Helsinki: AI Predicts E-Scooter Accidents | Smart City Tech

Helsinki Launches AI-Powered E-Scooter Pilot to Enhance Rider Safety

A new initiative in Helsinki is leveraging artificial intelligence to proactively address safety concerns surrounding the rapidly growing popularity of e-scooters. The pilot program, backed by the European Union, aims to move beyond reactive safety measures and identify potential hazards before accidents occur.

The project, initiated in Helsinki, involves 40 shared e-scooters operated by Tier-Dott, a leading European micromobility provider. Each scooter is equipped with sensors developed by UK-based See.Sense that detect critical rider actions and environmental factors. These include sudden braking, swerving, and vibrations indicative of uneven road surfaces or other potential dangers.

The data collected by these sensors is then analyzed and visualized using a mobility data platform created by French startup Vianova. This allows city planners and scooter operators to gain real-time insights into safety risks. “By using advanced technology, we can help the city gain new information about accidents and near misses, as well as places where risky situations are concentrated,” a senior project manager with the EU-funded ELABORATOR project stated. The pilot is coordinated by Forum Virium Helsinki, the city’s innovation agency.

Growing Concerns Over E-Scooter Safety in Europe

The launch of this pilot comes amid increasing scrutiny of micromobility across Europe. A surge in injuries and fatalities linked to e-scooter use has prompted cities to re-evaluate regulations and safety protocols. In Germany alone, police registered 9,425 e-scooter accidents in 2023, a grim statistic representing a doubling of incidents – including 22 fatalities – compared to the previous year.

This rise in accidents has led to a wave of restrictions. In 2023, Paris took the drastic step of banning rental e-scooters altogether. Other major cities, including Oslo and Madrid, have implemented measures such as capping fleet sizes, establishing no-parking zones, and reducing speed limits.

Shifting Focus to Infrastructure and Proactive Safety

The Helsinki pilot represents a shift in approach, moving beyond solely monitoring rider behavior to assess the quality of urban infrastructure. Partners believe this could address the underlying causes of many accidents. “Partnering altogether with the City of Helsinki allows us to go beyond reactive safety initiatives and to proactively identify risks thanks to real-time data,” said a company representative from Dott, emphasizing the collaborative nature of the project.

The merger of Tier and Dott in 2024 created a larger, more resilient operator focused on sustainable growth. Tier-Dott has publicly stated its commitment to data-driven collaboration with cities to ensure safe integration of e-scooters into urban mobility systems. Profitability remains a key challenge for operators, with rising costs and regulatory hurdles impacting margins.

The results of the Helsinki pilot will contribute to broader EU research on safe and inclusive transport, potentially influencing future regulations. For now, Helsinki stands as the latest example of a European city experimenting with innovative solutions to navigate the evolving landscape of micromobility.

Beyond Helsinki: Expanding teh Role of Data in E-Scooter safety and Urban planning

The Helsinki pilot project,in partnership with Tier-Dott,marks a pivotal moment in the evolution of e-scooter safety. By harnessing artificial intelligence and the power of real-time data, the initiative aims to transform how cities address the challenges posed by micromobility. But what are the wider implications of this approach, and how can it be replicated and scaled across Europe and beyond?

The concept hinges on a more extensive understanding of the factors contributing to e-scooter accidents. While rider behavior undoubtedly plays a role,the project recognizes that infrastructure and environmental conditions are equally,if not more,crucial.

The success of the Helsinki pilot could significantly influence future urban planning strategies. The insights gathered – from areas prone to accidents to the impact of road surfaces – can directly inform city design and investment in infrastructure upgrades. This data is pivotal.

Cities like Oslo and Madrid, already implementing restrictions, may find that data-driven insights offer a more nuanced approach to regulation. Rather of blanket bans or broad limitations, targeted interventions can address specific problem areas, leading to more efficient and effective safety improvements. The goal is not simply to restrict e-scooters but to create a safer environment for all road users.

The Power of Predictive Analytics

A crucial element of the Helsinki project is its proactive approach.Advanced algorithms analyze real-time data from sensors, identifying potential hazards before they lead to accidents. This predictive capability is a meaningful step forward from traditional, reactive measures. This will provide the ability to intervene before problems arise.

• Infrastructure Assessment: Pinpointing areas with poor road surfaces, inadequate lighting, or insufficient bike lane separation.
• Behavioral Analysis: Identifying common risk-taking behaviors and understanding the conditions in which they occur.
• Environmental Factors: Assessing the impact of weather, traffic congestion, and other external influences on safety.

By combining these data points from different sensors, city planners can better understand the complex interplay of factors that contribute to e-scooter accidents. This holistic perspective facilitates targeted interventions.

Real-World Examples and Future Applications

How can other cities adopt and adapt this approach?

The key is collaboration. The collaborative model employed in Helsinki, involving city planners, scooter operators, and technology providers, is essential for success. Sharing data openly and transparently, as Tier-Dott mentioned, fosters trust and allows for comprehensive analysis. The model allows for all parties to benefit.

Beyond e-scooters, the data-driven approach could also have broader applications in urban mobility. This same technology may prove highly beneficial for bike lanes,walking paths,and other forms of transportation. Imagine an interconnected urban environment where real-time data empowers cities to proactively address safety concerns across all modes of transport.

AI plays a critical role in e-scooter safety by identifying potential hazards before accidents. This proactive approach can lead to improved urban planning, infrastructure optimization, and potentially, even reduced fatalities.

Data-driven decision-making allows city planners to enact targeted safety measures. This leads to more efficient use of resources and a safer urban environment for everyone.

practical Tips for Implementing a Data-Driven Approach

• Invest in Sensor Technology: Partnering with companies such as See.Sense that specialize in sensor development is critical. These sensors are the foundation of data collection.
• Develop Data Analytics Capacity: Cities need to invest in mobility data platforms like Vianova to analyze and visualize data.
• Foster Collaboration: Building strong partnerships between city officials, micromobility operators, and technology providers is key.
• Prioritize Data Privacy: Establish clear data privacy protocols to ensure responsible data collection and use.
• Start Small, Scale Up: Begin with pilot projects focused on specific areas or problems, then expand based on the results.

The Future: A Safer, Smarter, More Sustainable Urban Mobility System

The Helsinki pilot and similar initiatives underscore the growing importance of data and technology in creating safer, more sustainable, and more inclusive urban environments. The potential for data-driven insights to transform urban planning, reduce accident rates, and improve overall quality of life is clear.By embracing innovation, cities can navigate the evolving landscape of micromobility and build a brighter future for all.