Fast Hidden Markov Model Map-Matching for Sparse and Noisy Trajectories

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

This paper discusses a case study evaluating the potential impact of ITS traffic management on CO2 and Black carbon tailpipe emissions. Results are based on extensive microsimulations performed using a calibrated VISSIM model in combination with the AIRE model for calculating the tailpipe emissions from simulated vehicle trajectories. The ITS traffic management options hereby consist of easily implementable actions such as the usage of a variable message sign (VMS) or the setting of fixed time signal plans. Our simulations show that in the current case shifting 5% of vehicles from one route to another one leads to an improvement in terms of emissions only if the VMS is complemented with an adaptation of the signal programs, while the VMS sign or the change of the signal plans alone do not yield benefits. This shows that it is not sufficient to evaluate single actions in a ceteris paribus analysis, but their joint network effects need to be taken into account.
OriginalspracheEnglisch
TitelProceedings 18th IEEE International Conference on Intelligent Transportation Systems (ITSC)
Seitenumfang5
DOIs
PublikationsstatusVeröffentlicht - 2015
Veranstaltung18th IEEE International Conference on Intelligent Transportation Systems (ITSC 2015) -
Dauer: 15 Sept. 201518 Sept. 2015

Konferenz

Konferenz18th IEEE International Conference on Intelligent Transportation Systems (ITSC 2015)
Zeitraum15/09/1518/09/15

Research Field

  • Ehemaliges Research Field - Mobility Systems

Fingerprint

Untersuchen Sie die Forschungsthemen von „Fast Hidden Markov Model Map-Matching for Sparse and Noisy Trajectories“. Zusammen bilden sie einen einzigartigen Fingerprint.

Diese Publikation zitieren