The 21st century is awash with data from sensors, vehicles, smartphones, parking systems, inventory tracking systems, ticketing systems, geographic applications, buildings,
energy distribution networks and multiple other digital and analogue sources including video streams. There are tremendous upsides from the use and fusion of these
data streams to better manage and optimise transport services and improve safety. There are also associated risks since much of this data is highly personal
in nature. It looks at the considerations authorities should have regarding the creation, processing, conditions of use and access to data that could help them
carry out their mandates.
How
We undertook this study on the basis of meetings and discussions amongst project partners, desktop research and invited the contribution of
an external expert group – Carlo Ratti Associati in conjunction with the MIT SENSEable City Laboratory.
What we found
The volume and speeds at which data today is generated, processed and stored is unprecedented and will fundamentally alter the transport sector
Embarked sensors and data storage/transmission capacity
in vehicles provide new opportunities for enhanced safety
for both conventional and increasingly automated vehicles
Multi-platform sensing technologies are able to precisely locate and track people, vehicles and objects in a way that has never before been possible
The fusion of purposely-sensed, opportunistically-sensed and crowd-sourced data generates new knowledge regarding transport activity and flows. It also creates unique privacy risks
Location and trajectory data is inherently personal in nature and difficult to anonymise effectively
Data protection policies are lagging behind new modes of data collection and uses – this is especially true for location data
Policy Insights
Road safety improvements can be accelerated through the specification and harmonisation of a limited set of safety-related vehicle data elements
Transport authorities will need to audit the data they use in order to understand what it says and does not say and how it can best be used
More effective protection of location data will have to be designed upfront into technologies, algorithms and processes
New models of public-private partnership involving data-sharing may be necessary to leverage both public and private benefits
Data visualisation will play an increasingly more import role in policy dialogue
