Related papers: How bad is time variability for users in mobility …
Mobility-on-Demand (MoD) services have been an active research topic in recent years. Many studies focused on developing control algorithms to supply efficient services. To cope with a large search space to solve the underlying vehicle…
Travel time savings are usually the most substantial economic benefit of transport infrastructure projects. However, questions surround whether small time savings are as valuable per unit as larger savings. Thresholds in individual choice…
Accurate and reliable bus travel time prediction in real-time is essential for improving the operational efficiency of public transportation systems. However, this remains a challenging task due to the limitations of existing models and…
Time-of-use pricing is promoted to manage demand at public EV charging stations, yet its effectiveness depends on short run flexibility and local constraints. Using station by day by hour data from Shenzhen and Amsterdam, we estimate…
Uncertainty is inevitable in transportation system due to the stochastic change of demand and supply. It is one of the most important factors affecting travelers' choice behavior. Based on the framework of Vickrey's bottleneck model, we…
Uncoordinated charging of a rapidly growing number of electric vehicles (EVs) and the uncertainty associated with renewable energy resources may constitute a critical issue for the electric mobility (E-Mobility) in the transportation system…
The increased uptake of electric vehicles (EVs) leads to increased demand for electricity, and sometimes pressure on power grids. Uncoordinated charging of EVs may result in stress on distribution networks, and often some form of…
Time-varying pricing tariffs incentivize consumers to shift their electricity demand and reduce costs, but may increase the energy burden for consumers with limited response capability. The utility must thus balance affordability and…
Many e-commerce marketplaces offer their users fast delivery options for free to meet the increasing needs of users, imposing an excessive burden on city logistics. Therefore, understanding e-commerce users' preference for delivery options…
Transient cloud servers such as Amazon Spot instances, Google Preemptible VMs, and Azure Low-priority batch VMs, can reduce cloud computing costs by as much as $10\times$, but can be unilaterally preempted by the cloud provider.…
Safe operation of connected vehicle platoons under stochastic disturbances and time-delayed dynamics requires accurate quantification of rare but dangerous events, such as inter-vehicle collisions. We propose a rigorous framework for…
The integration of electric vehicles (EVs) with the energy grid has become an important area of research due to the increasing EV penetration in today's transportation systems. Under appropriate management of EV charging and discharging,…
The rising demand for electric vehicles (EVs) worldwide necessitates the development of robust and accessible charging infrastructure, particularly in developing countries where electricity disruptions pose a significant challenge. Earlier…
The main goal of this paper is to time-effectively route and schedule a fleet of Electric Vehicles (EVs) on a road network in order to serve a set of customers. In particular, we aim to propose an optimized route planning by exploiting the…
Recent advancements in Connected Vehicle (CV) technology have prompted research on leveraging CV data for more effective traffic management. Despite the low penetration rate, such detailed CV data has demonstrated great potential in…
In this paper we propose a framework to analyze iterative first-order optimization algorithms for time-varying convex optimization. We assume that the temporal variability is caused by a time-varying parameter entering the objective, which…
Network Utility Maximization (NUM) provides the key conceptual framework to study resource allocation amongst a collection of users/entities across disciplines as diverse as economics, law and engineering. In network engineering, this…
We study a routing and appointment scheduling problem with uncertain service and travel times arising from home service practice. Specifically, given a set of customers within a service region that an operator needs to serve, we seek to…
This paper introduces a novel stochastic control framework to enhance the capabilities of automated investment managers, or robo-advisors, by accurately inferring clients' investment preferences from past activities. Our approach leverages…
We present the conditional value-at-risk (CVaR) in the context of Markov chains and Markov decision processes with reachability and mean-payoff objectives. CVaR quantifies risk by means of the expectation of the worst p-quantile. As such it…