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Article

Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles

by
Fayez Alanazi
1,* and
Mamdouh Alenezi
2
1
Department of Civil Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
2
Software Engineering and Disruptive Innovation (SEDI), College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(15), 8741; https://doi.org/10.3390/app13158741
Submission received: 7 July 2023 / Revised: 24 July 2023 / Accepted: 26 July 2023 / Published: 28 July 2023
(This article belongs to the Special Issue New Insights into Real-Time Urban Information Systems)
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Abstract

:
As the process of urbanization continues to accelerate, the demand for sustainable cities has become more critical than ever before. The incorporation of electric vehicles (EVs) is a key component in creating sustainable cities. However, the development of smart cities for EVs entails more than just the installation of charging stations. Software engineering plays a crucial role in realizing smart cities for electric vehicles. This paper examines the role of software engineering in the creation of smart cities for electric vehicles, the techniques utilized in electric vehicle charging infrastructure, the obstacles faced by software engineers, and the future of software engineering in sustainable cities. Specifically, the paper explores the significance of software engineering in integrating EVs into the transportation system, including the design of smart charging and energy management systems, and the establishment of intelligent transportation systems. Additionally, the paper offers case studies to demonstrate successful software engineering implementations for smart cities. Finally, the paper concludes with a discussion of the challenges that software engineers encounter in implementing intelligent transportation systems for EVs and provides future directions for software engineering in sustainable cities.

1. Introduction

Smart cities aim to create efficient, sustainable, and livable urban environments that enhance citizens’ quality of life by utilizing advanced technologies and data analytics to improve public services, reduce environmental impact, and promote economic growth [1,2]. A key aspect of smart cities is the adoption of sustainable practices and technologies, such as electric vehicles (EVs), which contribute to a reduced carbon footprint and a more sustainable future [3,4]. EVs play a significant role in smart cities by promoting sustainable transportation practices and technologies [5,6], offering numerous benefits such as reduced tailpipe emissions and the potential to use renewable energy sources for charging [7,8]. Intelligent transportation systems (ITS) further improve transportation efficiency, safety, and sustainability by optimizing resources, traffic flow, and enhancing safety [9,10,11].
Software engineering is pivotal in developing ITS solutions for EVs in smart cities [12,13]. It involves designing and developing systems that optimize EV usage, manage charging infrastructure, and provide real-time information to drivers while ensuring reliability, efficiency, and security. Software engineering practices, such as requirements analysis, design, and testing, are essential in creating effective ITS solutions for EVs in smart cities [14,15]. By leveraging these practices, developers can create software systems that optimize transportation resources, promote environmental sustainability, and enhance the overall quality of life of urban residents.
This investigation serves as a valuable resource for policymakers, urban planners, software engineers, and researchers who are interested in the confluence of software engineering, ITS, smart cities, and electric vehicles. Ultimately, this research contributes to the ongoing advancement of sustainable transportation solutions.

2. Literature Review

This literature review delves into three pertinent topics that underpin the development of smart cities for electric vehicles: the role of software engineering, the benefits of electric vehicles, and the potential of intelligent transportation systems (ITS). A synthesis of these themes provides a robust understanding of the existing body of knowledge and highlights areas for further exploration.

2.1. Software Engineering in the Context of EV-Integrated Smart Cities

Software engineering has emerged as a crucial discipline in the realm of smart cities for electric vehicles (EVs). The field involves the design, development, and maintenance of software systems, which are vital for the successful integration of EVs into the transportation network [13,16,17]. In the literature, there is a clear emphasis on the development of comprehensive software solutions that efficiently manage charging infrastructure, monitor energy consumption, and optimize traffic flow [18,19]. Figure 1 depicts a conceptual representation of smart city infrastructure.
The underlying premise is that well-designed software systems, built on the principles of software engineering, can support the unique needs of EVs in a rapidly evolving urban environment. These systems include smart charging systems, energy management systems, and intelligent transportation systems, which are central to the overall efficiency of the transportation network.
Discussion in the literature also highlights the role of software engineering in intelligent transportation systems (ITS). The application of engineering principles to the design, development, testing, and maintenance of software ensures that the software for ITS is reliable, efficient, and secure [20,21].
Research by Hilburn et al. [22] suggests that the employment of sound software engineering practices such as requirements analysis, system design, and rigorous testing can aid in the creation of software solutions that optimize the use of transportation resources, improve safety, and enhance the overall efficiency of the transportation system.

2.2. Benefits and Challenges of Electric Vehicles

The surge in popularity of electric vehicles has been a focal point in academic circles due to EVs’ potential to mitigate greenhouse gas emissions, improve air quality, and bolster energy security [23,24]. Studies show that EVs can drastically reduce greenhouse gas emissions, with potential reductions of up to 90% when compared to gasoline-powered vehicles [25,26].
However, it is critical to acknowledge the environmental impact of the production and disposal of batteries used in EVs. The manufacturing process requires significant energy, and the disposal of batteries can lead to toxic waste and environmental pollution [27,28]. Despite these considerations, the use of renewable energy sources for charging EV batteries can help mitigate these environmental impacts [8].
Moreover, EVs have the potential to promote energy security by relying on domestically-produced renewable energy sources rather than foreign oil imports, thereby reducing a country’s dependence on foreign oil and increasing its energy independence [29,30]. The literature also discusses the cost and convenience benefits of EVs. Although the initial cost of purchasing an EV may be higher, the overall cost of ownership may be considerably lower due to reduced fuel costs and maintenance requirements [31].
While the benefits of EVs are well-documented, research also points to challenges associated with their widespread adoption, such as the need for more extensive charging infrastructure and improvements in battery technology [32].

2.3. Potential of Intelligent Transportation Systems in Smart Cities

Intelligent transportation systems (ITS) have been widely researched, primarily due to their potential to improve transportation systems’ efficiency, safety, and sustainability [33,34].
The literature suggests that ITS can significantly improve traffic flow in smart cities by providing real-time information on traffic conditions, thus reducing congestion, lowering travel times, and improving the overall quality of life for city residents [35,36]. Research has also demonstrated ITS’s potential in enhancing safety, as these systems can provide real-time information on traffic conditions, weather, and other hazards, helping drivers make more informed decisions and avoid accidents [37,38].
In terms of economic implications, studies suggest that ITS can promote economic growth and job creation by fostering new business opportunities and stimulating innovation [39]. The literature, therefore, indicates that the potential impact of ITS in smart cities is significant. However, the deployment of these technologies requires a collaborative effort between different stakeholders and the development of innovative solutions to address the unique challenges of the smart city infrastructure.
In summary, the literature underscores the instrumental role of software engineering in the development of EV-integrated smart cities, the benefits and challenges of EVs, and the potential of ITS in smart cities. The integration of these themes forms a comprehensive understanding of the complex interplay between these areas, highlighting the need for further research and development.
The existing body of knowledge also suggests a need for more in-depth studies on software solutions that can address the unique challenges of EV-integrated smart cities. For instance, the development of robust software systems for managing charging infrastructure, optimizing energy consumption, and enhancing traffic flow remains a critical area of research.
The literature also points to the need for ongoing research to address the environmental impact of EVs, particularly concerning battery production and disposal. Further investigation into the use of renewable energy sources for charging EV batteries can provide insights into how to mitigate these environmental impacts.
Finally, while the potential of ITS in smart cities is widely acknowledged in the literature, many studies call for further exploration into this area. This includes research on how ITS can be effectively deployed in smart cities, the ways these systems can improve traffic flow and safety, and how they can stimulate economic growth.

3. Leveraging Software Engineering for Sustainable Smart Cities with Electric Vehicles

The rapid advancement of technology is shaping the future of cities, with electric vehicles (EVs) becoming an indispensable component of modern urban life [40]. Establishing smart cities that can support the growing demand for EVs necessitates a robust software engineering framework. Software engineering plays a crucial role in this context as it facilitates the development of intelligent solutions tailored to the unique needs of electric vehicles and their users. This section aims to delve into the various aspects of software engineering that contribute to the creation of smart cities for EVs by discussing the challenges, opportunities, and future trends in this domain.

3.1. Adapting the Software Development Life Cycle (SDLC) for Smart Cities

The software development life cycle (SDLC) is an essential component of software engineering as it delineates the various stages involved in developing and maintaining software [41]. In the context of constructing smart cities for electric vehicles (EVs), the SDLC demands meticulous planning, execution, and adaptation to ensure the development of high-quality, reliable software that effectively addresses this domain’s specific needs. The phases of a typical SDLC, depicted in Figure 2, can be summarized as follows:
  • Planning: This phase involves the identification of the software needs for managing EV-related systems in a smart city. Stakeholders like city planners, transportation officials, power grid operators, and EV manufacturers could contribute to defining the project’s scope. The focus is to create a robust software plan that can accommodate large-scale EV adoption; manage grid load during peak charging times; integrate with renewable energy sources; and handle data from various sources like charging stations, EVs, and the power grid.
  • Requirements analysis: In this phase, the specific needs for the software are gathered and analyzed. These might include features like the real-time tracking of EV charging, predictive analytics for peak load management, secure data transmission, and interoperability with various EV models and charging stations. The requirements are then thoroughly documented and verified by stakeholders before proceeding to the design phase.
  • Design: This phase involves creating a blueprint for the software that meets the requirements identified in the previous phase. For EVs, this could mean designing a system architecture that could scale to handle a large number of data; provide robust security to protect user and vehicle data; and offer a user-friendly interface for city officials, power grid operators, and EV users. The design should also consider the integration with existing city infrastructure and utility grids.
  • Development: Here, the actual coding of the software takes place. Developers write the software using appropriate programming languages and tools, following the design blueprint. For EV-related software, this might involve developing algorithms for efficient EV charging management, data processing modules for handling real-time data from EVs and charging stations, and user interfaces for different types of users.
  • Testing: The developed software is then tested to ensure it works as expected and meets all the defined requirements. Various testing methodologies like unit testing, integration testing, and system testing are used. Any bugs or issues identified are fixed before the software is deployed. For EV-related software, testing could include simulating various scenarios like peak load times, EV charging/discharging processes, and integration with other city systems.
  • Deployment: The software is then deployed in the real-world environment. It is installed on the necessary servers, integrated with the city’s power grid and EV charging infrastructure, and made available to the end-users. User training may be required to ensure that city officials, power grid operators, and EV users can effectively use the software.
  • Maintenance: After deployment, the software is regularly maintained and updated to adapt to changing requirements and conditions. This could involve adding new features, fixing bugs, or improving performance. For EV-related software, maintenance might involve updating the software to handle new EV models or charging technologies, improving the efficiency of load management algorithms, or enhancing the security of data transmission.
In this manner, the SDLC process can be effectively applied to the development of software for managing EVs in a smart, sustainable city. The focus is not just on creating a functional piece of software but on creating software that can adapt to the evolving needs of the city and its residents and contribute to the overall sustainability goals.
In the context of smart cities and electric vehicle infrastructure, the SDLC plays a pivotal role in developing software solutions that incorporate advanced technologies such as cloud/edge computing, the Internet of Things (IoT), and artificial intelligence (AI) [43]. These solutions enable real-time visibility and control, vehicle communication, and analytics and optimization for enhanced charging and load balancing.
Collaboration between software engineers, city authorities, and utility companies is essential for the successful deployment and maintenance of the software. Updates are introduced using techniques like A/B testing and canary releases to minimize disruptions, while stringent data security and privacy measures are enforced [44]. Performance and issues are continuously monitored to identify areas for improvement and ensure the software remains adaptive to the evolving needs of smart cities and electric vehicles.
The SDLC is integral to building software for smart city infrastructure, as following its iterative cycle ensures that user needs are reliably met. A successful SDLC for smart cities must incorporate advanced technologies, ensure efficient charging and load balancing, maintain data privacy, and monitor issues for continuous improvement. By adopting an agile, robust, and sustainable approach, software engineering can play a vital role in shaping the future of smart cities for electric vehicles.

3.2. Software Engineering Techniques for Sustainable EV-Based Smart Cities

The integration of electric vehicles (EVs) into sustainable smart cities requires an array of software engineering techniques to optimize urban planning, energy consumption, and transportation infrastructure. This subsection provides an overview of the most relevant software engineering methods, including agent-based modeling, machine learning, geographic information systems (GIS), system dynamics, multi-objective optimization, and simulation.
Agent-based modeling (ABM) is a computational approach that simulates the behaviors and interactions of autonomous agents within a given environment to study complex systems [45]. In the context of sustainable smart cities, ABM can be employed to model the behavior of individual EVs, the charging infrastructure, and the transportation network. This approach enables the examination of various scenarios to identify optimal strategies for EV adoption, the distribution of charging stations, and energy management [46].
Machine learning (ML) is a subset of artificial intelligence that uses algorithms to learn from and make predictions based on data [47]. ML techniques can be applied to improve the efficiency of EV charging and optimize traffic flow in smart cities. For instance, ML algorithms can predict future energy demand, allowing for the better utilization of renewable energy resources and minimizing the impact on the electricity grid [48]. Additionally, ML can be used to optimize traffic signal timings and routing strategies to reduce congestion and emissions from transportation [49].
Geographic information systems (GIS) is a framework for gathering, managing, and analyzing spatial data. In the context of sustainable smart cities, GIS can be used to analyze the spatial distribution of EV charging stations, identify areas with high EV adoption potential, and plan transportation infrastructure [50]. By combining GIS with other techniques such as ABM and ML, urban planners can design more efficient and environmentally friendly transportation networks that support the widespread adoption of EVs [51].
System dynamics (SD) is a modeling approach that helps one to understand the behavior of complex systems over time. It uses feedback loops and stocks and flows to represent the relationships among different components of a system. SD can be applied to model and analyze the interactions between EVs, the electricity grid, and renewable energy generation in a sustainable smart city. This method can help one to evaluate the long-term effects of various policies and interventions on EV adoption, energy consumption, and emissions reduction [52].
Multi-objective optimization (MOO) is a mathematical method that seeks to simultaneously optimize multiple conflicting objectives [53]. In the context of sustainable smart cities, MOO can be used to balance various goals, such as minimizing energy consumption, reducing greenhouse gas emissions, and improving transportation efficiency. By employing MOO techniques, urban planners can identify trade-offs and make informed decisions about the allocation of resources and infrastructure investments for EV integration [54].
Simulation is a technique that involves creating digital models of real-world systems to study their behavior under various conditions [55]. In the realm of sustainable smart cities, simulation can be used to analyze the performance of transportation networks and ecosystems, including EVs and charging infrastructure. This method allows for the examination of different scenarios and provides valuable insights to guide urban planning and policy-making [56].
Table 1 provides an overview of six software engineering techniques that can be employed to build sustainable cities with electric vehicles (EVs). These techniques include agent-based modeling, machine learning, geographic information systems (GIS), system dynamics, multi-objective optimization, and simulation. The table presents a brief description of each technique and highlights their applications in the context of sustainable urban planning and electric vehicle integration. Together, these techniques can help address various aspects of urban sustainability, such as energy consumption, transportation infrastructure, and spatial planning, to create a more sustainable, EV-friendly urban environment.

3.3. Software Engineering for Smart City Infrastructure

The rise of smart cities has highlighted the importance of software engineering as it plays a pivotal role in constructing sustainable and efficient urban environments [57]. Software engineers develop systems that connect and manage a wide range of technologies within cities, utilizing cutting-edge technologies such as IoT, AI, and blockchain to create intelligent and streamlined urban ecosystems [58,59].
In the context of electric vehicle (EV) charging stations and the integration of EV charging infrastructure with smart grids, software engineering practices are particularly important. Engineers can develop systems that monitor energy consumption, coordinate with other urban systems, and optimize EV charging efficiency [60]. These advancements optimize energy utilization and minimize waste, fostering a sustainable and efficient charging infrastructure for EVs. Incorporating EV charging infrastructure within smart grids also promotes the use of renewable energy sources for charging EVs, enhancing overall sustainability.
However, software engineers face challenges when developing smart city solutions for EVs. A significant challenge is managing the complexity of interconnected systems [61]. Smart cities consist of numerous interdependent systems that must function harmoniously, necessitating software engineers to possess a profound understanding of the city’s infrastructure and the technologies employed within it. Additionally, addressing security and privacy concerns is vital. As cities become increasingly interconnected and data-driven, the risk of cyberattacks and data breaches escalates. Software engineers must design secure systems that safeguard citizens’ privacy while still allowing the city to collect and analyze data for enhancing operations.
Overall, software engineering practices are indispensable for shaping sustainable and efficient smart cities. Engineers can aid cities in managing complex systems, maximizing technology utilization, and designing software systems that enable the seamless operation and integration of EV charging stations with smart grids. Despite challenges, software engineers can contribute to a sustainable and efficient future for urban development by achieving these goals.
Software engineering practices play a crucial role in designing electric vehicle (EV) charging stations. Engineers develop software systems that monitor energy usage and enable communication with other city systems, such as traffic management and smart grids, utilizing emerging technologies such as IoT and AI [18,60]. By taking distinctive identifiers into consideration when building an integrated data model, software engineers can accurately map and integrate semantic data, optimizing energy consumption and reducing waste to create a sustainable and efficient charging infrastructure for EVs [62].
In addition to optimizing charging efficiency and energy utilization, software engineering practices also address security and privacy concerns [63]. Software engineers must design secure systems that protect citizens’ privacy while still enabling the city to collect and use data to improve its operations, requiring a thorough understanding of best practices in security and privacy implementation.
Overall, software engineering practices are critical in designing EV charging stations. Engineers can develop software systems that optimize charging efficiency, energy utilization, and communication with other city systems while ensuring security and privacy [64]. By doing so, software engineers can help build sustainable and efficient charging infrastructure for EVs that is secure, private, and convenient for their users.

3.4. Integrating EV Charging Infrastructure with Smart Grids

Integrating electric vehicle (EV) charging infrastructure with smart electrical grids is essential for building smart cities [19,32]. Software engineers can develop systems that enable EV charging stations to communicate with smart grids, optimizing energy distribution and consumption while avoiding overloading the grid.
Intelligent integration is achieved through a network of sensors, smart meters, and software platforms that analyze energy usage data in real-time [65]. Software systems can dynamically control EV charging rates or schedule charging sessions to minimize peak loads. These techniques optimize energy consumption, reduce waste, and save costs.
Software engineers must overcome technical and design challenges by developing robust communication protocols and interoperability standards [66]. Incorporating advanced analytics, machine learning algorithms, and prediction models into software platforms enables intelligent and autonomous coordination between EVs and smart grids. Achieving optimal integration necessitates a holistic and systematic software engineering approach. Consequently, software engineering plays a pivotal role in developing sustainable and efficient transportation and energy solutions for smart cities.

3.5. Overcoming Software Engineering Challenges in EV Smart Cities

Managing complex systems is one of the significant challenges faced by software engineers in smart cities for electric vehicles (EVs). Smart cities are made up of various interconnected systems that need to work together seamlessly to achieve sustainable and efficient urban development. These systems include EV charging infrastructure, traffic management systems, public transportation systems, and more. Ensuring that these systems operate efficiently and effectively requires software engineers to have a deep understanding of the city’s infrastructure and the technologies used within it.
One of the primary challenges faced by software engineers in managing complex systems is ensuring interoperability between different systems. Each system may use different standards and technologies, which can result in semantic interoperability problems. To overcome this challenge, software engineers must develop systems that use a common data model and a common API. Additionally, distinctive identifiers should be taken into consideration to ensure that semantic data are accurately mapped and integrated. By doing so, software engineers can ensure that different systems can understand and interpret data in a consistent manner, promoting semantic interoperability.
In addition to managing complex systems, software engineers must also address security and privacy concerns as cities become more connected and data-driven. As cities become more interconnected and data-driven, there is an increased risk of cyberattacks and data breaches. Software engineers must design systems that are secure and protect citizens’ privacy while still enabling the city to collect and use data to improve its operations. This requires a thorough understanding of security and privacy best practices and the ability to implement them effectively in the software systems they develop.
Managing complex systems and addressing security and privacy concerns are significant challenges faced by software engineers in smart cities for EVs. Software engineers must develop systems that enable semantic interoperability, which requires a common data model and API. They must also design systems that are secure and protect citizens’ privacy while still enabling the city to collect and use data to improve its operations. By doing so, software engineers can help to build sustainable and efficient smart cities for EVs that are secure, private, and convenient for their users.

3.6. Envisioning the Future of Software Engineering for EV Smart Cities

The rising popularity of electric vehicles (EVs) necessitates software-engineered smart cities equipped to support their adoption. By harnessing Internet of Things (IoT), artificial intelligence (AI), and blockchain technologies, these cities can efficiently manage traffic and infrastructure for EVs.
IoT sensors and connected vehicles can optimize traffic and reduce congestion, a key urban challenge. For instance, sensors can detect available parking spots, mitigating traffic congestion [67]. AI-powered algorithms, meanwhile, can predict and prevent accidents, enhancing road safety [68].
Data analytics generated by EVs and charging infrastructures offer opportunities to refine smart cities. Analyzing this data allows for the optimization of charging infrastructure and energy consumption [69]. Efficient battery management systems can extend the EV range and cut charging time. Cybersecurity for EV charging networks is also critical, ensuring infrastructure security against cyber threats [70].
In EVs, software manages energy flow and optimizes powertrain performance while also providing driver assistance features [71]. In smart cities, software systems manage traffic, public services, and utilities, enabling smart applications like lighting and parking [72].
Scalability, interoperability, and security are vital in software development for EVs and smart cities. Software must manage vast data volumes, integrate with diverse technologies, and resist cyberattacks. By leveraging advancements in software engineering and emerging technologies, it is feasible to build smart cities that are sustainable, efficient, safe, and convenient. The potential of software engineering in shaping EV-friendly smart cities is significant, warranting multidisciplinary collaboration to address challenges and make this vision a reality.

3.7. The Vital Role of Software Engineers in the Development of Smart Cities

Building smart cities that fully support electric vehicles (EVs) requires collaboration across various engineering and technology disciplines. Effective interdisciplinary collaboration enables experts from fields such as mechanical engineering, electrical engineering, urban planning, and software engineering to work together in designing and implementing solutions tailored to the unique needs of EVs.
Among these disciplines, software engineering plays an especially critical role as software engineers have the skills and knowledge to develop advanced software systems that will power smart cities for EVs. Software engineers can leverage emerging technologies and advancements in their field to create an intelligent and efficient EV charging infrastructure that enables the sustainable future of transportation. For instance, software engineers can develop software platforms that allow EV charging stations to monitor energy usage in real-time and communicate with other city systems [73]. They can also design software that optimizes the charging of EVs to reduce charging times and increase the number of vehicles that can be charged concurrently [74].
By applying software engineering best practices, smart cities for EVs can be developed to be not only sustainable but also efficient, safe, convenient, and beneficial for all stakeholders. As EVs continue to gain mainstream popularity, the onus is on software engineers to rise to the challenges and opportunities presented by EVs and new technologies. Software engineers must pursue active collaboration with experts in other domains to address the complex needs of building smarter cities that support EVs while serving the environment and society.
Building a sustainable infrastructure for EVs requires a diverse range of skills and areas of expertise. Software engineers are uniquely positioned to make significant contributions by developing advanced software systems that enable smart energy and transportation solutions. However, interdisciplinary collaboration is key; software engineering solutions must be designed through cooperation with mechanical engineers, electrical engineers, urban planners, and policymakers to ensure the holistic success of smart cities for EVs. Overall, nurturing a collaborative ecosystem of experts across fields is a call to action that will drive innovation in smart city development to support the growth of electric mobility.

3.8. Software Engineering Solutions for Intelligent Transportation Systems (ITS)

Software engineering plays a critical role in the development and implementation of intelligent transportation systems (ITS) solutions for electric vehicles (EVs) in smart cities. The software used in these systems is responsible for managing the charging infrastructure, optimizing the use of energy resources, and ensuring the safety and security of the EVs and the smart city infrastructure. As such, the software must be designed, developed, and implemented with the highest standards of quality, reliability, and security.
Software engineering practices such as requirements analysis, design, testing, and maintenance are essential to the development and implementation of ITS solutions for EVs. Requirements analysis involves identifying the functional and non-functional requirements of the software, such as its ability to support different types of EVs and integrate them with other smart city systems. Design involves creating a software architecture that can accommodate these requirements and ensure the scalability and maintainability of the system. Testing involves verifying that the software meets the requirements and performs as expected, while maintenance involves ensuring the continued operation and optimization of the system.
One of the main challenges in software engineering for ITS solutions for EVs is the need for interoperability. Different systems and devices used in the charging infrastructure and other smart city components may use different protocols and standards, making it difficult to exchange data and communicate effectively. To address this challenge, software engineers must develop solutions that can support multiple protocols and standards and ensure that the software can communicate effectively with other systems and devices.
Finally, cybersecurity is a critical concern in the development and implementation of ITS solutions for EVs. Software engineers must design software that can protect against cyber attacks and ensure the safety and security of EVs and the smart city infrastructure. This involves implementing robust security features such as encryption, authentication, and intrusion detection systems, as well as regularly updating the software to address new threats and vulnerabilities.
Software engineering plays a critical role in the development and implementation of ITS solutions for EVs in smart cities. The software used in these systems must be designed, developed, and implemented with the highest standards of quality, reliability, and security to ensure the safe, efficient, and sustainable deployment of EVs in smart cities. Achieving this requires a collaborative effort between software engineers and other stakeholders involved in the deployment of the ITS solutions and the development of innovative solutions that can address the challenges and opportunities of the smart city infrastructure.

3.9. The Impact of ITS Solutions on EVs in Smart Cities

Intelligent transportation systems (ITS) solutions have the potential to revolutionize urban transportation by improving traffic flow, reducing energy consumption, increasing safety, and promoting economic growth. In the context of electric vehicles (EVs) in smart cities, ITS solutions can play a critical role in achieving these goals.
One of the primary benefits of ITS solutions for EVs is improved traffic flow [37]. By providing real-time information on traffic conditions and recommending alternative routes, these solutions can help to optimize the use of roads and reduce congestion. This, in turn, can reduce travel times, lower fuel consumption, and improve the overall quality of life for city residents.
Another benefit of ITS solutions for EVs is reduced energy consumption [75]. V2G charging stations, for example, enable EVs to store and discharge energy from the grid, helping to balance the supply and demand of electricity and reducing the need for fossil fuel-based power plants [74]. Additionally, smart charging systems can encourage EV owners to charge their vehicles during off-peak hours, when electricity demand is lower, helping to reduce the strain on the grid and promote energy efficiency.
ITS solutions for EVs can also increase safety by providing real-time information on traffic conditions, weather, and other hazards [76]. This information can help drivers to make more informed decisions and avoid accidents, reducing the risk of injury and death on the roads. Moreover, the development of autonomous driving systems can further improve safety by eliminating human error and reducing the risk of accidents caused by distracted or impaired driving.
In addition to the above, ITS solutions for EVs can promote economic growth and job creation [77]. The deployment of these solutions requires a collaborative effort between different stakeholders, creating new opportunities for entrepreneurship and innovation. Furthermore, the development of ITS solutions for EVs can create new jobs in areas such as software engineering, data analytics, and cybersecurity, stimulating economic growth and creating new opportunities for workers.
Achieving the benefits of ITS solutions for EVs requires one to address the challenges and opportunities of the smart city infrastructure. This includes overcoming technical challenges such as data integration, cybersecurity, and interoperability [78]. It also requires collaboration between different stakeholders, including utilities, local governments, and private companies, to develop innovative solutions that can address the unique needs of smart cities.
The adoption of ITS solutions for EVs in smart cities has the potential to create more efficient and sustainable transportation systems that promote a more livable and prosperous future. By improving traffic flow, reducing energy consumption, increasing safety, and promoting economic growth, these solutions can play a critical role in building a better world for future generations.
Software engineering plays a crucial role in building smart cities that can accommodate the growing presence of electric vehicles. The development of intelligent solutions for EV charging; infrastructure integration with smart grids; and the incorporation of software engineering in intelligent transportation systems all contribute to the establishment of efficient and sustainable urban environments. As challenges continue to arise in this domain, it is imperative that software engineers remain committed to addressing these issues and shaping the future of smart cities for electric vehicles. By embracing the opportunities presented by new technologies and employing innovative approaches, software engineers can drive the evolution of smart cities and ensure a greener, more connected future for all.

4. Integrating Electric Vehicles into Smart Cities: Challenges and Opportunities

The adoption of electric vehicles (EVs) and intelligent transportation systems (ITS) is accelerating in smart cities around the world. While EVs and ITS offer many benefits for sustainable mobility and smart infrastructure, integrating them also poses significant challenges. This section explores the major challenges of implementing ITS for EVs in smart cities, as well as the opportunities these technologies provide for advancing transportation networks, energy systems, and quality of life in urban environments. By proactively addressing the challenges and maximizing the opportunities, cities can develop holistic strategies for seamlessly connecting EVs, ITS, and smart grid technologies at scale.

4.1. Interoperability Challenges

The integration of electric vehicles (EVs) into smart cities requires the development of intelligent transportation systems (ITS) that enable seamless communication between EVs, charging infrastructure, and the city’s transportation network. However, several challenges arise in the implementation of ITS solutions for EVs in smart cities for interoperability. One of the most significant challenges is the lack of standardization in the communication protocols used by EVs and charging infrastructure, which impedes the interoperability of different systems. To overcome this challenge, stakeholders must develop and adopt common standards and protocols for data exchange, communication, and interoperability.
Another challenge is the need for a robust and reliable infrastructure to support the charging needs of EVs. To address this challenge, smart cities must invest in the deployment of charging infrastructure that is easily accessible, reliable, and efficient. Additionally, the charging infrastructure must be integrated with the smart grid to enable the optimal use of renewable energy sources and avoid overloading the grid. To achieve this, stakeholders must collaborate to develop a comprehensive plan for the deployment of charging infrastructure that takes into account the needs of different types of EVs and the expected growth in demand.
The integration of EVs into smart cities also requires the development of intelligent transportation systems that can optimize traffic flow and reduce congestion. However, this requires the collection and analysis of a large number of data from various sensors and sources, such as traffic cameras, GPS devices, and weather sensors. To overcome this challenge, stakeholders must develop data analytics tools and techniques that can process and analyze a large number of data in real-time to provide actionable insights for traffic management and optimization.
Finally, the integration of EVs into smart cities requires the development of user-friendly interfaces that can facilitate seamless interaction between EVs and the city’s transportation network. This requires the development of intuitive and easy-to-use interfaces that can provide drivers with real-time information on traffic conditions, available charging stations, and optimal routes. To achieve this, stakeholders must collaborate to develop user-centered design principles and best practices for the development of interfaces for EVs in smart cities.

4.2. Cybersecurity Challenges

The integration of electric vehicles (EVs) into smart cities requires the development of intelligent transportation systems (ITS) that enable seamless communication between EVs, the charging infrastructure, and the city’s transportation network. However, the implementation of ITS solutions for EVs in smart cities is also subject to cybersecurity challenges. One of the most significant challenges is the risk of cyber attacks on the communication systems that connect EVs to the city’s transportation network. Hackers could potentially exploit vulnerabilities in the communication systems to gain unauthorized access to sensitive data, such as location information, the personal information of drivers, and even control over EVs. To prevent such attacks, stakeholders must ensure that the communication systems are secure and use encryption to protect data at rest and in transit.
Another challenge is the risk of cyber attacks on the charging infrastructure. EV charging stations are connected to the internet and are vulnerable to attacks that could compromise the security and reliability of the charging network. Hackers could potentially exploit vulnerabilities in the charging infrastructure to gain unauthorized access to the charging network, overload the grid, or even cause physical damage to the charging stations. To address this challenge, stakeholders must ensure that the charging infrastructure is secure and uses encryption to protect data at rest and in transit.
The integration of EVs into smart cities also requires the development of secure software applications that can enable seamless communication between EVs and the city’s transportation network. Software engineers must ensure that the software applications are secure and follow best practices for secure software development, such as input validation, error handling, and secure coding. Additionally, software engineers must ensure that software applications are regularly updated and patched to address any security vulnerabilities that may arise.
Finally, the integration of EVs into smart cities requires the development of secure data analytics tools and techniques that can process and analyze a large number of data in real time while protecting the privacy and security of users’ data. To address this challenge, stakeholders must ensure that data analytics tools and techniques follow best practices for secure data processing, such as data anonymization, data minimization, and data encryption. Additionally, stakeholders must ensure that data are only accessible to authorized personnel and are protected from unauthorized access and disclosure.

4.3. Open-Source Software and Standards Opportunities

In the integration of electric vehicles (EVs) into smart cities, using open-source software (OSS) can be a valuable strategy for mitigating challenges and achieving interoperability, standardization, cybersecurity, and cost-effectiveness [79]. One of the main benefits of OSS is the ability for developers to collaborate and share code, leading to faster development and more robust software solutions. This is particularly beneficial in the development of intelligent transportation system (ITS) solutions for EVs in smart cities, where different stakeholders must collaborate to create interoperable and secure software solutions.
Using open standards and protocols is another benefit of OSS as it promotes standardization and interoperability, allowing easy integration with other software systems. This helps one to overcome the challenges of interoperability that arise in the integration of EVs into smart cities. Additionally, by sharing code and collaborating on development, OSS can promote the adoption of common standards and best practices, further facilitating interoperability.
OSS can also mitigate cybersecurity challenges in the integration of EVs into smart cities by allowing developers to review and audit code, identifying and addressing security vulnerabilities before they are exploited by hackers. By making the code available for public review, OSS can also increase transparency and accountability, building trust among stakeholders and users.
OSS can be a cost-effective strategy for developing software solutions for the integration of EVs into smart cities. Leveraging existing OSS solutions and building on top of them saves time and resources, particularly for small and medium-sized enterprises. Additionally, using OSS avoids licensing fees and other costs associated with proprietary software solutions.
However, developers must carefully evaluate the benefits and risks of open standards and open-source systems for each project. Ensuring compatibility and maintaining security are important challenges with these approaches.
The following are some examples of open-source systems that are used in smart cities:
  • OpenStreetMap: OpenStreetMap is a community-driven mapping platform that provides free and open geographic data to anyone who wants it. It is often used as a base map for smart city applications such as transportation planning, emergency response, and urban planning.
  • CityGML: CityGML is an open data model for the representation of 3D urban objects. It is used to create 3D digital models of cities, which can be used for applications such as urban planning, energy management, and environmental analysis.
  • CKAN: CKAN is an open-source data management system that provides tools for publishing, sharing, and finding data. It is often used by smart cities to manage and share data related to transportation, energy, and other aspects of urban life.
  • FIWARE: FIWARE is an open-source platform for building smart city applications. It provides a set of APIs and tools that developers can use to create applications for a variety of smart city use cases, such as transportation, energy, and environmental monitoring.
  • Eclipse IoT: Eclipse IoT is an open-source platform for building Internet of Things (IoT) applications. It provides a suite of tools and frameworks for building and managing IoT devices and applications, which can be used in smart city applications such as environmental monitoring, traffic management, and energy management.
  • ROS (robot operating system): ROS is an open-source robotics framework that is used in a variety of applications, including electric vehicles. It provides a set of libraries and tools for building and controlling robotic systems, and it can be used to develop advanced driver assistance systems (ADAS) for electric vehicles.
  • Eclipse Mosquitto: Eclipse Mosquitto is an open-source message broker that is used in IoT applications, including smart city systems and electric vehicles. It enables efficient communication between devices and systems, and it is designed to be scalable and secure.
  • OpenADR: OpenADR (open automated demand response) is an open-source standard for demand response management. It can be used in smart city energy management systems, as well as in electric vehicle charging infrastructure, to manage energy demand and ensure grid stability.
  • Open charge point protocol (OCPP): OCPP is an open-source protocol for communication between electric vehicle charging stations and central management systems. It enables interoperability between different charging station manufacturers and management systems, which is essential for the growth of the electric vehicle charging infrastructure.
These are just a few examples of the many open-source systems that are used in smart cities and electric vehicles. Open-source systems provide developers with a flexible and cost-effective way to build smart city applications, and they can help accelerate innovation and collaboration in the smart city ecosystem.
OSS can help develop robust and secure software solutions that enable the seamless integration of EVs into smart cities, mitigating challenges through collaboration, standardization, interoperability, cybersecurity, and cost-effectiveness [80]. Open-source systems are an essential part of building smart cities, providing developers with a flexible and cost-effective way to accelerate innovation and collaboration in the smart city ecosystem.

4.4. Regular Software Updates Opportunities

Regular software updates are crucial for addressing the challenges associated with integrating electric vehicles (EVs) into smart cities [81]. Software updates help mitigate risks in several ways:
  • Cybersecurity: Regular software updates patch security vulnerabilities and strengthen the communication systems connecting EVs to the smart grid. This reduces the risk of cyber attacks that could compromise these critical systems.
  • Interoperability: Frequent updates ensure that software solutions are compatible with evolving standards and other connected systems. This interoperability enables seamless communication between EVs, charging stations, and transportation networks.
  • Reliability and efficiency: Updating software in charging stations optimizes the infrastructure for different EVs and integrates it with the smart grid. This helps maximize the use of renewable energy and avoids overloading the grid.
  • User experience: Regular updates allow developers to address feedback, fix bugs, and add features that improve accessibility and inclusiveness. This enhances the overall user experience for all city residents.
Software updates are essential for developing robust, secure, and user-friendly solutions to integrate EVs into smart cities. By mitigating challenges related to cybersecurity, interoperability, reliability, and user experience, frequent updates help enable the seamless adoption of EVs across an intelligent transportation ecosystem. Overall, regular software updates provide a crucial mechanism for addressing key barriers in this domain.

5. Case Studies

This section presents a comparative case study to illustrate the significant role of software engineering in integrating electric vehicles into smart cities. We focus on the development and integration of EV charging infrastructure in San Diego, USA and Amsterdam, the Netherlands and provide quantifiable outcomes to demonstrate the efficiency and sustainability of the projects.

5.1. Case Study: EV Charging Infrastructure Projects in San Diego and Amsterdam

The cities of San Diego and Amsterdam carried out projects to incorporate electric vehicle (EV) charging infrastructure into their smart grids [82,83]. Despite geographical differences, the projects shared common objectives, faced similar challenges, and yielded noteworthy results, emphasizing the essential role of software engineering in shaping smart cities.
Software engineers in both cities designed systems that enabled bi-directional communication between the charging stations and the smart grid. These systems enabled real-time energy usage monitoring and integrated with other city systems such as traffic management and public transportation. As a result, the charging infrastructure increased in efficiency, reducing charging times and expanding the capacity for simultaneous charging. Let us consider some specific performance improvement data from both projects:
  • In San Diego, the integration of the EV charging infrastructure with the smart grid led to a 20% reduction in peak charging times, from an average of 4 h to 3.2 h. The system’s ability to charge multiple vehicles simultaneously increased by 15%, accommodating an additional 30 vehicles per charging station per day [82].
  • In Amsterdam, the development of a software application for locating and reserving charging stations resulted in a 25% increase in the utilization of available charging stations, equating to an additional 50 vehicles charged per day. The app also reduced the average searching time for a charging station from 15 min to less than 5 min [83].
Furthermore, software engineers were instrumental in addressing security and privacy concerns. They designed systems with robust security measures and privacy safeguards, enabling the cities to gather and utilize data optimally while maintaining citizens’ privacy. This required expertise in security best practices and the ability to incorporate these effectively into the developed software systems.

5.2. Conclusions and Common Challenges

The EV charging infrastructure projects in San Diego and Amsterdam underscore the pivotal role of software engineering in integrating electric vehicles into smart cities. By utilizing emerging technologies and advancements in software engineering, both projects yielded sustainable and efficient charging infrastructures that were effectively integrated with their smart grids.
These case studies illuminate common challenges that software engineers encounter in smart city projects for electric vehicles, such as managing complex systems, ensuring interoperability, and addressing security and privacy concerns. As electric vehicle adoption continues to surge, the role of software engineers in integrating these vehicles into urban environments will become more crucial, thereby supporting the evolution of smart cities globally.

6. Future Directions and Conclusions

The development of intelligent transportation system (ITS) solutions for electric vehicles (EVs) in smart cities presents a plethora of opportunities for future innovation. As technology progresses, machine learning (ML) and artificial intelligence (AI) can be leveraged to optimize charging infrastructure, improve traffic flow, and enhance safety. However, these technologies require a large number of data for effective training, and their implementation requires significant investments in infrastructure and resources, which may pose challenges for some cities.
To address the challenges of data management, blockchain technology can be utilized to create a secure network for managing EV charging data, such as station usage, electricity consumption, and payments. This provides efficiency, transparency, and privacy, which are crucial for the effective and secure management of EV charging infrastructure. However, blockchain technology is still in its nascent stage and requires further development and standardization before it can be widely adopted.
Connecting EVs, charging stations, and transportation infrastructure to the Internet of Things (IoT) can make systems more connected and efficient, reducing congestion and improving sustainability. However, the integration of IoT devices into existing transportation infrastructure may present challenges related to interoperability, security, and privacy. Paying careful attention to these challenges is vital to ensure the successful implementation of IoT solutions for EVs in smart cities.
The development of sustainable transportation in smart cities heavily relies on software engineering. The integration of ITS and EVs can optimize resources, reduce the environmental impact, and improve quality of life. Requirements analysis, design, and testing are critical to creating systems that achieve these goals. Additionally, advanced technologies such as ML, AI, blockchain, and IoT can transform cities by making transportation greener, safer, and more efficient. However, the implementation of these technologies and systems may face limitations and challenges that require interdisciplinary collaboration to overcome. As technology and infrastructure progress, ITS and EVs can continue to improve urban transportation and enable more livable, sustainable cities.

Author Contributions

Conceptualization, M.A. and F.A.; investigation, M.A. and F.A.; writing—original draft preparation, M.A. and F.A.; and writing—review and editing, F.A. and M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was funded by the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia under project number 223202.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The author extends his appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia for funding this research work through project number 223202.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Illustration of smart city infrastructure.
Figure 1. Illustration of smart city infrastructure.
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Figure 2. Software development life cycle (SDLC) [42].
Figure 2. Software development life cycle (SDLC) [42].
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Table
Table 1. Overview of software engineering techniques applicable to building sustainable cities with electric vehicles (EVs).
Table 1. Overview of software engineering techniques applicable to building sustainable cities with electric vehicles (EVs).
TechniqueApplication in Sustainable Cities with EVs
Agent-based modelingModeling the behavior and interactions of EVs, charging stations, and users to optimize energy consumption and traffic flow.
Machine learningPredicting EV energy demand, optimizing charging schedules, and identifying optimal EV fleet compositions.
Geographic information systems (GIS)Analyzing spatial patterns of EV adoption, locating optimal charging station sites, and planning EV-friendly infrastructure.
System dynamicsAnalyzing the long-term impacts of EV adoption on urban sustainability, energy consumption, and transportation infrastructure.
Multi-objective optimizationDesigning integrated sustainable urban planning solutions that balance the needs of EVs with other urban sustainability goals.
SimulationTesting the performance of EV charging infrastructures, traffic management systems, and renewable energy integration.
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Alanazi, F.; Alenezi, M. Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles. Appl. Sci. 2023, 13, 8741. https://doi.org/10.3390/app13158741

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Alanazi F, Alenezi M. Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles. Applied Sciences. 2023; 13(15):8741. https://doi.org/10.3390/app13158741

Chicago/Turabian Style

Alanazi, Fayez, and Mamdouh Alenezi. 2023. "Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles" Applied Sciences 13, no. 15: 8741. https://doi.org/10.3390/app13158741

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