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Publications (10 of 33) Show all publications
Chen, L. & Alklind Taylor, A.-S. (2023). Guardian angel — using lighting drones to improve traffic safety, sense of security, and comfort for cyclists.
Open this publication in new window or tab >>Guardian angel — using lighting drones to improve traffic safety, sense of security, and comfort for cyclists
2023 (English)Report (Other academic)
Abstract [en]

In the picturesque municipality of Skara, Sweden, an innovative endeavor named the Skara Skyddsängel project embarked on a mission to revolutionize the concept of nighttime cycling safety. Tackling the challenge of inadequate lighting on bike paths, especially during the long, dark Swedish winters, this project proposed a novel solution: the use of drones for dynamic, on-demand bicycle path illumination. Aimed at enhancing safety and comfort for cyclists, this initiative stood at the intersection of technological innovation, sustainable mobility, and community welfare. The project's journey began with meticulous planning and development of a drone lighting system, featuring commercial drones equipped with powerful LED spotlights. The technical prowess of these drones was matched with a suite of sophisticated software for precise navigation and cyclist tracking. The endeavor then extended into the realm of user experience. A series of user studies, including initial pilot tests, focus groups, and extensive field trials, were conducted. Participants first experienced the innovative lighting in a virtual setting with VR headsets. After further improvements, cyclists were invited and test the solution in real-world settings, providing invaluable feedback. The feedback from these user studies painted a picture of success and potential. Most participants expressed a sense of increased safety and comfort under the watchful illumination of the drones. The lighting was deemed effective, with its broad and strong coverage enhancing visibility significantly. While the technology showed immense promise, it also pointed out areas for refinement, such as improving drone stability and light distribution. The project's reach extended beyond the confines of Skara through an aggressive dissemination campaign. It garnered attention through press releases, was a subject of discussion in various media outlets, and featured prominently in events like Kista Mobility Day in Stockholm and the GMC Global Mobility Call in Spain. The project's milestones and findings were also shared at international conferences, including the prestigious Human-Computer Interaction International (HCII) 2023, the annual POLIS conference 2023, as well as Transportforum 2024. The Skara Skyddsängel project stands as a testament to the potential of integrating advanced technology into everyday life to enhance safety and promote sustainable practices. It underscores the feasibility of drone-based lighting solutions as a viable alternative to traditional infrastructure, particularly in resource-constrained settings. As the project transitions from concept to reality, it highlights the importance of continued innovation, regulatory considerations, and public engagement. The road ahead calls for further technical enhancements, broader user studies, and a deep dive into the regulatory and ethical aspects of drone usage, as well as economic analysis. In conclusion, the Skara Skyddsängel project is not just about bringing light to dark paths; it's about envisioning a future where technology and human-centric design converge to create safer, more inclusive, and sustainable communities. The project not only illuminates bike paths but also lights the way for future endeavors aiming to merge technology with public welfare.

Publisher
p. 29
Series
RISE Rapport ; 2023:148
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:ri:diva-71545 (URN)978-91-89896-38-3 (ISBN)
Note

The project is financed by the SwedishInnovation Agency Vinnova with project number 2021-03044.

Available from: 2024-02-05 Created: 2024-02-05 Last updated: 2024-02-05Bibliographically approved
Alklind Taylor, A.-S., Nalin, K., Holgersson, J., Gising, A., Ferwerda, B. & Chen, L. (2023). Guardian Angel: Using Lighting Drones to Improve Traffic Safety, Sense of Security, and Comfort for Cyclists. In: Vincent G. Duffy, Heidi Krömker, Norbert A. Streitz, Shin'ichi Konomi (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Volume 14057 LNCS, Pages 209 - 223: . Paper presented at 25th International Conference on Human-Computer Interaction, HCII 2023Copenhagen, Denmark. 23 July 2023 through 28 July 2023 (pp. 209-223). Springer Science and Business Media Deutschland GmbH, 14057 LNCS
Open this publication in new window or tab >>Guardian Angel: Using Lighting Drones to Improve Traffic Safety, Sense of Security, and Comfort for Cyclists
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2023 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Volume 14057 LNCS, Pages 209 - 223, Springer Science and Business Media Deutschland GmbH , 2023, Vol. 14057 LNCS, p. 209-223Conference paper, Published paper (Refereed)
Abstract [en]

Active mobility, such as biking, faces a common challenge in Swedish municipalities due to the lack of adequate lighting during the dark winter months. Insufficient lighting infrastructure hinders individuals from choosing bicycles, despite the presence of well-maintained bike paths and a willingness to cycle. To address this issue, a project has been undertaken in the Swedish municipality of Skara for an alternative lighting solution using drones. A series of tests have been conducted based on drone prototypes developed for the selected bike paths. Participants were invited to cycle in darkness illuminated by drone lighting and share their mobility preferences and perception. This paper summarizes the users’ perception of drone lighting as an alternative to fixed lighting on bike paths, with a special focus on the impact on travel habits and the perceived sense of security and comfort. Most participants were regular cyclists who cited bad weather, time, and darkness as significant factors that deterred them from using bicycles more frequently, reducing their sense of security. With drone lighting, the participants appreciated the illumination’s moonlight-like quality and its ability to enhance their sense of security by illuminating the surroundings. On the technology side, they gave feedback on reducing the drone’s sound and addressing lighting stability issues. In summary, the test results showcase the potential of drone lighting as a viable alternative to traditional fixed lighting infrastructure, offering improved traffic safety, sense of security, and comfort. The results show the feasibility and effectiveness of this innovative approach, supporting transformation towards active and sustainable mobility, particularly in regions facing lighting challenges.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Series
Lecture notes in Computer Science, ISSN 03029743, E-ISSN 1611-3349 ; 14057
Keywords
Accident prevention; Bicycles; Drones; Sporting goods; Active mobility; Drone lighting; Lighting solutions; Perceived safety; Safety sense; Sense of security; Swedishs; Traffic safety; User perceptions; Winter months; Lighting
National Category
Infrastructure Engineering Architectural Engineering Computer Systems
Identifiers
urn:nbn:se:ri:diva-68818 (URN)10.1007/978-3-031-48047-8_13 (DOI)2-s2.0-85178505361 (Scopus ID)9783031480478 (ISBN)
Conference
25th International Conference on Human-Computer Interaction, HCII 2023Copenhagen, Denmark. 23 July 2023 through 28 July 2023
Funder
Vinnova, 2021-03044
Note

The study is supported by the Swedish innovation agency Vin-nova through the project “Skara Guardian Angel-On-demand infrastructure services for active mobility” with project number 2021-03044. The authors thank the municipality of Skara for providing support on the test site selection and preparation as well as test participants recruiting; and the test participants for spending their time sharing their experiences and opinions for improving rural mobility. We especially want to thank Maria Nordström (Skara Municipality), Henrik Svensson (University of Skövde), Mahdere DW Amanuel (RISE), Kristoffer Bergman (RISE) and Rasmus Lundqvist (RISE).

Available from: 2024-01-08 Created: 2024-01-08 Last updated: 2024-01-15Bibliographically approved
Zhang, Y., Zou, Y., Xie, Y. & Chen, L. (2023). Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure. Computer-Aided Civil and Infrastructure Engineering, 39(5), 638
Open this publication in new window or tab >>Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure
2023 (English)In: Computer-Aided Civil and Infrastructure Engineering, ISSN 1093-9687, E-ISSN 1467-8667, Vol. 39, no 5, p. 638-Article in journal (Refereed) Published
Abstract [en]

A quantitative understanding of dynamic lane-changing interaction patterns is indispensable for improving the decision-making of autonomous vehicles (AVs), especially in mixed traffic with human-driven vehicles. This paper develops a novel framework combining the hidden Markov model (HMM) and graph structure to identify the difference in dynamic interaction patterns between mandatory lane changes (MLC) and discretionary lane changes (DLC). An HMM is developed to separate the interaction patterns considering heterogeneity in lane-changing processes and reveal the temporal properties of these patterns. Conditional mutual information is used to quantify the interaction intensity, and the graph structure is used to characterize the relationship between vehicles. Finally, a case study is conducted to demonstrate the practical value of the proposed framework and validate its effectiveness in predicting lane-changing trajectories. Based on the lane-changing events extracted from a real-world trajectory dataset, the proposed analytical framework is applied to model MLC and DLC under congested traffic with levels of service E and F. The results show that there could be multiple heterogeneous dynamic interaction patterns in a lane-changing process. A comparison of MLC and DLC demonstrates that MLC involves more intense interactions and more frequent transitions of the interaction network structure, while the evolution rules of interaction patterns in DLC do not exhibit a clear trend. The findings in this study are useful for understanding the connectivity structure between vehicles in lane-changing interactions and for designing safe and smooth driving decision-making models for AVs and advanced driver-assistance systems. 

Place, publisher, year, edition, pages
John Wiley and Sons Inc, 2023
Keywords
Advanced driver assistance systems; Automobile drivers; Decision making; Graphic methods; Vehicles; Autonomous Vehicles; Decisions makings; Dynamic interaction; Graph structures; Hidden Markov model structures; Interaction pattern; Lane change; Lane changing; Markov graph; Mixed traffic; Hidden Markov models
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:ri:diva-67984 (URN)10.1111/mice.13099 (DOI)2-s2.0-85171882706 (Scopus ID)
Available from: 2023-11-24 Created: 2023-11-24 Last updated: 2024-06-10Bibliographically approved
Yang, X., Zou, Y., Zhang, H., Qu, X. & Chen, L. (2023). Improved deep reinforcement learning for car-following decision-making. Physica A: Statistical Mechanics and its Applications, 624, Article ID 128912.
Open this publication in new window or tab >>Improved deep reinforcement learning for car-following decision-making
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2023 (English)In: Physica A: Statistical Mechanics and its Applications, ISSN 0378-4371, E-ISSN 1873-2119, Vol. 624, article id 128912Article in journal (Refereed) Published
Abstract [en]

Accuracy improvement of Car-following (CF) model has attracted much attention in recent years. Although a few studies incorporate deep reinforcement learning (DRL) to describe CF behaviors, proper design of reward function is still an intractable problem. This study improves the deep deterministic policy gradient (DDPG) car-following model with stacked denoising autoencoders (SDAE), and proposes a data-driven reward representation function, which quantifies the implicit interaction between ego vehicle and preceding vehicle in car-following process. The experimental results demonstrate that DDPG-SDAE model has superior ability of imitating driving behavior: (1) validating effectiveness of the reward representation method with low deviation of trajectory; (2) demonstrating generalization ability on two different trajectory datasets (HighD and SPMD); (3) adapting to three traffic scenarios clustered by a dynamic time warping distance based k-medoids method. Compared with Recurrent Neural Networks (RNN) and intelligent driver model (IDM), DDPG-SDAE model shows better performance on the deviation of speed and relative distance. This study demonstrates superiority of a novel reward extraction method fusing SDAE into DDPG algorithm and provides inspiration for developing driving decision-making model. © 2023 Elsevier B.V.

Place, publisher, year, edition, pages
Elsevier B.V., 2023
Keywords
Car-following model, Deep reinforcement learning, Driving behavior imitation, Stacked denoising autoencoders, Behavioral research, Decision making, Learning systems, Recurrent neural networks, Auto encoders, Car-following modeling, De-noising, Deterministics, Driving behaviour, Policy gradient, Reinforcement learnings, Stacked denoising autoencoder, Reinforcement learning
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:ri:diva-65535 (URN)10.1016/j.physa.2023.128912 (DOI)2-s2.0-85161640179 (Scopus ID)
Note

knowledgmentsThis research was funded by the National Natural Science Foundation of China (Grant No. 71971160) and the ShanghaiScience and Technology Committee (Grant No. 19210745700).

Available from: 2023-06-28 Created: 2023-06-28 Last updated: 2023-06-28Bibliographically approved
Chen, T., Guo, C., Li, H., Gao, T., Chen, L., Tu, H. & Yang, J. (2022). An Improved Multimodal Trajectory Prediction Method Based on Deep Inverse Reinforcement Learning. Electronics, 11(24), Article ID 4097.
Open this publication in new window or tab >>An Improved Multimodal Trajectory Prediction Method Based on Deep Inverse Reinforcement Learning
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2022 (English)In: Electronics, E-ISSN 2079-9292, Vol. 11, no 24, article id 4097Article in journal (Refereed) Published
Abstract [en]

With the rapid development of artificial intelligence technology, the deep learning method has been introduced for vehicle trajectory prediction in the internet of vehicles, since it provides relative accurate prediction results, which is one of the critical links to guarantee security in the distributed mixed-driving scenario. In order to further enhance prediction accuracy by making full utilization of complex traffic scenes, an improved multimodal trajectory prediction method based on deep inverse reinforcement learning is proposed. Firstly, a fused dilated convolution module for better extracting raster features is introduced into the existing multimodal trajectory prediction network backbone. Then, a reward update policy with inferred goals is improved by learning the state rewards of goals and paths separately instead of original complex rewards, which can reduce the requirement for predefined goal states. Furthermore, a correction factor is introduced in the existing trajectory generator module, which can better generate diverse trajectories by penalizing trajectories with little difference. Abundant experiments on the current popular public dataset indicate that the prediction results of our proposed method are a better fit with the basic structure of the given traffic scenario in a long-term prediction range, which verifies the effectiveness of our proposed method. © 2022 by the authors.

Place, publisher, year, edition, pages
MDPI, 2022
Keywords
dilated convolution, maximum entropy inverse reinforcement learning (MaxEnt RL), multimodal trajectory prediction, rasterization
National Category
Computer Sciences
Identifiers
urn:nbn:se:ri:diva-62579 (URN)10.3390/electronics11244097 (DOI)2-s2.0-85144907401 (Scopus ID)
Note

Funding details: 2019-03418; Funding details: National Natural Science Foundation of China, NSFC, 52172379, 62001058; Funding details: National Key Research and Development Program of China, NKRDPC, 2019YFE0108300; Funding details: Fundamental Research Funds for the Central Universities, 300102241201, 300102242806, 300102242901; Funding text 1: This research was funded by the National Key R&D Program of China (2019YFE0108300), the National Natural Science Foundation of China (62001058, 52172379), the Fundamental Research Funds for the Central Universities (300102241201, 300102242901, 300102242806), and the Swedish Innovation Agency VINNOVA (2019-03418).

Available from: 2023-01-20 Created: 2023-01-20 Last updated: 2023-05-25Bibliographically approved
Poinsignon, F., Chen, L., Jiang, S., Gao, K., Badia, H. & Jenelius, E. (2022). Autonomous Vehicle Fleets for Public Transport: Scenarios and Comparisons. Green Energy and Intelligent Transportation, 1(3), Article ID 100019.
Open this publication in new window or tab >>Autonomous Vehicle Fleets for Public Transport: Scenarios and Comparisons
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2022 (English)In: Green Energy and Intelligent Transportation, E-ISSN 2773-1537, Vol. 1, no 3, article id 100019Article in journal (Refereed) Published
Abstract [en]

Autonomous vehicles (AVs) are becoming a reality and may integrate with existing public transport systems to enable the new generation of autonomous public transport. It is vital to understand what are the alternatives for AV integration from different angles such as costs, emissions, and transport performance. With the aim to support AV integration in public transport, this paper takes a typical European city as a case study for analyzing the impacts of different AV integration alternatives. A transport planning model considering AVs is developed and implemented, with a methodology to estimate the costs of the transport network. Traffic simulations are conducted to derive key variables related to AVs. An optimization process is introduced for identifying the optimal network configuration based on a given AV integration strategy, followed by the design of different AV integration scenarios, simulation, and analyses. With the proposed method, a case study is done for the city of Uppsala with presentation of detailed cost results together with key traffic statistics such as mode share. The results show that integrating AVs into public transport does not necessarily improve the overall cost efficiency. Based on the results and considering the long transition period to fully autonomous vehicles, it is recommended that public transport should consider a gradual introduction of AVs with more detailed analysis on different combination and integration alternatives of bus services and AVs.

National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:ri:diva-63411 (URN)10.1016/j.geits.2022.100019 (DOI)
Available from: 2023-01-30 Created: 2023-01-30 Last updated: 2023-05-25Bibliographically approved
Yang, X., Zou, Y. & Chen, L. (2022). Operation analysis of freeway mixed traffic flow based on catch-up coordination platoon. Accident Analysis and Prevention, 175, Article ID 106780.
Open this publication in new window or tab >>Operation analysis of freeway mixed traffic flow based on catch-up coordination platoon
2022 (English)In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 175, article id 106780Article in journal (Refereed) Published
Abstract [en]

As one of the innovative technologies of intelligent transportation systems (ITS), Connected and Autonomous Vehicles (CAVs) have been deployed gradually. Given that there will be a long transition period before reaching a fully CAVs environment, it is crucial to assess the potential impacts of CAVs on mixed traffic flow. Considering platoon formation process, this study develops a platoon cooperation strategy based on “catch-up” mechanism, and then analyzes the impact on fundamental diagram, traffic oscillation, and traffic safety within mixed traffic. Simulation results show that with an increasing market penetration rate (MPR) of CAVs, road capacity shows an increasing trend. Compared with base scenario, a clear increase in road capacity is also observed under platoon scenario. With an increasing MPR, traffic oscillation is shown to reduce largely. Furthermore, the proposed platoon strategy could dampen frequent shockwaves and shorten the propagation range of waves. Regarding traffic safety, multiple surrogate safety measures (SSMs) are used to evaluate the traffic risk: including Criticality Index Function (CIF), Potential Index for Collision with Urgent Deceleration (PICUD), and Deceleration Rate to Avoid a Crash (DRAC). With increasing MPR, collision risk identified by CIF and DRAC shows an increase tendency, while that identified by PICUD has no apparent trend. Furthermore, the platoon strategy is shown to increase the severity of traffic conflicts significantly. Overall, this study provides novel insights into CAVs deployment through the analysis of platoon strategy. 

Place, publisher, year, edition, pages
Elsevier Ltd, 2022
Keywords
Autonomous and connected vehicles, Fundamental diagram, Microscopic simulation, Traffic oscillation, Traffic safety, Accident prevention, Autonomous vehicles, Intelligent systems, Motor transportation, Risk assessment, Autonomous and connected vehicle, Market penetration, Mixed traffic flow, Penetration rates, Road capacity, Roads and streets
National Category
Computational Mathematics
Identifiers
urn:nbn:se:ri:diva-60054 (URN)10.1016/j.aap.2022.106780 (DOI)2-s2.0-85135533304 (Scopus ID)
Note

 Funding details: National Natural Science Foundation of China, NSFC, 71971160; Funding details: Science and Technology Commission of Shanghai Municipality, STCSM, 19210745700; Funding details: China Scholarship Council, CSC; Funding details: Fundamental Research Funds for the Central Universities, 22120220013; Funding text 1: This research was funded by the National Natural Science Foundation of China (Grant No. 71971160 ), the Shanghai Science and Technology Committee (Grant no. 19210745700) and the Fundamental Research Funds for the Central Universities (Grant no. 22120220013). The first author would like to thank the China Scholarship Council (CSC) for financial support and Prof. Xiaobo Qu for his supervision on the manuscript.

Available from: 2022-10-04 Created: 2022-10-04 Last updated: 2023-05-25Bibliographically approved
Chen, L., Torstensson, M. & Habibovic, A. (2022). System of Systems for emergency response: the case with CAVs on highways. In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. Volume 2022-October, 2022, Pages 839-844: . Paper presented at 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022, 8 October 2022 through 12 October 2022 (pp. 839-844). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>System of Systems for emergency response: the case with CAVs on highways
2022 (English)In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. Volume 2022-October, 2022, Pages 839-844, Institute of Electrical and Electronics Engineers Inc. , 2022, p. 839-844Conference paper, Published paper (Refereed)
Abstract [en]

Emergency response system is a complex system of systems (SoS). The introduction of connected and autonomous vehicles (CAVs) introduces an extra dimension into the complexity. Future emergency response must be able to take into account of the autonomous vehicles with different automation levels and leverage the increasing connectivity and automation for efficient emergency response. Architecture frameworks have long been used for system engineering for large complex systems. The emerging unified architecture framework converges previous architecture frameworks for a unified one towards both military and civilian use. Based on the scenario of emergency response with CAVs on highways, this paper motivates an enterprise architecture for emergency response system of systems (ERSoS) with identification of the key challenges and opportunities in addition to a proposal of required capabilities. The work is a first iteration of an enterprise architecture for ERSoS with CAVs and forms part of the overall ERSoS architecture development process. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2022
Keywords
Autonomous vehicles, Computer architecture, Emergency services, Architecture frameworks, Automation levels, Complex system of systems, Emergency response, Emergency response systems, Enterprise Architecture, Extra dimensions, Large complex systems, System-of-systems, System of systems
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:ri:diva-61222 (URN)10.1109/ITSC55140.2022.9922378 (DOI)2-s2.0-85141841092 (Scopus ID)9781665468800 (ISBN)
Conference
25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022, 8 October 2022 through 12 October 2022
Note

Funding text 1: *This work is supported by the Swedish Innovation Agency Vinnova through projects ICV-Safe: Testing safety of intelligent connected vehicles in open and mixed road environment, and SoSER: Systme of Systems for Emergency Response.

Available from: 2022-12-07 Created: 2022-12-07 Last updated: 2024-05-22Bibliographically approved
Habibovic, A. & Chen, L. (2021). Connected Automated Vehicles: Technologies, Developments, and Trends. In: Roger Vickerman (Ed.), International Encyclopedia of Transportation: (pp. 180-188). Elsevier
Open this publication in new window or tab >>Connected Automated Vehicles: Technologies, Developments, and Trends
2021 (English)In: International Encyclopedia of Transportation / [ed] Roger Vickerman, Elsevier, 2021, p. 180-188Chapter in book (Other academic)
Place, publisher, year, edition, pages
Elsevier, 2021
Keywords
Connected automated vehicles, autonomous vehicles, vehicle communications
National Category
Transport Systems and Logistics Telecommunications
Identifiers
urn:nbn:se:ri:diva-56299 (URN)10.1016/B978-0-08-102671-7.10110-1 (DOI)
Available from: 2021-09-02 Created: 2021-09-02 Last updated: 2023-05-25Bibliographically approved
Autili, M., Chen, L., Englund, C., Pompilio, C. & Tivoli, M. (2021). Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination. IEEE transactions on intelligent transportation systems (Print), 22(4), 2088-2099
Open this publication in new window or tab >>Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination
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2021 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 22, no 4, p. 2088-2099Article in journal (Refereed) Published
Abstract [en]

With the emerging connected automated vehicles, 5G and Internet of Things (IoT), vehicles and road infrastructure become connected and cooperative, enabling Cooperative Intelligent Transport Systems (C-ITS). C-ITS are transport system of systems that involves many stakeholders from different sectors. While running their own systems and providing services independently, stakeholders cooperate with each other for improving the overall transport performance such as safety, efficiency and sustainability. Massive information on road and traffic is already available and provided through standard services with different protocols. By reusing and composing the available heterogeneous services, novel value-added applications can be developed. This paper introduces a choreography-based service composition platform, i.e. the CHOReVOLUTION Integrated Development and Runtime Environment (IDRE), and it reports on how the IDRE has been successfully exploited to accelerate the reuse-based development of a choreography-based Urban Traffic Coordination (UTC) application. The UTC application takes the shape of eco-driving services that through real-time eco-route evaluation assist the drivers for the most eco-friendly and comfortable driving experience. The eco-driving services are realized through choreography and they are exploited through a mobile app for online navigation. From specification to deployment to execution, the CHOReVOLUTION IDRE has been exploited to support the realization of the UTC application by automatizing the generation of the distributed logic to properly bind, coordinate and adapt the interactions of the involved parties. The benefits brought by CHOReVOLUTION IDRE have been assessed through the evaluation of a set of Key Performance Indicators (KPIs).

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2021
Keywords
C-ITS, eco-driving, Service choreographies, service composition, system of systems.
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:ri:diva-52916 (URN)10.1109/TITS.2021.3059394 (DOI)2-s2.0-85101755202 (Scopus ID)
Available from: 2021-04-09 Created: 2021-04-09 Last updated: 2023-05-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9808-1483

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