Intelligent decision technologies can support travelling as well as planning transport systems. Trip makers have to choose between transport modes and then plan the optimal route which depends on many factors e.g. journey time, walking distances, transfers, waiting times, price of the journey as well as the individual preferences of the trip maker. This paper gives an overview of decisions in both individual and public transport. Then it shows some examples how intelligent cognitive info-communications can support these decisions and how they can be built into passenger information services.
BaranyiPCsapóÁ. Definition and synergies of cognitive infocommunications. Acta Polytechnica Hungarica2012; 9: 67-83.
2.
BaranyiPCsapóÁVárlakiP. An overview of research trends in CogInfoCom. INES 2014 IEEE 18th International Conference on Intelligent Engineering Systems 3–5 Jul 2014; Tihany, HU, 181-186.
3.
BaranyiPCsapóÁSallaiG. Cognitive Infocommunications (CogInfoCom). Springer International Publishing Switzerland, 2015.
4.
BorsosABirthSVollprachtHJ. The role of human factors in road design. 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) 19–21 Oct 2015; Győr, HU, 363-367.
5.
FöldesDCsiszárC. Route plan evaluation method for personalized passenger information service. Transport2015; 30 (Special Issue on Smart and Sustainable Transport): 273-285.
6.
DijkstraEW. Note on two problems in connection with graphs (spanning tree, shortest path). Numerical Mathematics1959; 1: 269-271.
7.
HensherDARoseJMGreeneWH. Applied Choice Analysis – A Primer. Cambridge: Cambridge University Press, 2005.
8.
HorváthB. Tömegközlekedési ráterhelési modellek értékelő elemzése és fejlesztése. PhD Thesis. Budapest: Budapesti Műszaki és Gazdaságtudományi Egyetem, 2005.
9.
HorváthB. Cognitive infocommunications in transport related decision making. 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) 19–21 Oct 2015; Győr, HU, 303-306.
10.
MenetRendes. Online public transport passenger information and journey planning service [Internet], 2016. Available from: http://menetrendes.hu/.
11.
MillerGA. The cognitive revolution: A historical perspective. Trends in Cognitive Sciences2003; 7: 141-144.
12.
NagyECsiszárC. Research on automation of operative scheduling in urban public transportation. Acta Technica Jaurinensis Series Transitus2013; 6: 94-109.
13.
SimonH. A vezetői döntés új tudománya. Budapest: Statisz- tikai Kiadó, 1982.
14.
WinklerÁ. Collecting public transport passenger preference data online. Pollack Periodica2010; 5: 119-126.
15.
WinklerÁ. Experiments to discover passenger preferences in public transport. 11th International Scientific Conference MOBILITA '11, 26–27 May 2011; Bratislava SK, 136-141.
16.
WinklerÁ. Utazói döntések modellezése a városi közforgalmú közlekedésben. PhD Thesis. Győr: Széchenyi István Egyetem, Infrastrukturális Rendszerek Modellezése és Fejlesztése Multidiszciplináris Műszaki Tudományi Doktori Iskola, 2013.
17.
WinklerÁ, Horváth B. Application of cognitive infocommunications in public transport journey planning. 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) 19–21 Oct 2015; Győr, HU, 95-98.
