Bus arrival time prediction using stochastic time series and Markov chains

Public transit agencies rely on disseminating accurate and reliable information to transit users to achieve higher service quality and attract more users. With the development of new technologies, the concept of providing users with reliable information about bus arrival times at bus stops has become increasingly attractive. Due to the fact that bus operation parameters and variables are highly stochastic, modeling prediction of bus travel and arrival times has become one of the many challenging tasks. Stochastic time series and delay propagation models to predict bus arrival times using historical information were developed. Markov models were developed to predict propagation of bus delay to downstream bus stops based on heterogeneous conditions. The bus arrival times were predicted using a Markov model only and performance measures were obtained and a combined arrival time prediction model consisting of delay propagation and full autoregressive model was also developed. The inclusion of bus delay propagation into the bus arrival time prediction algorithm is an important contribution to the research efforts to predict bus arrival times. The research showed that Markov models can provide accurate bus arrival time predictions without increasing the need for a large number of bus operation variables, simulations and high polling frequency of the geographical bus location as used by other modeling approaches

Estimating Transit Ridership Patterns through Automated Data Collection Technology: A Case Study in San Luis Obispo, California

Public transportation offers a crucial solution to the travel demand in light of national and global economic, energy, and environmental challenges. If implemented effectively, public transit offers an affordable, convenient, and sustainable transportation mode. Implementation of new technologies for information-harvesting may lead to more effective transit operations. This study examines the potential of automated data collection technologies to analyzing and understand the origin-destination flow patterns, which is essential for transit route planning and stop location placement. This thesis investigates the collection and analysis of data of passengers onboard San Luis Obispo Transit buses in February and March 2017 using Bluetooth (BT) and automatic passenger counter (APC) data. Five BlueMAC detectors were placed on SLO Transit buses to collect Bluetooth data. APC data was obtained from San Luis Obispo Transit. The datasets were used to establish a data processing method to exclude invalid detections, to identify and process origin and destination trips of passengers, and to make conclusions regarding passenger behavior. The filtering methods were applied to the Bluetooth data to extract counts of unique passenger information and to compare the filtered data to the ground-truth APC data. The datasets were also used to study the San Luis Obispo Downtown Farmer’s Market and its impact on transit ridership demand. The investigation revealed that after carefully employing the filters on BT data there were no consistent patterns in differences between unique passenger counts obtained from APC data and the BT data. As a result, one should be careful in employing BT data for transit OD estimation. Not every passenger enables Bluetooth or owns a Bluetooth device, so relying on the possession of Bluetooth-enabled devices may not lead to a random sample, resulting in misleading travel patterns. Based on the APC data, it was revealed that transit ridership is 40% higher during the days during which Higuera Street in Downtown San Luis Obispo is used for Farmer’s Market – a classic example of tactical urbanism. Increase in transit ridership is one of the aspects of tactical urbanism that may be further emphasized. With rapidly-evolving data collection technologies, transit data collection methods could expand beyond the traditional onboard survey. The lessons learned from this study could be expanded to provide a robust and detailed data source for transit operations and planning

The application of information technologies to public transportation

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1994.Includes bibliographical references (leaves 2218-222).by Chi Fun Jimmy Lam.M.S

Exploring the relationship between intelligent transport system capability and business agility within the Bus Rapid Transit in South Africa

Abstract: More than 65% of South Africans use public transportation to access educational, business, and financial activity. Mobility of individuals and products, particularly in metropolitan areas, suffers from delays, unreliability, absence of safety and air pollution. On the other hand, mobility demand is increasing quicker than South Africa's accessible infrastructure. Public transport services are poor in general, but this picture is transforming a high-quality mass transit system using high-capacity buses along dedicated bus lanes by implementing the Bus Rapid Transit (BRT) system. The BRT system appeared as the leading mode of urban passenger transit in the first decade of the twenty-first century after a few pioneering applications in the later portion of the twentieth century. In addition, Intelligent Transport System’s (ITS) advantages motivate both advanced and developing nations, such as South Africa, to invest in these techniques rather than spending enormous quantities on expanding the transportation network. Various stakeholders in government, academia and industry are in the process of presenting a shared vision of this new strategy and first practical steps should be taken towards this objective. Intelligent transport system capacity can provide better and more inclusive public transportation facilities to commuters through enhanced reliability and accessibility; to operators through efficiency gains; and to customers and operators in terms of cost-effectiveness and service provision affordability. International experience shows that capacities of the ITS can boost transportation profits by as much as 10-15%...D.Phil. (Engineering Management

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

Improving the network performance of urban transit systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.Includes bibliographical references (leaves 152-153).by Corey J. Wong.S.M