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About 10,000 papers for “Bus network”

Bus Network

Tom J · Bulletin of Miscellaneous Information (Royal Gardens Kew)

Cited by 0

Bus network data.

Boya Gao (8840498), Jie Liu (15128) · Figshare · 2024

Cited by 0Open access

Merton bus network.

Thomas, Matthew Scott, Bedrossian, Nancy Ann, Aboyeji, Olufemi O. · Digital WPI · 1999

The purpose of this project was to recommend improvements to the bus network in the London Borough of Merton that would increase bus ridership, and decrease traffic congestion. We arrived at these conclusions after reviewing the literature on different international bus systems, examining the existing bus network in Merton, and interviewing traffic experts. Our report identifies several changes to the existing bus network that will improve the bus service and increase ridership.

Cited by 0Open access

Two bus network.

Fadi M. Albatsh (724276), Shameem Ahmad (724277), Saad Mekhilef (724278) et al. · Figshare · 2015

Cited by 0Open access

bus complex network

Yumeng Cui · Figshare · 2022

This is bus data for research.

Cited by 0Open access

bus complex network

Cui, Yumeng · Figshare · 2022

This is bus data for research.

Cited by 0Open access

Bus network design

Avishai Ceder, Nigel H. M. Wilson · Transportation Research Part B Methodological · 1986

Cited by 584

Bus network design

Ceder, Avishai, Wilson, Nigel H. M. · RePEc: Research Papers in Economics

This paper describes the bus network design problem, summarizes the different approaches that have been proposed for its solution and proposes a new approach incorporating some of the positive aspects of prior work. The proposed approach is intended to be easier to implement and less demanding in terms of both data requirements and analytical sophistication than previous methods. An algorithm is presented that can be used to design new bus routes taking account of both passenger and operator interests; however, this algorithm focuses on only a single component of the overall bus operations planning process described in this paper.

Cited by 0

School Bus Network Optimization

Al-Qawasmeh, Husam Abdelrahim · RIT Scholar Works (Rochester Institute of Technology) · 2020

The city of Dubai has more than 200 schools, with around 6,500 School buses that are either managed by the school itself or bus operator companies. A low percentage of bus-usage aggravates school traffic according to top RTA official that stated that only 11% of total school trips in Dubai are via bus (compared to 32% in the United States), school buses account for 13% of peak-hour traffic while they 53% of bus seats were occupied, as parents prefer private transport. Private transport schools remain as significant contributing factor traffic congestion, and environmental pollution as a major percentage of students are using their transportation due to reasons like cost and travel time on the bus. Bus routes that are improperly planned or buses that are over-utilized forcing buses to run for longer distances to collect few students do not help the traffic status in the city. Parents/drivers that are dropping children who are not utilizing the school bus are also contributing largely to the stats of the traffic. This city traffic impacts the city economy, including business and tourism, the city Leadership position, sustainability and Happiness, resources efficiency and environment, and including impact on children’s, the future workforce, health & academic performance. Many cities seek optimizing school bus network to accommodate every student in dynamic configuration (route and passenger) managed by a control center. This capstone project selects few schools, study the subset of students who use the bus, calculate what distances they would have travelled if used their own transport, then optimize their route as they use the school bus. Finally, the capstone also concludes by optimization of bus users across a sample of two different schools In this study, optimized routes for school buses were created each on their own, and then the methodology was repeated for them combined, allowing sharing buses between them. Such a study was not easily achievable in the past when some visualization tools (such as GPS, Google Maps, Data analytics) were not available. Clustering and Salesman Travel problems were utilized in this study. While this case is similar to other vehicle routing problems, such as shipment delivery, garbage containers collection, and other logistics optimization problem, it is much more difficult due to the time-sensitivity and nature of the subject of transport being the youngsters. In addition to saving cost to school bus operators and reduce student’s travel time on the school bus, further work in the future would also demonstrate how new phases of this project would allow for regulations (e.g. max student travel time on bus) enabled by analytics.

Cited by 0

Multiple communication bus network

Masaichi Kajiwara, Chiaki Hishinuma, Masaki Itoh · Electronics and Communications in Japan (Part I Communications) · 1981

Abstract A multiple communication bus network (MCNET) is proposed as a structure for a nationwide trunk network and its optimum method of circuit regulation and size of the network are discussed. MCNET is a network in which uniform, large‐capacity transmission paths achieve bus connection of plural exchange offices in a region and in which interoffice traffic is directly switched on transmission paths in bus form. Between different regions, the network is hierarchically structured with representative exchanges in regions and bus‐formed transmission paths between them. This paper describes the fundamental concepts and network structure. The circuit regulation method by which circuits are assigned semipermanently to each originating exchange is advantageous with respect to adantability for traffic loading and ease of regulation. The capacities of the MCNET are investigated by introducing a “traffic diffusion index” and it is concluded that the erlang capacities for the RA, DA and TA switching systems are in the ranges of some ten thousands to hundred thousands, from ten thousand to some ten thousands and from six thousand to nine thousands, respectively, and that the capacities of the transmission paths are also in erlang ranges of from 300 thousand to one million, from 200 thousand to 600 thousand and from 40 thousand to 60 thousands.

Cited by 0

IEEE 240 Bus network.

Balamurali Krishna Ponukumati (19864775), Pampa Sinha (19864778), Kaushik Paul (19864781) et al. · Figshare · 2024

<div><p>There has been a lack of a satisfactory solution for identifying and locating evolving faults in unbalanced distribution systems. The proposed approach is based on the cross-correlation technique as a key element for fault detection and location. Evolving faults, in this context, refer to two sequential faults that result in a change of fault phase. The captured QRS value reflects the occurrence of the second fault occurrence. In order to identify Evolving Faults, it makes use of the signal that is currently being monitored at any given point in the network. Typical system occurrences, such as a short circuit fault that grew into another short circuit fault, as well as cross-country faults, are simulated, and according to the suggested technique, they are accurately differentiated from one another. Using a real-time simulator, rigorous simulations are performed on the modified IEEE 240 bus distribution system. The results of these simulations reveal that they have the potential to uncover defects that are constantly changing. Regardless of the fault (location\\resistance\\inception angle), location of the monitored point, or sample frequency that is selected, the suggested approach is unaffected by any of these factors. In addition, the slime mold optimization approach is utilized in order to get the best monitoring points that accurately identify the bus in which the evolving fault has taken place.</p></div>

Cited by 0Open access

Redesign Your Bus Network

Jeff Speck · Island Press/Center for Resource Economics eBooks · 2018

Abstract IN MOST AMERICAN CITIES, your bus network is your real public transit workhorse. If it has not been comprehensively redesigned within the past two decades, chances are it should be, for three main reasons: First, we know a lot more about transit design then we used to. Current best practices may suggest an organization different from your current one. Second, most bus networks have received many tweaks over time, minor individual changes that may have made sense individually but that collectively have undermined the logic of the system, causing inefficiency, confusion, and potentially lost ridership. Finally, as discussed by Jarrett Walker, cities change. Each generation of growth is likely to alter working and living patterns in a way that impacts transit needs, and each generation of humans will have different values and priorities that govern its transit choices. Only a comprehensive redesign can address these changes rationally.

Cited by 1

Ring Buffered Network Bus

NASA Technical Reports Server (NASA)

This report describes the research effort to demonstrate the integration of a data sharing technology, Ring Buffered Network Bus, in development by Dryden Flight Research Center, with an engine simulation application, the Java Gas Turbine Simulator, in development at the University of Toledo under a grant from the Glenn Research Center. The objective of this task was to examine the application of the RBNB technologies as a key component in the data sharing, health monitoring and system wide modeling elements of the NASA Aviation Safety Program (AVSP) [Golding, 1997]. System-wide monitoring and modeling of aircraft and air safety systems will require access to all data sources which are relative factors when monitoring or modeling the national airspace such as radar, weather, aircraft performance, engine performance, schedule and planning, airport configuration, flight operations, etc. The data sharing portion of the overall AVSP program is responsible for providing the hardware and software architecture to access and distribute data, including real-time flight operations data, among all of the AVSP elements. The integration of an engine code capable of numerically "flying" through recorded flight paths and weather data using a software tool that allows for distributed access of data to this engine code demonstrates initial steps toward building a system capable of monitoring and modeling the National Airspace.

Cited by 0Open access

Urban Bus Network Electrification

Dávid Földes, Bálint Csonka, Péter Ákos Szilassy · IntechOpen eBooks · 2023

Electric busses are spreading in cities in hope of mitigating local air pollution. Currently, battery electric busses are more expensive and require novel operational methods to optimize their use (e.g., applying daytime charging, and operating trolleybuses). Despite these, the electrification of urban busses is usually ad-hoc, preliminary planning is superficial, and does not consider the relationships among bus lines. This chapter introduces a method regarding charging infrastructure planning, electric bus type selection, and cost estimation. Based on the characteristics of the vehicle, charging infrastructure, bus service (lines, timetable, etc.), and energy consumption, a line-group optimization is introduced, which is the main novelty. The method was applied in a case study considering static terminal and dynamic catenary charging. The results help operators to boost the electrification of the urban bus network.

Cited by 3Open access

Area Network Bus Analyzer

Ifsa Publishing, Hongwei Cui · 2014

Abstract: The detection method of automotive controller area network bus is researched in this paper. Failure identifying of CAN bus under different working conditions has been realized. In order to realizing intelligent failure diagnosis, data fusion means has been put forward in this paper. The composition of analysis and detection system is introduced. By analyzing and processing the data of CAN bus and sensors, work condition of automotive is achieved. Multi-pattern data fusion model and algorithm for failure diagnosis are researched. The analyzer and detection system designed in this paper can be applied to automotive fault analysis,

Cited by 0