相关论文: Impact of unplanned service disruptions on urban p…
Understanding passengers' path choice behavior in urban rail systems is a prerequisite for effective operations and planning. This paper attempts bridging the gap by proposing a probabilistic approach to infer passengers' path choice…
Understanding patterns of demand is fundamental for fleet management of bike sharing systems. In this paper we analyze data from the Divvy system of the city of Chicago. We show that the demand of bicycles can be modeled as a multivariate…
In broad terms, accessibility measures opportunities reachable (such as shops, residents, etc.) within a given time frame. Urban Rail Transit (URT) plays a crucial role in providing accessibility, but it is susceptible to disruptions. In…
Understanding user's perception of service variability is essential to discern their overall perception of any type of (transport) service. We study the perception of waiting time variability for ride-hailing services. We carried out a…
Public transport is one of the most disrupted sectors of the COVID-19 pandemic with reported ridership drops up to 90% in majorly affected countries. As many government authorities strive to partially resume activities, public transport…
Transportation infrastructures, particularly those supporting intermodal freight, are vulnerable to natural disasters and man-made disasters that could lead to severe service disruptions. These disruptions can drastically degrade the…
Even before the start of the COVID-19 pandemic, bus ridership in the United States had attained its lowest level since 1973. If transit agencies hope to reverse this trend, they must understand how their service allocation policies affect…
The ability to accurately predict public transit ridership demand benefits passengers and transit agencies. Agencies will be able to reallocate buses to handle under or over-utilized bus routes, improving resource utilization, and…
The network structure of an urban transportation system has a significant impact on its traffic performance. This study uses network indicators along with several traffic performance measures including speed, trip length, travel time, and…
Designing and maintaining resilient transportation systems rely on identifying potential vulnerabilities and inefficiencies before crises occur. However, given the complexity of transportation networks, as well as the diversity of ways in…
Different passenger demand rates in transit stations underscore the importance of adopting operational strategies to provide a demand-responsive service. Aiming at improving passengers' travel time, the present study introduces an advanced…
"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…
A comprehensive data analysis system is implemented for the extraction of information and comparison of North American public transport systems. The system is based on network representations of the transport systems and makes use of a span…
Investigating congestion in train rapid transit systems (RTS) in today's urban cities is a challenge compounded by limited data availability and difficulties in model validation. Here, we integrate information from travel smart card data, a…
The optimal operation of transportation systems is often susceptible to unexpected disruptions. Many established control strategies reliant on mathematical models can struggle with real-world disruptions, leading to significant divergence…
Efficient and accurate incident prediction in spatio-temporal systems is critical to minimize service downtime and optimize performance. This work aims to utilize historic data to predict and diagnose incidents using spatio-temporal…
We study the emergence of congestion patterns in urban networks by modeling vehicular interaction by means of a simple traffic rule and by using a set of measures inspired by the standard Betweenness Centrality (BC). We consider a…
With the widespread installation of location-enabled devices on public transportation, public vehicles are generating massive amounts of trajectory data in real time. However, using these trajectory data for meaningful analysis requires…
This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility under mixed traffic conditions. Specifically, we first devise a…
Large events such as conferences, concerts and sports games, often cause surges in demand for ride services that are not captured in average demand patterns, posing unique challenges for routing algorithms. We propose a learning framework…