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This paper introduces a new heuristic algorithm that aims to solve the military route vulnerability problem, which involves assessing the vulnerability of military cargo flowing over roads and railways subject to enemy interdiction.

Graph theory, a heuristic and a binary integer program are used in this paper.

This work allows transportation analysts at the United States Transportation Command to identify a relatively small number of roads or railways that, if interdicted by an enemy, could disrupt the flow of military cargo within any theater of operation.

This research does not capture aspects of time, such as the reality that cargo requirements and enemy threats may fluctuate each day of the contingency.

This work provides military logistics planners and decision-makers with a vulnerability assessment of theater distribution routes, including insights into which specific roads and railways may require protection to ensure the successful delivery of cargo from ports of debarkation to final destinations.

This work merges network connectivity and flow characteristics with enemy threat assessments to identify militarily-useful roads and railways most vulnerable to enemy interdictions. A geographic combatant command recently used this specific research approach to support their request for rapid rail repair capability.

Congestion at Ghana’s main seaports is a problem that has received much attention recently. This is as a result of continuous increase in containerized cargo. To increase the capacity of Ghana’ seaport, the Ministry of Transport through the Ghana Shippers Council initiated the Boankra Inland Port Project. The aim of this paper is to assess the feasibility and economic effects of implementing the Boankra Inland Port as a solution to reduce congestion at the main seaports, as well as reduce transportation cost.

The location of the inland port was assessed using the gravitational model. Data for the gravitational model are distances from the main seaports in Ghana and Boankra Inland Port to major hinterland destinations and population of the destinations. Also, 210 respondents were selected and interviewed on contribution of the dry port concept to the economy and transportation management in Ghana.

The results of the gravitational model support the location of Boankra as an inland port. A further comparison between Tema and Takoradi shows that Tema has a better location as a distribution center than Takoradi.

Although Tema and Takoradi are the main seaports in Ghana, the implementation of the Boankra inland port will reduce the transportation cost for cargo with hinterland destinations, therefore making it a rational and cost-efficient location for transit transportation.

This paper is among the first significant attempts to evaluate the suitability of inland port implementation in Ghana.

The purpose of this study is to investigate the influence of institutional dynamics on road accidents and whether this relationship is moderated by information and communication technology (ICT).

The study adopted a quantitative approach with 133 respondents. Research hypotheses were tested in AMOS version 21. In addition, moderated regression analysis was used to test the moderating role of ICT on the relationship between institutional dynamics and road accidents.

The results show that vehicle maintenance, policy enforcement, safety culture, driver training and driver management positively influence road accidents. Moreover, the study established that ICT moderates the relationship between institutional dynamics and road accidents.

The results of this study serve as a practical guideline for policymakers in the road haulage sector. Managers may gain insights on how to design effective interventions to reduce road accidents.

This research contributes to the existing body of knowledge by exploring previously unexplored moderating paths in the relationship between institutional dynamics and road accidents. By highlighting the moderating role of ICT, the study sheds new light on the institutional dynamics that influence road accidents in the context of road haulage companies.

To proactively draw efficient maintenance plans, road agencies should be able to forecast main road distress parameters, such as cracking, rutting, deflection and International Roughness Index (IRI). Nonetheless, the behavior of those parameters throughout pavement life cycles is associated with high uncertainty, resulting from various interrelated factors that fluctuate over time. This study aims to propose the use of dynamic Bayesian belief networks for the development of time-series prediction models to probabilistically forecast road distress parameters.

While Bayesian belief network (BBN) has the merit of capturing uncertainty associated with variables in a domain, dynamic BBNs, in particular, are deemed ideal for forecasting road distress over time due to its Markovian and invariant transition probability properties. Four dynamic BBN models are developed to represent rutting, deflection, cracking and IRI, using pavement data collected from 32 major road sections in the United Arab Emirates between 2013 and 2019. Those models are based on several factors affecting pavement deterioration, which are classified into three categories traffic factors, environmental factors and road-specific factors.

The four developed performance prediction models achieved an overall precision and reliability rate of over 80%.

The proposed approach provides flexibility to illustrate road conditions under various scenarios, which is beneficial for pavement maintainers in obtaining a realistic representation of expected future road conditions, where maintenance efforts could be prioritized and optimized.

The purpose of this study was to provide an outline of the process of developing an on-road driving test route and rating form. Comprehensive evaluation of medical fitness to drive should comprise of an off-road and an on-road assessment. Much research attention has focussed on the off-road phase of assessment, while there is less standardisation evident in the completion and measurement of the on-road phase of fitness-to-drive assessment.

A scholarship of practice approach was used to inform the development of an on-road test route and an associated generic on-road assessment tool that was guided by research evidence and best practice recommendations.

A step-by-step guide, outlining seven recommended phases in the development of an on-road route for the assessment of fitness to drive that aligns with best practice recommendations, was developed. A preliminary generic on-road assessment tool (the Maynooth–Trinity Driving Test) that includes higher-order cognition alongside element of strategic, tactical and operational driving ability was developed and piloted alongside the newly developed on-road test route.

This paper offers an overview of an approach to developing evidence-based on-road test routes and an associated generic assessment tool that may assist occupational therapists and on-road driving assessors establish a standard practice for testing on-road behaviour as part of a comprehensive approach to evaluate fitness to drive.

This paper aims to understand the trade transportation situation between China and Koreas, and to explore the possibility of establishing the surface transportation corridor between China and Koreas in the future. Moreover, the paper also intends to find out the mode choice behaviors of shippers, which can be used to analyze the substitute effects of the surface modes on the water one.

The paper first analyzes the Sino-Korean bilateral trade and the corresponding trade transportation between China and Koreas. Secondly, it presents the surface transportation network between China and Koreas, and analyzes the warming relations between the North and South. Finally, the modal split of trade transportation between China and Koreas is estimated by establishing a mode choice model based on a questionnaire survey.

With the increasingly stable political environment and the physical highway and railway connections, the surface transportation network would become possible. Moreover, the shippers need the multimodal transportation system between China and Koreas, and many shippers would select road or rail mode if a suitable road or rail network were available. Especially, between China and South Korea, the road, rail and water mode may be used evenly, while the road mode may play a more important role between China and North Korea. The surface modes would have a huge substitute effect on the water mode.

The existing literature conducted research mainly from the perspective of economy and geopolitics, while the topics of transportation between China and Koreas are rarely concerned. This paper intends to throw some light on the situation of the trade transportation between China and Koreas, consider the potential of relation improvement on the Korean Peninsula proactively and study the surface transportation issues between China and Koreas.

For the case of Sweden, this paper aims to determine how a range of different infrastructure fees and taxes influences modal split, port throughputs, air emissions, societal costs of greenhouse gas (GHG) emissions and air pollution, as well as logistics costs.

The Swedish national freight model is used to simulate a range of different proposed infrastructure fees, one by one and in combination. The volume of emissions of CO₂-equivalents, NOx, SOx and PM under the different scenarios is calculated in both volume and monetary terms, by applying national emission factors and EU values for external costs.

Road user fees are calculated to have the largest impact on the modal split, GHG emissions and air pollution. The impact increases slightly when road user fees are combined with higher fees for sea and rail and/or gate fees in all Swedish ports. The imposition of gate fees over €30 per truck in all ports leads to shifts in cargo to land-based modes and to ports outside Sweden. The logistics costs in Sweden are found to be three to ten times higher than the benefits of reduced GHG emissions and air pollution, although other benefits to society need to be considered as well.

Methods which attempt to evaluate alternative approaches to the internalisation of the external costs caused by transport need to be further developed. In particular, they need to encompass a more holistic perspective on “benefits to society”, other than merely reductions in GHG emissions and air pollution. To facilitate international acceptance and adoption, such methods require agreements to be reached on common definitions and routines.

The results can be used as basis for policy-making. They illustrate the environmental impacts of the fees and taxes one by one and in combination and to what extent these reinforce each other and should be co-ordinated.

The outcomes are relevant to national and international policymakers and authorities, as well as port authorities, shippers and transport companies who need to determine unilateral strategies on how to reduce GHG emissions and air pollution, without undermining their wider business objectives.

The approach is original in facilitating the testing of policies which impact on the transport system and the environment across different dimensions. The work has additional value in informing policy because of its use of Sweden’s national freight transport model.

This study empirically examines the impact of rural roads on consumption of households in Ethiopia.

Both descriptive statistics and econometric techniques are used to address the aforementioned objective. Specifically, quantile regression, fixed- and random-effect models are used to understand the impact of rural road quality on welfare.

The econometric analysis revealed that improving the quality of rural roads and/or creating access to all-weather roads raises households' average real consumption per capita by as much as 10%. The other transport indicator – mode of transport – also has a positive effect on real consumption per capita. The result indicated that real consumption per capita for households using the traditional mode of transport would increase by as much as 7% compared to those using foot as a major mode of transport. However, the fixed quantile estimation result revealed that rural road access has a positive and significant effect on consumption per capita only for the 0.8th and 0.9th percentiles, indicating that the access to roads is not pro-poor.

Improving rural roads to a level of all-weather road standards and provision of agricultural transport facilities should be strategic priorities.

This study provides empirical evidence pertinent to the effect rural mobility has on the consumption of households as well as the pro-poorness of such investments in rural settings.

The missing travel time data for roads is a common problem encountered by traffic management departments. Tensor decomposition, as one of the most widely used method for completing missing traffic data, plays a significant role in the intelligent transportation system (ITS). However, existing methods of tensor decomposition focus on the global data structure, resulting in relatively low accuracy in fibrosis missing scenarios. Therefore, this paper aims to propose a novel tensor decomposition model which further considers the local spatiotemporal similarity for fibrosis missing to improve travel time completion accuracy.

The proposed model can aggregate road sections with similar physical attributes by spatial clustering, and then it calculates the temporal association of road sections by the dynamic longest common subsequence. A similarity relationship matrix in the temporal dimension is constructed and incorporated into the tensor completion model, which can enhance the local spatiotemporal relationship of the missing parts of the fibrosis type.

The experiment shows that this method is superior and robust. Compared with other baseline models, this method has the smallest error and maintains good completion results despite high missing rates.

This model has higher accuracy for the fibrosis missing and performs good convergence effects in the case of the high missing rate.

Using the Social Network Analysis(SNA) method, this paper examines inter-country relationships between countries that may be part of the New Silk Road. Based on bilateral-trade data from more than 70 countries, the paper provides a more vivid understanding of overall features and effects of the New Silk Road policy. According to the results, India, Turkey, and Russia have the highest degree centrality, indicating that the success of the New Silk Road policy depends mainly on the ability of the Chinese government to incorporate these countries. Among European countries, only Germany can be successfully incorporated into the New Silk Road network. In addition, Central Asian countries such as Kazakhstan and Uzbekistan show no potential as hubs in the network. Most importantly, China has a dominant position in the New Silk Road network. China's focal and dominating status is also supported by the fact that there is no change in the clustering coefficient in the network, which implies that the Chinese government has to absorb into the system those countries that are less likely to benefit from the policy.