相关论文: Sharing Behavior in Ride-hailing Trips: A Machine …
Ride-pooling has become an important service option offered by ride-hailing platforms as it serves multiple trip requests in a single ride. By leveraging customer data, connected vehicles, and efficient assignment algorithms, ride-pooling…
Travel demand analysis at the planning stage is important for metro system development. In practice, travel demand can be affected by various factors. This paper focuses on investigating the factors influencing Taipei metro ridership at…
Transportation services play a crucial part in the development of modern smart cities. In particular, on-demand ridesharing services, which group together passengers with similar itineraries, are already operating in several metropolitan…
This study examines fairness within the rideshare industry, focusing on both drivers' wages and riders' trip fares. Through quantitative analysis, we found that drivers' hourly wages are significantly influenced by factors such as…
Human mobility regularity is crucial for understanding urban dynamics and informing decision-making processes. This study first quantifies the periodicity in complex human mobility data as a sparse identification of dominant positive…
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…
This paper studies the effects of economies of density in transportation markets, focusing on ridesharing. Our theoretical model predicts that (i) economies of density skew the supply of drivers away from less dense regions, (ii) the skew…
The usability of ride-sharing services like Uber and Lyft has been considerably improved by advancements in cellular communications. Such a tech-driven transportation system can reduce the number of private cars, in roads with limited…
While ride-hailing services offer increased travel flexibility and convenience, persistent nighttime safety concerns significantly reduce women's willingness to use them. Existing research often treats women as a homogeneous group,…
Ride-sharing is a modern urban-mobility paradigm with tremendous potential in reducing congestion and pollution. Demand-aware design is a promising avenue for addressing a critical challenge in ride-sharing systems, namely joint…
Eco-friendly service options (EFSOs) aim to reduce personal carbon emissions, yet their eco-friendly framing may permit increased consumption, weakening their intended impact. Such rebound effects remain underexamined in HCI, including how…
Dockless bike-sharing (DBS) users often encounter difficulties in finding available bikes at their preferred times and locations. This study examines the determinants of the users' mode shifts in the context of bike absence, using survey…
Vehicle-sharing systems -- such as bike-, car-, or motorcycle-sharing systems -- have become increasingly popular in big cities in recent years. On the one hand, they provide a cheaper and environmentally friendlier means of transportation…
The success of modern ride-sharing platforms crucially depends on the profit of the ride-sharing fleet operating companies, and how efficiently the resources are managed. Further, ride-sharing allows sharing costs and, hence, reduces the…
While multimodal mobility systems have the potential to bring many benefits to travelers, drivers, the environment, and traffic congestion, such systems typically involve multiple non-cooperative decision-makers who may selfishly optimize…
Accurately forecasting ridesourcing demand is important for effective transportation planning and policy-making. With the rise of Artificial Intelligence (AI), researchers have started to utilize machine learning models to forecast travel…
Despite the potential of online sharing economy platforms such as Uber, Lyft, or Foodora to democratize the labor market, these services are often accused of fostering unfair working conditions and low wages. These problems have been…
Autonomous mobility on demand services have the potential to disrupt the future mobility system landscape. Ridepooling services in particular can decrease land consumption and increase transportation efficiency by increasing the average…
This paper presents a framework to incorporate ride-pooling from a mesoscopic point of view, within time-invariant network flow models of Mobility-on-Demand systems. The resulting problem structure remains identical to a standard network…
Understanding the drivers of urban mobility is vital for epidemiology, urban planning, and communication networks. Human movements have so far been studied by observing people's positions in a given space and time, though most recent models…