Intelligent Safety Transport Framework for Schools: A Review of Route Planning and Tracking Systems

This work presents a review of recent literature in intelligent school transportation frameworks, particularly focusing on route planning, real time vehicle and children tracking. The focus on route planning and tracking is to identify the hidden practical problems and threats present in school transportation, bearing in mind safety. Different methods and technologies used for route planning and vehicle as well as children tracking are reviewed. A discussion is provided on the current frameworks along with the challenges and future research direction

CHIP NUMBER VEHICLE APPLICATIONS AS PART OF INTERNET OF THINGS (IoT)

Currently the number of motor vehicles is increasing in Indonesia. Based on BPS data 2014 Number of motor vehicles in 2014 as many as 114,209,266 vehicles consisting of passenger cars 12,599,138 units, 2,398,846 units of bus, car goods 6,235,136 units and the most dominant motorcycle 92,976,240 units. The city of Jakarta as the capital of the Republic of Indonesia in 2015 the number of motor vehicles as many as 17,523,967 units dominated by two-wheeled vehicles with the amount of 13,084,372 units. It was followed by private cars with 3,226,009 units, 673,661 units of freight cars, 362,066 units of buses and 137,859 units of special vehicles, while the road growth was only 0.01 percent so it was not comparable with the number of vehicles. One way to break down congestion in Jakarta is the reduction in the number of motor vehicles such as three in one for four-wheeled vehicles, the implementation of electronic road pricing (ERP), and the reduction in the number of motorcycles. The reduction in the number of motorcycles aims to reduce traffic density while reducing the number of traffic accidents. Guntoro Barovih, [1], The level of traffic accidents each year is increasing. This is due to the lack of awareness, discipline, tolerance and emotional high riders who have an impact on motorist negligence. Police korlantas data in zebra operations in 2015 there was a 5% increase or approximately 684,973 letters of infringement cases compared to 2014. In addition, another problem is the crime of motor vehicle theft. This is not independent of the behavior of vehicle users in driving a motor vehicle [2]. This accident or crime handling solution can be done in a way to control the number of vehicles in an integrated manner. The Internet Of Things (IoT) can be used as a vehicle detection control tool through the use of number plate chip

The school bus routing problem: An analysis and algorithm

In this paper we analyse a flexible real world-based model for designing school bus transit systems and note a number of parallels between this and other well-known combinatorial optimisation problems including the vehicle routing problem, the set covering problem, and one-dimensional bin packing. We then describe an iterated local search algorithm for this problem and demonstrate the sort of solutions that we can expect with different types of problem instance

An estimation of distribution algorithm for combinatorial optimization problems

This paper considers solving more than one combinatorial problem considered some of the most difficult to solve in the combinatorial optimization field, such as the job shop scheduling problem (JSSP), the vehicle routing problem with time windows (VRPTW), and the quay crane scheduling problem (QCSP). A hybrid metaheuristic algorithm that integrates the Mallows model and the Moth-flame algorithm solves these problems. Through an exponential function, the Mallows model emulates the solution space distribution for the problems; meanwhile, the Moth-flame algorithm is in charge of determining how to produce the offspring by a geometric function that helps identify the new solutions. The proposed metaheuristic, called HEDAMMF (Hybrid Estimation of Distribution Algorithm with Mallows model and Moth-Flame algorithm), improves the performance of recent algorithms. Although knowing the algebra of permutations is required to understand the proposed metaheuristic, utilizing the HEDAMMF is justified because certain problems are fixed differently under different circumstances. These problems do not share the same objective function (fitness) and/or the same constraints. Therefore, it is not possible to use a single model problem. The aforementioned approach is able to outperform recent algorithms under different metrics for these three combinatorial problems. Finally, it is possible to conclude that the hybrid metaheuristics have a better performance, or equal in effectiveness than recent algorithms

Asignación de estudiantes a establecimientos educativos: un enfoque multi-objetivo

En este trabajo se aborda el problema de Asignación de Estudiantes a Establecimientos Educativos (AEEE). Dicha problemática afecta la logística del sistema educativo, ya que se ve influenciada por variantes como: disponibilidad, distancia, infraestructura, entre otros. Se propone una nueva formulación matemática al problema de AEEE con un enfoque multi-objetivo para: (1) minimizar la diferencia entre la cantidad de estudiantes asignados y la cantidad óptima de estudiantes por clase, (2) minimizar la distancia promedio entre la vivienda del estudiante y el establecimiento y (3) maximizar la utilización de establecimientos con mejor infraestructura. Para resolver la formulación propuesta se plantea un Algoritmo Evolutivo Multi-Objetivo (MOEA) basado en el NSGA-II. Para la validación de esta propuesta se consideraron los datos provistos por el Ministerio de Educación y Ciencias del Paraguay (MEC) correspondientes a Ciudad del Este - Alto Paraná, del primer al tercer grado, de 90 establecimientos y 15.763 estudiantes, los resultados arrojan mejoras significativas en la cantidad de alumnos asignados por clases.XXI Workshop Tecnología Informática aplicada en Educación (WTIAE)Red de Universidades con Carreras en Informátic

OPTIMIZATION MODEL FOR SCHOOL TRANSPORTATION DESIGN BASED ON ECONOMIC AND SOCIAL EFFICIENCY

[EN] The purpose of this paper is to design a model that allows to suggest new planning proposals on school transport, so that greater efficiency operational will be achieved. It is a multiobjective optimization problem including the minimization of the cost of busing and minimizes the total travel time of all students. The foundation of the model is the planning routes made by bus due to changes in the starting time in schools, so the buses are able to perform more than one route. The methodology is based on the School Bus Routing Problem, so that routes from different schools within a given time window are connected, and within the restrictions of the problem, the system costs are minimized. The proposed model is programmed to be applied in any generic case. This is a multi-objective problem, in which there will be several possible solutions, depending on the weight to be assigned to each of the variables involved, economic point of view versus social point of view. Therefore, the proposed model is helpful for policy planning school transportation, supporting the decision making under conditions of economic and social efficiency. The model has been applied in some schools located in an area of Cantabria (Spain), resulting in 71 possible optimal options that minimize the cost of school transport between 2,7% and 35,1% regarding to the current routes of school transport, with different school start time and minimum travel time for students.Ezquerro Eguizábal, S.; Moura Berodia, JL.; Ibeas Portilla, A.; Benavente Ponce, J. (2016). OPTIMIZATION MODEL FOR SCHOOL TRANSPORTATION DESIGN BASED ON ECONOMIC AND SOCIAL EFFICIENCY. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 926-944. https://doi.org/10.4995/CIT2016.2015.4074OCS92694

Optimizing Bus Stop Environments: Analysis of Sun Glare Reduction with Green Elements in MLS and GPR Data

Urban transportation is pivotal in facilitating citizen mobility, and within this sphere, the thermal comfort experienced at bus stops significantly impacts pedestrians' well-being. This research delves into the analysis of direct sun glare at bus stops utilizing Mobile Laser Scanning (MLS) point clouds. Solar angles are calculated to evaluate sun rays, focusing particularly on the summer solstice, and considering the integration of trees to alleviate direct sun glare. The methodological approach comprises four stages: 1) Semantic segmentation of the bus stop environment, 2) Sun glare analysis, 3) Sun glare analysis integrating trees, and 4) Subsoil investigation with Ground-Penetrating Radar (GPR). Various algorithms, including DBSCAN and filters for height, width, and intensity, are employed to classify different elements contained in the bus stop. Sun rays are then derived based on sun angles, identifying intersections with street elements and vertical structures like bus stops or facades. Subsequently, these intersections are recalculated, incorporating trees in the bus stop vicinity. Finally, GPR is utilized to assess the viability of adding trees. Three bus stops in Vigo, Spain, serve as the focal points of analysis. The study delineates specific time intervals when sun rays either encounter new vegetation obstacles or remain unobstructed. While both small and large trees show potential in reducing sun glare, larger trees notably exhibit greater effectiveness in blocking sun glare for extended periods

Ruteo de buses escolares con consideraciones ambientales mediante Búsqueda Tabú Granular1

En el contexto actual es importante que el ruteo de buses escolares (SBRP) además de la eficiencia aborde también las dimensiones social y ambiental, para garantizar soluciones sostenibles. La dimensión ambiental ha sido abordada ampliamente en el VRP, sin embargo, el SBRP no ha contado con la misma suerte, a pesar de que existen estudios sobre la relación entre los problemas ambientales en el trasporte escolar y salud de los niños, no obstante, no se encuentran trabajos que aborden la dimensión ambiental en el ruteo de buses escolares, en tal sentido este artículo aborda el SBRP con consideraciones ambientales. Se formula un modelo matemático que minimiza el consumo de combustible, que se calcula en función de la distancia recorrida, el peso de los vehículos y el de los estudiantes. El modelo es resuelto de manera óptima para instancias pequeñas, y para instancias de mayor tamaño se emplea un algoritmo basado en Búsqueda Tabú Granular. La solución inicial es generada por el algoritmo de ahorros. Se evalúa el rendimiento del algoritmo comparando los tiempos y valores de función objetivo con respecto al método exacto, la meta heurística generó soluciones 99,96% en promedio más rápido que el método exacto y generó soluciones con valor de función objetivo alejado en promedio 13,98% de las del método exacto. En este trabajo se hace una extensión al SBRP, adicionando la dimensión ambiental, aproximado el consumo de combustible en función de la distancia y el peso