Search Results for author: Nikolce Murgovski

Found 8 papers, 0 papers with code

Integrated Charging Scheduling and Operational Control for an Electric Bus Network

no code implementations1 Sep 2023 Rémi Lacombe, Nikolce Murgovski, Sébastien Gros, Balázs Kulcsár

We propose a hierarchical control framework to solve this problem, where the charging and operational decisions are taken jointly by solving a mixed-integer linear program in the high-level control layer.

Scheduling

Interaction-Aware Trajectory Prediction and Planning in Dense Highway Traffic using Distributed Model Predictive Control

no code implementations24 Aug 2023 Erik Börve, Nikolce Murgovski, Leo Laine

In this paper we treat optimal trajectory planning for an autonomous vehicle (AV) operating in dense traffic, where vehicles closely interact with each other.

Model Predictive Control Trajectory Planning +1

Prediction of Time and Distance of Trips Using Explainable Attention-based LSTMs

no code implementations27 Mar 2023 Ebrahim Balouji, Jonas Sjöblom, Nikolce Murgovski, Morteza Haghir Chehreghani

Finally, the last model is based on two parallel At-LSTMs, where similarly, each At-LSTM predicts time and distance separately through fully connected layers.

Conflict-free Charging and Real-time Control for an Electric Bus Network

no code implementations13 Oct 2022 Rémi Lacombe, Nikolce Murgovski, Sébastien Gros, Balázs Kulcsár

The rapid adoption of electric buses by transit agencies around the world is leading to new challenges in the planning and operation of bus networks.

Scheduling

Optimal Thermal Management, Charging, and Eco-driving of Battery Electric Vehicles

no code implementations3 May 2022 Ahad Hamednia, Nikolce Murgovski, Jonas Fredriksson, Jimmy Forsman, Mitra Pourabdollah, Viktor Larsson

The formulated problem is then transformed into a hybrid dynamical system, where the dynamics in driving and charging modes are modeled with different functions and with different state and control vectors.

Computational Efficiency Management

A Unified Framework for Online Trip Destination Prediction

no code implementations12 Jan 2021 Victor Eberstein, Jonas Sjöblom, Nikolce Murgovski, Morteza Haghir Chehreghani

In this paper, we present a unified framework for trip destination prediction in an online setting, which is suitable for both online training and online prediction.

Autonomous Driving Clustering

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