Assessing Long-Term Impacts of Automation on Freight Transport and Logistics Networks by a Large-Scale LRP Integrated in Microscopic Transport Simulation for Strategic Transport and Logistics Network Planning

Up to now, bulk transports have been carried out via a hub-and-spoke network in the general cargo sector. However, it is expected that the use of autonomous vehicles will enable a more flexible delivery. Such developments may, economically, make sense for shippers. From an ecological point of view, also negative effects can be expected due to enhanced transport performance. In the framework of this research, the authors investigate the impacts of automation on general cargo transport at the logistics network level. For assessing the impacts of autonomous vehicles on logistics network structures and on freight transport routes ex-ante, an instrument for strategic transport and logistics network planning is needed. The authors develop an effective heuristic to find new facilities and adjust the network, while thereby considering the routing characteristics by tackling the large-scale location routing problem i.e. LRP. By the linked approach, they can estimate the exact logistics network and coordinates and measure exact transport distances, driving transport lead times and number of necessary vehicles on the infrastructure network. The authors carry out a case study-based qualitative evaluation of the new optimized network and investigate the logistics effects for the food retail distribution in Germany. In fact, this research reveals that the utilization of autonomous vehicles significantly enhances transportation ranges and the number of tours, while reducing the number of operating facilities.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 17p

Subject/Index Terms

Filing Info

  • Accession Number: 01764077
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-02848
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:19AM