Roads in the Netherlands are often heavily congested. Real-time travel time information can be a valuable instrument to reduce the impact of increasing traffic demand on travel time with advantages for traffic participants as well as for the traffic network managers. For urban roads travel time estimation is a more complex problem than for freeways. In order to provide online, real-time and accurate travel times, in this paper a new estimation approach is developed based on measurements supplied by the (vehicle-dependent) traffic controllers. These measurements include the occupancy from the corresponding long loop, the flow from the short loop, and the green percentages. Based on these measurements the location and length of the queues is estimated. Moreover, the approach transforms the data in a way that the underlying reason(s) of congestion becomes apparent (in terms of bottleneck location), which can be very useful for, e.g., advanced traffic information systems or decision support systems. Compared with the approach based on license plate recognition cameras, which is used in the Netherlands in many locations, this approach is expected to be more accurate in heavily congested situations, since for license plate recognition vehicles have to pass the end of the route before the traveled time can be measured. The approach is tested with real traffic data for an urban route in the Netherlands. The test case presented in the paper shows that the use of the additional data from traffic controllers (occupancy, green percentage, waiting time of first vehicle in queue) is beneficial.