Mode Choice Analysis: The Data, the Models and Future Ahead

Mode choice is one of the most vital stages in transportation planning process and it has direct impact on the policy making decisions. Mode choice models deals very closely with the human choice making behaviour and thus continues to attract researchers for further exploration of commuter’s choice making process. The objective of this study is to carryout detailed review on various modeling methods of mode choice analysis and bottlenecks associated with the same. The factors that affect the psyche of the travelers have been discussed; further various types of data required and their method of collection has been briefed up. This paper particularly emphasizes on statistical mode choice models such as multinomial logit and probit models as well as recent advanced soft computing techniques such as Artificial Neural Network models (ANN) and Fuzzy approach model that are employed for modal split analysis. Comparative analysis were made among various modeling techniques for modeling the complex mode choice of behaviour of models carried out by various researchers in the literature and a discussion on the need of future hybrid soft computing models has been attempted.

• Record URL:
  https://doi.org/10.7708/ijtte.2014.4(3).03
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/2217544X
• Authors:
  • Minal
  • Ravi Sekhar, Ch
• Publication Date: 2014

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 269-285
• Serial:
  • International Journal for Traffic and Transport Engineering
  • Volume: 4
  • Issue Number: 3
  • Publisher: City Net Scientific Research Center Ltd.
  • ISSN: 2217-544X
  • EISSN: 2217-5652
  • Serial URL: http://www.ijtte.com/home/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Choice models; Data collection; Logits; Mode choice; Planning methods; Probits; Soft computing; Travel behavior
• Subject Areas: Data and Information Technology; Passenger Transportation; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01540048
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 9 2014 9:01AM