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Pereira, G. C., Wahlberg, B., Pettersson, H. & Mårtensson, J. (2023). Adaptive reference aware MPC for lateral control of autonomous vehicles. Control Engineering Practice, 132, Article ID 105403.
Open this publication in new window or tab >>Adaptive reference aware MPC for lateral control of autonomous vehicles
2023 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 132, article id 105403Article in journal (Refereed) Published
Abstract [en]

This work addresses the design of a path tracking controller for autonomous vehicles. It reformulates the Reference Aware MPC in order to guarantee closed-loop stability, while maintaining a safe and comfortable ride, and minimizing wear and tear of vehicle components. Stability is proved via Lyapunov techniques. Furthermore, to adapt the response of the controller online while in operation, a novel model for the nonlinear curvature response of the vehicle is proposed. This model is estimated online by means of Kalman filtering. Both the proposed controller and curvature response model are evaluated with simulations and through experiments on a Scania construction truck, where the advantages to the previous state-of-the-art are highlighted and discussed.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Model predictive control, Stability, Adaptive, Automatic control, Autonomous vehicles
National Category
Control Engineering Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-323429 (URN)10.1016/j.conengprac.2022.105403 (DOI)000909858200001 ()2-s2.0-85144613717 (Scopus ID)
Note

QC 20230404

Available from: 2023-02-01 Created: 2023-02-01 Last updated: 2023-04-04Bibliographically approved
Andruetto, C., Mårtensson, J. & Pernestål Brenden, A. (2023). Categorization of urban logistics concepts according to their sustainability performance. In: 2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022: . Paper presented at 2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022, Lisboa, Portugal, Nov 14 2022 - Nov 17 2022 (pp. 2708-2715). Elsevier BV, 72
Open this publication in new window or tab >>Categorization of urban logistics concepts according to their sustainability performance
2023 (English)In: 2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022, Elsevier BV , 2023, Vol. 72, p. 2708-2715Conference paper, Published paper (Refereed)
Abstract [en]

The transport-related externalities of the urban logistics system impact the urban environment and the health of the citizens: there is a need to improve the sustainability of the system. In this paper, we use a framework for sustainability performance abessment and a literature review to analyse the urban logistics concepts of electrification, consolidation, cargo bikes and automation. In the literature, there is a focus on pollution, while a holistic perspective on sustainability is lacking. A Sustainability Performance Abessment (SPA) matrix is the main result of this paper, as a tool for comparing the concepts and understanding how they can be combined to achieve integrated benefits. To make informed decisions, stakeholders need knowledge from a holistic perspective. The findings presented in this paper are a first step to achieving this required knowledge.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Automation, Cargo Bikes, Consolidation, Electrification, Sustainability, Urban Logistics
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-342804 (URN)10.1016/j.trpro.2023.11.811 (DOI)2-s2.0-85182951868 (Scopus ID)
Conference
2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022, Lisboa, Portugal, Nov 14 2022 - Nov 17 2022
Note

QC 20240208

Available from: 2024-01-31 Created: 2024-01-31 Last updated: 2024-02-08Bibliographically approved
Chen, X. & Mårtensson, J. (2023). Invariant Safe Contingency Model Predictive Control for Intersection Coordination of Mixed Traffic. In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023: . Paper presented at 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, Sep 24 2023 - Sep 28 2023 (pp. 3369-3376). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Invariant Safe Contingency Model Predictive Control for Intersection Coordination of Mixed Traffic
2023 (English)In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 3369-3376Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the coordination challenge at intersections of mixed traffic involving both Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs). To strike a balance between coordination performance and safety guarantees, we propose an invariant safe Contingency Model Predictive Control (CMPC) framework. The CMPC framework incorporates two parallel horizons for the ego vehicle: a nominal horizon optimized for performance based on the most likely prediction of the opponent HDV, and a contingency horizon designed to maintain an invariant safe backup plan for emergencies. In the contingency horizon, we consider the worst-case behavior of the human driver and formulate safety constraints using the forward reachable sets of the HDV within the planning horizon. These safety constraints are complemented by maximal invariant safe sets as terminal constraints. The two horizons are tied together by enforcing equality of the feedback inputs at the beginning of the horizons. We provide theoretical evidence supporting the recursive feasibility and persistent performance improvement of the invariant safe CMPC compared to our previously proposed nominal invariant safe Model Predictive Control (MPC). Through simulation studies, we evaluate the proposed method. The simulation results demonstrate that the CMPC approach achieves enhanced performance by reducing conservatism while simultaneously preserving the invariant safety property.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Series
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, ISSN 2153-0009
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-344360 (URN)10.1109/ITSC57777.2023.10422617 (DOI)2-s2.0-85186524798 (Scopus ID)
Conference
26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, Sep 24 2023 - Sep 28 2023
Note

QC 20240314

Part of ISBN 979-8-3503-9946-2

Available from: 2024-03-13 Created: 2024-03-13 Last updated: 2024-03-14Bibliographically approved
Emanuelsson, W., Riveiros, A. P., Li, Y., Johansson, K. H. & Mårtensson, J. (2023). Multiagent Rollout with Reshuffling for Warehouse Robots Path Planning. In: IFAC-PapersOnLine: . Paper presented at 22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023 (pp. 3027-3032). Elsevier B.V., 56
Open this publication in new window or tab >>Multiagent Rollout with Reshuffling for Warehouse Robots Path Planning
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2023 (English)In: IFAC-PapersOnLine, Elsevier B.V. , 2023, Vol. 56, p. 3027-3032Conference paper, Published paper (Refereed)
Abstract [en]

Efficiently solving path planning problems for a large number of robots is critical to the successful operation of modern warehouses. The existing approaches adopt classical shortest path algorithms to plan in environments whose cells are associated with both space and time in order to avoid collision between robots. In this work, we achieve the same goal by means of simulation in a smaller static environment. Built upon the new framework introduced in (Bertsekas, 2021a), we propose multiagent rollout with reshuffling algorithm, and apply it to address the warehouse robots path planning problem. The proposed scheme has a solid theoretical guarantee and exhibits consistent performance in our numerical studies. Moreover, it inherits from the generic rollout methods the ability to adapt to a changing environment by online replanning, which we demonstrate through examples where some robots malfunction.

Place, publisher, year, edition, pages
Elsevier B.V., 2023
Series
IFAC-PapersOnLine, ISSN 2405-8963 ; 56
Keywords
industrial applications of optimal control, multi-agent systems applied to industrial systems, Reinforcement learning control
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-343697 (URN)10.1016/j.ifacol.2023.10.1430 (DOI)2-s2.0-85184959499 (Scopus ID)
Conference
22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023
Note

QC 20240222

Part of ISBN 9781713872344

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-22Bibliographically approved
Li, Y., Karapetyan, A., Lygeros, J., Johansson, K. H. & Mårtensson, J. (2023). Performance Bounds of Model Predictive Control for Unconstrained and Constrained Linear Quadratic Problems and Beyond. In: : . Paper presented at 22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023 (pp. 8464-8469). Elsevier BV
Open this publication in new window or tab >>Performance Bounds of Model Predictive Control for Unconstrained and Constrained Linear Quadratic Problems and Beyond
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2023 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We study unconstrained and constrained linear quadratic problems and investigate the suboptimality of the model predictive control (MPC) method applied to such problems. Considering MPC as an approximate scheme for solving the related fixed point equations, we derive performance bounds for the closed-loop system under MPC. Our analysis, as well as numerical examples, suggests new ways of choosing the terminal cost and terminal constraints, which are not related to the solution of the Riccati equation of the original problem. The resulting method can have a larger feasible region, and cause hardly any loss of performance in terms of the closed-loop cost over an infinite horizon.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Model predictive control, optimal control theory
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-343166 (URN)10.1016/j.ifacol.2023.10.1133 (DOI)2-s2.0-85183625465 (Scopus ID)
Conference
22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023
Note

Part of proceedings ISBN 9781713872344

QC 20240213

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-02-13Bibliographically approved
Johansson, A., Bai, T., Johansson, K. H. & Mårtensson, J. (2023). Platoon Cooperation Across Carriers: From System Architecture to Coordination. IEEE Intelligent Transportation Systems Magazine, 15(3), 132-144
Open this publication in new window or tab >>Platoon Cooperation Across Carriers: From System Architecture to Coordination
2023 (English)In: IEEE Intelligent Transportation Systems Magazine, ISSN 1939-1390, Vol. 15, no 3, p. 132-144Article in journal (Refereed) Published
Abstract [en]

Truck platooning is a well-studied technology that has the potential to reduce both the environmental impact and operational costs of trucks. The technology has matured over the last 20 years, and the commercial rollout of platooning is approaching. Cooperation across carriers is essential for the viability of platooning; otherwise, many platooning opportunities are lost. We first present a cross-carrier platooning system architecture in which many carriers cooperate in forming platoons through a platoon-hailing service. Then, we present a cross-carrier platoon coordination approach in which each carrier optimizes its platooning plans according to the predicted plans of other carriers. A profit-sharing mechanism to even out the platooning profit in each platoon is embedded in the platoon coordination approach. Finally, a simulation study over the Swedish road network is performed to evaluate the potential of platooning under realistic conditions. The simulation study shows that the energy consumption of trucks in Sweden can be reduced by 5.4% due to platooning and that cooperation across carriers is essential to achieve significant platooning benefits.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-330106 (URN)10.1109/MITS.2022.3219997 (DOI)000899945500001 ()2-s2.0-85144749356 (Scopus ID)
Note

QC 20230626

Available from: 2023-06-26 Created: 2023-06-26 Last updated: 2023-06-26Bibliographically approved
Johansson, A., Nekouei, E., Johansson, K. H. & Mårtensson, J. (2023). Platoon Coordination in Large-Scale Networks: A Game Theoretic Approach. In: Systems and Control: Foundations and Applications (pp. 79-100). Springer Nature, Part F1964
Open this publication in new window or tab >>Platoon Coordination in Large-Scale Networks: A Game Theoretic Approach
2023 (English)In: Systems and Control: Foundations and Applications, Springer Nature , 2023, Vol. Part F1964, p. 79-100Chapter in book (Other academic)
Abstract [en]

The emerging commercial rollout of heavy-duty vehicle platooning necessitates the development of efficient platoon coordination solutions. The commercial vehicle fleet consists of vehicles owned by different transportation companies with different objectives. To capture their strategic behavior, we study platoon coordination that aims to maximize profits for individual vehicles. The interaction among vehicles is modeled as a non-cooperative game. In our cyber-physical system, we consider a large number of vehicles with fixed routes in a transportation network that can wait at hubs along their routes to form platoons. Each vehicle aims to maximize its utility function, which includes a reward for platooning and a cost for waiting. We propose open-loop coordination solutions when the vehicles decide on their waiting times at the beginning of their trips and do not update their decisions during their trips. It is shown that the corresponding game admits at least one Nash equilibrium. We also propose feedback solutions in which the vehicles are allowed to update their decisions along their routes. In a simulation study over the Swedish road network, we compare the proposed platoon coordination solutions and evaluate the benefits of non-cooperative platooning at a societal scale.

Place, publisher, year, edition, pages
Springer Nature, 2023
National Category
Control Engineering Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-341957 (URN)10.1007/978-3-031-43448-8_5 (DOI)2-s2.0-85180442454 (Scopus ID)
Note

Part of ISBN 978-3-031-43447-1

QC 20240108

Available from: 2024-01-08 Created: 2024-01-08 Last updated: 2024-01-08Bibliographically approved
Bai, T., Li, Y., Johansson, K. H. & Mårtensson, J. (2023). Rollout-Based Charging Strategy for Electric Trucks With Hours-of-Service Regulations. IEEE Control Systems Letters, 7, 2167-2172
Open this publication in new window or tab >>Rollout-Based Charging Strategy for Electric Trucks With Hours-of-Service Regulations
2023 (English)In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 7, p. 2167-2172Article in journal (Refereed) Published
Abstract [en]

Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. This letter studies the optimal charging problems of electric trucks with delivery deadlines under HoS constraints. We assume that a collection of charging and rest stations is given along a pre-planned route with known detours and that the problem data are deterministic. The goal is to minimize the total cost associated with the charging and rest decisions during the entire trip. This problem is formulated as a mixed integer program with bilinear constraints, resulting in a high computational load when applying exact solution approaches. To obtain real-time solutions, we develop a rollout-based approximate scheme, which scales linearly with the number of stations while offering solid performance guarantees. We perform simulation studies over the Swedish road network based on realistic truck data. The results show that our rollout-based approach provides near-optimal solutions to the problem in various conditions while cutting the computational time drastically.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Charging strategy, electric trucks, HoS regulations, rollout
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-332184 (URN)10.1109/LCSYS.2023.3285137 (DOI)001021356700013 ()2-s2.0-85162711815 (Scopus ID)
Note

QC 20230721

Available from: 2023-07-21 Created: 2023-07-21 Last updated: 2023-07-21Bibliographically approved
Wang, N., Xiang, Y. & Mårtensson, J. (2023). Rollout-Based Interactive Motion Planning for Automated Vehicles ∗. In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023: . Paper presented at 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, Sep 24 2023 - Sep 28 2023 (pp. 4187-4194). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Rollout-Based Interactive Motion Planning for Automated Vehicles ∗
2023 (English)In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 4187-4194Conference paper, Published paper (Refereed)
Abstract [en]

Longitudinal and lateral motion planning poses a significant challenge to achieving full autonomy in automated vehicles. This work focuses on studying the motion planning problem for automated vehicles specifically in a highwaymerging scenario. The problem is modeled as an infinite horizon optimal control problem, taking into account finite control sets for the ego agents and uncontrolled state components of surrounding traffic. For this type of control problem, obtaining a real-time solution that meets both high safety and efficiency requirements can be difficult. In this study, we employ the rollout approach, which involves online optimization following the simulation of a known baseline policy instead of relying solely on extensive offline training. We compare the performance of one and multistep lookahead rollout algorithms against several state-of-the-art benchmark policies in simulation. The simulation results indicate that the rollout algorithm significantly enhances safety while simultaneously maintaining a high average speed within the merging scenario. Furthermore, we conduct simulation studies to assess the rollout methods in adapting to varying behaviors of surrounding vehicles. Additionally, we investigate the impact of different horizon settings and the introduction of terminal cost approximation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-344361 (URN)10.1109/ITSC57777.2023.10422575 (DOI)2-s2.0-85186509770 (Scopus ID)
Conference
26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, Sep 24 2023 - Sep 28 2023
Note

Part of ISBN 9798350399462

QC 20240315

Available from: 2024-03-13 Created: 2024-03-13 Last updated: 2024-03-15Bibliographically approved
Chen, X., Jiang, F., Narri, V., Adnan, M., Mårtensson, J. & Johansson, K. H. (2023). Safe Intersection Coordination with Mixed Traffic: From Estimation to Control. In: : . Paper presented at 22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023 (pp. 5697-5702). Elsevier BV
Open this publication in new window or tab >>Safe Intersection Coordination with Mixed Traffic: From Estimation to Control
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2023 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose an integrated framework for safe intersection coordination of connected and automated vehicles (CAVs) in mixed traffic. An intelligent intersection is introduced as a central node to orchestrate state data sharing among connected agents and enable CAV to acknowledge the presence of human-driven vehicles (HDVs) beyond the line of sight of onboard sensors. Since state data shared between agents might be uncertain or delayed, we design the intelligent intersection to safely compensate for these uncertainties and delays using robust set estimation and forward reachability analysis. When the intersection receives state data from an agent, it first generates a zonotope to capture the possible measurement noise in the state estimate. Then, to compensate for communication and processing delays, it uses forward reachability analysis to enlarge the set to capture all the possible states the agent could have occupied throughout the delays. Finally, using the resulting set as the initial condition, a distributed model predictive control onboard the CAV will plan an invariant safe motion by considering the worst-case behavior of human drivers. As a result, the vehicle is guaranteed to be safe while driving through the intersection. A prototype of our proposed framework is implemented using.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Autonomous vehicles, Decentralized control and systems, Intelligent Transportation Systems, Multi-vehicle systems, Sensor integration and perception
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-343691 (URN)10.1016/j.ifacol.2023.10.508 (DOI)2-s2.0-85184961235 (Scopus ID)
Conference
22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023
Note

Part of ISBN 9781713872344

QC 20240222

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-22Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3672-5316

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