Environmental Impact of Bundling Transport Deliveries Using SUMO Analysis of a cooperative approach in Austria

  • Aso Validi (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

Abstract: Urban Traffic is recognized as one of the major CO 2 contributors that puts a high burden on the environment. Different attempts have been made for reducing the impacts ranging from traffic management actions to shared-vehicle concepts to simply reducing the number of vehicles on the streets. By relying on cooperative approaches between different logistics companies, such as sharing and pooling resources for bundling deliveries in the same zone, an increased environmental benefit can be attained. To quantify this benefit we compare the CO 2 emissions, fuel consumption and total delivery time resulting from deliveries performed by one cargo truck with two trailers versus by two single-trailer cargo trucks under real conditions in a simulation scenario in the city of Linz in Austria. Results showed a fuel consumption and CO2 emissions reduction of28% and 34% respectively in the scenario in which resources were bundled in one single truck.
Period24 Jun 2020
Event titleCISTI'2020 - 15th Iberian Conference on Information Systems and Technologies
Event typeConference
LocationAustriaShow on map

Fields of science

  • 202003 Automation
  • 303 Health Sciences
  • 501 Psychology
  • 102029 Practical computer science
  • 203 Mechanical Engineering
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 102 Computer Sciences
  • 202041 Computer engineering
  • 202040 Transmission technology
  • 501030 Cognitive science
  • 211911 Sustainable technologies
  • 203004 Automotive technology
  • 201306 Traffic telematics
  • 211917 Technology assessment
  • 102013 Human-computer interaction
  • 102034 Cyber-physical systems
  • 201305 Traffic engineering
  • 102015 Information systems
  • 501026 Psychology of perception
  • 501025 Traffic psychology
  • 202038 Telecommunications
  • 102019 Machine learning
  • 303008 Ergonomics
  • 202037 Signal processing
  • 202036 Sensor systems
  • 202035 Robotics
  • 202034 Control engineering
  • 202031 Network engineering
  • 202030 Communication engineering
  • 211902 Assistive technologies
  • 102021 Pervasive computing
  • 102002 Augmented reality
  • 102024 Usability research
  • 102001 Artificial intelligence
  • 211908 Energy research
  • 102026 Virtual reality
  • 211909 Energy technology
  • 102003 Image processing

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management