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Relevant bibliographies by topics / Public Transit Routing

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Journal articles
Dissertations / Theses
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Academic literature on the topic 'Public Transit Routing'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Public Transit Routing"

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Delling, Daniel, Thomas Pajor, and Renato F. Werneck. "Round-Based Public Transit Routing." Transportation Science 49, no. 3 (August 2015): 591–604. http://dx.doi.org/10.1287/trsc.2014.0534.

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Uchimura, Keiichi, Hiro Takahashi, and Takashi Saitoh. "Advanced Public Transit System Routing and Scheduling." IFAC Proceedings Volumes 30, no. 8 (June 1997): 753–58. http://dx.doi.org/10.1016/s1474-6670(17)43912-7.

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Delling, Daniel, Thomas Pajor, and Renato Werneck. "Round-Based Public Transit Routing (Extended Abstract)." Proceedings of the International Symposium on Combinatorial Search 4, no. 1 (August 20, 2021): 213. http://dx.doi.org/10.1609/socs.v4i1.18270.

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We study the problem of computing all Pareto-optimal journeys in a dynamic public transit network for two criteria: arrival time and number of transfers. Existing algorithms consider this as a graph problem, and solve it using variants of Dijkstra's algorithm. Unfortunately, this leads to either high query times or suboptimal solutions. We take a different approach. We introduce RAPTOR, our novel round-based public transit router. Unlike previous algorithms, it is not Dijkstra-based, looks at each route (such as a bus line) in the network at most once per round, and can be made even faster with simple pruning rules and parallelization using multiple cores. Because it does not rely on preprocessing, RAPTOR works in fully dynamic scenarios. Moreover, it can be easily extended to handle flexible departure times or arbitrary additional criteria, such as fare zones. When run on London's complex public transportation network, RAPTOR computes all Pareto-optimal journeys between two random locations an order of magnitude faster than previous approaches, which easily enables interactive applications. This is an extended abstract of the paper published at ALENEX 2012.

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Jeon, I., H. Nam, and C. Jun. "IMPROVED PUBLIC TRANSIT ROUTING ALGORITHM FOR FINDING THE SHORTEST K-PATH." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W9 (October 30, 2018): 255–64. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w9-255-2018.

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<p><strong>Abstract.</strong> Most of the existing public transit routing algorithms were developed on the basis of graph theory. Recently, algorithms are being developed that can compute for O-D public transit paths by using timetable information only, not using network structure consisting of nodes and links. The timetable-based public transit routing algorithm produces one shortest path to destination, using departure time and arrival time by stop. But it has limitations in reflecting additional factors, such as transfer penalty and alternative path selection, in the process of path calculation. In addition, since public transit passengers tend to choose one among various alternative paths, it is necessary to calculate multiple paths rather than a single path as in the existing methods. Therefore, this study proposes an improved RAPTOR algorithm that can consider transfer penalty and produce multiple paths, while it is based on RAPTOR, the existing timetable-based public transit routing algorithm. The transfer penalty was applied at the point of transfer, and differently according to transfer types. As a result of analyzing computed paths of the algorithms before and after improvement, it was found that computed paths with the improved RAPTOR algorithm proposed by this study were more similar to Seoul public transit passengers' actual travel paths than computed paths by the existing RAPTOR alone.</p>

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Rouhieh, Behzad, and Ciprian Alecsandru. "Adaptive route choice model for public transit systems: an application of Markov decision processes." Canadian Journal of Civil Engineering 39, no. 8 (August 2012): 915–24. http://dx.doi.org/10.1139/l2012-080.

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Over the past couple of decades the advancements in the areas of information and computational technology allowed for a variety of intelligent transportation systems developments and deployments. This study investigates an advanced traveler information system (ATIS) and (or) an advanced public transit system (APTS) adaptive and real-time transit routing component. The proposed methodology is applied to bus routes with fixed, predefined bus line alignments. It is shown that routing buses on such systems can be modeled in real-time by employing an associated Markov chain with reward model to minimize the impact of congested traffic conditions on the travelers and the overall operation cost of the transit system. A case study using a traffic and transit data from a real-world bus line was used to apply the proposed bus routing approach. It was found that under certain traffic congestion conditions buses should be re-routed to minimize their travel time and the associated system costs. The hypothetical congestion scenarios investigated show that individual bus travel time delays range between 50 and 740 s when the proposed adaptive routing is employed. The proposed methodology is also suitable for application to transit systems that run on a demand-adaptive basis (the bus line alignment changes with the travelers demand). Additional calibration and future integration of the system into specific ATIS and (or) APTS user services will be investigated.

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Mrad, Mehdi, Olfa Chebbi, Mohamed Labidi, and Mohamed Ali Louly. "Synchronous Routing for Personal Rapid Transit Pods." Journal of Applied Mathematics 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/623849.

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Personal rapid transit (PRT) is a public and automated transport system in which a fleet of small driverless vehicles operate in order to transport passengers between a set of stations through a network of guided ways. Each customer is carried from one station to another directly with no stop in intermediate stations. This mode of transport can result in a high level of unused capacity due to the empty moves of the vehicles. In this paper, we model the problem of minimizing the energy consumed by the PRT system while assuming predeterministic list of orders; then we solve it using some constructive heuristics. Experiments are run on 1320 randomly generated test problems with various sizes. Our algorithms are shown to give good results over large trip instances.

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Rios, Miguel. "GeOpps-N: Opportunistic Routing for VANET in a Public Transit System." IEEE Latin America Transactions 14, no. 4 (April 2016): 1630–37. http://dx.doi.org/10.1109/tla.2016.7483493.

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Choudhury, Shushman, Kiril Solovey, Mykel J. Kochenderfer, and Marco Pavone. "Efficient Large-Scale Multi-Drone Delivery using Transit Networks." Journal of Artificial Intelligence Research 70 (February 17, 2021): 757–88. http://dx.doi.org/10.1613/jair.1.12450.

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We consider the problem of routing a large fleet of drones to deliver packages simultaneously across broad urban areas. Besides flying directly, drones can use public transit vehicles such as buses and trams as temporary modes of transportation to conserve energy. Adding this capability to our formulation augments effective drone travel range and the space of possible deliveries but also increases problem input size due to the large transit networks. We present a comprehensive algorithmic framework that strives to minimize the maximum time to complete any delivery and addresses the multifaceted computational challenges of our problem through a two-layer approach. First, the upper layer assigns drones to package delivery sequences with an approximately optimal polynomial time allocation algorithm. Then, the lower layer executes the allocation by periodically routing the fleet over the transit network, using efficient, bounded suboptimal multi-agent pathfinding techniques tailored to our setting. We demonstrate the efficiency of our approach on simulations with up to 200 drones, 5000 packages, and transit networks with up to 8000 stops in San Francisco and the Washington DC Metropolitan Area. Our framework computes solutions for most settings within a few seconds on commodity hardware and enables drones to extend their effective range by a factor of nearly four using transit.

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Zhang, Cai Xia, Liang Liang Zhuang, Xiang Dong Wang, and Hai Wu Rong. "Research on Optimal Routing Algorithm for Public Transit Transfer Based on the Adjacency Matrix." Applied Mechanics and Materials 40-41 (November 2010): 341–46. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.341.

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This paper introduces the Adjacency Matrix at the very beginning, the least transfer between two nodes can be obtained by using the Adjacency Matrix, and then Z matrix is introduced to achieve optimal routing algorithm for public transit transfer and to obtain optimal route by using the “two-step-descending-proliferation” algorithm. Through the "two-step" approach, efficiency and feasibility of data processing was increased. The algorithm focus on multi-objective optimization - takes the least transfer, the least cost, the shortest time, and so on.

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Nadeem, Imran, Sheik Uduman, and Aijaz Dar. "An integrated bus - based routing and dispatching approach for flood evacuation." Yugoslav Journal of Operations Research 30, no. 4 (2020): 443–60. http://dx.doi.org/10.2298/yjor190415028n.

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Floods are among the most persistent natural disasters that lead to massive economic and human loss globally. In this regard, this study has proposed an optimisation model for evacuating people before the occurrence of the flood using bus transit. The process of evacuation commences with the issue of warning and extends up to a certain time before the flood forecasts to strike. This model provides an optimised framework for 1) Locating pickup points and shelters, 2) Assigning pickup points to the nearest shelter by opting the shortest route among the available routes. On the basis of demand, each pickup point is allocated with a certain number of trips. The modelling of dispatch sequence of public buses, random adventing of evacuees at pickup points and evacuees transit to the shelters are presented by developing a simulation tool. The results of simulation serve for assessing the route design and then, a local search heuristic is suggested to improve the route design during the evacuation.

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Dissertations / Theses on the topic "Public Transit Routing"

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Moyo, Oliveros Manuel [Verfasser], Kai [Akademischer Betreuer] Nagel, and Thomas [Akademischer Betreuer] Richter. "Calibration of public transit routing for multi-agent simulation / Manuel Moyo Oliveros. Gutachter: Thomas Richter. Betreuer: Kai Nagel." Berlin : Technische Universität Berlin, 2014. http://d-nb.info/1066161852/34.

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Vieira, Alexandre Barra. "Roteirização de ônibus urbano: escolha de um método para as grandes cidades brasileiras." Universidade de São Paulo, 1999. http://www.teses.usp.br/teses/disponiveis/18/18137/tde-30102003-194827/.

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O ônibus é o principal modo de transporte público de passageiros das grandes cidades brasileiras. Ultimamente as redes de transporte público vêm sofrendo modificações estruturais importantes, visando sua melhoria. Esta Dissertação descreve a pesquisa de mestrado que teve como objetivo o estudo de métodos racionais de Roteirização de Ônibus Urbano para a escolha de um método adequado à aplicação nas grandes cidades brasileiras. A revisão bibliográfica dá mais ênfase aos métodos que atendem a esse objetivo e que possibilitam sua aplicação imediata com ou sem modificação. Para se conhecer as diferenças locais em termos de planejamento dos itinerários nas maiores capitais brasileiras, apresenta-se um levantamento feito junto a 11 (onze) órgãos gestores. Comparam-se os procedimentos adotados no Brasil com os adotados nos Estados Unidos e Canadá e escolhe-se o melhor método com base em critérios existentes na literatura. O objetivo principal foi alcançado: o método indicado pode ser aplicado, com algumas modificações concernentes principalmente à coleta de dados. Espera-se que esta pesquisa contribua para a divulgação das técnicas de roteirização baseadas em modelos matemáticos de modo a auxiliar o especialista: (a) na alteração e/ou concepção das rotas (b) na completa reformulação de complexos sistemas de transporte público.
Bus transit is the main urban public transportation mode available in large-size Brazilian cities. Brazilian transit networks have held important structural modifications lately, seeking their improvement. This dissertation describes a masters research that had as the main objective the study of rational bus transit routing methods. The goal is to choose the best of these methods for application in large-size Brazilian cities. The literature review focused on methods which are addressed to this objective, and that could be used with or without changes for this purpose. A total of 11 (eleven) transit agencies answered a national survey made to identify local differences in the planning techniques used in the largest Brazilian capitals. Procedures adopted in Brazil were compared with the ones applied in the United States and in Canada and one method was then chosen, taken into account evaluation criteria found in the literature. The main objective of this research was reached: the method selected can be applied with some minor modifications concerning mainly the data collection procedure. This research shall contribute for the popularization of mathematical models as routing techniques that could help planners: (a) to design a new bus route and/or to redesign an existing one (b) to completely redesign complex transit systems.

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Beduhn, Tyler James. "Reliable routing in schedule-based transit networks." Thesis, 2014. http://hdl.handle.net/2152/28096.

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A framework is proposed for determining the least expected cost path in a schedule-based time-expanded public transit network where travel times, and thus bus arrival and departure times at stops, are stochastic. Transfer reliability is incorporated in a label-correcting algorithm with a penalty function for the expected waiting time when transferring that reflects the likelihood of making a successful transfer. The algorithm is implemented in transit assignment on an Austin, Texas test network, using actual bus arrival and departure time distributions from vehicle location data. Assignment results are compared with those of a deterministic shortest path based on the schedule and from a calibrated transit assignment model. Simulations of the network and passenger paths are also conducted to evaluate the overall path reliability. The reliable shortest path algorithm is found to penalize transferring and provide paths with improved transfer and overall reliability. The proposed model is realistic, incorporating reliability measures from vehicle location data, and practical, given the efficient shortest path approach and application to transit assignment.
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"Data organization for routing on the multi-modal public transportation system: a GIS-T prototype of Hong Kong Island." 2001. http://library.cuhk.edu.hk/record=b5890808.

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Yu Hongbo.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references (leaves 130-138).
Abstracts in English and Chinese.
ABSTRACT IN ENGLISH --- p.i-ii
ABSTRACT IN CHINESE --- p.iii
ACKNOWLEDGEMENTS --- p.iv-v
TABLE OF CONTENTS --- p.vi-viii
LIST OF TABLES --- p.ix
LIST OF FIGURES --- p.x-xi
Chapter CHAPTER I --- INTRODUCTION
Chapter 1.1 --- Problem Statement --- p.1
Chapter 1.2 --- Research Purpose --- p.5
Chapter 1.3 --- Significance --- p.7
Chapter 1.4 --- Methodology --- p.8
Chapter 1.5 --- Outline of the Thesis --- p.9
Chapter CHAPTER II --- LITERATURE REVIEW
Chapter 2.1 --- Introduction --- p.12
Chapter 2.2 --- Origin of GIS --- p.12
Chapter 2.3 --- Development of GIS-T --- p.15
Chapter 2.4 --- Capabilities of GIS-T --- p.18
Chapter 2.5 --- Structure of a GIS-T --- p.19
Chapter 2.5.1 --- Data Models for GIS-T --- p.19
Chapter 2.5.2 --- Relational DBMS and Dueker-Butler's Data Model for Transportation --- p.22
Chapter 2.5.3 --- Objected-oriented Approach --- p.25
Chapter 2.6 --- Main Techniques of GIS-T --- p.26
Chapter 2.6.1 --- Linear Location Reference System --- p.26
Chapter 2.6.2 --- Dynamic Segmentation --- p.27
Chapter 2.6.3 --- Planar and Non-planar Networks --- p.28
Chapter 2.6.4 --- Turn-table --- p.28
Chapter 2.7 --- Algorithms for Finding Shortest Paths on a Network --- p.29
Chapter 2.7.1 --- Overview of Routing Algorithms --- p.29
Chapter 2.7.2 --- Dijkstra's Algorithm --- p.31
Chapter 2.7.3 --- Routing Models for the Multi-modal Network --- p.32
Chapter 2.8 --- Recent Researches on GIS Data Models for the Multi-modal Transportation System --- p.33
Chapter 2.9 --- Main Software Packages for GIS-T --- p.36
Chapter 2.10 --- Summary --- p.37
Chapter CHAPTER III --- MODELING THE MULTI-MODAL PUBLIC TRANSPORTATION SYSTEM
Chapter 3.1 --- Introduction --- p.40
Chapter 3.2 --- Elaborated Stages and Methods for GIS Modeling --- p.40
Chapter 3.3 --- Application Domain: The Multi-modal Public Transportation System --- p.43
Chapter 3.3.1 --- Definition of a Multi-modal Public Transportation System --- p.43
Chapter 3.3.2 --- Descriptions of the Multi-modal Public transportation System --- p.44
Chapter 3.3.3 --- Objective of the Modeling Work --- p.46
Chapter 3.4 --- A Layer-cake Based Application Domain Model for the Multi- modal Public Transportation System --- p.46
Chapter 3.5 --- A Conceptual Model for the Multi-modal Public Transportation System --- p.49
Chapter 3.6 --- Logical and Physical Implementation of the Data Model for the Multi-modal Public Transportation System --- p.54
Chapter 3.7 --- Criteria for Routing on the Multi-modal Public Transportation System --- p.57
Chapter 3.7.1 --- Least-time Routing --- p.58
Chapter 3.7.2 --- Least-fare Routing --- p.60
Chapter 3.7.3 --- Least-transfer Routing --- p.60
Chapter 3.8 --- Summary --- p.61
Chapter CHAPTER IV --- DATA PREPARATION FOR THE STUDY AREA
Chapter 4.1 --- Introduction --- p.53
Chapter 4.2 --- The Study Area: Hong Kong Island --- p.63
Chapter 4.2.1 --- General Information of the Transportation System on Hong Kong Island --- p.63
Chapter 4.2.2 --- Reasons for Choosing Hong Kong Island as the Study Area --- p.66
Chapter 4.2.3 --- Mass Transit Routes Selected for the Prototype --- p.67
Chapter 4.3 --- Data Source and Data Collection --- p.67
Chapter 4.4 --- Geographical Data Preparation --- p.71
Chapter 4.4.1 --- Data Conversion --- p.73
Chapter 4.4.2 --- Geographical Data Input --- p.79
Chapter 4.5 --- Attribute Data Input --- p.86
Chapter 4.6 --- Summary --- p.88
Chapter CHAPTER V --- IMPLEMENTATION OF THE PROTOTYPE
Chapter 5.1 --- Introduction --- p.89
Chapter 5.2 --- Construction of the Route Service Network --- p.89
Chapter 5.2.1 --- Generation of the Geographical Network --- p.90
Chapter 5.2.2 --- Setting Attribute Data for the Route Service Network --- p.95
Chapter 5.3 --- A GIS-T Prototype for the Study Area --- p.102
Chapter 5.4 --- General GIS Functions of the Prototype --- p.104
Chapter 5.4.1 --- Information Retrieve --- p.104
Chapter 5.4.2 --- Display --- p.105
Chapter 5.4.3 --- Data Query --- p.105
Chapter 5.5 --- Routing in the Prototype --- p.105
Chapter 5.5.1 --- Routing Procedure --- p.108
Chapter 5.5.2 --- Examples and Results --- p.110
Chapter 5.5.3 --- Comparison and Analysis --- p.113
Chapter 5.6 --- Summary --- p.118
Chapter CHAPTER VI --- CONCLUSION
Chapter 6.1 --- Research Findings --- p.123
Chapter 6.2 --- Research Limitations --- p.126
Chapter 6.3 --- Direction of Further Studies --- p.128
BIBLIOGRAPHY --- p.130

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"Drinking and Driving and Public Transportation: A Test of the Routine Activity Framework." Master's thesis, 2014. http://hdl.handle.net/2286/R.I.25060.

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abstract: Driving under the influence (DUI) is a problem in American society that has received considerable attention over recent decades from local police agencies, lobby groups, and the news media. While punitive policies, administrative sanctions and aggressive media campaigns to deter drinking and driving have been used in the past, less conventional methods to restructure or modify the urban environment to discourage drunk driving have been underused. Explanations with regard to DUIs are policy driven more often than they are guided by criminological theory. The current study uses the routine activities perspective as a backdrop for assessing whether a relatively new mode of transportation - an urban light rail system - in a large metropolitan city in the Southwestern U.S. can alter behaviors of individuals who are likely to drive under the influence of alcohol. The study is based on a survey of undergraduate students from a large university that has several stops on the light rail system connecting multiple campuses. This thesis examines whether the light rail system has a greater effect on students whose routines activities (relatively unsupervised college youth with greater access to cars and bars) are more conducive to driving under the influence of alcohol. An additional purpose of the current study is to determine whether proximity to the light rail system is associated with students driving under the influence of alcohol, while controlling for other criminological factors
Dissertation/Thesis
M.S. Criminology and Criminal Justice 2014

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Book chapters on the topic "Public Transit Routing"

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Delling, Daniel, Thomas Pajor, and Renato F. Werneck. "Round-Based Public Transit Routing." In 2012 Proceedings of the Fourteenth Workshop on Algorithm Engineering and Experiments (ALENEX), 130–40. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611972924.13.

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Witt, Sascha. "Trip-Based Public Transit Routing." In Algorithms - ESA 2015, 1025–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48350-3_85.

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Handte, Marcus, Lisa Kraus, Matteo Zella, Pedro José Marrón, and Heike Proff. "Integrated Bicycle and Public Transit Routing for InnaMoRuhr." In Towards the New Normal in Mobility, 529–45. Wiesbaden: Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-39438-7_31.

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Phan, Duc-Minh, and Laurent Viennot. "Fast Public Transit Routing with Unrestricted Walking Through Hub Labeling." In Lecture Notes in Computer Science, 237–47. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34029-2_16.

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Delling, Daniel, Julian Dibbelt, and Thomas Pajor. "Fast and Exact Public Transit Routing with Restricted Pareto Sets." In 2019 Proceedings of the Twenty-First Workshop on Algorithm Engineering and Experiments (ALENEX), 54–65. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2019. http://dx.doi.org/10.1137/1.9781611975499.5.

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Balagapo, Joshua, Jerome Sabidong, and Jaime Caro. "Transit Journaling and Traffic Sensitive Routing for a Mixed Mode Public Transportation System." In Intelligent Computing Systems, 227–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49179-9_11.

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Bhardwaj, Akashdeep. "Review of Solutions for Securing End-User Data Over Cloud Applications." In New Age Cyber Threat Mitigation for Cloud Computing Networks, 70–83. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815136111123010008.

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With more and more organizations working on the cloud over unsecured internet, sharing files and emails and saving them on cloud storage is imperative. Securing the end-user sensitive data in transit has thus started to get maximum priority to protect it from Cloud company staff, hackers, and data thieves. In this study, an attempt is made to review the research on end-user data security. There is an urgent need for solutions for end-users data protection privacy during the times when migrating from one cloud service provider to another. This chapter reviews the challenges in Cloud computing services regarding end-user data, analyzes the issues face, and presents solutions to overcome them. The chapter identifies end-users data security issues when using cloud computing services. The focus is directed to critical issues related to unauthorized access to integrity during data in transit. This can be addressed using Public Key Cryptography or PKI. For Confidentiality and Data Integrity for end-user data over Cloud. Then for migrating from one cloud service provider to another, data security and privacy are addressed by Cloud-aware applications. Lastly, using Multi-Factor Authentication combined with network and application detection systems, Intrusion Detection Systems, and Network traffic routing in case of cyber-attacks can help achieve denial of service attack mitigation or prevent man-in-the-middle and network snooping in Cloud Computing.

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Cavalcante, Andre. "We’re Just Living Life." In Struggling for Ordinary. NYU Press, 2018. http://dx.doi.org/10.18574/nyu/9781479881307.003.0006.

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This chapter examines why the ordinary and the everyday emerged as such potent themes in my fieldwork. It renders visible transgender individuals’ struggle for the ordinary, or the constant and deliberate work devoted to achieving the common inclusions and affordances of everyday life. In this way, the chapter theorizes everyday life as an ongoing, practical accomplishment. For the participants in my study, the rhythms and routines of the ordinary and everyday were elusive and often out of reach. Daily tasks such as running errands or using a public restroom were often complicated and potentially risky endeavors. To manage, navigate, and overcome these challenges, participants turned to the affordances of digital media. This chapter explores and celebrates the simple pleasures of everyday life—sociability, anonymity, recognition, mobility, having a day out, etc.—and shows the digital strategies that trans people used to achieve them.

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Elsaadi, Riyad, and Mahmoud Shafik. "Intelligent Healthcare Platform Solution and Medication Management System for Elderly People with Long Term Health Conditions." In Advances in Transdisciplinary Engineering. IOS Press, 2021. http://dx.doi.org/10.3233/atde210041.

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Healthcare and NHS faces many challenges in monitoring health conditions specially for patients with long term health conditions and the elderly. The forward view for healthcare providers and the NHS is moving from the hospital routine medical checks towards home environment care with the use of smart IoT and AI. Medication errors and missed medication across the globe, is the main source of harm to the public health. Technologies, specifically wireless health technologies are potential solutions for medication error and medication nonadherence in tracking patients’ medication. This paper presented a solution by developing a real-time wireless sensor network to monitor and check patient’s health condition using devices that transmits data from homes wirelessly to the relevant (caregiver, GP, Hospitals and specialist doctors). The proposed system benefits form the use of algorithms, which is used to provide the quality and quick health care advice to the patients at home. The algorithm processes the data from the database webserver. The database stores the patient health history conditions with all measurement obtained from the devices, such as blood pressure, blood glucose, heart rate and body temperature. This data is processed in machine learning algorithm to generate notifications for any changes occur in user’s health and by checking their history records. ML can detect patterns within patient healthcare records and inform clinicians of any anomalies.

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Conference papers on the topic "Public Transit Routing"

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Balagapo, Joshua, Jerome Sabidong, and Jaime Caro. "Data crowdsourcing and traffic sensitive routing for a mixed mode public transit system." In 2014 5th International Conference on Information, Intelligence, Systems and Applications (IISA). IEEE, 2014. http://dx.doi.org/10.1109/iisa.2014.6878754.

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Song, Rui, and Shiwei He. "A Genetic Algorithm Based Routing Method with GPS Technology for Public Transit Vehicles." In Second International Conference on Transportation and Traffic Studies (ICTTS ). Reston, VA: American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40503(277)127.

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Bian, Zheyong, and Xiang Liu. "A Detour-Based Pricing Mechanism for First-Mile Ridesharing in Connection With Rail Public Transit." In 2018 Joint Rail Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/jrc2018-6148.

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Rail public transit provides passengers with low cost, widely covered, environment-friendly travel service. However, many travelers do not choose the rail public transit because they are hindered by the first mile bottleneck — how to get to the train station. Ridesharing emerges as a viable transportation mode in connection with rail public transit. This paper designs a detour-based discounting mechanism for the first-mile ridesharing service to encourage more passengers to use the rail public transit. Specifically, passengers are incentivized by the mechanism to participate in the first-mile ridesharing service in connection with train stations. The mechanism accounts for passengers’ personalized requirement on the detour in determining the optimal vehicle-passenger matching, vehicle routing plan, and the pricing scheme. The New Brunswick train station (a New Jersey Transit station) is selected as the testbed to implement the proposed first-mile ridesharing mechanism. The results verify the application viability of the mechanism and demonstrate that the mechanism is effective to incentivize passengers to use the rail public transit.

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Ware, Simon I., Antonis F. Lentzakis, and Rong Su. "A Simulation Modeling Framework with Autonomous Vehicle Region-based Routing and Public Transit Diversion Integration." In 2019 IEEE Intelligent Transportation Systems Conference - ITSC. IEEE, 2019. http://dx.doi.org/10.1109/itsc.2019.8917309.

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Sivagnanam, Amutheezan, Salah Uddin Kadir, Ayan Mukhopadhyay, Philip Pugliese, Abhishek Dubey, Samitha Samaranayake, and Aron Laszka. "Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/546.

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Vehicle routing problems (VRPs) can be divided into two major categories: offline VRPs, which consider a given set of trip requests to be served, and online VRPs, which consider requests as they arrive in real-time. Based on discussions with public transit agencies, we identify a real-world problem that is not addressed by existing formulations: booking trips with flexible pickup windows (e.g., 3 hours) in advance (e.g., the day before) and confirming tight pickup windows (e.g., 30 minutes) at the time of booking. Such a service model is often required in paratransit service settings, where passengers typically book trips for the next day over the phone. To address this gap between offline and online problems, we introduce a novel formulation, the offline vehicle routing problem with online bookings. This problem is very challenging computationally since it faces the complexity of considering large sets of requests—similar to offline VRPs—but must abide by strict constraints on running time—similar to online VRPs. To solve this problem, we propose a novel computational approach, which combines an anytime algorithm with a learning-based policy for real-time decisions. Based on a paratransit dataset obtained from the public transit agency of Chattanooga, TN, we demonstrate that our novel formulation and computational approach lead to significantly better outcomes in this setting than existing algorithms.

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Qian, Wei, Cong Fu, Yu Zhu, Deng Cai, and Xiaofei He. "Translating Embeddings for Knowledge Graph Completion with Relation Attention Mechanism." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/596.

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Knowledge graph embedding is an essential problem in knowledge extraction. Recently, translation based embedding models (e.g., TransE) have received increasingly attentions. These methods try to interpret the relations among entities as translations from head entity to tail entity and achieve promising performance on knowledge graph completion. Previous researchers attempt to transform the entity embedding concerning the given relation for distinguishability. Also, they naturally think the relation-related transforming should reflect attention mechanism, which means it should focus on only a part of the attributes. However, we found previous methods are failed with creating attention mechanism, and the reason is that they ignore the hierarchical routine of human cognition. When predicting whether a relation holds between two entities, people first check the category of entities, then they focus on fined-grained relation-related attributes to make the decision. In other words, the attention should take effect on entities filtered by the right category. In this paper, we propose a novel knowledge graph embedding method named TransAt to learn the translation based embedding, relation-related categories of entities and relation-related attention simultaneously. Extensive experiments show that our approach outperforms state-of-the-art methods significantly on public datasets, and our method can learn the true attention varying among relations.

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