: The container ship that destroyed the Francis Scott Key Bridge has crashed before

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Reporting by Zaheer Kachwala and Akash Sriram in Bengaluru and Joe White in Detroit; Editing by Shilpi Majumdar, Arun Koyyur and Devika Syamnath

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Thomson Reuters

Akash reports on technology companies in the United States, electric vehicle companies, and the space industry. His reporting usually appears in the Autos & Transportation and Technology sections. He has a postgraduate degree in Conflict, Development, and Security from the University of Leeds. Akash's interests include music, football (soccer), and Formula 1.

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