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About this book

This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Smart Cities and Green ICT Systems, SMARTGREENS 2017, and the Third International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2017, held in Porto, Portugal in April 2017.
The 8 full papers of SMARTGREENS 2017 presented were carefully reviewed and selected from 70 submissions. VEHITS 2017 received 77 paper submissions from which 9 papers were selected and published in this book. The papers reflect topics such as smart cities, energy-aware systems and technologies, sustainable computing and communications, sustainable transportation and smart mobility.

Table of Contents


Energy-Aware Systems and Technologies


Towards an Integrated Development and Sustainability Evaluation of Energy Scenarios Assisted by Automated Information Exchange

Today, decision making in politics and businesses should aim for sustainable development, and one field of action is the transformation of energy systems. To reshape energy systems towards renewable energy resources, it has to be decided today on how to accomplish the transition. Energy scenarios are widely used to guide decision making in this context. While considerable effort has been put into developing energy scenarios, researchers have pointed out three requirements for energy scenarios that are not fulfilled satisfactorily yet: The development and evaluation of energy scenarios should (1) incorporate the concept of sustainability, (2) provide decision support in a transparent way, and (3) be replicable for other researchers. To meet these requirements, we combine different methodological approaches: story-and-simulation (SAS) scenarios, multi-criteria decision making (MCDM), information modeling, and co-simulation. We show how the combination of these methods can lead to an integrated approach for development and sustainability evaluation of energy scenarios assisted by automated information exchange. We concretize this approach with a sustainability evaluation process (SEP) model and an information model. We highlight, which artifacts are developed during the SEP and how the information model can help to automate the information exchange in this process. The objectives are to facilitate a sustainable development of the energy sector and to make the development and decision support processes of energy scenarios more transparent.
Jan Sören Schwarz, Tobias Witt, Astrid Nieße, Jutta Geldermann, Sebastian Lehnhoff, Michael Sonnenschein

Day-Ahead Scheduling of Electric Heat Pumps for Peak Shaving in Distribution Grids

In future electric distribution networks, demand flexibility offered by controllable loads will play a key role for the effective transition towards the smart grids. Electric heat pumps are flexible loads whose operation can be controlled, to some extent, to foster the efficient operation of the distribution grids. This paper presents an optimization algorithm that defines a smart day-ahead scheduling of electric heat pumps aimed at achieving power peak shaving in the distribution grid, while providing customers with the desired thermal comfort over the day. The proposed optimization relies upon a Mixed Integer Linear Programming approach and allows defining both the time schedule and the operating points of the heat pump, guaranteeing an energy efficient solution for the customers. Performed tests show the benefits achievable by means of the proposed optimal scheduling both at the distribution grid level and at the customer side, proving the goodness of the conceived solution.
Marco Pau, Jochen Lorenz Cremer, Ferdinanda Ponci, Antonello Monti

The SAGITTA Approach for Optimizing Solar Energy Consumption in Distributed Clouds with Stochastic Modeling

Facing the urgent need to decrease data centers’ energy consumption, Cloud providers resort to on-site renewable energy production. Solar energy can thus be used to power data centers. Yet this energy production is intrinsically fluctuating over time and depending on the geographical location. In this paper, we propose a stochastic modeling for optimizing solar energy consumption in distributed clouds. Our approach, named SAGITTA (Stochastic Approach for Green consumption In disTributed daTA centers), is shown to produce a virtual machine scheduling close to the optimal algorithm in terms of energy savings and to outperform classical round-robin approaches over varying Cloud workloads and real solar energy generation traces.
Benjamin Camus, Fanny Dufossé, Anne-Cécile Orgerie

Using Energy Supply Scenarios in an Interdisciplinary Research Process

The sustainable energy transition (Energiewende) is a multidisciplinary challenge. While for technical disciplines, the focus is on the development of technologies which can supply, transmit and store energy in a sustainable way, economic research focuses for example on the analyses of costs and risks of different asset portfolios. Yet another perspective is taken by the social sciences who focus on social challenges associated with the implementation of measures for realizing the Energiewende (decarbonization, high energy efficiency, high shares of renewables, nuclear phaseout), for example their acceptability. A solution for energy supply and storage which is optimized only according to one of these perspectives will, however, fail to meet other essential criteria. To develop sustainable solutions for energy supply and storage, which are technically feasible, cost-effective, and supported by local residents, interdisciplinary cooperation of researchers is thus needed. Interdisciplinary research, however, is subject to many barriers, for example the need to agree on a common analytical framework. In this paper, a process model for interdisciplinary energy research is proposed, in which specific scenarios are used to aid interdisciplinary cooperation and reciprocal integration of results. Based on a current research project, the phases of the model and the use of the scenarios in disciplinary and interdisciplinary work packages are described, as well as challenges and shortcomings of the model.
Barbara S. Zaunbrecher, Thomas Bexten, Jan Martin Specht, Manfred Wirsum, Reinhard Madlener, Martina Ziefle

Integrated Electric Vehicle to Small-Scale Energy Management System

The deployment of electric vehicle (EV) for transportation has received a massive intention due to its economic, environmental performance, and convenience. In addition, the controllable charging and discharging of EV lead to the potential of EV utilization to provide services to the electrical grid or energy management system (EMS). In this study, an integration of EV to support a small-scale EMS has been demonstrated and studied. This report covers the investigation of charging and discharging behavior of EV and the demonstration test of the developed integrated EV to small-scale EMS. Initially, charging behavior of EV under different ambient temperatures (seasons) were evaluated in order to clarify the impact of surrounding temperature to the charging rate. From the experimental test, it was found that charging in higher ambient temperature (during summer) results in a higher rate than charging in lower ambient temperature (during winter). Furthermore, the integration of EVs to small-scale EMS (such as office building) for peak-load shifting showed a very positive effect. Discharging of EVs during noon’s peak load is able to cut and shift the peak load. Hence, high contracted capacity and large consumption of electricity with high price can be reduced leading to lower total electricity cost.
Muhammad Aziz

Smart Cities


An Influence-Based Model for Smart City’s Interdependent Infrastructures: Application in Pricing Design for EV Charging Infrastructures

While smart critical infrastructures are principle components of smart cities, isolated and individually optimized infrastructures will not necessarily realize the vision of smart city in providing efficient solutions and services to citizens. This is mainly due to the interdependencies among critical infrastructures, which suggest the need for collaborative solutions and synergistic modeling and analysis of these systems. In this paper, an integrated framework based on influence model, a networked Markov chain framework, is proposed for modeling interdependent infrastructures and capturing their interactions based on the rules and policies governing their internal and interaction dynamics. To demonstrate the benefits of synergistic approaches, in this paper, the interdependencies between transportation networks and power infrastructures, through electric-vehicle (EV) charging infrastructures, are considered. Particularly, the proposed integrated framework is used to design an algorithm for assigning dynamic charging prices for the EV charging infrastructure with the goal of increasing the likelihood of having balanced charging and electric infrastructures. The proposed scheme for charging prices is traffic and power aware as the states and interactions of transportation and power infrastructures are captured in the integrated framework. Finally, the cyber infrastructure plays a critical role in enabling such collaborative solutions and their role is also discussed.
Upama Nakarmi, Mahshid Rahnamay-Naeini

All Eyes on You! Impact of Location, Camera Type, and Privacy-Security-Trade-off on the Acceptance of Surveillance Technologies

While surveillance technologies are increasingly used to prevent or detect crimes and to improve security, critics perceive recording and storage of data as a violation of individual privacy. Thus, it has to be analyzed empirically where and to what extent the use of surveillance technologies is accepted and whether the needs for privacy and security differ depending on the location of surveillance, the type of technology, or the individual characteristics of city residents. By applying a conjoint analysis, our study investigated the relationship between different locations of surveillance, different types of cameras, increase of safety implemented by reduction of crime and intrusion of privacy operationalized as different ways of handling the recorded footage. Findings show that locations are the most important factor for crime surveillance scenario preferences, followed by increase of security, and intrusion of privacy. In the decision scenarios, the type of camera played only a minor role. Sensitivity analyzes enabled detailed examinations of the trade-off between privacy and security and a segmentation of different respondent profiles led to an identification of influencing characteristics on the acceptance of crime surveillance. Outcomes show the importance of integrating city residents’ preferences into the design of infrastructural city concepts.
Julia Offermann-van Heek, Katrin Arning, Martina Ziefle

A Strategic Urban Grid Planning Tool to Improve the Resilience of Smart Grid Networks

The unresponsive and poor resilience of the traditional city architecture may cause instability and failure. Therefore, strategical positioning of new urban electricity or city components do not only make the city more resilient to electricity outages, but also a step towards a greener and a smarter city. Money and resilience are two conflicting goals in this case. In case of blackouts, distributed energy resources can serve critical demand to essential city components such as hospitals, water purification facilities, fire and police stations. In addition, the city level stakeholders may need to envision monetary saving and the overall urban planning resilience related to city component changes. In order to provide decision makers with resilience and monetary information, it is needed to analyze the impact of modifying the city components. This paper introduces a novel tool suitable for this purpose and reports on the validation efforts through a stakeholder workshop. The outcomes indicate that predicted outcomes of two alternative solutions can be analyzed and compared with the assistance of the tool.
Eng Tseng Lau, Kok Keong Chai, Yue Chen, Alexandr Vasenev

Intelligent Vehicle Technologies


Scenario Interpretation for Automated Driving at Intersections

Driving at urban intersections is a very tough issue due to the complexity of the scenario. The driver is required to understand the traffic rules, predict the motion of other vehicles and, accordingly, make the proper decision. In this sense, automated driving systems in such environments become an important objective from a research point of view. Particularly, understanding the surrounding of the ego vehicle represents a challenging task. In this paper we propose an approach that simplifies the interpretation of the scenario. This concept aims to break down the whole maneuver in a set of primary situations. Accordingly, this facilitates the decision making at intersection and the following planning along the desired driving corridor.
David Perdomo Lopez, Rene Waldmann, Christian Joerdens, Raul Rojas

Fuel Optimal Control of an Articulated Hauler Utilising a Human Machine Interface

Utilising optimal control presents an opportunity to increase the fuel efficiency in an off-road transport mission conducted by an articulated hauler. A human machine interface (HMI) instructing the hauler operator to follow the fuel optimal vehicle speed trajectory has been developed and tested in real working conditions. The HMI implementation includes a Dynamic Programming based method to calculate the optimal vehicle speed and gear shift trajectories. Input to the optimisation algorithm is road related data such as distance, road inclination and rolling resistance. The road related data is estimated in a map module utilising an Extended Kalman Filter (EKF), a Rauch-Tung-Striebel smoother and a data fusion algorithm. Two test modes were compared: (1) The hauler operator tried to follow the optimal vehicle speed trajectory as presented in the HMI and (2) the operator was given a constant target speed to follow. The objective of the second test mode is to achieve an approximately equal cycle time as for the optimally controlled transport mission, hence, with similar productivity. A small fuel efficiency improvement was found when the human machine interface was used.
Jörgen Albrektsson, Jan Åslund

Intelligent Offloading Distribution of High Definition Street Maps for Highly Automated Vehicles

Highly automated vehicles will change our personal mobility in the future. To ensure the safety and the comfort of their passengers, the cars have to rely on as many information regarding their current surrounding traffic situation, as they can obtain. In addition to classical sensors like cameras or radar sensors, automated vehicles use data from a so called High Definition Street Map. Through such maps, the vehicles are provided with continuous updates regarding their future driving environment on a centimeter accurate level. The required amount of data, which is necessary therefore, motivates the development of more efficient data transmission concepts. In this paper we present HD-Wmapan extension of our previous work the Dynamic Map Update Protocol. Based on each vehicle’s current context the Dynamic Map Update Protocol achieves a highly data efficient transmission of map updates compared to existing distribution approaches. HD-Wmapfurther reduces the costs of such transmissions by enabling map data to be shared via ad hoc communication between the vehicles. To evaluate the capabilities of HD-Wmapwe perform a first simulation of the morning commuting traffic within the area of Cologne, Germany. In this scenario HD-Wmapachieved an ad hoc map data off loading quota from cellular networks of up to 25.5%. These results demonstrate the gains of our approach to realize efficient map distribution via ad hoc communication, releasing load from wireless Internet access networks.
Florian Jomrich, Aakash Sharma, Tobias Rückelt, Doreen Böhnstedt, Ralf Steinmetz

Classification of Automotive Electric/Electronic Features and the Consequent Hierarchization of the Logical System Architecture

From Functional Chains to Functional Networks
In the established Automotive Systems Engineering (ASE) practice, an important factor in handling the complexity of product development is the partitioning of the vehicle into different domains. The current technological advances enable increasingly complex features for assisted and automated driving that reach across these different domains and are difficult to handle by the existing approaches. To cope with these challenges, new innovative methods, procedures and techniques are required that integrate well with the established practice. In this contribution, we analyze existing and future automotive features and classify them in a comprehensive taxonomy. Based on this characterization, established industrial and new research approaches for logical system architectures are consolidated. The introduction of new levels of hierarchy in the logical system architecture facilitates the attribution of specific design schemes and engineering approaches to the related functional elements. This approach facilitates the management of features with high internal variety and wide distribution over several subsystems. The systematic approach provides a novel rationale for the evolution from functional chains to functional networks in the automotive industry.
Johannes Bach, Stefan Otten, Eric Sax

User-Based Relocation of Stackable Car Sharing

The relocation of carsharing vehicles is one of the main challenges facing its economic viability, in addition to the operational costs and infrastructure deployment. In this paper, we take advantage of an innovative technological proposal of a one-way carsharing system, to test and validate a user-based relocation strategy. The new technology allows vehicles to be driven in a road train by either an operator (up until eight vehicles) or a customer (up to two). The proposed strategy encourages a customer to take a second vehicle along the way, when he/she happens to be moving from a station with excess of vehicles, to a deficient station. As a case study, we have considered a suburban area of the city of Lyon, of which we have a 2015 household travel survey to build a synthetic population undertaking various activities during a day. Then, we inject this population in a detailed multi-agent and multi-modal transport simulation model, to compare the relocation performance of a lower/upper-bound availability algorithm with three other naively intuitive algorithms. The study shows that: (i) relocation algorithm is very sensitive to the ratio of parking slots to fleet size, and (ii) with the right infrastructure we can relocate one vehicle and generate at least one additional trip.
Haitam Laarabi, Chiara Boldrini, Raffaele Bruno, Helen Porter, Peter Davidson

A Maneuver Based Interaction Framework for External Users of an Automated Assistance Vehicle

Automated vehicles become gradually available for restricted environments. Fully Automated Vehicles (FAV) operate without a driver and need to cooperate and interact with other road users of any kind. This article illustrates an interaction framework, which allows a human user outside the car to interfere with the FAVs guidance. This is achieved by communicating a desired maneuver, where the external user is asked to choose among a set of possible maneuvers. This set of maneuvers is communicated by the FAV to the user and has been checked for execution feasibility by the FAV, based on its perception. To this end, the environment is represented as an occupancy grid and a path search without distinct goal is performed. A small set of paths will be selected and communicated to the external user in an abstract level. This article presents the planning framework, as well as basic implementations for suited path search algorithms. The conclusion addresses unsolved challenges.
Mohsen Sefati, Denny Gert, Kai D. Kreiskoether, Achim Kampker

A Personal Robot as an Improvement to the Customers’ In-store Experience

Robotics is a growing industry with applications in numerous markets, including retail, transportation, manufacturing, and even as personal assistants. Consumers have evolved to expect more from the buying experience, and retailers are looking at technology to keep consumers engaged. There are currently many interesting initiatives that explore how robots can be used in retail. In today’s highly competitive business climate, being able to attract, serve, and satisfy more customers is a key to success. A happy customer is more likely to be a loyal one, who comes back and often to the store. It is our belief that smart robots will play a significant role in physical retail in the future. One successful example is wGO, a robotic shopping assistant developed by FollowInspiration. The wGO is an autonomous and self-driven shopping cart, designed to follow people with reduced mobility in commercial environments. With the Retail Robot, the user can control the shopping cart without the need to push it. This brings numerous advantages and a higher level of comfort since the user does not need to worry about carrying the groceries or pushing the shopping cart. The wGO operates under a vision-guided approach based on user-following with no need for any external device. Its integrated architecture of control, navigation, perception, planning, and awareness is designed to enable the robot to successfully perform personal assistance while the user is shopping. This paper presents the wGOs functionalities and requirements to enable the robot to successfully perform personal assistance while the user is shopping in a safe way. It also presents the details about the robot’s behaviour, hardware and software technical characteristics. Experiments conducted in real scenarios were very encouraging and a high user satisfaction was observed. Based on these results, some conclusions and guidelines towards the future full deployment of the wGO in commercial environments are drawn.
António J. R. Neves, Daniel Campos, Fábio Duarte, Filipe Pereira, Inês Domingues, Joana Santos, João Leão, José Xavier, Luís de Matos, Manuel Camarneiro, Marcelo Penas, Maria Miranda, Ricardo Silva, Tiago Esteves

Road Safety: Human Factors Aspects of Intelligent Vehicle Technologies

The design of road-vehicle systems has a crucial impact on the driver’s user experience. A post-market trial-and-error approach of the product is not acceptable, as the cost of failure may be fatal. Therefore, to design a suitable system in the automotive context that supports the driver during their journey in an unobtrusive way, a thorough survey of human factors is essential. This article elucidates the broad issues involved in the interaction of road users with intelligent vehicle technologies and summaries of previous work, detailing interaction-design concepts and metrics while focusing on road safety.
Cristina Olaverri-Monreal

Evaluation Methodology for Cooperative ADAS Utilizing Simulation and Experiments

Wireless vehicular networks are to be deployed in both Europe and the USA within upcoming years. Such networks introduce a new promising source of information about vehicular environments to be used by cooperative advanced driver assistance systems (ADAS). However, development and evaluation of such cooperative ADAS is still challenging. Hence, we introduce a novel methodology for their development and evaluation processes. It is applied to evaluate the fulfillment of requirements on position accuracy information within exchanged messages. Such requirements are only roughly defined and not sufficiently evaluated in field tests. This holds especially for Global Navigation Satellite Systems (GNSS) optimized for maximum integrity of obtained positions. Such configuration is required to increase robustness and reliability of safety critical ADAS. We find that pure GNSS-based positioning cannot fulfill position accuracy requirements of studied ADAS in most test cases.
Sebastian Bittl, Dominique Seydel, Jakob Pfeiffer, Josef Jiru


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