Dashboard | D4AMS

Ghent

Bologna

Munich

Amsterdam

For the city of Ghent, a new MATSim model was developed based on the three-annual travel survey the city organises. These travel diaries were used as input for the model. We did this for data from 2015, with 1500 respondents, from 2018, with 3000 respondents, and from 2021, with 1500 respondents. For this dashboard, only the simulation data for 2018 is shown.

The scenarios with street closures are based on the real-life programme Living Street or "leefstraten" in Ghent (Belgium). Each year, residents can organise themselves and apply for a street closure in their street during the summer months. We used the interventions of the past several years in our model, resulting in a total of 35 street closures across the city. For the extreme scenario, we added an additional 30 street closures.

General results

We can see that the street closures create a shift in car traffic from the city centre towards the ring roads, both the inner ring road (R40) as the outer ring road (R4), specifically for key-points that provide access to the ring roads. Implementing street closures result in an overall decrease of car traffic and increase in bicycle traffic. This is even more so when implementing a higher amount of street closures.

For the bike-sharing scenario, we see a similar result, leading to an increase in bicycle traffic and a decrease in car traffic. The opposite is true for adding car-sharing stations.

Ghent City Workshop

To test the scenarios, we organised a workshop with the City of Ghent. We invited mobility experts and transport planners to evaluate the use of the scenarios presented and create new hypothetical scenarios of interest to the city.

Relevant links:

BAU scenario

Street closures

Car-sharing +
Street closures

Bike-sharing +
Street closures

GENT BAU Scenario
We can see here in dark blue where car traffic is present. Since the data is only from people living in Ghent, we can see that the inner ring road (R40) has most car traffic, together with some other arterial roads and the outer ring road. The modal split here is: 43% cars, 31% bicycle, 16% walking, and 10% public transport.

Limited street experiment scenario
In a scenario where 35 streets are no longer accessible by cars, we see that areas with high car traffic are similar to the BAU scenario. Overall, there is a small decrease in car traffic as we can see in the modal split. On the map, we see that mainly the ring road is the area where there is the largest absolute decrease in car traffic. When looking at the difference between the two scenarios, mainly the southern and western parts of the inner ring have an increase in car traffic, whereas the inner-city remains more or less the same, with some slight differences. Remarkably, in Gentbrugge (southeast of the inner ring) a significant decrease in car traffic occurs. This can be attributed to a bridge that is closed for car traffic in this scenario. The modal suggests that implementing street closures in residential streets across the city, might result in a shift in car traffic from the city centre to the ring roads.

Limited street experiment scenario + car-sharing
In this scenario where the 35 street closures are accompanied by car-sharing stations, concentrations of high car traffic occur in similar areas. The areas where there is a decrease in car traffic (green hexagons) are rather limited in this scenario. Instead, we see multiple hexagons with strong increases (red) and multiple areas with no increases (yellow) all around the city. It is clear that an increase of car usage has appeared in this scenario. This suggests that an increased uptake of car-sharing stations could lead to an rise in car traffic.

Limited street experiment scenario + bike-sharing
Closing 35 streets for car traffic and accompanying them with a bike-sharing station, generally results in small increase in bike traffic. Overall car traffic remains more or less the same, but some spatial difference can be noted. The areas where there is a strong decrease in car traffic (green hexagons) are very limited in this scenario. Rather, we see multiple hexagons with strong increases (red) and multiple areas with with no increase or decrease (white) both in the city centre and beyond. However, most increases are located within the inner ring road area and on some key-points along this road.

For the city of Bologna, we developed a series of MATSim scenarios based on a synthetic population of 25 000 inhabitants with hypothetical travel plans. Unlike to the case study of Ghent, the trips made by this synthetic population are only taking place inside of the city of Bologna. This means that traffic in some parts of the city, for example on the outer-ring road, is underrepresented.

For this city, only one hypothetical scenario was created. This was done in collaboration with the City of Bologna and the other EX-TRA project partners. The scenario involved the creation of several street experiments in combination with low-traffic streets (streets with limited car capacity). All these potential street interventions are situated near schools where the City of Bologna aims to enhance safety in the vicinity. This resulted in a total of 20 streets that were entirely closed off for car traffic and 35 streets where the car capacity flow was halved.

Bologna Tool Combination

Bologna was used as a case study to test the co-applicability of the three tools developed in the EX-TRA project (GOAT by Plan4Better, Munich and IAPI by PoliMi, Milan). In this analysis, we focused on school streets and their direct vicinity. Together with the City of Bologna, a number of neighbourhoods of interest was selected. The three tools analysed accessibility, walkability and car traffic in these neighbourhoods. Find out more here!

Relevant links:

www.comune.bologna.it

BAU scenario

Street closures

This scenario shows the BAU result of the model of Bologna. It depicts the status-quo, as if nothing has changed in the city and shows the average daily travel. It serves here as a baseline for comparison with the other scenarios. Similar to the Ghent case study, traffic is concentrated within the outer-ring road and mainly present along the inner-ring road and some arterial roads. We can also see a lot of car traffic in the city centre.

This scenario shows the hypothetical street experiment scenario in Bologna. What immediately stands out when comparing this scenario to the BAU situation, is that the areas with the most differences in terms of car traffic volume are located in the vicinity of the street interventions. For many of the street closures implemented, we can see a sharp decrease in car traffic in the direct vicinity, but at the same time an increase in areas next to the street closure. This is because traffic is being re-routed to other streets. In the city centre, there are both areas with a large increase and areas with a large decrease. The inner-ring road, on the other hand, mainly experiences decreases in car traffic, which is surprising because one would expect traffic rerouting to roads with a high car capacity due to the street interventions.

For the city of Munich, we developed a series of MATSim scenarios based on a 22% synthetic population of 324 000 inhabitants with hypothetical travel plans. For this city, three hypothetical scenarios were created. These are similar to the ones of Ghent and Amsterdam, which allows to make a comparison over the different cities. In the first scenario, a total of 35 streets are closed off for car traffic. The second scenario depicts the same street closures combined with station based shared car stations near the closed streets. The third scenario depicts the same as the previous, but shared cars are replaced by free floating shared bikes.

Relevant links:

BAU scenario

Street closures

Car-sharing +
Street closures

Bike-sharing +
Street closures

This scenario shows the BAU result of the model of Munich. It depicts the status-quo, as if nothing has changed in the city and shows the average daily car traffic volume. It serves as a baseline for comparison with the other scenarios. In the city centre, most car traffic is present, beside this we also see the roads flowing in and out of the city are the areas with the highest traffic volumes.

When the street closures are combined with additional car-sharing alternatives, we see that there is a strong increase in the usage of cars in the city of Munich. This happens almost everywhere, yet some trends are visible. Especially in the city centre and the roads feeding the centre from the suburban zones, the strongest increase in car traffic is present. In the city centre, there are some areas with a decrease in car traffic. In the suburban zones, the strongest decreases are present.

Compared to the other scenarios, the scenario where bike-sharing has been implemented, shows a majority of neighbourhoods where a decrease of car traffic takes place. This is mainly occurring in the suburban areas of Munich. In the city centre and the roads flowing in and out the city, there is a more mixed image. Overall, there is a decrease in car traffic, but some areas experience an increase in car traffic, although this is rather minor, especially compared to the scenario with car-sharing.

For the city of Amsterdam, we developed a series of MATSim scenarios based on a 18% synthetic population of 150 000 inhabitants with hypothetical travel plans. For this city, three hypothetical scenarios were created. These are similar to the ones of Ghent and Munich, which allows to make a comparison over the different cities. The three scenarios are respectively one where only 35 streets are closed off for car traffic. The second scenario depicts the same street closures combined with additional station based shared car stations near the closed streets. The third scenario depicts the same as the previous but instead of share cars, now shared bikes are present.

Relevant links:

Mobiliteit Amsterdam

BAU scenario

Street closures

Car-sharing +
Street closures

Bike-sharing +
Street closures

This scenario shows the BAU result of the model of Amsterdam. It depicts the status-quo, as if nothing has changed in the city and shows the average daily car traffic volume. It serves as a baseline for comparison with the other scenarios. Clearly noticeable are high traffic volumes on the outer ring road, which is the main arterial traffic link surrounding the city. Beside this we see that the inner city also has fairly high levels of traffic in certain neighbourhoods.