TIDE Transferability Methodology TIDE Final Conference Barcelona, September 2015 Birendra Shrestha Senior Traffic Modeller, Transport for London Visiting Fellow, TRG, University of Southampton, UK

Background Different city characteristics -transport and traffic conditions (infrastructure, traffic control and management, etc.), geographical, environmental, demographic, socio-economic as well as institutional frameworks -sucess in one city does not gurantee sucess elsewhere Important to identify key factors to ensures the measure‘s success in new location. Valuable to identify barriers so that they can be addressed/overcome

Transferability Process of verifying the chances of a successful implementation of a measure which has proved successful elsewhere Analysis of relevant factors Opportunity to learn lessons from the previous experience and to avoid mistakes! Source: Dziekan et al, 2013

TIDE Methodology (1) Mission statement/objectives and scoping (2) Clarification of the impacts of the measure (3) Identification of up-scaling/down-scaling need (4) Identification of the main components and characteristics (5) Identification of the level of importance of characteristics (6) Assessment of the characteristics of the adopter city (7) Conclusions

Example Source: Reading London Open data for apps based traveller information Pioneer city Adopter city

Step 1: Mission statement and scope A clearly defined mission statement (or clear objectives) and a realistic scope for a measure Should avoid any misunderstanding during the subsequent transferability and implementation processes Rest of the transferability steps should only be carried out after the adopter understands and agrees with the objectives and scope of the measure

Reading’s open data Mission statement To make traffic data available in open data server to encourage apps based traveller information Scope Management of data from traffic management and control systems only. It does not cover the traffic management control systems.

Step 2: Impacts Efficiency (capacity, journey time) Environment (emissions, noise, visual intrusion) Safety Accessibility Vehicle occupancy Benefit-to-cost ratio (BCR) Multi-Criteria Analysis (MCA)

Impacts (Reading’s open data) Wider dissemination of traffic/travel information Potential to address specific user needs (e.g. elderly and disabled). Reduce passenger waiting time More informed and better travel choices leading to modal change to public transport Increase bus patronage and revenue Support to some economic activities in the area (apps development)

Step 3: Up-scaling Determination of up-scaling (or scaling down) need: To match the city’s need To recognise the requirements and implications e.g. Route -> City-wide Source: Dziekan et al, 2013

Scaling (Reading’s open data) Reading is much smaller than London and hence the scale of implementation is much smaller This may have implications on system requirements, costs and benefits – especially demand for the information

Step 4: Main components & characteristics Factors that can contribute to the success (or failure) of a measure : Components (main factors): -Policy, stakeholders, finance, technical requirements, etc. Characteristics (sub-categories) e.g. for policy: -Public transport policy, traffic management policy, accessibility policy, pollution reduction policy

Components & characteristics (open data) ComponentsCharacteristics Strategies and policies Open data policy Traffic management policy Finances Capital costs of design and implementation Running costs Economic benefits Stakeholders involvement Urban Traffic manager/controller Public transport operators Government (local) Other requirements Market demand Data quality

Step 5: Level of importance of characteristics According to the adopter city High/medium/low Supporting comments

Importance of characteristics (open data) CharacteristicsImportanceComments Open data policyHighThe main objective to be supported by the measure Traffic management policy HighOpen data supports overall traffic management policy Capital costsMedium The implementation cost is relatively lower than the infrastructure providing data Running costsMediumSimilar to existing ITS systems Urban Traffic managerHigh Traffic manager were in favour of fewer priority interventions as a result of advanced priority, but concerned over potential complexity Bus operatorsHighOperators needed to be convinced the about the benefits of open data Local governmentHighLocal government needs to approved and financed the scheme Market demandHigh Market demand influences the involvement of 3 rd parties in apps development Data qualityHighGood quality data is needed to assure apps developers and travellers

Step 6: Assessment of characteristics Subjective assessment of ease/difficulty in implementation by adopter city Assessment scale: +2strong support for transferability +1modest support for transferability 0neutral -1modest constraint for transferability -2strong constraint for transferability

Assessment of characteristics (open data) CharacteristicsImportanceAssessment Public transport policyHigh+2 Traffic management policyHigh+2 Capital costs of design, implementationMedium0 Running costsMedium0 Urban Traffic manager/controllerHigh+1 Public transport operatorsHigh0 Government (local)High0 Market demandHigh Data qualityHigh

Step 7: Conclusions Drawing conclusions through the assessment One or more strong constraints (-2) to transferability -no transfer unless the conditions can be overcome One or two modest constraints(-1) (no strong constraints) -difficult to transfer the measure unless the conditions can be addressed If there are no constraints at all -likely that the measure could be successfully transferred

Conclusions (Reading’s open data) The measure is potentially transferable to Reading dependent on: Data quality – Needed to make sure that the data available is reliable Market demand – pump priming may be needed to develop initial apps and generate interest amongst apps developers and travellers

Birendra Shrestha Thank you!