Developing a De-centralised AI-enabled Optical Sensor for Mobility

开发分散式人工智能移动光学传感器

• 批准号: 10073710
• 金额: $ 5.82万
• 依托单位: CUMRA LTD
• 依托单位国家: 英国
• 项目类别: Grant for R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10073710
• 关键词: Developing; De; centralised; AI; enabled

The average car in England is driven just 4% of the time. For the rest of the time, the car is either parked at home (73%) or parked elsewhere (23%). Though when it comes to mobility, parking is often overlooked.Poorly managed parking spaces cause stressful experiences for drivers, lead to 30% of traffic congestion, contribute to air pollution, and incur huge economic costs.The challenges that parking presents are compounded due to the lack of parking data: drivers have no visibility over the available parking spaces, city councils utilise their parking spaces relying on outdated information, and traffic authorities lack the tools to implement dynamic policies.We aim to develop a smart city platform to tackle this problem by making parking data accessible, on demand, and real time. We aim to improve the users' transport experience, reduce the carbon footprint of cruising cars, enhance local economies, and make cities more liveable.Using this Platform, drivers won't need to cruise for an available parking space, city councils will be able to make data-driven decisions based on real time data, and traffic control authorities will be able to implement dynamic policies to control traffic and reduce congestion.

在英国，汽车的平均行驶时间只有4%。其余时间，汽车要么停在家里（73%），要么停在其他地方（23%）。虽然在移动出行方面，停车往往被忽视。管理不善的停车位会给驾驶员带来压力，导致30%的交通拥堵，造成空气污染，并产生巨大的经济成本。由于缺乏停车数据，停车带来的挑战更加复杂：驾驶员无法看到可用的停车位，市政委员会依靠过时的信息来使用他们的停车位，我们的目标是开发一个智慧城市平台，通过使停车数据可访问，按需和真实的时间来解决这个问题。我们的目标是改善用户的交通体验，减少巡航汽车的碳足迹，增强地方经济，使城市更宜居。使用这个平台，司机将不需要巡航一个可用的停车位，市议会将能够根据真实的时间数据做出数据驱动的决策，交通管理当局将能够实施动态政策来控制交通和减少拥堵。