Real Route Research Articles

Optimal Vehicle Scheduling and Charging Infrastructure Planning for Autonomous Modular Transit System

Prioritizing the development of public transport is an effective way to improve the sustainability of the transport system. In recent years, bus passenger flow has been declining in many cities. How to reform the operating mode of the public transportation system is an important issue that needs to be solved. An autonomous modular bus (AMB) is capable of physical coupling and uncoupling to flexibly adjust vehicle capacity as well as provide high-quality service under unbalanced passenger demand conditions. To promote AMB adoption and reduce the operating cost of the bus route, this paper presents a joint optimization method to simultaneously determine the AMB dispatching plan, charging plan, and charging infrastructure configuration scheme. Then, a mixed-integer programming model is formulated to minimize the operating costs of the bus route. A hybrid intelligent algorithm combining enumeration, cloning algorithm, and particle swarm optimization algorithm is designed to resolve the formulated model. Subsequently, an actual bus route is taken as an example to validate the proposed method. Results indicate that the developed method in this paper can reduce the operating costs and operational energy consumption of the route compared with the real route operating plan. Specifically, the reduction ratio of the former is 23.85%, and the reduction ratio of the latter is 5.92%. The results of this study validate the feasibility and advantages of autonomous modular transit service, contributing positively to the sustainable development of the urban public transportation system.

A two-step approach for deploying heterogeneous vessels and designing reliable schedule in liner shipping services

Schedule reliability is a crucial metric for measuring liner container shipping service. Due to the inherent uncertainties at sea and ports, schedule delays and unreliable on-time performance have long plagued shipping companies. In practice, the heterogeneity of container vessels also creates challenges for deployment and schedule optimization. To address the problem, we develop a two-step approach with two programming sub-models. In the first step, we tackle the challenges of ship deployment and scheduling by considering heterogeneous vessels and capturing the interarrival time between adjacent ports of call. In the second step, we use the conditional value-at-risk (CVaR) to address the uncertainty risk avoidance in schedule design. To solve the stochastic programming models, we employ a solution framework based on the outer linear approximation method and the risk measure method, where CVaR is specified as the risk measure. We illustrate the application of our model on a case study concerning a real route operated by COSCO Shipping Lines. The results show that the total cost of liner shipping service with heterogeneous fleet on the route can be reduce by 4.77% compared with homogeneous fleet. And the cost of risk with the reliable schedule can be decreased by 8.04% compared with the ideal schedule. The research conclusions can provide some useful decision-making references for shipping companies to deploy heterogeneous vessels and design reliable schedules.

Вдосконалення процесу обробки абразивно-повітряним струменем робочих поверхонь лопаток моноколіс закритого типу на основі даних чисельного моделювання за допомогою програмного комплексу ANSYS CFX

The correct choice of technological modes can guarantee the results of inkjet processing. However, the need to consider a significant amount of input data, namely the parameters of the equipment, the abrasive jet, the physical and mechanical properties of the material, and the shape of the processed product surfaces, as well as the lack of clear recommendations and technological data, significantly complicates the process. The subject of this study is the process of processing the surface of closed-type blades with an abrasive-air jet made in one piece with a disk of the "monowheel" type, using the SLM technology of Inconel 718 alloy. The goal of this task is to model the jet processing of closed-type monowheel blades using the ANSYS CFX finite element analysis software system. This article presents the results of numerical modeling of the surface treatment of closed turbine blades and the identification of technological factors that affect the roughness and quality of the surface of the compressed air environment on samples of closed turbine blades made of Inconel 718 alloy. The task: to develop a research plan and study the processing process and accompanying phenomena occurring during processing using the finite element method using the ANSYS CFX software complex, considering the physical and mechanical properties of the abrasive often, the environment, and the processed material. The following results were obtained: during mathematical modeling using the finite element method, data were obtained for sixteen calculation variants of blade surface treatment, from which the most optimal one was chosen, which provides the largest contact area of abrasive particles and their uniform interaction with the processing surface. In addition, during the research, the impact of "unevenness of erosion" and the graininess of abrasive materials on the quality of the treated surface was studied. Further analysis of the data of the research results made it possible to find ways to solve these tasks, which was confirmed by the control and verification results. Conclusions. The scientific novelty of the obtained results is as follows: for the first time, the processing of closed turbine blades made in one piece with a "monowheel" type disk and obtained by the additive method with an abrasive air jet was investigated. The obtained research data were used as a basis for developing a real route technological process for processing closed-type turbine blades manufactured using the additive method.

Rebalancing in bike sharing systems: Application to the Lisbon case study

This work presents a mathematical programming formulation for the static Bike Rebalancing Problem to meet the practical constraints faced by the operators of Bike Sharing Systems. Adaptating a Mixed Integer Linear Programming formulation, it now includes different types of vehicles and bicycles, the autonomy of each vehicle, the duration of its route and the stations that require inspection actions. An intermediate station is introduced to temporarily store bicycles, relaxing the restrictions imposed by the vehicles’ capacity. After incorporating different acceleration procedures, a Branch-and-Cut scheme is run for 30 min to find optimized routes for the reposition vehicle on five real instances of the Lisbon Bike Sharing System. The computed routes resulted in a 30% to 75% decrease in total length, when compared to the real routes. This decrease is mainly attributed to the integration of all the mentioned factors in one global model, encouraging its future implementation.

Investigation of Blind Spatial Cognition and Understanding of Spaces to Navigate without Vision

This study is aimed to report the perspective of people with V.I about their use of spatial representation(cognitive maps) for determining the support level and applicability of cognitive maps while traveling on real routes. This research utilized the methodology of qualitative research in the form of semi structured interviews in order to obtain insights of persons having visual impairment about their navigation in different environments. The interviews were conducted with 20 persons having visual impairment working in different fields of life. The data analysis was done through thematic analysis approach. The participants were intended to answer the questions about the representation and understanding of space, the support level of these representations while traveling, and the role of other senses for successful navigation. The results showed that persons having visual impairment do have spatial representation and the creation of spatial representations does not require visual experience. The study suggested the strong need to assess the way in which persons having visual impairments develop cognitive maps of their environment because it is extremely significant both theoretically and practically and throws light on the role of sensory modalities in the development of mental mapping skills which can in turn recommend how spatial developments might be nourished.

Optimal battery management strategies for plug-in electric hybrid buses on routes including green corridors

Public transport is a cornerstone in the transition towards sustainable cities. Moreover, greenhouse gas emissions can be further reduced through powertrain electrification. In this context, plug-in electric hybrid buses emerge as a suitable and flexible solution. They can switch between an electric motor and a combustion engine during operation. An optimal electric drive assignment strategy allows achieving a high electric range and reduced tailpipe emissions. In this work, we look for optimal strategies for maximizing the distance traversed in electric mode and minimizing the total emissions, for real routes including green corridors where the combustion engine cannot be used. Contrary to existing works, this approach does not only focus on the improvement of the bus performance in terms of energy consumption, but also on the environmental benefits and livability of cities. This challenge is solved using two multi-objective state-of-the-art evolutionary algorithms, and a novel heuristic, GreenK. Two real- world scenarios are analyzed, namely bus routes M6 in Badalona, and 18 in Grudziadz. Results show a significant reduction in emissions of up to 21% with respect to the strategy found by GreenK, meaning 24 kg less pollutants emitted daily and over 22.5% electric range increase, compared to the currently deployed solution.

Satisfied railway flow route problem integrated with ideal route and real trajectory information

ABSTRACT Transportation enterprises have started to pay more attention to the vast amount of historical operational data. In this paper, real route information is extracted from the freight car trajectory data and a satisfied route is proposed based on this information. The satisfied route not only can reduce the travel cost but also conform to the actual transportation situation. A solution framework driven by trajectory data is developed to obtain the satisfied route. A case study associated with the Chinese railway is used to verify the model and the solution framework proposed in this paper.

Synthetic data: a real route to eliminating bias in biometrics

Synthetically produced data could be the ‘next big thing’ in biometrics, helping to cut discrimination in facial recognition and other apps. But, says Jan Lunter of Innovatrics, there are pitfalls users must avoid to get the best out of this innovation.

Влияние весов прямых измерений на результаты решения обратных задач фотограмметрии

The article is the second in a series of publications dealing with studying various aspects of statistical quality at solving inverse photogrammetry matters. The author examines the influence of direct measurement weights over the results of the equalization. It is noted that significant errors in evaluating weights of direct measurements of equalized parameters’ residuals can lead not only to the transformation of projecting beams’ bundles, but also to the phototriangulation unit’s deformation. A graphic illustration of this phenomenon is given by the example of a real route of optical-electronic space survey. The concepts of statistical quality of equalization for direct and indirect measurements are introduced. Analytical expressions are proposed for estimating this quality. The differences between the residuals fixed terminologically in their names are shown. The criteria of equalizing the above mentioned measurements’ statistical quality are obtained. The advantages and disadvantages of the weighting method of least squares in comparison with its generalized version in determining the weights of direct measurements of correlated equalized parameters are noted. An algorithm for correcting them was developed to improve the statistical quality of their equalizing. Experimental calculations were performed based on real satellite images obtained with the panchromatic equipment of the Resurs-DK spacecraft, which confirmed the effectivity of the proposed algorithm.

ENERGY EFFICIENCY OPTIMIZATION OF LAST MILE SUPPLY SYSTEM WITH REVERSE LOGISTICS CONSIDERATION

Last mile supply system takes great importance in the designed supply chain management, especially in the big urban areas, where various goods delivery locations should be tackled. Transportation routes and vehicles play a critical share in the optimization of the energy spent in this system because it is considered a complicated case due to its high solutions possibilities. Also, part of these transport processes is considered reverse logistics, where the goods take the way back, starting from the customer. Using a metaheuristic optimization is usually a good way to increase operations efficiency and save time and energy, next to raising sustainability. Within this paper, the last mile supply system within urban areas focusing on the goods' delivery and collection tasks is presented. The model design is described, mathematical optimization modelling is detailed, and a case study to investigate the impact of using diesel and electric trucks on energy efficiency is solved. After an introduction and theoretical background that includes a brief literature review, the designed system and used methodology are described. The designed system incorporates cloud computing, real routes of vehicles, analysis of collected data, energy consumption optimization, and time windows. Also, a mathematical model is developed with the aim of optimizing the total energy consumption. Real thirty locations in Budapest in the VII district are described and used as a case study for finding the solutions of the optimized taken routes and energy consumption by the genetic algorithm for both diesel and electric trucks. In the end, the results are analyzed and compared against a random solution to clarify the presented optimization's effectiveness.

A Study of Applying Eco-Driving Speed Advisory System on Transit Signal Priority

Transit Signal Priority (TSP) has long been seen as a cost-effective way to reduce bus delays at intersections. With Connected Vehicle (CV) technology, a speed advisory system guides buses to pass intersections in an energy-saving way. The integration of TSP and speed advisory may reduce bus delays and enhance energy consumption performances. This study proposed a system of integrating eco-driving speed advisory on TSP under CV environment. A TSP strategy based on intersections passing probability is designed. In addition to signal priority, this study designed and implemented an eco-driving speed advisory algorithm. A real electric bus route in Tainan City, Taiwan is used for the case study. Intersection layout and traffic related parameters are established in microscopic traffic simulation software SUMO (Simulation of Urban Mobility) to verify the effectiveness of the proposed model. The results provide an insight into how cooperation between signals and vehicles can enhance performances of energy consumption and signal-incurred traffic delays.

Feminism for Women: The Real Route to Liberation. By Julie Bindel (Constable Press, 2021, 248pp. £12.99 pb)

In the 1980s, radical feminism was part of criminology, but somewhere in the 1990s, it left. The focus shifted slowly away from male violence and women’s experiences of injustice towards a descriptive analysis of the various ways that gender (as a performance) related to offending and the administration of justice. Now, nearly 40 years later, radical feminism in criminology might just be making a comeback and we can thank Julie Bindel for that. Her latest book is a must read—even for those who disagree with her. Bindel’s book is written from the perspective of a 40-year long history of research and activism. It is an uncompromising defence of radical feminism as a theory and politics that is rooted in the idea that women’s oppression is related to their status as a sex class. Women here are defined as biologically female. These days, this is not always a popular position to take in the face of the political drive to expand the definition of woman to include those who identify as such. Each of the eight substantive chapters moves between empirical facts and stories from Bindel’s activism and working life. The book is written in Bindel’s characteristic style. She pulls no punches to get her points made.

Map Matching for the public transport network in Xalapa City / Map Matching para a rede de transportes públicos na Cidade de Xalapa

In Xalapa, Veracruz, Mexico, there was not a correct description of the more than 100 public transport bus routes that existed, for which a collective event was held to collect Global Positioning System locations. The trajectories obtained were not adjusted to the layout of the city's public road network, due to measurement errors caused by the variety of devices used for tracking. To recover the correct trajectories, a Map Matching algorithm was used based on the optimization of paths in graphs whose nodes belong to the public roads of the city. This work presents the description of the data collection methodology and the construction of the graphs for the implementation of the algorithm that finally recovered the real routes.

Численное дифференцирование в задачах фотограмметрического уравнивания

The author presents the results of studying numerical differentiation step influence in photogrammetric equalization tasks on the main characteristics of the resulting solution. A list of the main evaluated characteristics is presented and explanations of their role in the analysis of the photogrammetric equalization results are given. Using the example of several real routes of optical-electronic space survey, experimental calculations were performed, the purpose of which is to establish the dependence of the inverse photogrammetric serif’s main solution characteristics at the stage of numerical differentiation. The results of the equation calculations are analyzed and a conclusion is made on the instability of the estimated characteristics and not quite satisfactory outcome of equalization when assigning a step of numerical differentiation through known methods. A criterion for the optimality of the numerical differentiation step in photogrammetric equation tasks is proposed and an algorithm for calculating the step based on a new standard is developed. Its essence is explained and the graphical interpretation is given. Based on experimental calculations, the effectiveness of the developed criterion is confirmed.

Development of a New Method to Support a Participatory Planning for Piped Water Supply Infrastructure in Informal Settlements

For decades, infrastructure planning in informal settlements has been a major challenge for urban planners and engineers. In particular, the planning process for the rapidly changing heterogeneous structures in these areas usually require individual and non-sustainable solutions. In this report, a method for the sustainable and practical planning of a piped water distribution system (WDS) that generates different expansion variants as a planning support tool is presented. In this tool, all real-world routing options are included in the decision-making process, based on the existing infrastructure, settlement structure, and identifiable open spaces. Additionally, proposals for the localization of the future public water points are supported by methods from Logistics. The consideration of the existing settlement structure and real route lengths (pedestrian walking distance) to a potential water point location lead to very practical and realizable results. The principle of participatory planning was considered, to easily include individual adjustments at any given timeframe. At the same time, automated processes generate fast results. The method is modular and linked to a geographic information system (GIS) to directly visualize the impacts and effects of the planning and decision-making process.

Concept for Generating Energy Demand in Electric Vehicles with a Model Based Approach

Hybrid energy storage systems (HESS) for electric vehicles, which consist of lithium-ion batteries and supercapacitors, have become an increasing focus of research and development in recent years. The combination of the two combines the advantages of each storage technology (high energy density in batteries and high power density in supercapacitors) in one system. To effectively manage the energy flow between these two different storage technologies, an intelligent energy management system (EMS) is required. In the development of the EMS, it is usual to run preliminary checks in a simulation environment that is as close to reality as feasible already during the development process. For this purpose, this paper presents a concept for the creation of a simulation environment consisting of realistic routes and a holistic vehicle model. The realistic route data are generated by a route-generating algorithm, which accesses different map services via application programming interfaces (API) and retrieves real route data to generate a simulated route. By integrating further online services (e.g., OpenWeather API), the routes are further specified with, for example, real weather data, traffic data, speed limits and altitude data. For the complete vehicle model, components including the suspension, chassis and auxiliary consumers are simulated as blackbox models. The components that can be accessed during the simulation are simulated as white box models. These are the battery, the supercapacitor, the DC/DC converter and the electric motor. This allows the EMS to control and regulate the HESS in real time during the simulation. To validate the simulation environment presented here, a real BMW i3 was driven on a real route, and its energy demand was measured. The same route was simulated in the simulation environment with environmental conditions that were as realistic as feasible (traffic volume, traffic facilities, weather) and the vehicle model of the BMW i3. The resulting energy demand from the simulation was recorded. The results show that the simulated energy consumption value differs by only 1.92% from the real measured value. This demonstrates the accuracy of the simulation environment presented here.

Design of Cyber-Physical Waste Management Systems Focusing on Energy Efficiency and Sustainability

Industry 4.0 tools, such as the Internet of Things, artificial intelligence, digital twinning, and cloud computing, create a technological revolution that accelerates efforts to optimize the efficiency of cyber-physical operations and services. The waste management system requires a critical share of city logistics optimization, especially when using cyber-physical systems. Modern tools reduce the required municipal waste handling, such as loading and unloading, transportation, and warehousing, which leads to an increase in efficiency and flexibility, saving energy and time, and protecting the environment. In this paper, we present a cyber-physical waste management system solution by providing a cyber-physical model design and description, mathematical modeling, and two cases to investigate the impact on energy consumption and emissions. After an introduction and literature review, we describe the design of the cyber-physical model and tackle the first echelon. The designed system incorporates the IoT, smart bins with multi-percentage sensors, data and information analysis, vehicles’ actual routes, energy and emissions optimization, multi-echelon systems, time windows, and flexibility. Mathematical modeling equations for the optimized total energy consumption are presented. Thirty and twenty smart bins located in VIII District in Budapest are detailed as two case studies, where solutions for the optimized real routes and energy consumption are found using three metaheuristic algorithms: genetic, particle swarm, and simulated annealing optimization algorithms. The accrued emissions of CO, NMHC, CH4, NOx, and PM for the optimized solutions are calculated. Finally, the results are compared with a random traditional solution to measure the effectiveness.

Simulation-Based Comparative Assessment of a Multi-Speed Transmission for an E-Retrofitted Heavy-Duty Truck

Electric retrofitting (e-retrofitting) is a viable option for accelerating the renewal of heavy-duty vehicle fleets to reduce the related emissions. We introduce a simulation-based assessment of e-retrofitting strategies for heavy-duty vehicles. Our simulation tool, an electric vehicle fleet simulation toolbox, comprises three modules, namely driving cycles, vehicle dynamics, and vehicle profiles. The first allows for the creation of realistic driving cycles based on GPS data from real routes. The vehicle dynamics and vehicle profiles incorporate, e.g., the modelling of the powertrain and driving conditions. Ten realistic driving cycles were created and used for investigating and comparing three different powertrain alternatives, including the original diesel powertrain, electric with a single-speed transmission and electric with a multi-speed transmission. The vehicles were simulated in two different heavy-load scenarios. First, driving with a cargo load represented by the maximum vehicle weight and second, driving with snow ploughing. We found that the multi-speed transmission in an electric heavy-duty truck significantly improved its traction performance and gradeability. On the other hand, the effect on the electric powertrain efficiency, and thereby on the energy consumption, remained rather minor. Considering the given workload scenarios, our results advocate employing rather than omitting the gearbox in the e-retrofit truck process.

A Smart Information System for Passengers of Urban Transport Based on IoT

Several developed countries have implemented smart systems for public transport that provide mobility services for citizens. Most of these systems use special infrastructures to determine the location of citizens and public buses. However, the implementation of these systems does not take into account the poor infrastructure of developing countries. In Mexico, Urban Passenger Transport has insufficient transport units to meet the demand of passengers who move throughout the day, and these do not consider hardware infrastructure. Our solution is focused on inexpensive devices that are accessible to citizens, such as mobile phones. In this research work, a smart information system for passengers of urban transport is presented that allows passengers to know the expected arrival times and also to know the availability of seats on the bus that is heading towards their position. The solution was evaluated with real routes, and the results are promising for a pilot project to be put in practice.

Cardiac Autonomic Control and Neural Arousal as Indexes of Fatigue in Professional Bus Drivers

BackgroundBus driving is a mentally demanding activity that requires prolonged attention to ensure safety. The aim of the study was to assess mental fatigue caused by driving a public bus and to find a profile of workers at higher risk. MethodsWe evaluated changes of critical flicker fusion (CFF) (index of central arousal) and heart rate variability (HRV) (index of autonomic balance) in a 6-hour driving shift on a real route, in 31 professional bus drivers, and we tested the influence of personal factors such as sleep quality, BMI, and age. Paired t-test was used to test differences of CFF and HRV between both initial and final phase of driving, while multiple linear regression tested the influence of personal variables on the indexes of mental fatigue. ResultsResults showed that CFF significantly decreased after 6 hours of bus driving (41.91 Hz, sd 3.31 vs. 41.15 Hz, sd 3.15; p = 0.041), and heart rate significantly decreased in the final phase of driving, with respect to the initial phase (85 vs. 78 bpm, p = 0.027). Increasing age (beta = -0.729, p = 0.022), risk of obstructive sleep apnea syndrome (beta = -0.530, p = 0.04), and diurnal sleepiness (beta = -0.406, p = 0.017) showed a significant effect on influencing mental fatigue. ConclusionElderly drivers at higher risk of sleep disorders are more prone to mental fatigue, when exposed to driving activity. Monitoring indexes of central arousal and autonomic balance, coupled with the use of structured questionnaires can represent a useful strategy to detect profile of workers at higher risk of mental fatigue in such duty.