相关论文: Public Transit for Special Events: Ridership Predi…

Many public transportation systems are unable to keep up with growing passenger demand as the population grows in urban areas. The slow or lack of improvements for public transportation pushes people to use private transportation modes,…

A reliable and accurate knowledge of the ridership in public transportation networks is crucial for public transport operators and public authorities to be aware of their network's use and optimize transport offering. Several techniques to…

The potential of integrating public transit with ridesharing includes shorter travel time for commuters and higher occupancy rate of personal vehicles and public transit ridership. In this paper, we describe a centralized transit system…

In a transport network, the onboard occupancy is key for gaining insights into travelers' habits and adjusting the offer. Traditionally, operators have relied on field studies to evaluate ridership of a typical workday. However, automated…

In an effort to improve user satisfaction and transit image, transit service providers worldwide offer delay compensations. Smart card data enables the estimation of passenger delays throughout the network and aid in monitoring service…

Arrival time prediction (ATP) of public transport vehicles is essential in improving passenger experience and supporting traffic management. Deep learning has demonstrated outstanding performance in ATP due to its ability to model…

The metro system is playing an increasingly important role in the urban public transit network, transferring a massive human flow across space everyday in the city. In recent years, extensive research studies have been conducted to improve…

Suppose $A$ and $B$ are two stations within the mass rapid transit network of a city. Both stations see approximately the same average daily number of passengers entering and exiting their gates. However, passengers are evenly distributed…

Increasing urban concentration raises operational challenges that can benefit from integrated monitoring and decision support. Such complex systems need to leverage the full stack of analytical methods, from state estimation using…

Public transportation is a fundamental infrastructure for the daily mobility in cities. Although its capacity is prepared for the usual demand, congestion may rise when huge crowds concentrate in special events such as massive…

In the context of rail transit operations, real-time passenger flow prediction is essential; however, most models primarily focus on normal conditions, with limited research addressing incident situations. There are several intrinsic…

Accurate forecasting of bus ridership (passengers numbers) is crucial for efficient management and optimization of public transport systems. Traditional forecasting models often fail to capture the unique and localized dynamics of different…

"An advanced city is not a place where the poor move about in cars, rather it's where even the rich use public transportation". This is what Enrique Penalosa, the celebrated ex-mayor of Bogota once said. However, in order to achieve this…

This study contributes to the advancement of vehicle occupancy estimation in Automated Guideway Transit (AGT) systems using Wi-Fi probe requests and deep learning models. We propose a comprehensive framework for evaluating various…

Urban rail transit often operates with high service frequencies to serve heavy passenger demand during rush hours. Such operations can be delayed by two types of congestion: train congestion and passenger congestion, both of which interact…

Due to increasing concerns about environmental impact, operating costs, and energy security, public transit agencies are seeking to reduce their fuel use by employing electric vehicles (EVs). However, because of the high upfront cost of…

Congestion; operational delays due to a vicious circle of passenger-congestion and train-queuing; is an escalating problem for metro systems because it has negative consequences from passenger discomfort to eventual mode-shifts. Congestion…

The analysis of the transportation usage rate provides opportunities for evaluating the efficacy of the transportation service offered by proposing an indicator that integrates actual demand and capacity. This study aims to develop a…

Bus transit systems are the backbone of public transportation in the United States. An important indicator of the quality of service in such infrastructures is on-time performance at stops, with published transit schedules playing an…

This paper proposes a self-calibrated transit service monitoring framework that aims to obtain the performance of a transit system using automated collected data. We first introduce an event-based transit simulation model, which allows the…