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Cristofer Englund
RISE Research Institutes of Sweden

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Journal article
Published: 18 May 2021 in Smart Cities
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Smart cities and communities (SCC) constitute a new paradigm in urban development. SCC ideate a data-centered society aimed at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with Internet of Things enables data collection and with the help of artificial intelligence (AI) situation awareness can be obtained to feed the SCC actors with enriched knowledge. This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control. Perception, smart traffic control and driver modeling are described along with open research challenges and standardization to help introduce advanced driver assistance systems and automated vehicle functionality in traffic. To fully realize the potential of SCC, to create a holistic view on a city level, availability of data from different stakeholders is necessary. Further, though AI technologies provide accurate predictions and classifications, there is an ambiguity regarding the correctness of their outputs. This can make it difficult for the human operator to trust the system. Today there are no methods that can be used to match function requirements with the level of detail in data annotation in order to train an accurate model. Another challenge related to trust is explainability: models can have difficulty explaining how they came to certain conclusions, so it is difficult for humans to trust them.

ACS Style

Cristofer Englund; Eren Aksoy; Fernando Alonso-Fernandez; Martin Cooney; Sepideh Pashami; Björn Åstrand. AI Perspectives in Smart Cities and Communities to Enable Road Vehicle Automation and Smart Traffic Control. Smart Cities 2021, 4, 783 -802.

AMA Style

Cristofer Englund, Eren Aksoy, Fernando Alonso-Fernandez, Martin Cooney, Sepideh Pashami, Björn Åstrand. AI Perspectives in Smart Cities and Communities to Enable Road Vehicle Automation and Smart Traffic Control. Smart Cities. 2021; 4 (2):783-802.

Chicago/Turabian Style

Cristofer Englund; Eren Aksoy; Fernando Alonso-Fernandez; Martin Cooney; Sepideh Pashami; Björn Åstrand. 2021. "AI Perspectives in Smart Cities and Communities to Enable Road Vehicle Automation and Smart Traffic Control." Smart Cities 4, no. 2: 783-802.

Journal article
Published: 24 February 2021 in IEEE Transactions on Intelligent Transportation Systems
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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).

ACS Style

Marco Autili; Lei Chen; Cristofer Englund; Claudio Pompilio; Massimo Tivoli. Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination. IEEE Transactions on Intelligent Transportation Systems 2021, PP, 1 -12.

AMA Style

Marco Autili, Lei Chen, Cristofer Englund, Claudio Pompilio, Massimo Tivoli. Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination. IEEE Transactions on Intelligent Transportation Systems. 2021; PP (99):1-12.

Chicago/Turabian Style

Marco Autili; Lei Chen; Cristofer Englund; Claudio Pompilio; Massimo Tivoli. 2021. "Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-12.

Journal article
Published: 15 December 2020 in IEEE Transactions on Intelligent Transportation Systems
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Platooning refers to a group of vehicles that--enabled by wireless vehicle-to-vehicle (V2V) communication and vehicle automation--drives with short inter-vehicular distances. Before its deployment on public roads, several challenging traffic situations need to be handled. Among the challenges are cut-in situations, where a conventional vehicle--a vehicle that has no automation or V2V communication--changes lane and ends up between vehicles in a platoon. This paper presents results from a simulation study of a scenario, where a conventional vehicle, approaching from an on-ramp, merges into a platoon of five cars on a highway. We created the scenario with four platooning gaps: 15, 22.5, 30, and 42.5 meters. During the study, the conventional vehicle was driven by 37 test persons, who experienced all the platooning gaps using a driving simulator. The participants' opinions towards safety, comfort, and ease of driving between the platoon in each gap setting were also collected through a questionnaire. The results suggest that a 15-meter gap prevents most participants from cutting in, while causing potentially dangerous maneuvers and collisions when cut-in occurs. A platooning gap of at least 30 meters yield positive opinions from the participants, and facilitating more smooth cut-in maneuvers while less collisions were observed.

ACS Style

Maytheewat Aramrattana; Tony Larsson; Cristofer Englund; Jonas Jansson; Arne Nabo. A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations. IEEE Transactions on Intelligent Transportation Systems 2020, PP, 1 -7.

AMA Style

Maytheewat Aramrattana, Tony Larsson, Cristofer Englund, Jonas Jansson, Arne Nabo. A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations. IEEE Transactions on Intelligent Transportation Systems. 2020; PP (99):1-7.

Chicago/Turabian Style

Maytheewat Aramrattana; Tony Larsson; Cristofer Englund; Jonas Jansson; Arne Nabo. 2020. "A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-7.

Chapter
Published: 10 December 2020 in Advanced Controllers for Smart Cities
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Reducing fuel consumption is one of the major benefits of platooning. While introducing platooning in mixed traffic, surrounding traffic will interfere with the platoon, risking a loss in fuel savings. In this work, a method for estimating potential fuel loss due to cut-ins in platoons is presented. Based on interviews with truck drivers with experience from platooning, and naturalistic data from previous research, we estimate the potential loss of fuel savings due to cut-ins and compare two scenarios with different amounts of traffic. The results show that platoons spend as much as 20% of time in cut-ins on typical European roads, reducing fuel savings in platooning from 13% down to 10%. Consequently, avoiding cut-ins has a positive environmental effect worth considering.

ACS Style

Alexey Voronov; Jonas Andersson; Cristofer Englund. Cut-ins in Truck Platoons: Modeling Loss of Fuel Savings. Advanced Controllers for Smart Cities 2020, 11 -26.

AMA Style

Alexey Voronov, Jonas Andersson, Cristofer Englund. Cut-ins in Truck Platoons: Modeling Loss of Fuel Savings. Advanced Controllers for Smart Cities. 2020; ():11-26.

Chicago/Turabian Style

Alexey Voronov; Jonas Andersson; Cristofer Englund. 2020. "Cut-ins in Truck Platoons: Modeling Loss of Fuel Savings." Advanced Controllers for Smart Cities , no. : 11-26.

Journal article
Published: 23 December 2018 in Transportation Research Part D: Transport and Environment
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Free-floating car-sharing (FFCS) allows users to book a vehicle through their phone, use it and return it anywhere within a designated area in the city. FFCS has the potential to contribute to a transition to low-carbon mobility if the vehicles are electric, and if the usage does not displace active travel or public transport use. The aim of this paper is to study what travel time and usage patterns of the vehicles among the early adopters of the service reveal about these two issues. We base our analysis on a dataset containing rentals from 2014 to 2017, for 12 cities in Europe and the United States. For seven of these cities, we have collected travel times for equivalent trips with walking, biking, public transport and private car. FFCS services are mainly used for shorter trips with a median rental time of 27 min and actual driving time closer to 15 min. When comparing FFCS with other transport modes, we find that rental times are generally shorter than the equivalent walking time but longer than cycling. For public transport, the picture is mixed: for some trips there is no major time gain from taking FFCS, for others it could be up to 30 min. For electric FFCS vehicles rental time is shorter and the number of rentals per car and day are slightly fewer compared to conventional vehicles. Still, evidence from cities with an only electric fleet show that these services can be electrified and reach high levels of utilization.

ACS Style

Frances Sprei; Shiva Habibi; Cristofer Englund; Stefan Pettersson; Alex Voronov; Johan Wedlin. Free-floating car-sharing electrification and mode displacement: Travel time and usage patterns from 12 cities in Europe and the United States. Transportation Research Part D: Transport and Environment 2018, 71, 127 -140.

AMA Style

Frances Sprei, Shiva Habibi, Cristofer Englund, Stefan Pettersson, Alex Voronov, Johan Wedlin. Free-floating car-sharing electrification and mode displacement: Travel time and usage patterns from 12 cities in Europe and the United States. Transportation Research Part D: Transport and Environment. 2018; 71 ():127-140.

Chicago/Turabian Style

Frances Sprei; Shiva Habibi; Cristofer Englund; Stefan Pettersson; Alex Voronov; Johan Wedlin. 2018. "Free-floating car-sharing electrification and mode displacement: Travel time and usage patterns from 12 cities in Europe and the United States." Transportation Research Part D: Transport and Environment 71, no. : 127-140.

Journal article
Published: 15 November 2017 in IEEE Transactions on Intelligent Transportation Systems
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Cooperative adaptive cruise control and platooning are well-known applications in the field of cooperative automated driving. However, extension toward maneuvering is desired to accommodate common highway maneuvers, such as merging, and to enable urban applications. To this end, a layered control architecture is adopted. In this architecture, the tactical layer hosts the interaction protocols, describing the wireless information exchange to initiate the vehicle maneuvers, supported by a novel wireless message set, whereas the operational layer involves the vehicle controllers to realize the desired maneuvers. This hierarchical approach was the basis for the Grand Cooperative Driving Challenge (GCDC), which was held in May 2016 in The Netherlands. The GCDC provided the opportunity for participating teams to cooperatively execute a highway lane-reduction scenario and an urban intersection-crossing scenario. The GCDC was set up as a competition and, hence, also involving assessment of the teams' individual performance in a cooperative setting. As a result, the hierarchical architecture proved to be a viable approach, whereas the GCDC appeared to be an effective instrument to advance the field of cooperative automated driving.

ACS Style

Jeroen Ploeg; Elham Semsar-Kazerooni; Alejandro I. Morales Medina; Jan F. C. M. De Jongh; Jacco Van De Sluis; Alexey Voronov; Cristofer Englund; Reinder J. Bril; Hrishikesh Salunkhe; Alvaro Arrue; Aitor Ruano; Lorena Garcia-Sol; Ellen Van Nunen; Nathan Van De Wouw. Cooperative Automated Maneuvering at the 2016 Grand Cooperative Driving Challenge. IEEE Transactions on Intelligent Transportation Systems 2017, 19, 1213 -1226.

AMA Style

Jeroen Ploeg, Elham Semsar-Kazerooni, Alejandro I. Morales Medina, Jan F. C. M. De Jongh, Jacco Van De Sluis, Alexey Voronov, Cristofer Englund, Reinder J. Bril, Hrishikesh Salunkhe, Alvaro Arrue, Aitor Ruano, Lorena Garcia-Sol, Ellen Van Nunen, Nathan Van De Wouw. Cooperative Automated Maneuvering at the 2016 Grand Cooperative Driving Challenge. IEEE Transactions on Intelligent Transportation Systems. 2017; 19 (4):1213-1226.

Chicago/Turabian Style

Jeroen Ploeg; Elham Semsar-Kazerooni; Alejandro I. Morales Medina; Jan F. C. M. De Jongh; Jacco Van De Sluis; Alexey Voronov; Cristofer Englund; Reinder J. Bril; Hrishikesh Salunkhe; Alvaro Arrue; Aitor Ruano; Lorena Garcia-Sol; Ellen Van Nunen; Nathan Van De Wouw. 2017. "Cooperative Automated Maneuvering at the 2016 Grand Cooperative Driving Challenge." IEEE Transactions on Intelligent Transportation Systems 19, no. 4: 1213-1226.

Conference paper
Published: 29 June 2017 in Advanced Microsystems for Automotive Applications 2016
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Technology is to a large extent driving the development of road vehicle automation. This Chapter summarizes the general overall trends in the enabling technologies within this field that were discussed during the Enabling technologies for road vehicle automation breakout session at the Automated Vehicle Symposium 2016. With a starting point in six scenarios that have the potential to be deployed at an early stage, five different categories of emerging technologies are described: (a) positioning, localization and mapping (b) algorithms, deep learning techniques, sensor fusion guidance and control (c) hybrid communication (d) sensing and perception and (e) technologies for data ownership and privacy. It is found that reliability and extensive computational power are the two most common challenges within the emerging technologies. Furthermore, cybersecurity binds all technologies together as vehicles will be constantly connected. Connectivity allows both improved local awareness through vehicle-to-vehicle communication and it allows continuous deployment of new software and algorithms that constantly learns new unforeseen objects or scenarios. Finally, while five categories were individually considered, further holistic work to combine them in a systems concept would be the important next step toward implementation.

ACS Style

Cristofer Englund; John Estrada; Juhani Jaaskelainen; Jim Misener; Surya Satyavolu; Frank Serna; Sudharson Sundararajan. Enabling Technologies for Road Vehicle Automation. Advanced Microsystems for Automotive Applications 2016 2017, 177 -185.

AMA Style

Cristofer Englund, John Estrada, Juhani Jaaskelainen, Jim Misener, Surya Satyavolu, Frank Serna, Sudharson Sundararajan. Enabling Technologies for Road Vehicle Automation. Advanced Microsystems for Automotive Applications 2016. 2017; ():177-185.

Chicago/Turabian Style

Cristofer Englund; John Estrada; Juhani Jaaskelainen; Jim Misener; Surya Satyavolu; Frank Serna; Sudharson Sundararajan. 2017. "Enabling Technologies for Road Vehicle Automation." Advanced Microsystems for Automotive Applications 2016 , no. : 177-185.