• Energy Research
• 2016-2025close

The diffusion of the smartphone and the urban sprawl is pushing both private and public actors to revisit the concept of demand-responsive transport (DRT). This paper provides a historical overview of DRT experiences, understanding their pros and cons. In addition, it presents the case study of Mokumflex, a 12-month DRT pilot program that replaced the regular bus service in low-density areas of Amsterdam, the Netherlands. Based on a close collaboration with the private enterprise that operated the service and also with the local bus operator, we performed an empirical before and after comparison. These insights help to understand the impacts of DRT systems and support (future) design of DRT and public transport. A set of indicators was chosen for the intermodal comparison: travel distances, ridership, costs, Greenhouse Gases (GHG), emissions and population's perception. Ridership dropped from 78.1 passengers/day to 15.9 passengers/day, however, for being “demand-tailored”, passenger-km reduced even more, going from 1252.8 km/day to 136.6 km/day, hence reducing the costs and GHG emissions per passenger. In regards to population's perception, the system enjoyed a good evaluation.

We present and validate the image analysis algorithm μ-scope to capture personal mobility devices’ (PMDs) movement characteristics and extract their movement dynamics even when they interact with each other and with pedestrians. Experimental data were used for validation of the proposed algorithm. Data were collected through a large-scale, semicontrolled, real-track experiment at the University of Patras campus. Participants (N = 112) included pedestrians, cyclists, and e-scooter drivers. The experiment was video recorded, and μ-scope was used for trajectory extraction. Some of the participants had installed, beforehand, the Phyphox application in their smartphones. Phyphox accurately measures x-y-z acceleration rates and was used, in our case, as the baseline measurement (i.e., “ground truth”). Statistical comparison between Phyphox and camera-based measurements shows very low difference in most cases. High pedestrian densities were the only case where relatively high root mean square errors were registered. The proposed algorithm can be thus considered capable of producing reliable speed and acceleration estimates. Low-quality conventional smartphone cameras were used in this experiment. As a result, the proposed method can be easily applied to all urban contexts under normal traffic conditions, but eventually not in the case of special or emergency events generating very high pedestrian densities.