Related papers: Forecasting and Mitigating Disruptions in Public B…
Affordable public transit services are crucial for communities since they enable residents to access employment, education, and other services. Unfortunately, transit services that provide wide coverage tend to suffer from relatively low…
Mobility-on-demand (MoD) systems represent a rapidly developing mode of transportation wherein travel requests are dynamically handled by a coordinated fleet of vehicles. Crucially, the efficiency of an MoD system highly depends on how well…
Recently, the traffic congestion in modern cities has become a growing worry for the residents. As presented in Baidu traffic report, the commuting stress index has reached surprising 1.973 in Beijing during rush hours, which results in…
This paper presents a mathematical model for the routing of multicommodity freight in an intermodal network under disruptions. A stochastic mixed-integer program was formulated to minimize not only operational costs of various modes and…
Advanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics…
Forecasting traffic flows is a central task in intelligent transportation system management. Graph structures have shown promise as a modeling framework, with recent advances in spatio-temporal modeling via graph convolution neural…
We derive a learning framework to generate routing/pickup policies for a fleet of autonomous vehicles tasked with servicing stochastically appearing requests on a city map. We focus on policies that 1) give rise to coordination amongst the…
Supervised Machine Learning is an innovative method that aims to mimic human learning by using past experiences. In this study, we utilize supervised machine learning algorithms to analyze the factors that contribute to the punctuality of…
Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies in order to provide a high customer quality of service (QoS). Previous works on autonomous MOD systems have developed methods for rebalancing single…
Recent research in the social sciences has identified situations in which small changes in the way that information is provided to consumers can have large aggregate effects on behavior. This has been promoted in popular media in areas of…
Already today, driver assistance systems help to make daily traffic more comfortable and safer. However, there are still situations that are quite rare but are hard to handle at the same time. In order to cope with these situations and to…
Over the past few decades, efforts of road traffic management and practice have predominantly focused on maximizing system efficiency and mitigating congestion from a system perspective. This efficiency-driven approach implies the equal…
Balancing traffic flow by influencing drivers' route choices to alleviate congestion is becoming increasingly more appealing in urban traffic planning. Here, we introduce a discrete dynamical model comprising users who make their own…
Modelling, simulation, and forecasting offer a means of facilitating better planning and decision-making. These quantitative approaches can add value beyond traditional methods that do not rely on data and are particularly relevant for…
Advances in artificial intelligence (AI) including foundation models (FMs), are increasingly transforming human society, with smart city driving the evolution of urban living.Meanwhile, vehicle crowdsensing (VCS) has emerged as a key…
This paper presents a queueing network approach to the analysis and control of mobility-on-demand (MoD) systems for urban personal transportation. A MoD system consists of a fleet of vehicles providing one-way car sharing service and a team…
For past several decades, research efforts in population modelling has proven its efficacy in understanding the basic information about residential and commercial areas, as well as for the purposes of planning, development and improvement…
The literature on transportation network companies (TNCs), also known as ride-hailing services, has often characterized these service providers as predominantly substitutive to public transit (PT). However, as TNC markets expand and mature,…
Autonomous mobility-on-demand (AMoD) systems, centrally coordinated fleets of self-driving vehicles, offer a promising alternative to traditional ride-hailing by improving traffic flow and reducing operating costs. Centralized control in…
Understanding the behavior of road users is of vital importance for the development of trajectory prediction systems. In this context, the latest advances have focused on recurrent structures, establishing the social interaction between the…