Skip main navigation

£199.99 £139.99 for one year of Unlimited learning. Offer ends on 28 February 2023 at 23:59 (UTC). T&Cs apply

Find out more

Processing sensor data

Many different factors need to be considered to develop an autonomous vehicle. Dr Lyudmila Mihaylova outlines her research into what is needed.
This is part of a video surveillance system where people are moving and the purpose of this system is to detect pedestrians and track their motion, and possibly analyse behaviour. One application area for autonomous vehicles is airports and train stations. You can think about Heathrow, Terminal Five, where the pods are transporting passengers from the terminal to the parking place. The pods, they need to know how many passengers are at Terminal Five and how many they need to transport to the parking. And with my research, we focus on sensor data fusion algorithms that can detect the number of people that are at the parking, and then the pods will transport them to the terminal.
Before we see autonomous cars being ubiquitous there’s a long way to go. Whereas it’s much easier to have connected vehicles, because the vehicle can have all kinds of sensors and be connected with other vehicles, and with a transportation centre. In order to facilitate commuters to go from place A to B, we are developing algorithms that can predict better paths, and the shortest, or the most beautiful paths. Or going through areas where there are historical monuments, the most economical paths, and those with least pollution. So these are different objectives which can be achieved. We have data from the city centre of Birmingham. These are traffic loop data. We have video camera feeds.
We have a GSM data, possibly data from bus stations, taxi drivers, and others, and from metropolitan areas. One of the objectives is to predict the traffic. Also we have social networks. So we have the involvement of social network information from Twitter, from Facebook. If people want to find out in real time what’s the weather, what’s the traffic status, they can use Twitter and online data, then send their information, and improve their mobility. We are working together with the city centres. It depends on how quickly the cities, the councils, would accept this technology in our everyday life. It should come in the next two, three years.

Autonomous systems need to process large volumes of data which can arrive from multiple, diverse sensors such as RADAR, LIDAR and cameras. In this video, Dr Lyudmila Mihaylova explains how her research is tackling this challenge, by developing intelligent algorithms that can extract meaningful information from these large data sets.

Lyudmila also discusses her research with the SETA consortium, which is helping to change the way that mobility is organised, monitored and planned in large metropolitan areas. By collecting and processing dynamic data from people, cars, city sensors and distributed databases, this project hopes to inform decision makers on how to improve town planning and infrastructure, as well as allowing individuals to plan their journeys in a more efficient and sustainable way.


Would you like to see this sort of technology applied to where you live? How do you think it could help you?
This article is from the free online

Building a Future with Robots

Created by
FutureLearn - Learning For Life

Our purpose is to transform access to education.

We offer a diverse selection of courses from leading universities and cultural institutions from around the world. These are delivered one step at a time, and are accessible on mobile, tablet and desktop, so you can fit learning around your life.

We believe learning should be an enjoyable, social experience, so our courses offer the opportunity to discuss what you’re learning with others as you go, helping you make fresh discoveries and form new ideas.
You can unlock new opportunities with unlimited access to hundreds of online short courses for a year by subscribing to our Unlimited package. Build your knowledge with top universities and organisations.

Learn more about how FutureLearn is transforming access to education