How to Measure the Potential of Transferring Trips from Car to Public Transport and Soft Modes: the Case of Madrid

How to Measure the Potential of Transferring Trips from Car to Public Transport and Soft Modes: the Case of Madrid


Prof. Andres Monzon, TRANSyT, Polytechnic University of Madrid, ES; Luis A. Vega, UPTC, CO


This paper explain the methodology designed to measure the potential of transferring car trips to public transport and soft modes. It is applied to Madrid city and a nuber of policy recommendations could be done on the results.


Automobile has been a key element to foster economic, social and cultural development in metropolitan areas. However it has also facilitated a wide urban sprawl and produced a number of externalities. In addition, the growing number of car trips has reduced the effectiveness because traffic congestion minimize speed which is one of the main advantages.

Therefore there is big concern to achieve a more balanced modal split in urban areas. Many urban policies are oriented to increase trips in public transport, walking and bicycle. But it is not possible to provide reliable and rapid public transport services in some areas (low density) or to walk or cycle when distances are long. Therefore it is necessary to identify which is the actual potential of transferring trips from car in each urban area. It is not possible to figure out that all car trips could be transferred to other alternative modes without affecting seriously economic activities and social life. This figure is very dependent on local conditions and the characteristics of the activities.

The paper focuses on a new methodology to calculate how many trips could be transferred to either public transport or soft modes in each origin-destination pairs of zones. This potential of transfer is determined without changing main trips characteristics: trip time, possibility of multiple destinations trips, and total budget of time (1,2 hours/day) dedicated to travel in week days. In other words, the proposed methodology tends to identify which trips could be done in public transport or soft modes, instead of car, without affecting drivers? trip diary.

The analysis carried out demonstrates that many trips can not change their mode because either there is not a valid (trip time) alternative in public transport, the driver is doing a multiple destination trip or he/she is using car to carry other persons (children to school, typically) in his way to work, etc.

In addition, city characteristics influence the potential of transfer a lot: urban density, location of jobs, schools, etc. There is also a number of issues that have also a big influence in mode choice: timetable, type of job, etc.

To consider all these conditions a decision-tree has been designed which is applied to each origin-destination relation in the mobility surveys. This decision-tree analyses the potential of transfer in a sequential way: number of trips that are not linked to car due to personal or social conditions, capability of alternative modes to offer the same trip, then comparability of trip time for each trip, and not exceeding the daily budget of time for the total number of trips performed in a week day.

To validate the proposed methodology, it has been applied to a case study: the city centre area of Madrid with some one million inhabitants. This area has a good offer of public transport, is quite dense and has chronic traffic congestion.

The results show that the potential of transfer is not as big as expected because the rationale of mode decision has to fulfil all the conditions explained above. It can be said that, in this case-study, a big number of possible public transport or walking trips are already done in this way. The potential of transfer accounts for 168.000 car trips each day (only 11% of total car trips). Among them, 75% could be transferred to public transport, 15% to bicycle and 10% to walking. This figures could be higher if municipality would offer better facilities for public transport, cycling or walking in some zones. They could also change according to the traffic conditions: more congestion would produce higher transfer and fluid conditions lower.

The method allows also to design and to test targeted policies to improve the potential of transfer in those areas or corridors where results are poorer.


Association for European Transport