co-ump-logo

Cooperative Urban
Mobility Portal

Explore Connected and Cooperative Mobility

Reliable And Efficient Transport Operation

Cooperative

Urban Mobility Portal

Explore Connected and Cooperative Mobility

Reliable And Efficient Transport Operation

Reliable And Efficient Transport Operation

Business scenario

Traffic information services, such as road hazard warning, road works warning, or traffic jam warning, aim to inform the driver in a timely manner, allowing the driver to be better prepared for upcoming obstacles, to improve his or her decision making while driving, and to take necessary actions in advance. These services can either be offered through road-side units (RSUs) or combined with in-vehicle signage services. RSUs can collect data on road hazards, road works and traffic jams, as well on real-time behavior of traffic users. Consequently, through either in-vehicle signage or RSUs, this data can be integrated and communicated to traffic users, allowing them to improve their decision making.

Business model blueprint

The business model blueprint presented aims to support reliable and efficient public transportation for public transport operators through the operators’ bundle of C-ITS services. The bundle includes services, such as road hazards warning, road works warning, GLOSA, and slow or stationary traffic warning. Traffic data is integrated by the service provider and consequently communicated to the public transport operator as well as other traffic users. Other traffic users can use this traffic data to improve their decision making whilst driving. This may include slowing down to adequately cope with hazardous scenarios further up the road or taking a different route instead to avoid a hazardous scenario or traffic congestion. As other traffic users are more informed of upcoming traffic and may potentially change their behavior leading to decrease in congestion.

As public transportation vehicles (e.g., busses) are typically confined to standard routes and are not allowed to deviate from these routes, arrival and trip times for busses would become more predictable and reliable as well, considering real-time traffic data. As such, bus operators can offer more reliable trip and arrival times to their customers (commuters by transit).

To further improve the efficiency of transportation for bus operators, the service provider moreover can collect usage data for vehicles from commuters by transit. This data can be communicated to bus operators, showing when peak or high demand periods for busses may occur. Consequently, the operator can adapt the fleet to match these demand patterns, improving efficiency of the service.

The business model can be extended by including a social media partner, that can serve to extend the current information platform. In this variant, other road users can receive traffic data from social media channels, serving as an alternative to on-board units. The social media provider can potentially receive a fee for doing so, which is compensated by the decreased operating costs (as part of the information platform is now covered by social media) for the service provider. Moreover, given the adoption of the service, the social media provider can potentially benefit from an increased user base, as road users will use the channel to receive real-time traffic data.

Business model viability

Viability of the business model blueprint significantly depends on the reduction of road accidents and reduction of pollution generated through use of the service solution. In the current scenario, service use is financed by the road operator, requiring the benefits for the road operator to offset the costs of the service incurred. Depending on the penetration of the service for public transport operators as well as other road users, the effects on road safety can be considerable to do so. Considering the benefits for the public transport operator in terms of reduced fuel consumption, the public transport operator can be motivated to cover part of the service expenses.

This website has received funding from the European Union’s Horizon 2020 Research and Innovation Programme
under Grant Agreement number 723311.