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008			220103s2022 sz | s |||| 0|eng d
020			_a9783030933708
024	7		_a10.1007/978-3-030-93370-8 _2doi
040			_aTR-AnTOB _beng _erda _cTR-AnTOB
041			_aeng
050		4	_aHE336.T7
072		7	_aTNH _2bicssc
072		7	_aTEC009020 _2bisacsh
072		7	_aTNH _2thema
090			_aHE336.T7EBK
245	1	0	_aPresent Approach to Traffic Flow Theory and Research in Civil and Transportation Engineering _h[electronic resource] / _cedited by Elżbieta Macioszek, Grzegorz Sierpiński.
250			_a1st ed. 2022.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Intelligent Transportation and Infrastructure, _x2523-3459
520			_aThis book presents many valuable tips for making decisions related to traffic flow in the transport networks. The knowledge base in practical examples, as well as the decision support systems described in this book, finds interest among people who face the daily challenge of searching for solutions to the problems of contemporary transport networks and systems. The publication is therefore addressed to local authorities related to the planning and development of development strategies for selected areas with regard to transport (both in the urban and regional dimension) and to representatives of business and industry, as people directly involved in the implementation of traffic engineering solutions. The tips contained in individual sections of the publication allow to look at a given problem in an advanced way and facilitate the selection of the appropriate strategy (among others, in relation to the evaluation of BEV and FCHEV electric vehicles in the creation of a sustainable transport systems, development of ecological public transport on the example of selected cities, impact of drivers' waiting time on the gap acceptance at median, uncontrolled T-intersections). In turn, due to a new approach to theoretical models (including, inter alia, the application of genetic algorithms for the planning of urban rail transportation system, comprehensive estimate of life cycle costs of new technical systems using reliability verification algorithm, application and comparison of machine learning algorithms in traffic signals prediction), the publication also interests scientists and researchers carrying out research in this area.
650		0	_aTransportation engineering.
650		0	_aTraffic engineering.
650		0	_aComputational intelligence.
650	1	4	_aTransportation Technology and Traffic Engineering.
650	2	4	_aComputational Intelligence.
653		0	_aTraffic flow -- Congresses
700	1		_aMacioszek, Elżbieta. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aSierpiński, Grzegorz. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
830		0	_aLecture Notes in Intelligent Transportation and Infrastructure, _x2523-3459
856	4	0	_uhttps://doi.org/10.1007/978-3-030-93370-8 _3Springer eBooks _zOnline access link to the resource
942			_2lcc _cEBK