How will AI and big data impact urban transportation in 2024? Transport and technology experts make their predictions…
Mark Cracknell, Programme Director – CAM, Zenzic
In 2024, we envision a transformative landscape for urban transportation and mobility, driven by the synergies of artificial intelligence (AI) and data analytics. AI-powered systems can manage traffic flow, providing efficient and safe urban environments by utilising real-time adjustments and predictive analytics.
This evolution will allow the way for connected and automated mobility (CAM), where AI-driven automated vehicles can support safety standards and promote shared mobility services, reducing the reliance on private car ownership and supporting overall urban efficiency.
Data analytics will empower cities to create personalised mobility solutions, with an emphasis on inclusivity and multimodal connectivity tailored to individual needs. Using the insights derived from IoT devices, sensors and connected infrastructure, cities can make evidence-based decisions, supporting innovation, investment and sustainable development.
Philippe Perret, Mobility Insights Technical Lead, BT Active Intelligence
2024 presents a critical juncture for urban transportation and mobility, as cities tackle escalating congestion, overcrowding, and a return to pre-Covid journey levels, but more importantly one of the biggest challenges is that people behaviours toward travel have changed completely as the result of the pandemic and because of the fast-evolving transport landscape with micromobility and mobility-as-a-service being on an upward trajectory.
Hence, transport professionals are facing a key challenge, adapting to this new world whilst it continues to evolve at a fast pace. Concepts developed over the last 50 years cannot apply anymore.
This where artificial intelligence (AI) will come to help in 2024. As AI can ingest large amounts of data and identify patterns which would otherwise take us months or years to discern (this being compounded by the vast amount of mobility data now being collected from CCTVs, automated traffic counts or mobile phones including contextual data such as socio-demographics). These patterns, which can be identified both in historic datasets, or near real-time, are the key to improving the transport systems both short term and long term.
This will push toward better joined up mobility, helping to bring all modes together rather than having them competing for the same space, through the development of more thought through multimodal interchanges helping to use the right mode of transport for right journey. Data and AI can provide a deeper understanding of customer behaviour, enabling the optimisation of the journey experience. This includes end-to-end journey management and ensuring seamless transitions between different modes of transport.
Alex Sbardella, Commercial and Product Director, Unicard
It’s important to talk about the opportunities that artificial intelligence (AI) can offer, but for the majority of local authorities we’re a little way off seeing those benefits just yet. Unfortunately, most of them aren’t in a position to deliver the building blocks AI needs like well-structured data, headcount with data expertise, or a clear business case to justify the cost of generating insights.
However, some are at least able to improve on the basics, thanks in part to migrating key transport and ticketing data to the cloud, while taking advantage of the readily available tools and partner ecosystem already built into the solution.
While local authorities might be behind the curve, they are accumulating lots of valuable data that can be put to good use once the right AI infrastructure is in place. The good news is that there are plenty of easy wins in terms of improving transport provision and passenger experience just through reporting and analytics, laying the groundwork for full-blown AI solutions in the future.
Anthony Sayers, Edge IOT/IIOT Ambassador, EMEA Edge Computing, Lenovo
Artificial intelligence (AI) and data will have a transformative impact on urban transportation and mobility in 2024, shaping the way ‘cognitive’ cities evolve for city dwellers. Data is the lifeblood of urban spaces, flowing directly between the cameras, sensors and meters that connect community services, including transport systems. If used to its full potential, data will empower city planners to harness the huge amounts of data generated by Internet of Things (IoT) sensors.
IoT technology is pivotal to urban mobility, delivering data on everything from local weather conditions to traffic information, harvested via networks of sensors across the city. Enabled by AI technology, data will make transport networks ‘smarter’ by sending messages from traffic lights to cars, allowing drivers to travel in a fuel-efficient way by driving at the right speed to avoid stopping and starting at red lights.
In the past, the focus has always been on capturing data, such as monitoring traffic hotspots or areas of congestion. But in 2024, cities will increasingly respond dynamically to the changing physical world, adjusting in real-time with the help of AI technologies.
For example, large language models can be used to enhance urban mobility, making it easy for both city planners and ordinary citizens to interact with the city they live in. AI will also be a crucial enabler for edge computing.
For example, edge computing nodes enable ‘smart parking’ by sensing empty parking spaces and directing cars there in real-time. It will also help first responders get to the scene of incidents faster by alerting emergency services, and then AI can preconfigure the safest and quickest route to get to the scene, rerouting other vehicles if necessary.
Paraic Quirke, Associate Director and Head of Infrastructure, Murphy Geospatial
All industries and sectors are on a digital transformation journey and urban transport is no different. Digital data promises to optimise many aspects of our urban transport systems and infrastructure. Accurately captured geospatial data, for example, enables planners and designers to use digital design and collaboration tools to expedite urban transport projects with a higher degree of certainty. This is where AI has the potential to have a significant impact.
In the geospatial sector, we are already utilising AI in our data processing workflows, helping to extract features from dense datasets such as point cloud and 360-degree imagery. What we need to address is the speed of adoption of these new digital and AI-enabled technologies. Urban transport is a risk averse sector, and for good reason, since safety of transport users and the public is paramount. In the geospatial industry for example, mass capture technologies are a great way to undertake survey data capture at scale. However, the amount of data we can gather outstrips the capabilities of the hosting and processing technology to efficiently handle these datasets.
Advancements in data hosting and analysis tools are required to fully realise the value of these datasets so that they can be further utilised by urban transport. In the UK, the recently mandated zero-emission rules will mean a significant acceleration in the roll-out of the EV charging infrastructure is now required, for example charging stations and induction charging lanes on existing roads. We’re data rich and processing poor and AI can be our ally in this and help to solve the issue, or it could just add to the problem if we’re not careful. Standardisation is going to be an essential part of how AI is embedded within transport and mobility and that will take collaboration.
Sarah Gates, Director of Public Policy, Wayve
With artificial intelligence (AI) already fundamentally changing all aspects of our lives, the next great leap will come from embodied AI – deploying AI in the physical world creating AI systems that can sense, act, learn and adapt to human behaviour in complex real-world environments. Self-driving vehicles are a great example of embodied AI. By reducing human error and improving efficiency, self-driving technology will help to make transportation safer, smarter and more sustainable.
End-to-end AI can be used to enable any vehicle to drive autonomously in any city. This mapless technology learns to drive like a human driver, from experience and data, and is then able to adapt its intelligence to new driving situations and locations. In 2024, we expect to see legislation in place that will help realise the benefits of AI-enabled maples technology. One of the key benefits of self-driving vehicles is a potential to vastly reduce road traffic accidents. The UK government’s analysis shows 85% of accidents are caused by human error. The industry is also expected to drive an economic boost of £42bn by 2035.
It was encouraging to last year see the introduction of the UK’s milestone Automated Vehicles Bill to parliament, which sets out a comprehensive liability and consumer protection framework for the safe deployment of self-driving vehicles. This legislation is world-leading – it will provide the basis for crucial public trust of this technology, paving the way for the commercialisation of self-driving technologies in the UK.
John Gillan, UK General Manager, Stuart
Tech logistics companies see enormous potential in the widespread adoption of artificial intelligence (AI). Automation promises immense gains in precision, efficiency and sustainability, but measured steps are prudent.
AI’s benefits rely on thoughtful implementation. A multifaceted approach can capture AI’s upside while delivering shared prosperity. Investment in supportive infrastructure and equitable access will allow companies of all sizes to leverage AI, not just major players. It’s important to support all policies and public-private initiatives that democratise capability rather than centralising it.
The future looks bright for AI-enabled delivery, but we must build the foundations for broad capability today. With responsible development and deployment, enhanced logistics can drive progress across the triple bottom line of sustainability, positive societal impact and commercial success.
Samuel Hurley, Co-Founder & Managing Director, Novos
In 2024, Artificial Intelligence (AI) and data are set to revolutionise urban transportation, heralding a new era of efficiency and sustainability. AI’s capacity to process vast amounts of data rapidly allows for more efficient traffic management, significantly reducing congestion and enhancing travel times. Public transit systems stand to gain immensely from AI-driven predictive maintenance. This technology not only bolsters the reliability of transportation networks but also streamlines their operational efficiency.
A key development in this revolution is the integration of autonomous vehicles into urban landscapes. With AI’s guidance, these vehicles promise to alleviate congestion and minimise pollution, contributing to a cleaner, healthier urban environment. Moreover, AI’s role in improving mobility-as-a-service platforms cannot be overstated. By providing personalised travel recommendations, AI ensures a more user-centric approach to urban mobility, catering to individual preferences and needs.
The impact of AI and data extends beyond mere operational improvements; it paves the way for a sustainable and user-friendly urban transportation landscape. However, this technological advancement brings with it a significant challenge: ensuring equitable implementation across all city areas. It is imperative that these innovations benefit every city dweller, irrespective of their socioeconomic status, to truly transform urban transportation into an inclusive and accessible system for all.
Mustapha Koaik, Country Manager – KSA, Ipsotek
Artificial intelligence (AI)-powered computer-vision technologies are becoming a prerequisite for organisations relying on camera streams to protect their assets and develop better environments. Furthermore, recent policy changes and new regulations by governing bodies indicate an increased understanding of AI technologies’ ROI and the progress made by tech companies in the AI field.
These advancements have made it possible for automated systems to identify critical events and support human eyesight and analysis, making it easier for people to mobilise within urban environments. Transportation and mobility are critical aspects for smart city transformations, and the flexibility to move with fewer obstacles caused by traffic events can be crucial to what governments see as an enhanced lifestyle toward a smart and sustainable living.
Now, all the technological progress made in this direction is beginning to converge to actual implementations and projects. Such data generated from roads and highways surveillance monitoring, in addition to IoT systems integrations, is fused into big data lakes and therefore processed by AI modules to transform raw and scattered data into actionable information and enhance smart decision-making.
Looking at the bigger picture for 2024 and beyond, we can see countries investing in transport surveillance systems at a national scale, and computer-vision solutions powered by AI are gaining more attention. Whether it is a small or large surveillance deployment, governance and policies are already in place to ensure that such deployments comply with people’s privacy and communities’ protection and rights while maintaining the necessary smart objectives.
With such governance readiness, we can expect AI-powered computer vision technologies to be at the heart of national digital transformation plans, urban transportation and mobility, and smart cities’ security and safety in 2024 and beyond.
This article was originally published in the February 2024 issue of CiTTi Magazine
Achievements and innovations in AI and data analytics will be celebrated at the third annual CiTTi Awards, which will be held on 26 November 2024 at De Vere Grand Connaught Rooms in London. Nominations are now officially open! Please visit www.cittiawards.co.uk to learn more about this unmissable event for the UK’s transportation sector.
