Efficient routing of snow removal vehicles

This research addresses the problem of finding a minimum cost set of routes for vehicles in a road network subject to some constraints. Extensions, such as multiple service requirements, and mixed networks have been considered. Variations of this problem exist in many practical applications such as snow removal, refuse collection, mail delivery, etc. An exact algorithm was developed using integer programming to solve small size problems. Since the problem is NP-hard, a heuristic algorithm needs to be developed. An algorithm was developed based on the Greedy Randomized Adaptive Search Procedure (GRASP) heuristic, in which each replication consists of applying a construction heuristic to find feasible and good quality solutions, followed by a local search heuristic. A simulated annealing heuristic was developed to improve the solutions obtained from the construction heuristic. The best overall solution was selected from the results of several replications. The heuristic was tested on four sets of problem instances (total of 115 instances) obtained from the literature. The simulated annealing heuristic was able to achieve average improvements of up to 26.36% over the construction results on these problem instances. The results obtained with the developed heuristic were compared to the results obtained with recent heuristics developed by other authors. The developed heuristic improved the best-known solution found by other authors on 18 of the 115 instances and matched the results on 89 of those instances. It worked specially better with larger problems. The average deviations to known lower bounds for all four datasets were found to range between 0.21 and 2.61%

GIS routing and modelling of residential waste collection for operational management and cost optimization

In this paper, optimum routing was developed based on the travel salesman method and integrated in ArcInfo GIS using linear programming. The results of the optimized travel distances and times for residential waste collection and routing to disposal site were used to calculate the number and type of required track collection, labour requirement, costing of waste collection and to determine the overall solid waste management efficiency through waste management operation research methods. The objective of the study was to optimize residential collection and hauling to disposal site through operation cost minimization for Petaling Jaya Municipality in the state of Selangor, Malaysia. The study determined that with optimized routes and recycling possibilities, the total cost of waste collections could be reduced from RM90,372 to RM20,967, with a reduction of 76.8%. It was also revealed that optimum routes might not necessarily be the shortest distance from point A to point B as travel time maybe high on short distances due to traffic congestion and the presence of many traffic lights. Techniques and methods developed using general GIS have proven effective in route optimization and allowed management of data to suit local conditions and limitations of waste management for the studied area. Thus, scenarios of travel distances, time and waste quantity value generated from the GIS enabled appropriate determination of the number of waste trucks and labour requirements for the operation and the overall calculation of costs of waste management based on the operation research methods used in the study

Optimized Planning and Management of Domiciliary and Selective Solid Waste: Results of Application in Brazilian Cities (SisRot^®Lix)

We show a new technology to manage solid waste services through optimization methods (on sectoring, routing costs, and resources). This technology is called optimized planning and integrated logistics management (OPILM). It is being applied to Brazilian municipalities as it attends to their major natural features. The technology is formed by a framework of computational systems that uses optimization methods from sector arc routing and scheduling, fleet and staff scheduling, using also mobile smartphone apps. We present some of the results of real cases evaluated for residential refuse collection and selective waste collection in two Brazilian cities (Petrópolis/RJ and Bom Jesus dos Perdões/SP). The plan implementations achieved 17.9% from actual fixed and variable cost savings for sectors (vehicles and workers) and routes (time and distances) for residential refuse collection in Petrópolis/RJ. For the selective waste collection, we detail how we made our project to Bom Jesus dos Perdões/SP. We also present the returns considering costs involved in the management of the operational level and amortized by the investment required to use and apply the proposed technology for Petrópolis/SP

An Investigation of Higher Capacity Urban Freight Vehicles

Studies have shown that increasing the capacity of Heavy Goods Vehicles is one of the most effective ways of reducing fuel consumption per tonne-kilometre of freight moved, with consequent reductions in greenhouse and noxious emissions. Some of the disadvantages of larger vehicles are more pronounced in urban environments, including safety of other road users, and reduced manoeuvrability. This thesis discusses technologies for improving safety of vulnerable road users, and frameworks for assessing the maximum size of urban freight vehicles. An overview of the freight industry is provided in Chapter 1, with a focus on maximising capacity as a method for reducing emissions. Chapter 2 focusses on the safety of vulnerable road users, through development of a camera-based detection system for cyclists, which is essential for a predictive collision avoidance system. The proposed system is accurate to within 10 cm at distances of greater than 1 m from the vehicle, but suffers from loss of accuracy at close range, and in poor lighting conditions. The logistics of urban freight operations are analysed in Chapter 3, including a comparison between two supermarket home delivery operations, and an analysis of refuse collection schedules. A framework is proposed for selecting an optimum vehicle size for a multi-drop operation, given reductions in driving distance and time spent on other procedures. A potential capacity increase of 80% is demonstrated, requiring a 50% reduction in driving distance, and automation of certain procedures. Chapters 4 to 6 propose a novel framework for assessing the optimum size of Heavy Goods Vehicles, according to the limits of their manoeuvrability. This method is based on simulation of vehicles attempting a library of real-world manoeuvres. Simulation models are described in Chapter 4, and path planning algorithms in Chapter 5. The framework is evaluated on three case studies: a 4.25 t grocery delivery vehicle, a 44 t articulated refuse collection vehicle, and a 44 t general urban vehicle with rear axle steering. A range of potential higher capacity vehicles are proposed in Chapter 6 for those applications The impact of rear axle steering on manoeuvrability is also considered in detail in Chapter 6. It is shown that the use of rear axle steering does not always allow the use of a longer vehicle, because a rear axle steered vehicle cannot compromise between cut-in and tailswing in the way a conventional vehicle can. However, the use of rear axle steering allows reduction in both tyre wear and rear axle load limits, which permits greater vehicle fill before rear axle loads are exceeded. These results are compared, in Chapter 7, to an alternative method for modelling manoeuvrability (Performance-Based Standards). Finally, Chapter 8 presents some concluding remarks and recommendations for future work, including investigation of an improved cyclist detection system fusing cameras and ultrasonic sensors, and increased development of the manoeuvrability models to more accurately reflect real driving.This work was supported by the EPSRC, as well as the Cambridge Vehicle Dynamics Consortium, and the Centre for Sustainable Road Freigh

Development and evaluation of cooperative intersection management algorithm under connected vehicles environment

Recent technological advancements in the automotive and transportation industry established a firm foundation for development and implementation of various automated and connected vehicle (C/AV) solutions around the globe. Wireless communication technologies such as the dedicated short-range communication (DSRC) protocol are enabling instantaneous information exchange between vehicles and infrastructure. Such information exchange produces tremendous benefits with the possibility to automate conventional traffic streams and enhance existing signal control strategies. While many promising studies in the area of signal control under connected vehicle (CV) environment have been introduced, they mainly offer solutions designed to operate a single isolated intersection or they require high technology penetration rates to operate in a safe and efficient manner. Applications designed to operate on a signalized corridor with imperfect market penetration rates of connected vehicle technology represent a bridge between conventional traffic control paradigm and fully automated corridors of the future. Assuming utilization of the connected vehicle environment and vehicle to infrastructure (V2I) technology, all vehicular and signal-related parameters are known and can be shared with the control agent to control automated vehicles while improving the mobility of the signalized corridor. This dissertation research introduces an intersection management strategy for a corridor with automated vehicles utilizing vehicular trajectory-driven optimization method. The Trajectory-driven Optimization for Automated Driving (TOAD) provides an optimal trajectory for automated vehicles while maintaining safe and uninterrupted movement of general traffic, consisting of regular unequipped vehicles. Signal status parameters such as cycle length and splits are continuously captured. At the same time, vehicles share their position information with the control agent. Both inputs are then used by the control algorithm to provide optimal trajectories for automated vehicles, resulting in the reduction of vehicle delay along the signalized corridor with fixed-time signal control. To determine the most efficient trajectory for automated vehicles, an evolutionary-based optimization is utilized. Influence of the prevailing traffic conditions is incorporated into a control algorithm using conventional data collection methods such as loop detectors, Bluetooth or Wi-Fi sensors to collect vehicle counts, travel time on corridor segments, and spot speed. Moreover, a short-term, artificial intelligence prediction model is developed to achieve reasonable deployment of data collection devices and provide accurate vehicle delay predictions producing realistic and highly-efficient longitudinal vehicle trajectories. The concept evaluation through microsimulation reveals significant mobility improvements compared to contemporary corridor management approach. The results for selected test-bed locations on signalized arterials in New Jersey reveals up to 19.5 % reduction in overall corridor travel time depending on different market penetration and lane configuration scenario. It is also discovered that operational scenarios with a possibility of utilizing reserved lanes for movement of automated vehicles further increases the effectiveness of the proposed algorithm. In addition, the proposed control algorithm is feasible under imperfect C/AV market penetrations showing mobility improvements even with low market penetration rates

Minimização do número de más viragens na recolha de resíduos sólidos urbanos

Mestrado em Matemática Aplicada à Economia e à GestãoO problema da determinação de percursos a efectuar por veículos afectos à remoção de resíduos sólidos urbanos pode ser visto como um problema de optimização de rotas, com procura nos arcos e restrições adicionais. Usualmente os algoritmos para determinar soluções admissíveis para este tipo de problemas não têm em conta o tipo de viragem que os veículos são obrigados a fazer. Dadas as características dos veículos envolvidos na recolha de resíduos, entende-se por má viragem uma inversão de marcha ou uma viragem à esquerda. Na prática é, em geral, exigida a minimização do número de más viragens, devendo mesmo algumas ser impossibilitadas, quer por se tornarem perigosas, quer por questões de regras de trânsito. Neste trabalho o problema da minimização do número de más viragens é definido e modelizado como um problema de redes. São desenvolvidos métodos para a determinação de soluções admissíveis. Os métodos implementados são testados num conjunto de problemas teste gerados aleatoriamente. Como se mostra, os resultados podem ser considerados bastante bons, dado permitirem obter soluções com um baixo número de más viragens sendo evitadas a quase totalidade das inversões de marcha proibidas. Muito embora a heurística se baseie na expansão da rede nos nodos onde as inversões de marcha não são permitidas, os resultados permitiram concluir que nem todos os nodos têm que ser expandidos para que as respectivas inversões de marcha sejam impossibilitadas.Finding the optimal set of tours for vehicles dedicated to household refuse collection can be looked at as an are routing problem with additional constraints. Typically, the algorithms used in determining feasible solutions to these problems do not account for the type of turn that the vehicles actually must perform. Given the specifíc characteristics of the vehicles assigned to household refuse collection, a bad-turn translates to a U-turn or to a left-turn. In practical terms it is generally mandatory to minimize the total number of bad-turns, some of which really must be avoided either due to its intrinsic danger or to traffic regulation restrictions. Throughout this thesis the problem of minimizing the number of bad-turns is defmed and modeled as a network problem. Some methods are developed to determine feasible solutions. These methods have been tested over a set of randomly generated problems. It is shown that the overall results are to be considered pretty good since they represent feasible solutions with a very low number of bad-turns, where nearly every forbidden U-turns are avoided.info:eu-repo/semantics/publishedVersio

Planning and control of AGVs in AMRF decision hierarchy

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1993.Thesis (Master's) -- Bilkent University, 1993.Includes bibliographical references leaves 90-94.Scheduling efforts made without considering the special limitations of the material handling system might lead to infeasible results. This problem especially becomes important when the Automated Guided Vehicles (AGV) are the main material handling media due to their inherent flexibility and adaptability that increase the scheduling complexity. In this thesis, an analytical model is proposed, first, to incorporate the AGV module into the overall decision making hierarchy. A mathematical formulation is developed to include interaction between the AGV module and other modules in the system by considering the restrictions of the material handling system. A micro-opportunistic approach is proposed to solve the AGV scheduling problem. Finally, the proposed method is compared with a number of dispatching rules.Yılmaz, HalukM.S

Environmental monitoring using a drone-enabled wireless sensor network

Water quality monitoring traditionally occurs via resource intensive field surveys, such as when a researcher manually collects data in a stream. Limiting factors such as time, money, and accessibility often result in less oversight of impaired water bodies, significantly threatening ecosystemic health and related ecosystem services. According to the United States Environmental Protection Agency, 84% of rivers and streams within the United States remain unassessed, resulting in significant lapses in available data. Such lapses prohibit efficient and effective monitoring, restoration, and conservation efforts throughout the United States. The objective of this project was to employ an unmanned aerial vehicle to remotely collect data regarding water quality from a wireless sensor network. The site under analysis was Boones Run, a tributary of the South Fork of the Shenandoah River near Elkton, Virginia. This project served as a proof-of-concept that communication with a wireless sensor node has the capability to be deployed to collect data in remote areas efficiently and effectively. This system would be useful in areas where accessibility is difficult, and transmission of data for processing is not readily available due to the lack of network connectivity. Initial analysis of environmental data gathered by hand indicated that surrounding land use had a significant impact on Boones Run water quality. This conclusion was reached given the trends seen in dissolved oxygen, water temperature, pH, and conductivity data from upstream to downstream over time. The completion of this project also lead to the successful data flow amongst all parts in the wireless sensor network. Three sensors soldered to a breadboard and connected to an Arduino Uno were able to gather data and send it to a Raspberry Pi 0. The Raspberry Pi 0 acted as a temporary storage device for the data before it was sent wirelessly to a Raspberry Pi 3 acting as an access point. The Raspberry Pi 3 device was mounted to an unmanned aerial vehicle so it could be flown over the node to decrease data collection time as well as adding the ability to collect data from places that are otherwise difficult for humans to access

Land pollution and population density : the case of Kwekwe City residential areas, Zimbabwe

In most developing countries, the problem of inefficient municipal solid waste management (MSWM) is endemic. The problem is manifested by heaps of uncollected solid waste found on open areas and by the street sides. This dissertation examines the relationship between land pollution and population density resulting from solid waste generation in the City of Kwekwe in Zimbabwe. Questionnaires and interviews were conducted to 375 randomly selected households in low, medium and high density residential suburbs. The household survey was triangulated with field observations, key informant interviews and secondary data sources. The average household size in high, medium and low density residential areas was 11, 8 and 5 people respectively. The study revealed that the amount and composition of solid waste generated varied according to household size, income and education levels of residents. The higher the population density, the more the solid waste produced. However, waste generated was not carried to the dumpsites for disposal. Also the higher the income, the higher the amount of solid waste produced, although residents with high income were able to ferry their wastes to the dumpsites hence less land pollution. The solid waste generation rate in high density areas was 0.04 kg/capita day, in medium density areas was 0.35 kg/capita/day and in low density areas were 0.84 kg/capita/day. It was also observed that among high income earners, the educated people produced more waste than low income earners. However, the low income earners and the less educated people could not take care of their environment to limit roadside and open space littering. However, lack of public awareness coupled with inefficient and ad hoc waste management system continue make provision of effective solid waste management services illusive. Based on the research findings, it is suggested sound environmental stewardship amongst residents will limit land pollution in the city of Kwekwe.Environmental SciencesM.A. (Environmental Management

Disparities in the distribution of municipal services

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering; and, (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1971.Bibliography: leaves 148-151.by Robert Marlay.M.C.P.M.S