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

A Partial Allocation Local Search Matheuristic for Solving the School Bus Routing Problem with Bus Stop Selection

This paper addresses the school bus routing problem with bus stop selection, which jointly handles the problems of determining the set of bus stops to visit, allocating each student to one of these bus stops and computing the routes that visit the selected bus stops, so that the total routing cost is minimized and the walking distance of the students is limited by a given value. A fast and efficient matheuristic is developed based on an innovative approach that first partially allocates the students to a set of active stops that they can reach, and computes a set of routes that minimizes the routing cost. Then, a refining process is performed to complete the allocation and to adapt the routes until a feasible solution is obtained. The algorithm is tested on a set of benchmark instances. The computational results show the efficiency of the algorithm in terms of the quality of the solutions yielded and the computing time

A Branch-Price-and-Cut Algorithm for the Capacitated Multiple Vehicle Traveling Purchaser Problem with Unitary Demand

The multiple vehicle traveling purchaser problem (MVTPP) consists of simultaneously selecting suppliers and routing a fleet of homogeneous vehicles to purchase different products at the selected suppliers so that all product demands are fulfilled and traveling and purchasing costs are minimized. We consider variants of the MVTPP in which the capacity of the vehicles can become binding and the demand for each product is one unit. Corresponding solution algorithms from the literature are either branch-and-cut or branch-and-price algorithms, where in the latter case the route-generation subproblem is solved on an expanded graph by applying standard dynamic-programming techniques. Our branch-price-and-cut algorithm employs a novel labeling algorithm that works directly on the original network and postpones the purchasing decisions until the route has been completely defined. Moreover, we define a new branching rule generally applicable in case of unitary product demands, introduce a new family of valid inequalities to apply when suppliers can be visited at most once, and show how product incompatibilities can be handled without considering additional resources in the pricing problem. In comprehensive computational experiments with standard benchmark sets we prove that the new branch-price-and-cut approach is highly competitive

A Metaheuristic Solution for the School Bus Routing Problem with Homogeneous Fleet and Bus Stop Selection

Context: Optimization problems allow representing real-life situations, and, with the right method, a good solution to a problem can be reached. Conceptually, the problem under study is known as the School Bus Routing Problem. This work can be taken as a starting point for the creation of tools for this problem. Method: In this work, a mathematical model based on the literature was designed and implemented, and it was adapted to be solved using metaheuristics. Three mutation operators and a selection mechanism based on weights were implemented according to the improvements that each of them offered to the solution. To evaluate the results, a statistical comparison was made with another solution in the literature based on the evaluation of 112 instances of the problem. Results: In the solution of the 112 instances of the problem, the following algorithms were used: the Tabu Search, Hill Climbing variants, Simulated Annealing, and an algorithm portfolio that includes the previous ones. The results showed that the best behavior was obtained by the portfolio, with results comparable to those in the literature. However, as the number of instances grows, the results tend to get worse. Conclusions: With this research, it was possible to obtain a model that represents the initial problem, as well as two algorithms for finding solutions by means of metaheuristics. According to the results obtained, future work should be directed towards new ways of building the initial solution and the implementation of new assignment operators.Contexto: Los problemas de optimización permiten representar situaciones de la vida real, y con un método apropiado se puede llegar a una buena solución del problema. Conceptualmente, el problema bajo estudio se conoce como problema de planificación de ruta de autobuses escolares. El presente trabajo puede ser tomado como punto de partida para la creación de herramientas para este problema. Método: En este trabajo se diseñó e implementó un modelo matemático del problema basado en la literatura y se adaptó para su solución usando algoritmos metaheurísticos. Se implementaron tres operadores de mutación y un mecanismo de selección basado en pesos, según las mejoras que brindaba cada uno a la solución. Para evaluar los resultados, se realizó una comparación estadística con otra solución de la literatura a partir de la evaluación de 112 instancias del problema. Resultados: En la solución de las 112 instancias del problema se utilizaron los siguientes algoritmos: búsqueda tabú, variantes del escalador de colinas, recocido simulado y un portafolio de algoritmos que incluye a los anteriores. Los resultados reflejaron que el mejor comportamiento lo obtuvo el portafolio con resultados comparables a los de la literatura. Sin embargo, a medida que crece el número de instancias, los resultados tienden a empeorar. Conclusiones: Con esta investigación se obtuvo un modelo que permite representar el problema inicial, así como dos algoritmos para la búsqueda de soluciones utilizando metaheurísticas. Según los resultados obtenidos, los trabajos futuros deben encaminarse hacia nuevas formas de construcción de la solución inicial y la implementación de nuevos operadores de asignación y mutación

A heuristic algorithm for finding cost-effective solutions to real-world school bus routing problems

This paper proposes a heuristic algorithm for designing real-world school transport schedules. It extends previously considered problem models by considering some important but hitherto overlooked features including the splitting and merging of routes, gauging vehicle dwell times, the selection of stopping points, and the minimisation of walking distances. We show that this formulation contains a number of interacting combinatorial subproblems including the time-constrained vehicle routing problem, set covering, and bin packing. As a result, a number of new and necessary algorithmic operators are proposed for this problem which are then used alongside other recognised heuristics. Primarily, the aim of this algorithm is to minimise the number of vehicles used by each school, though secondary issues concerning journey lengths and walking distances are also considered through the employment of suitable multiobjective technique

Solving school bus routing and student assignment problems with heuristic and column generation approach.

In this dissertation, we solve a school bus routing problem of transporting students including special education (handicapped) students and assigning them in Oldham county education district. The main contribution of this research is that we consider special education students (Type-2) along with other students (Type-1) and design a comprehensive school bus schedule to transport both kinds of students at the same time. Also, a student assignment mathematical model is presented to optimize the number of bus stops in use as well as one important measure of service quality, the total student walking distance. Comparing to the classic clustering methods, heuristic methods, or other methods from previous literatures, a mathematical optimization model is developed to solve a student assignment problem and to obtain the global optimal solution. The modeling constraints include budget limit, travel time limit, equity, school time window, and etc. Especially, the main difference between our model and other models is that it takes Type-2 students into consideration along with critical constraints accordingly, and solves the resulting more complex problem. Moreover, the school bus routing model in this work is one of the most general optimization models representing the school bus routing problem. On the other hand, similar to all existing models, the developed model considers the total system cost as the objective function value to minimize, different bus capacities, and common vehicle routing constraints such as flow conservation on routes and subtour elimination. Furthermore, another main difference is that the bus scheduling and school time window is also considered and solved in the model. With two different types of students, both Type-1 and Type-2, the time restrictions are varying, resulting in more complexity and additional constraints. The results in this work present the difficulties of meeting the requirement of Type-2 student riding time limit and school time window simultaneously. Also, the constraints regarding service equity and quality are provided and they can be used by decision makers if necessary. Either densely populated urban areas or sparsely populated rural areas, the school bus routing problem is difficult to solve due to a large number of students or long travel distance. The school bus routing problem falls under vehicle routing problem (VRP) with additional requirements because each student represents one unit of capacity. In this dissertation, we present a modeling framework that solves a student assignment problem with bus stop selection, and subsequently a school bus routing problem with school time window constraints. We demonstrate the efficacy of heuristic methods as well as a column generation technique implemented to solve the problems using real data

A safety transport framework for hired coaches for school transport.

Safety in school transport is a critical issue which involves children who are the most vulnerable users of it. On an average 973 trips are made per person in a year, out of which 105 are on school runs. In the United Kingdom (UK) alone, 1218 children were injured in 381 coach crashes between 2005 and 2016. Driver errors or technical faults in vehicles were the most commonly reported contributory factors for coach accidents. Coaches are considered as the safest mode of transport for children, but coach accidents result in a high number of fatalities per accident as coaches carry more children compared to any other means of school transport. There are more than 24000 schools in England alone and each school makes at least two field trips per year, which is equivalent to 48000+ trips. Schools in the UK rely on coach operators to provide vehicles for short and long school trips. In the UK there are strict regulations on operator’s compliance with the government safety regulations. In last year alone, 78 coach operators’ licenses have been revoked without public inquiries in the UK due to operator’s non-compliance. Though the government has strict safety regulations, accidents are still happening. Most of the existing literature has focused on economical and shortest routes to transport children, but they do not consider the safety aspects of the coach operators, coaches and the drivers in terms of compliance with the government safety regulations. Proper selection of coach operator, coach and driver can considerably mitigate safety risks for school transport. Only limited studies have examined safety of children travelling by coaches in the UK. This research involves a thorough analysis of the existing literature, national accident statistics, government policies, and traffic commissioner’s report. Two surveys were conducted with stakeholders (parents, school headmasters, coach operators, coach drivers, council transport officers and road safety analysts) to identify safety-related issues and the requirements of stakeholders in coach-based school transport in the UK. The analysis of the outcome shows that there are significant safety issues exist and there is a requirement for a safety transport framework to support users of hired private coaches in the UK to transport schoolchildren. A novel safety transport framework for hired coaches is proposed to address the identified safety issues. The framework validates coach operators, their coaches and drives using safety scores, based on their track record. This information can be shared with the school headmasters and parents before booking coaches. The framework also provides recommendations to coach operators to improve their fleet safety. The framework is prototyped, and both the framework and the prototype were evaluated within the UK. The evaluation shows that the framework has achieved its intended objectives and received positive feedback from the stakeholders