Predicting how shared and autonomous vehicles will transform a city
About 2.8 million people live in the metropolitan area of Portugal’s capital Lisbon, and they make over 5 million trips per day – over 60% of them by cars. The city wanted to find an efficient way to substitute private cars with shared rides by introducing Mobility as a Service (MaaS).
That’s why The Lisbon Study (full name: Urban Mobility System Upgrade: How shared self-driving cars could change city traffic) was created, with support of PTV Group’s modeling. The study, commissioned by the International Transport Forum, assesses the impact of a shared self-driving vehicles replacing car trips.
Based on traffic demand data, PTV set up a transportation model of Lisbon in PTV Visum and analyzed the potential outcomes of MaaS. In the model, motorized trips were either done by Lisbon’s metro system or by fleets of autonomous vehicles. This way, transport runs at optimum capacity, with minimum detours and delays.
Turning drivers into passengers keeps services efficient and convenient, as currently most private cars are used for less than an hour per day. The models showed that switching to MaaS reduces by up to 90% the number of vehicles needed to cover all trips. This means less pollution and elimination of on-street parking, freeing up valuable urban spaces that can be re-purposed.
Even during peak hours, the number of needed vehicles can be kept at bay. To prove this, two simulation runs were created: One modeling an entire day in Lisbon, and the second covering only the peak hours. In the 24-hour scenario, the number of vehicles required is only 10% of existing fleet; during peak times, 35% of vehicles were sufficient to serve all customers.
The results of the modeling provide an excellent starting point to explore new mobility concepts and business models for public and private operators - in Europe and worldwide. Modelling MaaS operations before deploying them is an eye-opener for what is possible and what is necessary to ensure success.
City-wide models showed number of vehicles can be reduced by up to 90%
Models showed how the city can cope with peak hours demand
Lisbon can rely on the models as it develops new mobility concepts