Probit-Based Traffic Assignment: A Comparative Study between Link-Based Simulation Algorithm and Path-Based Assignment and Generalization to Random- Coefficient Approach

  • سال انتشار: 1393
  • محل انتشار: نشریه بین المللی مهندسی حمل و نقل، دوره: 2، شماره: 3
  • کد COI اختصاصی: JR_IJTE-2-3_002
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 702
دانلود فایل این مقاله

نویسندگان

Milad Haghani

Ph.D. Candidate, Department of Civil Engineering, Institute of Transport Studies, Monash University, Melbourne, Australia

Zahra Shahhoseini

Ph.D. Candidate, Department of Civil Engineering, Institute of Transport Studies, Monash University, Melbourne, Australia

Majid Sarvi

Associate Professor, Department of Civil Engineering, Institute of Transport Studies, Monash University, Melbourne, Australia

چکیده

The problem of path overlapping in network modelling has been one of the main issues to be tackled. Due to its flexible covariance structure, probit model can adequately address the problem. Despite that probit is one of the most appealing choice models, due to the lack of closed form expressions for evaluating choice probabilities; it has not received extensive attention by network modeling researchers. This study is set out to focus on this approach of traffic assignment.Computational difficulty of application of probit model in the large-scale network equilibrium problem has triggered development of some link-based probit network loading methods which exemptthe analyst from generating and maintaining path-flow variables explicitly. The bias of theseheuristic link-based methods has not been studied so far. This contribution primarily focuses on investigation of such potential bias in link-based probit assignment methods. In this research, thisbias for a certain simulated link-based method is empirically considered and investigated throughcomparison with path-based probit equilibrium solution. Capable of representing utility correlation and heteroscedasticity, probit model has always beenone of the most theoretically attractive models for representing route choice behavior. However, this soundness of theory could further be enhanced through combining the ideas of probit and random-coefficient modeling which enables the analyst to capture random taste heterogeneity over travelers as well.

کلیدواژه ها

Probit Model, multivariate normal distribution, Monte Carlo Simulation, randomcoefficient choice models, link-based and path-based traffic assignment

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.