مطالعه تطبیقی مدل‌های تخصیص ترافیک تصادفی لوجیت- مبنا

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشکده مهندسی عمران و محیط زیست، دانشگاه تربیت مدرس، تهران، ایران

2 دانشیار، دانشکده مهندسی عمران و محیط زیست، دانشگاه تربیت مدرس، تهران، ایران

3 دانشیار، دانشکده مهندسی عمران، پردیس دانشکده‌های فنی، دانشگاه تهران، تهران، ایران

10.22034/tri.2021.278334.2886

چکیده

پس از کاربرد مدل لوجیت به عنوان مدل انتخاب مسیر در الگوریتم‌های اولیۀ تخصیص ترافیک تصادفی، مدل‌های دیگری برای غلبه بر ضعف نظری آن در به حساب آوردن همپوشانی مسیرها توسعه یافته‌اند. این مدل‌ها فرم بسته و راحتی محاسباتی لوجیت را حفظ می‌کنند، در حالی که نیازی به شبیه‌سازی و تلاش‌های محاسباتی پروبیت ندارند. هدف از این مقاله، ارزیابی مهمترین این مدل‌ها در مقایسه با یکدیگر است. مدل‌های مورد بررسی عبارتند از: مدل لوجیت چندگانه (MNL)، دو مدل MNL اصلاح‌شده با نام‌های C-logit و PS-logit، و دو مدل از خانوده مقدارحدی تعمیم‌یافته با نام‌های لوجیت آشیانه‌ای متقاطع (CNL) و لوجیت ترکیبی دوتایی (PCL). این مقایسه‌ها در سطوح مختلف ازدحام شبکه (تقاضای مبدأ- مقصد) و مقادیر متفاوت پراکنش درک کاربران شبکه (پارامتر مقیاس) انجام شده و نیز با نتایج تخصیص ترافیک قطعی مقایسه شد. نتایج برای یک شبکه نُه‌گره‌ای و شبکه نیوین نشان می‌دهد که با افزایش سطح ازدحام، الگوهای کلی جریان‌های کمانی تخصیص‌های تصادفی به جریان‌های کمانی تخصیص قطعی نزدیک می‌شوند؛ در حالی که اختلاف این جریان‌های کمانی در چهار مدلی که تأثیر همپوشانی مسیرها را در نظر می‌گیرند، نسبت به مدل MNL افزایش می‌یابد. هم‌چنین، با افزایش پراکنش درک کاربران، اختلاف جریان‌های کمانی در تخصیص‌های تصادفی نسبت به مدل MNL و هم نسبت به تخصیص قطعی زیاد می‌شوند. به علاوه، نتایج مدل‌های مورد بررسی برای شبکه سوفالز نشان می‌دهند که جریان‌های مسیری در تخصیص‌های تصادفی نسبت به تخصیص قطعی دارای انتروپی به مراتب بیشتری هستند، و بنابراین مدل‌های تصادفی از این نظر جواب‌های محتمل‌تری تولید می‌کنند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Comparative Analysis of Logit-Based Stochastic Traffic Assignment Models

نویسندگان [English]

  • Hadi Gholi 1
  • Amir Reza Mamdoohi 2
  • Abbas Babazadeh 3
1 Ph.D., Candidate, Transportation Planning Dept., Civil & Envi., Engineering Faculty, Tarbiat Modares University, Tehran, Iran.
2 Associate Professor, Transportation Planning Dept., Civil & Envi. Engineering Faculty, Tarbiat Modares University, Tehran, Iran.
3 Associate Professor, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
چکیده [English]

After applying the logit model as a route choice model in early stochastic traffic assignment algorithms, other models have been developed to overcome its theoretical weakness in considering path overlap. These models maintain the closed-form and computational convenience of logit, while not requiring simulation and computational efforts of probit. The purpose of this paper is to evaluate the most important of these models in comparison with each other. The models under consideration are Multinomial-logit (MNL) model, two modified MNL models called C-logit and PS-logit, and two models from the generalized extreme value family called cross-nested logit (CNL) and Paired-Combinatorial logit (PCL). These comparisons were performed at different levels of network congestion (origin-destination demand) and different values of perception variance of network users (scaling parameter) and were also compared with results of deterministic traffic assignment. Results of a nine-node and the Nguyen network show that as the congestion level increases, general patterns of link flows of stochastic assignments approach the deterministic assignment link flows; While the difference of these link flows in four models that consider the effect of path overlap increases compared to MNL model. Also, as the variance of user perceptions increases, the difference of link flows of stochastic assignments relative to the MNL model and relative to the deterministic assignment increases. Besides, results of the studied models for the Sioux-falls network show that path flows in stochastic assignments have much more entropy than the deterministic assignment, and therefore stochastic models produce more probable answers in this regard.

کلیدواژه‌ها [English]

  • Generalized extreme value (GEV)
  • logit model
  • path overlap
  • route choice model
  • stochastic traffic assignment

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