All Transport
ITF 交通运输展望2023
Transport Outlook, Policy Insights,
15 May 2024
- 为未来交通运输及燃料补充基础设施制定全面的发展战略
- 加速向清洁车辆转变
- 在最有效的地区实施交通模式转变和交通需求管理政策
- 评估政策时要考虑城区的额外收益
- 改革车辆税,捕获新车辆的外部成本
Perspectives des transports FIT 2023
Transport Outlook, Policy Insights,
29 April 2024
- Élaborer des stratégies globales au service de la mobilité et des infrastructures de demain
- Accélérer la transition vers des flottes de véhicules propres
- Mettre en œuvre des politiques de report modal et de gestion de la demande là où elles sont le plus efficaces
- Au stade de l’évaluation, considérer les avantages additionnels qu’une politique peut apporter aux zones urbaines
- Réformer la fiscalité automobile de façon à capter les coûts externes des nouveaux parcs de véhicules
Urban Planning and Travel Behaviour
Roundtable Report, Policy Insights,
19 December 2022
- Improve co-ordination between transport planning and other policy areas.
- Foster effective metropolitan governance of transport.
- Develop and implement sustainable urban mobility plans.
- Move beyond planning based on demand forecasts towards vision-led, strategic transport planning.
- Use relevant indicators to monitor the performance of transport systems.
- Rectify biases in policies that favour car travel over alternative transport options.
- Prioritise investments that improve the use of low-range and sustainable transport modes.
- Reallocate road space to sustainable, efficient and safe transport modes.
Reporting Mobility Data: Good Governance Principles and Practices
Corporate Partnership Board Report, Policy Insights,
9 March 2022
- Embed individual privacy rights at the heart of data-reporting policies.
- Adopt coherent data-governance frameworks.
- Establish, document and communicate the basis for public authority data-reporting mandates.
- Align data-reporting mandates to targeted outcomes.
- Create and adhere to clear personal data processing, retention and destruction policies.
- Explore ways to ensure that data reporting preserves privacy and protects commercial interests by default.
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.
Calles Más Seguras: Benchmarking Mundial de Seguridad Vial Urbana
Research Report, Policy Insights,
12 March 2019
- Desarrollar observatorios de movilidad en las ciudades.
- Recolectar datos de accidentes de tráfico de los hospitales, no solo de los registros policiales.
- Adoptar objetivos ambiciosos para reducir el número de víctimas.
- Centrarse en la protección de los usuarios vulnerables de la vía pública.
- Utilizar indicadores apropiados para medir la seguridad de los usuarios vulnerables de la vía pública en las ciudades.
- Calcular la población que se desplaza de día para mejorar la comparabilidad de las estadísticas de seguridad vial.
- Dar prioridad a la investigación sobre accidentes de tráfico urbanos.
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.