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The second part is about evaluation and development of algorithms to use for planning of demand responsive transport.The project will result in recommendations on how to coordinate different forms of public transport, and give estimations on the financial savings that new planning algorithms can give.Our project aims to develop and evaluate such a method based on optimization techniques in cooperation with our partners, with the purpose to increase the reliability and punctuality of the Swedish railway traffic.
In the second part, implementation of taxation shifts, we study the difficulties that arise related to the taxation shift that results from the charging scheme implementation.
Partners: Marie Karlsson and Jonas Sundberg, Sweco.
One challenge is therefore to design robust timetables which contain margins on strategic places known to the traffic managers and thus increasing the possibilities for the network to absorb certain disturbances.
The Swedish Transport Administration and SJ have also stated the need for methods which can compute robust timetables and create an improved feed-back loop between the timetabling phase and the real-time traffic management.
By developing existing models and methods for designing charging zones, the effects of these systems can be evaluated and compared with existing, traditional, types of congestion charge systems.
For example, the same type of social-economic dimensions of calculation previously used for the Stockholm system can be used on this type of system. Output from the method is proposed tolling zones, i.e., zone boundaries and the charge per kilometer within the zone.
It is a very positive trend but the growing demand for railway transportation has also resulted in a capacity insufficiency and a high sensitivity to traffic disturbances.
Even a small disturbance of one single train can have a significant impact on other trains since the capacity is fully utilized with very little buffer.
Participants: Clas Rydergren, Nils Breyer (TS), David Gundlegård (MT) and Di Yuan (MT) The project aims at estimation of travel demand in cities and metropolitan areas, via utilization of signaling data in cellular communications networks.
The key applications of using cellular network data range from dynamically managing road traffic to long-term infrastructure planning.