Disruption management in public transit: the bee colony optimization approach

Disruptions in carrying out planned bus schedules occur daily in many public transit companies. Disturbances are often so large that it is necessary to perform re-planning of planned bus and crew activities. Dispatchers in charge of traffic operations must frequently find an answer to the following question in a very short period of time: How should available buses be distributed among bus routes in order to minimize total passengers' waiting time on the network? We propose a model for assigning buses to scheduled routes when there is a shortage of buses. The proposed model is based on the bee colony optimization (BCO) technique. It is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. It has been shown that this developed BCO approach can generate high-quality solutions within negligible processing times.     

Assessing the impacts of driving environment on driving behavior patterns

Transportation - Considering the role of behavioral and environmental factors on road accidents and traffic intensities, the characterization of vehicle use and driver behavior opens new...     

Auction-Based Congestion Pricing

Abstract

Planners, engineers and economists have introduced various demand management methods in an attempt to reduce the fast growing traffic congestion. The basic idea behind various demand management strategies is to force drivers to travel and use transportation facilities more during off-peak hours and less during peak hours, as well as to increase the usage of underutilized routes. In this paper, a new demand management concept – Auction-based Congestion Pricing – is proposed and modeled.     

An advanced theory of thin-walled girders with application to ship vibrations

The paper presents an outline of the advanced theory of thin-walled girders. The improvement includes shear influence on torsion as an extension of shear influence on bending. The analogy between bending and torsion is recognized and pointed out throughout the paper. Complete differential equations of coupled flexural and torsional vibrations for a prismatic girder are derived. In addition, the 8 d.o.f. beam finite element, utilizing the energy approach, is constituted with stiffness and mass matrices, and load vectors. The paper describes determining of geometrical properties of multi-cell open cross-sections by employing the strip element method. Numerical procedures for vibration analyses are outlined. Furthermore, dry natural vibrations of a VLCS (Very Large Container Ship) are analysed by 1D FEM model as a prerogative for hydroelastic analyses of these relatively flexible vessels. Influence of transverse bulkheads is taken into account by increasing torsional stiffness of the ship hull proportionally to their deformation energies. Validation of 1D FEM model is checked by correlation analysis with the vibration response of the fine 3D FEM model.     

Development of the Lane Keeping Control System Using State-Varying Surface for Vulnerable Road Users

This paper proposes a new Lane Keeping Assist (LKA) system based on the integrated control strategy with AFS and BTV. To be specific, the steering controller calculates the gear ratio of AFS to align with the target lane whereas the braking controller determines differential brake pressure using Sliding Mode Control (SMC) theory according to the state-varying sliding surface with Fuzzy model. In recent years, auto industries have produced the lane keeping applications to prevent lane departure caused by drivers’ distractions or drowsiness. To also prevent wrist injury in drivers while steering, current LKA systems limit the output values of steering-wheel assist torque. This limiting mechanism, however, can cause a problem that cannot follow a road curvature when an older driver overexerts an inappropriate control effort. A new LKA system of the AFS and BTV integrated controller has since been drafted to solve this problem, and validated its performance in regards to the test conditions given with various driver models.     

Design factor optimization of 3D flash lidar sensor based on geometrical model for automated vehicle and advanced driver assistance system applications

Sensor technologies have been innovated and enhanced rapidly for highly automated vehicle and advanced driver assistance systems (ADAS) in automotive industry; however, in order to adopt sensors into mass production vehicle in near future, various requirements should be satisfied such as cost, durability, and maintainance without any loss of overall performance of the sensors. In this sense, a 3D flash lidar is one of primising range sensors because of no moving parts, compact package, and precise measure for distance by using a laser. In spite of the several advantages, the 3D flash lidar is not commonly used in automotive industry because it is quite expensive for adoption and it is manufactured with only general purpose currently; therefore, the cost reduction and optimal design to satisfy various purposes of ADAS or autonomous driving should be accomplished. In this paper, we propose a novel approach for design factor optimization of the 3D flash lidar based on a geometrical model by using structural similarity between the 3D flash lidar and 2D digital camera. In particular, focal length and area of a receiver (focal plane array and read-out integrated circuit) which directly affect on sensor performance (field of view and maximum detection range) are optimized as the design factors. From the optimization results in simulation, we show that optimal design factors according to various purposes required in ADAS could be easily determined and the sensor performances could be evaluated before manufacturing. It will reduce temporal and economic burdens for design and manufacturing in development process.     

Development of an IoT-based container tracking system for China’s Belt and Road (B&R) initiative

To ensure the successful implementation of China’s Belt and Road (B&R) Initiative, it is essential to enable the real-time monitoring of containers’ locations, prevent theft during cargo delivery, ensure more efficient logistics management and reduce carbon emissions. For this, it is vital to have an economic and effective system to track and control containers across multiple countries. However, this requirement cannot be met by today’s container tracking systems because they are either limited within the borders of each country or expensive to employ internationally. This study thus presents a framework for an IoT-based container tracking system that enables users not only to grasp the international flow of container movement with one check but also to achieve smooth cross-border procedures. To verify the system’s performance, an empirical test was made for an actual container shipped from Korea to Poland. The test results showed that the system could successfully track the location of the container in real time across international borders. Last, this study discusses the policy development and international cooperation that should take place to enable the introduction of this container tracking system.     

Determining the number and location of winter road maintenance depots – a case study of the district road network in Serbia

Determining the number and location of depots for winter road maintenance (WRM) represents one of the important strategic decisions while planning WRM activities. However, most organizations dealing with WRM make empirically based decisions. Optimizing the number and location of WRM depots has the potential to achieve considerable cost savings, improve mobility and efficiency, as well as reduce environmental impacts. This paper presents two optimization models. The first model determines the location of WRM depots by minimizing the total distance travelled by maintenance vehicles. The second model determines the optimum number and location of WRM depots by minimizing total transportation costs and capital expenditure and operational expenditure of the depots. The models are then applied to the district road network in Serbia. Results show that their application could lead to significant reductions in WRM costs.     

Resilience in railway transport systems: a literature review and research agenda

ABSTRACT

Critical infrastructure networks, such as transport and power networks, are essential for the functioning of a society and economy. The rising transport demand increases the congestion in railway networks and thus they become more interdependent and more complex to operate. Also, an increasing number of disruptions due to system failures as well as climate changes can be expected in the future. As a consequence, many trains are cancelled and excessively delayed, and thus, many passengers are not reaching their destinations which compromises customers need for mobility. Currently, there is a rising need to quantify impacts of disruptions and the evolution of system performance. This review paper aims to set-up a field-specific definition of resilience in railway transport and gives a comprehensive, up-to-date review of railway resilience papers. The focus is on quantitative approaches. The review analyses peer-reviewed papers in Web of Science and Scopus from January 2008 to August 2019. The results show a steady increase of the number of published papers in recent years. The review classifies resilience metrics and approaches. It has been recognised that system-based metrics tend to better capture effects on transport services and transport demand. Also, mathematical optimization shows a great potential to assess and improve resilience of railway systems. Alternatively, data-driven approaches could be potentially used for detailed ex-post analysis of past disruptions. Finally, several rising future scientific topics are identified, spanning from learning from historical data, to considering interdependent critical systems and community resilience. Practitioners can also benefit from the review to understand a common terminology, recognise possible applications for assessing and designing resilient railway transport systems.