The streets of Cambridge are to play host to Britain's first self-driving shuttle from today in milestone tests that will see the bus ferry passengers on a busy main road. Developed by Aurrigo, the three Auto-Shuttles are running a two-mile route from Madingley Road Park and Ride around the University of Cambridge's West Campus. This is the first time that a custom-made driverless shuttle has operated a route in the UK while surrounded by other traffic, bicycles and pedestrians. Each shuttle will be able to seat 10 passengers after social distancing measures are lifted, with the passengers selected for the trial using an app to arrange a journey. The streets of Cambridge are to play host to Britain's first self-driving shuttle (pictured) from today in milestone tests that will see the bus ferry passengers on a busy main road Aurrigo's Auto-Shuttle is the world's first conventionally driven electric and autonomous purpose-built vehicle.

The streets of Cambridge are to play host to Britain's first self-driving shuttle from today in milestone tests that will see the bus ferry passengers on a busy main road. Developed by Aurrigo, the three Auto-Shuttles will run a two-mile route from Madingley Road Park and Ride around the University of Cambridge's West Campus. This is the first time that a custom-made driverless shuttle has operated a route in the UK while surrounded by other traffic, bicycles and pedestrians. Each shuttle will be able to seat 10 passengers after social distancing measures are lifted, with the passengers selected for the trial using an app to arrange a journey. The streets of Cambridge are to play host to Britain's first self-driving shuttle (pictured) from today in milestone tests that will see the bus ferry passengers on a busy main road Aurrigo's Auto-Shuttle is the world's first conventionally driven electric and autonomous purpose-built vehicle.

The maker community and manufacturers have come together along with their 3D-printers to fight the pandemic. People ranging from garage hobbyists to established companies are 3D-printing equipment from face shields through swabs to ventilator parts. Telemedicine is a technology that provides medical advice to the concerned people in home confinement. Technology has found a quick fix during the pandemic. Telemedicine is a ready-made option, wherein, concerned people can consult doctors from the comfort of their homes regarding their symptoms.

Many countries have introduced social distancing measures to slow the spread of the COVID-19 pandemic. To understand if these recommendations are effective, we need to assess how far they are being followed. To assist with this, our team has developed an urban data dashboard to help understand the impact of social distancing measures on people and vehicle movement within a metropolitan city in real time. The Newcastle University Urban Observatory was established to better understand the dynamics of movement in a city. It makes use of thousands of sensors and data sharing agreements to monitor movement around the city, from traffic and pedestrian flow to congestion, car park occupancy and bus GPS trackers.

Motivated by the current COVID-19 outbreak, we introduce a novel epidemic model based on marked temporal point processes that is specifically designed to make fine-grained spatiotemporal predictions about the course of the disease in a population. Our model can make use and benefit from data gathered by a variety of contact tracing technologies and it can quantify the effects that different testing and tracing strategies, social distancing measures, and business restrictions may have on the course of the disease. Building on our model, we use Bayesian optimization to estimate the risk of exposure of each individual at the sites they visit, the percentage of symptomatic individuals, and the difference in transmission rate between asymptomatic and symptomatic individuals from historical longitudinal testing data. Experiments using real COVID-19 data and mobility patterns from T\"{u}bingen, a town in the southwest of Germany, demonstrate that our model can be used to quantify the effects of tracing, testing, and containment strategies at an unprecedented spatiotemporal resolution. To facilitate research and informed policy-making, particularly in the context of the current COVID-19 outbreak, we are releasing an open-source implementation of our framework at https://github.com/covid19-model.