RISC Software GmbH offers its customers software solutions and applications which, tailored to their individual needs, contribute to comprehensive traffic information, the optimisation of freight and passenger traffic and the fulfilment of mobility requirements.
With its broad know-how and successful projects, RISC Software GmbH is thus driving a promising development in the sense of sustainability and efficiency in road transport and mobility management.
Real-time traffic situation information, simulation and forecasting: TOMS
The Traffic Online Monitoring System TOMS enables traffic on Upper Austrian roads to be recorded in order to generate area-wide, real-time traffic information and forecasts. The system is configured for monitoring traffic on Upper Austrian roads, but can also be extended or adapted for other regions.
A hybrid approach is being pursued in which various sensor systems and a supplementary traffic simulation are used. The resulting data will be integrated into TOMS, resulting in the following benefit aspects:
RISC Software GmbH develops tailor-made solutions for complex transport and route planning problems for its customers. Different definable optimization parameters such as CO2 efficiency, costs, time and route can be taken into account.
Transport statistics and analysis: TESS
The traffic statistics tool TESS (Traffic Evaluation and Sensor Statistics) was developed to check and analyse historical sensor data in Upper Austria. It is possible to extend or adapt the tool and its functions according to individual needs. The program includes the following functions:
Multimodality, Mobility as a Service and Shared Mobility
The joint use of means of transport not only allows synergy effects to be exploited, but also makes a significant contribution to sustainable environmental development. RISC Software GmbH has already successfully implemented numerous projects in the field of shared mobility and is a competent partner in the development of software solutions in this area.
The lead project DOMINO (hub for intermodal mobility services and technologies) focuses on integrated personal mobility with the aim of developing a universal and publicly available mobility offer. For this purpose, a large ride sharing pool of different mobility providers is used and integrated into the system.
Through the design of multimodal transport and the use of different modes of transport, it is possible to find measures for the optimisation of the modes of transport by means of machine learning methods. This allows, for example:
- derive optimal transport intervals and measures against congestion in the field of passenger transport.
- in the field of freight traffic, determine optimal transhipment hubs and control the timing of transports.