All Transport
Governing Transport in the Algorithmic Age
Corporate Partnership Board Report, Policy Insights,
22 May 2019
- Make transport policy algorithm-ready and transport policy makers algorithmically-literate.
- Ensure that oversight and control of algorithms is proportional to impacts and risks.
- Build in algorithmic auditability by default into potentially impactful algorithms.
- Convert analogue regulations into machine-readable code for use by algorithmic systems.
- Use algorithmic systems to regulate more dynamically and efficiently.
- Compare the performance of algorithmic systems with that of human decision-making.
- Algorithmic assessment should go beyond transparency and explainability.
- Establish robust regulatory frameworks that ensure accountability for decisions taken by algorithms.
- Establish clear guidelines and regulatory action to assess the impact of algorithmic decision-making.
- Adapt how regulation is made to reflect the speed and uncertainty around algorithmic system deployment.
Big Data and Transport
Corporate Partnership Board Report, Policy Insights,
30 April 2015
- 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 what it 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 all the benefits of Big Data.
- Data visualisation will play an increasingly important role in policy dialogue.
Urban Mobility System Upgrade
Corporate Partnership Board Report, Policy Insights,
31 March 2015
- Self-driving vehicles could change public transport as we currently know it.
- The potential impact of self-driving shared fleets on urban mobility is significant. It will be shaped by policy choices and deployment options.
- Active management is needed to lock in the benefits of freed space.
- Improvements in road safety are almost certain. Environmental benefits will depend on vehicle technology.
- New vehicle types and business models will be required.
- Public transport, taxi operations and urban transport governance will have to adapt.
- Mixing fleets of shared self-driving vehicles and privately-owned cars will not deliver the same benefits as a full TaxiBot/AutoVot fleet - but it still remains attractive.