Impacts of Vehicle Sharing with Driverless Cars on Urban Transport

  • Markus Friedrich
  • Maximilian HartlEmail author
  • Christoph Magg
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 889)


Autonomous vehicles (=AV) enabling driverless transport may change the ways of traveling and traffic volumes dramatically. To estimate potential impacts of AV on traffic in an urban area nine scenarios are examined, varying the rate of carsharing, ridesharing and the availability of rail services. The number of required vehicles, vehicle kilometers and the necessary number of parking spaces quantify each scenario.

The study builds on an existing travel demand model of the Stuttgart Region. An algorithm extends this model for bundling person trips in ridesharing systems and by an algorithm for vehicle blocking. The results show that the size of the car fleet can be reduced considerably. The vehicle kilometers traveled in the network, can only be reduced in cases where most travelers use ridesharing instead of carsharing or privately owned cars. However, an increase of the car kilometers traveled is more likely and may lead to a lower quality of traffic flow.


Autonomous vehicle Automated driving Self-driving car Carsharing Ridesharing Public transport 



The research project MEGAFON was financed by the Ministry for Transport of the Land Baden-Württemberg, the VDV (Association of German Transport Companies), the public transport operator SSB (Stuttgarter Straßenbahnen AG) and the transport association VVS (Verkehrs- und Tarifverbund Stuttgart). The Stuttgart Region (VRS) provided the database for the calculations.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Markus Friedrich
    • 1
  • Maximilian Hartl
    • 1
    Email author
  • Christoph Magg
    • 1
  1. 1.Institute for Road and Transport ScienceUniversity of StuttgartStuttgartGermany

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