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What are enablers and barriers when working on sustainable solutions for urban mobility? We have invited city representatives, traffic engineers and mobility providers from the public and the private sector to join our annual User Group Meeting. Together with our software users, we have discussed best practices and current challenges. Here is what we learned:
Reducing air pollution is a key factor to improve the livability in cities.
From banning cars completely in city centres to investing in bicycle infrastructure and encouraging people to make the transition to zero-emission cars – cities and municipalities push forward a range of measures to improve the quality of life with better mobility services, less congestion and fewer emissions. For this to work cities and citizens have to work together to achieve a change in behaviour overcoming old habits of always relying on cars instead of using public transport, bikes or ride sharing.
As the number of cars on our streets will not drop overnight, it is important to optimise traffic during the transitional phase towards fewer privately owned vehicles. Adaptive-signal control systems are a proven tool to reduce stop-and-go traffic thereby decreasing emissions and waiting times. The model-based tools optimise the usage of the pre-existing network or of individual junctions. They also allow the control of different modes. Public transport can, for example, be prioritised when assigned a high weighting. Buses or trams then receive priority at an intersection because they move more people than cars which often do not have more than more passenger.
Ride sharing services need strategic planning to integrate them with a city’s public transport.
Strengthening public transport is one way to discourage people using or buying cars. But expanding the bus, metro or tram network is not always the best strategy, especially in areas where the demand is very heterogeneous and cannot be met by a fixed line. To complement public transport serving the first and the last mile, Mobility as a Service (MaaS) is the on-demand shared solution.
But predicting the future market share of a MaaS fleet is difficult and trial-and-error involves financial and operational risks. Strategic planning is the key to efficient and successful ride sharing concepts. With the right software tool, cities and mobility providers calculate the relevant performance indices to create an effective business model for MaaS – from operational to passenger service related KPI, including congestion impact analyses.
Air taxis are one option to escape peak hour road congestion in urban areas.
To tackle congestion on the ground and reduce air pollution, autonomous on-demand and electric drones for passengers are no longer a future scenario, test flights are already under way. While at first the target group may be business travellers, coming from the airport and continuing their journey to the city centre or vice versa, air taxis will be a safe and affordable way of travelling for everyone in the long run.
But to create an urban air solution requires extensive planning. It is crucial to calculate the optimal number of locations, at which the take-off and landing sites should be placed. Prime candidates include existing car parks with large enough upper decks or roofs, helicopter pads and highway intersections. Traffic simulation software, especially microsimulation, helps to create models that make it easy to calculate the most profitable locations and routes.
This post is also available in: German