Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

There is a wide body of evidence that suggests sustainable mobility is not only a technological question, but that automotive technology will be a part of the solution in becoming a necessary albeit insufficient condition. Sufficiency is emerging as a paradigm shift from car ownership to vehicle usage, which is a consequence of socio-economic changes. Information and Communication Technologies (ICT) now make it possible for a user to access a mobility service to go anywhere at any time. Among the many emerging mobility services, Multiple Passenger Ridesharing and its variants look the most promising. However, challenges arise in implementing these systems while accounting specifically for time dependencies and time windows that reflect users’ needs, specifically in terms of real-time fleet dispatching and dynamic route calculation. On the other hand, we must consider the feasibility and impact analysis of the many factors influencing the behavior of the system – as, for example, service demand, the size of the service fleet, the capacity of the shared vehicles and whether the time window requirements are soft or tight. This paper analyzes - a Decision Support System that computes solutions with ad hoc heuristics applied to variants of Pick Up and Delivery Problems with Time Windows, as well as to Feasibility and Profitability criteria rooted in Dynamic Insertion Heuristics. To evaluate the applications, a Simulation Framework is proposed. It is based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system. It also interacts with the Decision Support System by feeding it with the required data for making decisions in the simulation that emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The obtained results prove the potential feasibility of the mobility concept.Postprint (published version

Understanding Transit Ridership Demand for a Multi-Destination, Multimodal Transit Network in an American Metropolitan Area, Research Report 11-06

This study examines the factors underlying transit demand in the multi-destination, integrated bus and rail transit network for Atlanta, Georgia. Atlanta provides an opportunity to explore the consequences of a multi-destination transit network for bus patrons (largely transit-dependent riders) and rail patrons (who disproportionately illustrate choice rider characteristics). Using data obtained from the 2000 Census, coupled with data obtained from local and regional organizations in the Atlanta metropolitan area, we estimate several statistical models that explain the pattern of transit commute trips across the Atlanta metropolitan area. The models show that bus riders and rail riders are different, with bus riders exhibiting more transit-dependent characteristics and rail riders more choice rider characteristics. However, both types of riders value many of the same attributes of transit service quality (including shorter access and egress times and more direct trips) and their use of transit is influenced by many of the same variables (including population and employment). At the same time, the factors that influence transit demand vary depending on the type of travel destination the rider wishes to reach, including whether it is the central business district (CBD) or a more auto-oriented, suburban destination. The results of the study offer new insights into the nature of transit demand in a multi-destination transit system and provide lessons for agencies seeking to increase ridership among different ridership groups. The results suggest that more direct transit connections to dispersed employment centers, and easier transfers to access such destinations, will lead to higher levels of transit use for both transit-dependent and choice riders. The results also show that the CBD remains an important transit destination for rail riders but not for their bus rider counterparts. Certain types of transit-oriented development (TOD) also serve as significant producers and attractors of rail transit trips

LDAVI : LambDa architecture driVen implementation

Data has been playing an important role in many areas of society. It has massively increased among time and can be a powerful source of knowledge. The way data is handled, and this knowledge is extracted had also to be adapted to support this huge amount of information coming from different sources. Lambda Architecture comes to supply this need of having a Big Data architecture capable of processing both historical data and stream data. We present LDAVI, a Lambda Architecture Driven Implementation based on Lambda Architecture approach (KIRAN, 2015), a data-processing architecture for handling massive amount of data by decomposing the problem into three layers: batch layer – for historical data processing - serving layer and speed layer – for streaming processing. Main technologies used for building this architecture are Apache Hadoop, Apache Spark, Apache Impala and Apache Kafka. The main focus is to this describe this architecture as well as its implementation, as it can apply to any type of problem where one needs to store and process huge amount of data – either in streaming or batch modes. Our objective in this work is to demonstrate the powerful, capacity and feasibility of this architecture and that it can be used to approach different type of Big Data scenarios. In this work we address Smart Mobility are as our case of study to evaluate LDAVI. We analyze passengers smart card and buses GPS and stops location from the city of Schenzhen, aiming to extract passengers density and flow. Lambda Architecture is a new architectural concept that emerged with the raise of Big Data Analytics. In this work we approach and provide an implementation of this architecture, building it with the main Big Data technology stack. Although it has started being used in some areas such as search engines and platforms requiring real-time processing – such as video stream players – we demonstrate that this architecture can also bring benefits for Smart Mobility, more precisely in public transportation. Differently from related works, we approach three different types of trip: simple trip, connection trip and round trip, what makes the analysis complete and more accurate.Os dados têm desempenhado um papel importante em muitas áreas da sociedade. Eles aumentaram massivamente com o tempo e podem ser uma poderosa fonte de conhecimento. A forma como os dados são tratados, e esse conhecimento é extraído, também deve ser adaptada para suportar essa enorme quantidade de informações vindas de diferentes fontes. A Lambda Architecture vem suprir essa necessidade de ter uma arquitetura Big Data capaz de processar dados históricos e dados em tempo real. Apresentamos o LDAVI, uma implementação da Lambda Architecture baseada na arquitetura Lambda (KIRAN, 2015), uma arquitetura de processamento de dados para manipular uma quantidade massiva de dados decompondo o problema em três camadas: camada de lote - para processamento de dados históricos - camada de veiculação e camada de velocidade - para processamento de streaming. As principais tecnologias usadas para construir essa arquitetura são o Apache Hadoop, o Apache Spark, o Apache Impala e o Apache Kafka. O foco principal é descrever essa arquitetura, bem como sua implementação, pois ela pode ser aplicada a qualquer tipo de problema em que seja necessário armazenar e processar uma grande quantidade de dados - nos modos de fluxo contínuo ou lote. Nosso objetivo neste trabalho é demonstrar o poder, a capacidade e a viabilidade dessa arquitetura e que ela pode ser usada para abordar diferentes tipos de cenários de Big Data. Neste trabalho, abordamos a Mobilidade Inteligente como nosso caso de estudo para avaliar o LDAVI. Analisamos os cartoes de passageiros, GPS de ônibus e paradas de ônibus da cidade de Schenzhen, com o objetivo de extrair a densidade e o fluxo de passageiros. Lambda Architecture é um novo conceito arquitetônico que surgiu com o aumento da area de Big Data Analytics. Neste trabalho, abordamos e fornecemos uma implementação dessa arquitetura, construindo-a com a principal pilha de tecnologia de Big Data. Embora tenha começado a ser usado em algumas áreas, como mecanismos de busca e plataformas que exigem processamento em tempo real - como reprodutores de fluxo de vídeo - demonstramos que essa arquitetura também pode trazer benefícios para a Mobilidade Inteligente, mais precisamente no transporte público. Diferentemente dos trabalhos relacionados, abordamos três tipos diferentes de viagem: viagem simples, viagem de conexão e ida e volta, o que torna a análise completa e mais precisa

Improving Pathways to Transit for Persons with Disabilities

Persons with disabilities can achieve a greater degree of freedom when they have full access to a variety of transit modes, but this can only be achieved when the pathways to transit – the infrastructure and conditions in the built environment – allow full access to transit stops, stations, and vehicles. Since passage of the Americans with Disabilities Act (ADA) in 1990, many transit agencies and governmental jurisdictions have made significant progress in this area. Policy initiatives, incremental enhancements, modifications, and other measures undertaken by transit agencies and their partners have significantly improved access to transit for persons with disabilities, others who rely on public transportation, and individuals who chose to utilize these services. This research study explores, through case study work, efforts that have been effective in improving pathways to transit. Interviews and site visits were conducted with five transit agencies, along with their partners, that are actively engaged in improving pathways to connect transit consumers – particularly people with disabilities – with transit stations and stops. These agencies are: Broward County Transit (Broward County, FL), Memphis Area Transit Authority (Memphis, TN), NJ TRANSIT (Newark and New Brunswick, NJ), Tri-County Metropolitan Transportation District of Oregon (Portland, OR), and Link Transit (Wenatchee, WA). Promising practices and/or lessons were identified through the case study analysis; these should be considered by any transit agency seeking to create improved access to its services for persons with disabilities

Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events

This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event

ASSESSMENT OF BUS SYSTEM SERVICE AND PERFORMANCE FOR PUBLIC TRANSPORT IMPROVEMENT

This study, entitled “Assessment of Bus System Service and Performance for Public Transport Improvement” was based on a case study of bus service at the Ipoh- Lumut corridor in Perak, Malaysia. This corridor is serviced by stage buses in mixed traffic. The problems faced are low quality of buses, inconvenience, long waiting time, limited facilities, low reliability and low passengers loading which have caused the system to be unattractive to passengers. The purposes of the study were to analyze bus service characteristics and performance of the bus system, to assess bus service reliability and to formulate strategies for the improvement of bus service performance. A fieldwork investigation was conducted covering preliminary survey, primary data survey and secondary data collection. The primary data consisted of bus service operation and passenger boarding and alighting. The approaches of study included description of study area, analysis of bus service characteristics, performance, improvement strategies, evaluation of ridership factors elasticity and sensitivity of bus service demand. Bus service characteristics were analyzed based on fundamental theory, World Bank Standard and TCQSM Standard. In addition, statistical methods such as ANOVA, MARE, MAPPE, ARIMA, MLR and SNN model were applied. The proposed performance indicators to evaluate bus service quality and reliability comprised of on-time performance, regularity, punctuality and waiting time. The concept of elasticity and sensitivity were explored to evaluate bus service demand with respect to ridership factors changes. Finally, gravity model was calibrated to estimate passenger trip distribution by using data of passenger boarding and alighting. From this study, it was concluded that the improvement of bus service quality and performance can be done by changing of frequency, the capacity of passenger and improving the bus service reliability. Based on the elasticity analysis, in the service characteristics category, travel time was an elastic factor, whereas ticket fare, fuel price, per capita income, frequency and headway were inelastic factors in the bus service demand. Meanwhile, in the service reliability category, the punctuality, waiting time, regularity and on-time performance were categorized as elastic factors. Moreover, the bus service demand increased by changes of factors such as the increase in punctuality, decrease in waiting time, increase in level of service and increase in regularity

Design criteria of high capacity bus transportation systems

Thesis (Master)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2005Includes bibliographical referencesText in English; Abstract: Turkish and Englishxii, 109 leavesThis thesis proposes to figure out a new model of public bus transportation mode in Turkey which is more competitive and effective among the conventional public transportation modes.In theoretical framework, the focus is on the new concepts and implementations developed in the urban transportation sector. The effective transportation systems regarding lower expenditures were handled according to the travel demands they serve.However, in general, the effectiveness of the modes is determined according to the economic parameters; mainly the conventional modes are discussed and the effectiveness of BRT systems and LRT systems are compared.A brief survey of the BRT (Bus Rapid Transportation) systems is handled to some extent. The design considerations and the results of the implemented examples are handled to constitute a guideline. The major public transportation modes of Izmir are handled to constitute a guideline. The major public transportation modes of Izmir are discussed. A reserved bus-transportation system is designed in the case study stage.Meanwhile the reserved bus concept along the Inönü Street is not designed according to the existing proposals. A distinctive model is concluded regarding the local conditions of Izmir. At final stage, the energy consumption rates of the systems are calculated and the economic comparison of the systems is based on this parameter