City transport analysis using the General Motors (GM) microscopic model

Automobile, bus and trolleybus traffic flow in urban areas is increasing because of transport growth and continuous demand for it. The developing economy and changing social status of the population increases the need for mobility. Therefore, urban transport flow is increasing, resulting in traffic congestions, since the street network throughput in practice does not change. The negative effect caused by the traffic congestions is most notable in the largest cities, where traffic density is relatively high, with characteristically low and often variable speed (acceleration and deceleration). The authors present in this paper a modification of General Motors (GM) traffic flow simulation model in order to identify best possible prerequisites for traffic flow management. The forecasting model employs the following independent variables: vehicle movement speeds, service time (traffic light signal duration), traffic flow intensity, average service frequencies, and the lengths of formed queues. By specifying different functional forms of response time they propose a generalized methodology for traffic management and obtain a theory, which is demonstrated in this paper through both numerical simulation and theoretical analyses. The developed simulation model based on GM’s car following model shows good correlation to the field data. To this end, this paper presents a designed assessment method for the short-term congestion, expressing the negative impact of the transport system in monetary units.

• Record URL:
  https://doi.org/10.1007/s12469-014-0094-z
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/1866749X
• Supplemental Notes:
  • Copyright © 2015, Springer-Verlag Berlin Heidelberg.
• Authors:
  • Raslavičius, Laurencas
  • Keršys, Artūras
  • Pukalskas, Saugirdas
  • Bazaras, Jonas
  • Jablonskytė, Janina
  • Ilgakojytė-Bazarienė, Jurga
  • Makaras, Rolandas
• Publication Date: 2015-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 159-183
• Serial:
  • Public Transport
  • Volume: 7
  • Issue Number: 2
  • Publisher: Springer Publishing
  • ISSN: 1866-749X
  • EISSN: 1613-7159
  • Serial URL: http://link.springer.com/journal/12469

Subject/Index Terms

• TRT Terms: Microscopic traffic flow; Traffic congestion; Traffic forecasting; Traffic simulation; Urban transportation
• Identifier Terms: General Motors Corporation
• Subject Areas: Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01571060
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 14 2015 10:42AM