Despite their inherent vulnerability to structural and functional degradation, transportation networks play a vital role in the aftermath of disasters by ensuring physical access to the affected communities and providing services according to the generated needs. In this setting of operational conditions and service needs which deviate from normal, a restructuring of network functions is deemed to be beneficial for overall network serviceability. In such context, this paper explores the planning of post-disaster operations on a network following a hazardous event on one of the network’s nodes. Lane reversal, demand regulation and path activation are applied to provide an optimally reconfigured network with reallocated demand, so that the network performance is maximized. The problem is formulated as a bi-level optimization model; the upper level determines the optimal network management strategy implementation scheme while the lower level assigns traffic on the network. Three performance indices are used for that purpose: the total network travel time (TNTT), the total network flow (TNF) and the special origin-destination pair (OD pair) accessibility. A genetic algorithm coupled with a traffic assignment process is used as a solution methodology. Application of the model on a real urban network proves the computational efficiency of the algorithm; the model systematically produces robust results of enhanced network performance, indicating its value as an operation planning tool.

Traffic paradox is an important phenomenon which needs attention in transportation network design and traffic management. Previous studies on traffic paradox always examined user equilibrium (UE) or stochastic user equilibrium (SUE) conditions with a fixed traffic demand (FD) and set the travel costs of links as constants under the SUE condition. However, traffic demand is elastic, especially when there are new links added to the network that may induce new traffic demand, and the travel costs of links actually depend on the traffic flows on them. This paper comprehensively investigates the traffic paradox under different equilibrium conditions including the user equilibrium and the stochastic user equilibrium with a fixed and elastic traffic demand. Origin-destination (OD) mean unit travel cost (MUTC) has been chosen as the main index to characterize whether the traffic paradox occurs. The impacts of travelers’ perception errors and travel cost sensitivity on the occurrence of the traffic paradox are also analyzed. The conclusions show that the occurrence of the traffic paradox depends on the traffic demand and equilibrium conditions; higher perception errors of travelers may lead to a better network performance, and a higher travel cost sensitivity will create a reversed traffic paradox. Finally, several appropriate traffic management measures are proposed to avoid the traffic paradox and improve the network performance.

Design and development of systems for delivering real-time information to people with disabilities and elderly persons need to be based on defined user requirements. For this purpose, the user requirements have been defined in this paper according to the everyday needs of people who use traffic networks and move in closed spaces. The logical presentation of the functionality of the informing system operation and its subsystems includes all the information (data) important for designing a user information delivery system. The paper presents a conceptual architecture system for delivering user informing services related to the environment based on the Internet of Things concept. The aim of the user informing service is an increase in the level of mobility of persons with disabilities and the senior age groups of users. In order to check the operation of the proposed architecture, the informing system operation was monitored on Arduino Uno and Raspberry Pi platforms in laboratory conditions. A simulation confirmed the interdependence of individual data from different subsystems in order to provide real-time information to the system user. The proposed conceptual architecture can contribute to a more efficient approach to the modeling of assistive technologies (with the aim of informing the users) based on dew/fog/cloud technologies in the Internet of Things  environment.

This study focuses on a distribution problem involving incompatible products which cannot be stored in a compartment of a vehicle. To satisfy different types of customer demand at minimum logistics cost, the products are stored in different compartments of fleet vehicles, which requires the problem to be modeled as a multiple-compartment vehicle routing problem (MCVRP). While there is an extensive literature on the vehicle routing problem (VRP) and its numerous variants, there are fewer research papers on the MCVRP. Firstly, a novel taxonomic framework for the VRP literature is proposed in this study. Secondly, new mathematical models are proposed for the basic MCVRP, together with its multiple-trip and split-delivery extensions, for obtaining exact solutions for small-size instances. Finally, heuristic algorithms are developed for larger instances of the three problem variants. To test the performance of our heuristics against optimum solutions for larger instances, a lower bounding scheme is also proposed. The results of the computational experiments are reported, indicating validity and a promising performance of an approach.

Bicycle traffic flow suffers from the impact of tracks at an intersection in which a modern streetcar route is laid. The primary objective of this study involves discussing the impacts of modern streetcar tracks on bicycling through an intersection and developing a quantitative approach to calculate bicycle delay. Field investigations are conducted at eight sites in Nanjing and Shenyang, China. The sites are related to five intersections. Two of the five intersections are designed with a central modern streetcar style of track. Other two intersections operate on a roadside style of track and the last intersection is without tracks. The impact of the differences in bicycle speed are tested at each site based on the observed data. The results show that modern streetcar tracks exert a significant influence on bicycle speed and bicycling behavior and lead to delay, discomfort and unsafe conditions. Furthermore, a model is proposed to predict bicycle delay caused by modern streetcar tracks. The proposed model achieved a relatively accurate prediction. The findings of this study help in adequately understanding the impacts of modern streetcar tracks on bicycling. The results also suggest that longer crossing times should be used in signal design for bicycling at an intersection in which a modern streetcar route is laid.

The performance of a traffic system tends to improve as the percentage of connected vehicles (CV) in total flow increases. However, due to low CV penetration in the current vehicle market, improving the traffic signal operation remains a challenging task. In an effort to improve the performance of CV applications at low penetration rates, the authors develop a new method to estimate the speeds and positions of non-connected vehicles (NCV) along a signalized intersection. The algorithm uses CV information and initial speeds and positions of the NCVs from loop detectors and estimates the forward movements of the NCVs using the Gipps’ car-following model. Calibration parameters of the Gipps’ model were determined using a solver optimization tool. The estimation algorithm was applied to a previously developed connected vehicle signal control (CVSC) strategy on two different isolated intersections. Simulations in VISSIM showed the estimation accuracy higher for the intersection with less lanes. Estimation error increased with the decrease in CV penetration and decreased with the decrease in traffic demand. The CVSC strategy with 40% and higher CV penetration (for Intersection 1) and with 20% and higher CV penetration (for Intersection 2) showed better performance in reducing travel time delay and number of stops than the EPICS adaptive control.

The main objective of this paper is to define the repositioning strategy of the Port of Adria, which is the leading container maritime port of Montenegro. The strategy is an integral reflection of the analysis of internal (competitive advantage and financial strength) and external (the potential of container maritime port industry and environmental stability) repositioning criteria. The case study in this paper is mainly accomplished through the definition of specific propositions that clarify the connections between these criteria and the repositioning strategy. Knowledge and attitudes of stakeholders are used with the purpose of modeling a marketing strategy, which is based on an inductive study. The paper proposes a model based on a specific maritime port case which can be applied to any other case of maritime port repositioning as well.

Intermodal transport enables energy, costs and time savings, improves the service quality and supports sustainable development. The basic element of the intermodal transport system is an intermodal terminal, whose efficiency largely depends on the subsystems’ technologies. Accordingly, the topic of this paper is the evaluation and the selection of the appropriate handling equipment within the intermodal terminal. As the decision-making on the handling equipment is influenced by different economic, technical, technological and other criteria, the appropriate multi-criteria decision-making (MCDM) methods have to be applied in order to solve the problem. In this paper, a novel hybrid model which combines the fuzzy step-wise weight assessment ratio analysis (FSWARA) and the fuzzy best-worst method (FBWM) is developed. The defined model is applied for solving the case study of selecting adequate handling equipment for the planned intermodal terminal in Belgrade. The reach stacker is selected as the most adequate handling equipment since it suits best the characteristics of the planned terminal in the given conditions and in relation to the defined criteria. Solving the case study demonstrated the justification for using the MCDM methods to solve these kinds of problems as well as the applicability of the proposed MCDM model.

The aim of this study is to find a suitable methodology for planning the locations of intermodal terminals in an urban transit context. The location planning approach, which has been developed and makes this possible, consists of three phases. The first phase is the making of the geographic information system (GIS) database which enables determining the potential locations of intermodal terminals. For every potential location of the terminal, the number of citizens gravitating to a certain terminal is calculated, which at the same time represents the output from the first phase of the model. The second phase uses an optimization algorithm in order to determine the locations of the intermodal terminals. The optimization algorithm provides several solutions for a different number of terminals, and such solutions need to be evaluated. The main contribution of this research is in upgrading the location planning approach by introducing an additional step in assessing the solutions obtained by the optimization algorithm.