Bus rapid transit

Effective public transit is central to development. For the vast majority of developing city residents, public transit is the only practical means to access employment, education, and public services, especially when such services are beyond the viable distance of walking or cycling. Unfortunately, the current state of public transit services in developing cities often does little to serve the actual mobility needs of the population. Bus services are too often unreliable, inconvenient and dangerous. In response, transport planners and public officials have sometimes turned to extremely costly mass transit alternatives such as rail-based metros. Due to the high costs of rail infrastructure, cities can only construct such systems over a few kilometres in a few limited corridors. The result is a system that does not meet the broader transport needs of the population. Nevertheless, the municipality ends up with a long-term debt that can affect investment in more pressing areas such as health, education, water, and sanitation. However, there is an alternative between poor public transit service and high municipal debt. Bus Rapid Transit (BRT) can provide high-quality, metro-like transit service at a fraction of the cost of other options. This document provides municipal officials, non-governmental organizations, consultants, and others with an introduction to the concept of BRT as well as a step-by-step process for successfully planning a BRT system

Optimization of transit smart card data publishing based on differential privacy

“Privacy budget allocation is a key step of the differential privacy (DP)-based privacy-preserving data publishing (PPDP) algorithm development, as it directly impacts the data utility of the released dataset. This research describes the development of an optimal privacy budget allocation algorithm for transit smart card data publishing, with the goal of publishing non-interactive sanitized trajectory data under a differential privacy definition. To this end, after storing the smart card trajectory data with a prefix tree structure, a query probability model is built to quantitatively measure the probability of a trajectory location pair being queried. Next, privacy budget is calculated for each prefix tree node to minimize the query error, while satisfying the differential privacy definition. The optimal privacy budget values are derived with Lagrangian relaxation method, with several solution property proposed. Real-life metro smart card data from Shenzhen, China that includes a total of 2.8 million individual travelers and over 220 million records is used in the case study section. The developed algorithm is demonstrated to output sanitized dataset with higher utilities when compared with previous research”--Abstract, page iii

RESEARCH ON URBAN TRANSIT RELIABILITY USING SMART CARD DATA

Ph.DDOCTOR OF PHILOSOPH

USING ARCHIVED TRANSIT DATA TO ANALYZE THE EFFECT OF RAINFALL ON TRANSIT PERFORMANCE MEASURES AT THE ROUTE LEVEL

This study investigates the effect of rainfall on transit performance measures at the route level in the Puget Sound region of Washington State. Transit agencies are required to report certain performance metrics to the Federal Transit Administration (FTA), but performance measures can also be used to evaluate service and provide customers with information regarding the transit system. Using a three-year sample of archived automatic vehicle location (AVL) and hydrologic data the relationships between ridership, travel time, delay, and rainfall were investigated. The analysis of daily ridership and rainfall resulted in no statistically significant results, however, the results are supported by the existing research in this field. There was a generally negative trend in ridership with respect to rainfall. The analysis of travel time and rainfall did not result in the expected outcome. It was hypothesized that travel time would vary with rainfall, but that was not always the case. During many rainfall events the travel time remained average. The analysis of delay and rainfall shows that the impact of rainfall on delay is more complex than assumed. The delay during dry trips was different than the delay during light and moderate rain, but during heavy rain the statistical different disappeared. These results, implications for transit operators, and future research opportunities are discussed

Smart bus stop: people counting in a multi-view camera environment

As paragens de autocarros nos dias de hoje tem de estar cada vez mais ao serviço dos utentes, esta dissertação explora as ideias fundamentais sobre o que deve ser uma paragem de autocarro inteligente, reunindo num texto os conceitos mais utilizados e as mais recentes tecnologias sobre este tópico. Os fundamentos do que é uma paragem de autocarro inteligente são explorados, bem como a arquitetura de todo o sistema, não só a paragem propriamente dita. Ao analisar a bibliografia já existentes compreende-se que a paragem de autocarro não é uma entidade totalmente independente, pois esta está dependente de informação vinda de variadíssimas fontes. Assim sendo, a paragem de autocarro inteligente será um subsistema de um sistema muito mais complexo, composto pela própria paragem, pelo autocarro e por uma central. Em que a comunicação flui entre estes de forma a manter toda a informação do sistema atualizada em tempo real. O autocarro recolherá informação, como quantos passageiros tem abordo e a sua localização geográfica por exemplo. A central receberá toda a informação de todos os autocarros existentes assim como de todas as paragens de autocarro existentes. Por sua vez a paragem de autocarro, recolherá dados também, tais como quantas pessoas estão na paragem, temperatura, humidade, emissões de dióxido de carbono, ruido, entre outros. A paragem de autocarro deverá contar com um conjunto de interfaces de comunicação, tais como Bluetooth e/ou NFC, hi-fi e RFID ou Beacons, para que possam ser feitas comunicações com os utilizadores, com os autocarros e com a central. Deverá ter também ecrãs interativos que poderão ser acedidos usando gestos e/ou toque e/ou voz para que se possam efetuar as ações pretendidas. A informação não será apenas transmitida nos ecrãs interativos, será transmitida também através de som. A informação contida na paragem pode ser de todo o tipo, desde as rotas, horários, posição atual do próximo autocarro, assim como o número do mesmo, publicidade animada, etc. A paragem conta também com outras funcionalidades como conectores onde se possam carregar dispositivos móveis, aquecimento, iluminação controlada face à afluência de utilizadores e horário, um sistema de armazenamento de energia pois deverá contar com fontes de energia renováveis para que possa ser o mais autossustentável possível, e obviamente câmeras de vigilância para segurança dos utilizadores. Sendo o principal objetivo deste trabalho, o desenvolvimento de um algoritmo capaz de contar quantas pessoas se encontram na paragem de autocarro, através do processamento das imagens vindas de várias câmaras, o foco principal é explorar as tecnologias de visão computacional e como estas podem ser utilizadas dentro do conceito da paragem de autocarro inteligente. Uma vez que o mundo da visão computacional evoluiu muito nos últimos anos e as suas aplicações são quase ilimitadas, dai a sua implementação nas mais diversas áreas, como reconstrução de cenários, deteção de eventos, monitorização de vídeo, reconhecimento de objetos, estimativa de movimento, restauração de imagem, etc. Ao combinar os diferentes algoritmos das diferentes aplicações, podem ser criadas ferramentas mais poderosas. Assim sendo o algoritmo desenvolvido utiliza redes neuronais convulsionais para detetar todas as pessoas de uma imagem, devolvendo uma região de interesse. Essa região de interesse é processada em busca de caras e caso estas existam essa informação é guardada no perfil da pessoa. Isto é possível através da utilização de reconhecimento facial, que utiliza um algoritmo de Deep Learning (DL). Essa região de interesse também é convertida para uma escala de cinzentos e posteriormente para uma matriz, essa matriz será também guardada no perfil do utilizador. Está informação é necessária para que se possa treinar um modelo que utiliza algoritmos de aprendizagem de máquina (Support Vector Machine - SVM). Os algoritmos de DL e SVM são necessários para que se possa fazer a identificação dos utilizadores a cada imagem e para que se possa cruzar os vários perfis vindos das várias origens, para que possa eliminar os perfis repetidos. Com isto a mesma pessoa é contada as vezes que apareça nas imagens, em função do número de câmeras existentes na paragem. Assim sendo é preciso eliminar essas repetições de forma a ter um número de pessoas correto. Num ambiente controlado o algoritmo proposto tem uma taxa de sucesso elevada, praticamente sem falhas, mas quando testado no ambiente para o qual foi desenhado já não é bem assim, ou porque numa paragem de autocarro as pessoas estão em contante movimento ou porque ficam na frente umas das outras e não é possível visualizá-las a todas. Mesmo com muitas câmeras colocadas no local, acabam sempre por haver pontos mortos, devido à estrutura da paragem ou até mesmo devido ao meio, por exemplo árvores ou um carro mal-estacionado, etc.Bus stops nowadays have to be increasingly at the user’s service, this thesis explores the fundamentals ideas of what a Smart Bus Stop should be and bring all together into one concept using today’s technologies. Although the fundamentals of a Smart Bus Stop (SBS) are explored, the primary focus here is to explore computer vision technology and how they can be used inside the Smart Bus Stop concept. The world of computer vision has evolved a lot in recent years and its applications are almost limitless, so they have been incorporated into many different areas like scene reconstruction, event detection, video tracking, object recognition, motion estimation, image restoration, etc. When combining the different algorithms of the different applications more powerful tools can be created. This work uses a Convolutional Neural Network (CNN) based algorithm to detect people in a multi video feeds. It also counts the number of persons in the SBS, using facial recognition, using with Deep Learning algorithm, and Support Vector Machine algorithm. It is important to stress, these last two are used to keep track of the user and also to remove the repeated profiles gathered in the different video sources, since the SBS is in a multi-camera environment. Combining these technologies was possible to count how many people were in the SBS. In laboratory the propose algorithm presents an extremely high success rate, when applied to real bus stops que success rate decreases due to blind spots for instance

Simulating service reliability of a high frequency bus route using automatically collected data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references.High frequency bus routes are subject to a variety of influences that can affect the quality of service provided to passengers. Since they have short headways and high passenger demand interaction between buses can easily develop, causing degradation in service reliability. This, in turn, can prompt service interventions to correct service reliability. Transit agencies are implementing new technology that provide rich data sets for analysis and are also experimenting with a variety of operating policies to improve service reliability. This research develops a simulation model of high frequency bus service in order to study the causes of service unreliability and strategies to alleviate it. The model is designed to be used in conjunction with data recorded by the Automatic Voice Annunciation System (AVAS), Automatic Passenger Counting (APC), and Automatic Fare Collection (AFC) systems and is calibrated to represent route 63, a key bus route in the Chicago Transit Authority (CTA) network The simulation model is first used to conduct a sensitivity analysis of the factors influencing reliability, such as passenger demand, terminal departure behavior, and unfilled trips. Next, several operating strategies, including terminal departure and timepoint holding for schedule or headway, are modeled and evaluated for their potential to improve reliability. The sensitivity analysis and application testing support the use of passenger-centric metrics such as passenger-experienced waiting time and crowding over more aggregate headway measures such as large headways and bunching. Model results show that headway management strategies implemented at the terminal can significantly improve bus service reliability and ameliorate the impacts of unfilled trips on route 63, as measured by passenger waiting time, crowding, and big-gaps / bunches.(cont.) The simulation model is a valuable research tool for applications beyond those tested in this thesis. The model developed can be applied with from data collected by automatic collection systems which is a particularly useful feature for transit agencies.by Martin Nicholas Milkovits.S.M

Analysis of service reliability of public transportation in the Helsinki capital region: The case of bus line 550

The rate of automobile ownership in Helsinki Capital Region has been on the rising trajectory, even bypassing population growth rate of the region. The population of the region expected to double in 2050, planning for a sustainable mobility becomes crucial. Effort is being exerted to minimize private car dependence and innovative transport solutions are being tested in the region. Increasing the share of public transport (PT) in the region is the main goal of Helsinki Regional Transport Authority (HSL). To increase the share of PT, improving its efficiency and reliability becomes a crucial strategy by attracting private car users and keeping existing passengers. Therefore, PT agencies need to continuously evaluate the reliability of their service and take improvement actions accordingly. A reliable PT service is one that adheres to schedule and whose vehicles run on-time. It is generally recognized that deviation from schedule (unreliability) in PT is an important operational problem that affects both operators and passengers. Measuring the level of deviation from schedule helps operators and PT authorities identify and improve gaps in service delivery. Recorded large operational data from Automatic Vehicle Location (AVL) and Automatic Passenger Counter (APC) provide an opportunity to analyze operational performance quality of a PT with a minimum cost. The objective of the thesis was to analyze service reliability of a circumferential high-frequency bus line 550 in Helsinki Capital Region (HCR) using data from AVL and APC systems. Five different service reliability measures were used in this study. These were on-time performance, headway adherence, vehicle trip-time variability, passenger wait time and passenger travel time. The first three are agency oriented reliability measures and the last two are passenger oriented. This study has provided a quantitative overview over several service performance measures. The results of the agency-based analysis revealed that for trips along direction 1, 60% of all departures at five stops were on-time using 0.5-minutes-early and 1-minute -late time window. The corresponding average headway deviation was 84 seconds, with average vehicle run time of 1.4 minutes. The passenger-based analysis showed that for all trips along direction 1, the average additional waiting time per passenger was 42 seconds with average additional passenger travel time of 1.7 minutes. The APC data analysis along direction 1 revealed that average passenger load was 26.5 passengers per bus per direction. The average highest and lowest passenger loads were 38.3 passengers per bus and 2.7 passengers per bus respectively. Overall, Passenger activity over the first half of the route is characterized by high load which is about twice that of the second half of the route. The overall analysis revealed that performance deteriorated further along the line in both directions. The occurrence of bunching increased towards the end of the route. There is a room for improvement in both agency and passenger oriented measures. Keeping a regular headway on the route is very important, especially for short headway service periods. Passengers perceive reliability mainly in terms of additional waiting and travel time. Improving these aspects of service leads to higher passenger satisfaction which could translate into increased patronage for the PT agency