{"id":21519,"date":"2021-12-26T11:27:57","date_gmt":"2021-12-26T10:27:57","guid":{"rendered":"https:\/\/www.intellias.com\/?p=21519"},"modified":"2024-07-23T12:42:00","modified_gmt":"2024-07-23T10:42:00","slug":"ai-in-urban-mobility-give-citizens-what-they-want-or-die-trying","status":"publish","type":"blog","link":"https:\/\/intellias.com\/ai-in-urban-mobility-give-citizens-what-they-want-or-die-trying\/","title":{"rendered":"AI in Urban Mobility: Give Citizens What They Want or Die Trying"},"content":{"rendered":"

Today, half of the world\u2019s population lives in urban areas. The United Nations expects this proportion to grow to 68% by 2050<\/b>. The needs of these urban residents are obvious. As they adapt to a city\u2019s pace, culture, and spirit, they all want to get something in return: a little bit of comfort while commuting to work or the ability to anticipate a timely delivery. Such things can make anyone\u2019s day better.<\/p>\n

Cities should adapt to their citizens \u2014 to understand and care about them. And this is where AI in urban mobility<\/a> steps up.<\/p>\n

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How can technology solution providers apply AI in urban mobility?<\/h2>\n

Despite the hype around artificial intelligence in\u00a0urban mobility<\/a>, even state-of-the-art AI applications perform only very specific tasks. Teaching traffic AI to predict and control traffic density, optimize the route to stick to the estimated time of arrival, and plan drone last-mile delivery<\/a> seems like an easy job, but in reality it\u2019s not. Road infrastructure, connected cars, and mobile devices generate only raw data. Mobility service providers need to put every effort into getting the most value out of this data and teaching AI systems how to interpret it. Mobility providers can then use these results to perform complex tasks and build an AI-powered mobility ecosystem with smart urban mobility solutions<\/a>.<\/p>\n

Ways to reinforce AI with big data generated across different sources<\/b>
\n\"AI<\/p>\n

Adoption of AI in urban mobility brings benefits for both private stakeholders (citizens, mobility app users) and public stakeholders (municipalities, transportation and mobility service providers). Combining urban mobility and artificial intelligence software developmen<\/a>t, cities can start saving money on energy and transportation planning, while users can save time and nerves when commuting to work and receive better services using an intelligent routing system.<\/p>\n

How is artificial intelligence used in mobility and transportation services?<\/b>
\n\"AI<\/p>\n

Even the most developed cities have room for improvement in terms of the availability, convenience, safety, and performance of transportation, logistics, supply chains<\/a>, and micro-mobility services.<\/p>\n

Top 10 cities by urban mobility ranking<\/b>
\n\"AI
\nSource: McKinsey & Company \u2013 Elements of success: Urban transportation systems of 24 global cities<\/a><\/em><\/p>\n

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At the moment I need 17 apps to use all the various means of transport. In future this will probably be covered by just one app, that also knows my own personal preferences.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\tMirko Knaak, <\/span> Head of AI and machine learning at IAV Digital Lab<\/span><\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section>\n

As cities continue to grow, municipalities and mobility service providers should prepare to mitigate the consequences of inefficient and environmentally unfriendly transportation systems. AI can play a huge role in the battle to design cities for people, supporting adequate growth while addressing its negative consequences impact. We\u2019ll focus on the following AI-powered urban mobility solutions<\/a> that make citizens fall in love with the cities in which they live:<\/p>\n

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  • Intelligent routing and AI navigation systems<\/li>\n
  • Smart search for parking spots<\/li>\n
  • Traffic prediction and monitoring<\/li>\n
  • Improved road safety<\/li>\n
  • Enhanced delivery services<\/li>\n
  • Electrification of transportation and infrastructure<\/li>\n<\/ul>\n

    Intelligent routing and AI navigation systems<\/h2>\n

    Nowadays, navigation systems are location-first tools that get contextual updates only quarterly or once a year. On-board navigation systems are usually based on proprietary map data that\u2019s hard to update even with critical content like information about road repairs and emergencies. Moreover, drivers often complain about these systems\u2019 detached user interfaces and outdated mobile device connectivity.<\/p>\n

    Drivers want to use navigation systems without stumbling with their functionality and be able to receive real-time contextual data personally tailored to them without being distracted from the road. Implementing best practices<\/a> in the development of smart navigation systems and artificial intelligence route planning may alleviate pressure on busy and overcrowded streets across cities, assisting drivers in planning optimal routes. AI navigation may change a planned route in response to real-time events by collecting data from other cars, cameras, IoT sensors, and connected infrastructure.<\/p>\n

    The trigger for re-planning a route could be a traffic jam in the city center, worsening weather conditions and increased taxi calls, or the next Lakers game gathering thousands of fans around the Staples Center. AI navigation takes all these factors into account when offering route suggestions to save drivers\u2019 time and save the whole city from being paralyzed by congestion.<\/p>\n

    Voice recognition based on natural language processing also contributes to the adoption of AI technologies in the car navigation segment. When drivers don\u2019t need to manually input commands to their navigation system but can speak them instead, they can focus on the road, decreasing the chance of incidents.<\/p>\n

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    Learn how a premium car manufacturer built a hassle-free navigation HMI with voice recognition to bring routing and guidance excellence to the luxury car segment<\/p>\n

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    <\/div>\n <\/div>\n <\/div>\n Read more<\/span>\n\t\t <\/a><\/div>\n

    Smart search for a parking spot<\/h2>\n

    You may hurry for a meeting and arrive on time to your destination only to find there\u2019s nowhere to park. All your speeding and rushing traffic lights didn\u2019t save you. Your risks were in vain, as the parking in front of the building is full. Now you have to find a place to park a few blocks away. Probably every driver has faced the problem of finding a parking spot in the city center.<\/p>\n

    Smart navigation systems<\/a> may plan routes taking into consideration where to leave the car while you\u2019re doing your business. The typical smart parking search algorithm<\/a> for mobile or in-car navigation systems goes as follows:
    \n\"AI<\/p>\n

    Watch an example of a smart parking solution to find a free parking spot during busy hours without losing extra time.<\/p>\n