How to ensure the su
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The basic premise of Demand-Responsive Transport (DRT): smart vehicle routes that group as many passengers as possible, matching trips to capacity is seen as a promising solution to establish emission-free transport. It’s both efficient and reduces the need for individual cars.
However, DRT services are by no means the same. The deployment of an on-demand service does not follow a template that can be applied equally to all regions and areas. The key to successfully establishing a DRT in a given area is based on the analysis and correct interpretation of data collected before the service is introduced and whilst it is operational. Good data will show how the service is being used, and whether there is room for improvement. For example, data can show whether the fleet size is optimal for the service and how it works with the existing transport network (for example, whether the on-demand service ensures connections with train services, or competes with high-frequency buses at peak times).
The Smart Transport Conference took place in London at the end of November. Bringing together, mobility experts, innovative transport companies and top politicians, including Parliamentary Under-Secretary of State for Transport, Trudy Harrison, the conference addressed the most pressing mobility issues of our time: how do we achieve the climate targets we have set ourselves, how can innovative transport concepts be promoted, or how should the infrastructure change in order to encourage the use of lower-emission means of transport?
The entire UK team of Padam Mobility was represented at the event in London. David Carnero, Head of International Business Development, spoke in the breakout session “Technology and Innovation” about the important role of data in the development of on-demand services.
Using specific examples, each showing anonymised real data scenarios from customers, David highlighted the importance of the skilled eye of Padam Mobility’s mobility experts in launching and sustaining DRT services.
The choice of the fleet size is crucial to the success or failure of an on-demand service. If the fleet is too large, it is costly to maintain, vehicles are not optimally utilised, and additional staff are required. However, if there are not enough vehicles to meet the demand, other problems tend to arise that damage the overall project. Users trying to book a journey who are repeatedly unable to do so because all vehicles are already fully booked may turn away from the service. This problem is illustrated by David in his presentation (see Figure 1). The chart shows the daily average refusal rate (blue bars) and the total refusal rate (orange line) are very high at almost all times of the day. In this situation more vehicles are needed to meet demand, and this will be suggested to the operator.
A further example shared by David illustrated how skilled interpretation of data can have an impact on services. Before the realignment of the DRT offer shown in Figure 2, rather low user numbers were recorded. This could be for many reasons, however, it would be wrong to jump to the conclusion that people in the region are not open to on-demand mobility.
The service was adjusted, and from around August 2020, the data shows passenger numbers increasing rapidly. This suggests that the service change made about two months earlier succeeded and meets the users’ actual needs much better. In this case, several stops were added and the service area was enlarged.
David used further examples to make clear how extensive the analyses are that Padam Mobility conducts for their customers, and that careful data evaluation can be decisive for success.
For example, he illustrated the possible reasons why trip searches might not lead to bookings. Figure 3 shows the point at which (around November 2020), the conversion rate of searches to bookings increases significantly compared to the previous period. User analysis indicated that people may have been unable to find suitable stops in their proximity or were not satisfied with the given service area. In this case, a service enhancement resulting from the analysis has helped to accommodate more user queries and thus increase the ratio of search queries to actual bookings.
Expansion of the service area, a larger fleet size or more stops are not the only possible adjustments. Service configurations which are matched to the individual circumstances and needs of each region are essential. Padam Mobility tests and measures the most appropriate models. For some areas, a free-floating model, which does not envisage a fixed routing, may make sense, for example, in order to save vehicle kilometres and offer passengers a flexible and individualised driving experience. In other regions, however, a feeder configuration may be more appropriate, for example, if a specific transport hub, such as a train station, is the main point of contact for most on-demand users. In very large areas, it may be beneficial to define zones in which a specific on-demand service operates. This helps the operators to keep a clear overview of the performance and the resources needed for each service.
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Padam Mobility
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