Three Mobility Trends to Watch For in 2024

The Future of Mobility is at Our Fingertips


The Mobility sector is undergoing a transformation, reshaping the way we think about and interact with transportation. A revolution is making our vehicles and even the process by which they’re created greener and more integrated into our lives.  Looking to the year ahead, we expect three major trends to have outsized impacts, including electric autonomous vehicles, virtual homologation, and ethical AI. Let’s explore these trends alongside the challenges and benefits they may provide.

Electric Autonomous Vehicles

As we move toward a more sustainable future, demand for electric autonomous vehicles (AV-Es) is growing rapidly. With manufacturers new to the market and legacy brands offering consumers more choices, the future of mobility is looking more sustainable than ever before. AV-Es offer several benefits to consumers and the environment, including:

  • Reduced greenhouse gas emissions
  • Increased safety by decreasing human error, which is the cause of 94 percent of serious collisions
  • Less traffic congestion, leading to faster travel times

Despite advances, scientists and vehicle manufacturers still have concerns with AV-Es. Vehicles must be tested in multiple conditions and ensure that they are secure from cyber threats. Looking ahead, we can expect to see more safety and cybersecurity standards introduced to address these critical issues.

This year, more car companies are expected to reveal their versions of AV-Es. By combining the benefits of both electric cars and autonomous technology, the new vehicles on the market promise to be more sustainable, safer, and more efficient than traditional cars.

Virtual Homologation

Virtual Homologation is a method of testing that allows autonomous vehicles to be evaluated using simulations and digital models, instead of physical testing. It can help reduce the environmental impact of the transportation industry by reducing the number of required physical tests, which can lead to lower energy consumption, reduced  carbon emissions and more sustainable outcomes.

A critical factor for success using virtual homologation is to ensure that the simulation software uses a virtual environment as rigorous as real-life scenarios. Rigorous standards can help ensure this, including the use of  ethical AI to support safety needs and requirements.

Ethical AI

Connected and Automated Vehicles (CAVs) leverage both Connected Vehicle (CV) and Automated Vehicle (AV) technologies by using wireless exchange of data to allow vehicles to communicate with one another and with the roadway infrastructure.

Connected Vehicles (CV) receive and send alerts by communicating in the following ways:

  • Vehicle to vehicle (V2V): real-time communication and data exchange between vehicles. Essentially, each vehicle can capture, send, and transport signals that help proactively alert drivers of potential hazards.
  • Vehicle to infrastructure (V2I): information exchange between a vehicle and nearby road infrastructure such as smart sensors installed in road signs, streetlights, and traffic lights.
  • Vehicle to pedestrian (V2P): collision warnings and pedestrian detections enabled by in-vehicle camera systems such as LiDAR technology to generate collision warnings and detect pedestrians to alert drivers.
  • Vehicle to Everything (V2N to V2E): data is transmitted to the Transportation Management Center (TMC) for analysis, including demand management, travel times, and incident response.

Automated driving will rely on Light Detection and Radar (LiDAR), cameras, radar, and inertial sensors to provide situational awareness. Connectivity adds a new layer of information to augment what sensors can detect while enabling proactive information management to inform the vehicle what to do.

CAVs are a revolutionary way to leverage data and AI to transport people and goods—provided that operators follow ethical procedures. They improve safety and efficiency and provide accessible transportation. However, with advanced sensing and AI technology, CAV standards and guidelines are needed to enforce safety and cybersecurity. Potential guidelines for the use of CAVs could include:

  • Ensuring that CAVs reduce physical harm to persons
  • Managing dilemmas by principles of risk distribution and shared ethical principles
  • Safeguarding informational privacy and informed consent
  • Developing transparency strategies to inform users and pedestrians about data collection and associated rights
  • Promoting data, algorithmic, AI literacy, and public participation
  • Promoting a culture of responsibility with respect to the obligations associated with CAVs
  • Promoting a fair system for the attribution of moral and legal culpability for the behavior of CAVs

CAVs have the potential to be an ideal platform to support ethical AI decision-making standards development. There is a possibility for standards in ethical CAV-decision making for:

  • Classification of obstacles
  • Methodology to assess
  • Acceptable outcomes
  • Cultural variances
  • Definition of “harm”
  • Definition of the reasonable use of personal characteristics

Ethical AI is crucial when making decisions related to CAV because it can help ensure that the technology is developed and deployed responsibly. Standards for CAVs infrastructure are important for the deployment of connected and automated cars, and as CAV continues to evolve into this exciting technology, we can expect to see standards and ethical AI being elevated to ensure the accountable use of AI technologies.

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