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【学术报告】丹麦技术大学姜宇副教授——Integrated Public Transport Planning & Incorporating Personalization and Bounded Rationality into Stochastic Transit Assignment Model

2021-12-22  来源:mg娱乐登录地址 点击:[]

主讲人:姜宇

丹麦技术大学(Technical Universityof Denmark)副教授

目:

(1) Integrated Public Transport Planning

(2) Incorporating Personalization and Bounded Rationality into Stochastic Transit Assignment Model
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姜宇教授简介:姜宇博士现为丹麦技术大学副教授,山东大学本科,新加坡国立大学硕士,香港大学博士,牛津大学、兰卡斯特大学、香港大学博士后。姜宇博士目前专注于未来公交的,优化模型的开发与其算法方面的研究,主要研究兴趣包括公交系统优化、交通网络设计、多目标优化、元启发式算法、机场运行规划、基础设施弹性及脆弱性。他用于研究交通问题的数学方法处在世界领先水平,已在交通领域国际顶级期刊发表SCI索引论文20 余篇。谷歌学者引用1091次,H-index为16,I10-index为18,单篇最高引用超过150次。


丹麦技术大学简介:丹麦技术大学,又译丹麦科技大学,是世界顶尖的理工大学之一,也是北欧地区最好的工科大学,在世界范围内享有盛誉,同时也是世界上最古老的科技大学之一,是丹麦培养高级工程技术人员的最主要学府,是欧洲卓越理工大学联盟北欧五校联盟成员之一,坐落于丹麦首都哥本哈根北部的孔恩斯灵比(Kongens Lyngby)。2017年美国US News世界大学排名中,其工学位列世界第18,欧洲第4,北欧第1;泰晤士高等教育排名,其工学位列世界第31,欧洲第9,北欧第1;在2015年世界大学学术排名ARWU),其工学位列世界第38,大欧洲(含英国)第6,北欧第1。2022年US News世界大学排名99名。


Integrated Public Transport Planning

An integrated optimisation model for transit networks with joint frequency- and schedule-based services is established. The frequencies and schedules are simultaneously determined to minimise the operation costs and total passenger-perceived generalised travel cost. The passengers’ route choice behaviour is described by the bounded stochastic user equilibrium (BSUE). The in-vehicle congestion effect is represented using a set of constraints that differ in terms of the seating and standing costs as sitting and standing passengers perceive crowding differently. This set of constraints captures the realistic behavioural feature that having occupied a seat, the user remains seated at subsequent stops in the same vehicle. The problem is formulated as a mixed integer nonlinear programming problem, which is subsequently linearised to a mixed integer linear programming problem and solved using a branch-and-bound algorithm. A column generation-and-reduction phase is embedded in the solution algorithm to obtain the bounded choice set according to the BSUE constraints. Experiments are conducted to illustrate the model properties and evaluate the performance of the solution method. In particular, we demonstrate a Braess-like paradoxical phenomenon in the context of transit scheduling and highlight that well-synchronised transit services can deteriorate the network performance in terms of the total passengers’ generalised travel cost.

Incorporating Personalization and Bounded Rationality into Stochastic Transit Assignment Model
The use of smartphone applications (apps) to acquire real-time information for trip planning has become and progressively continues becoming a more instinctive behavior among public transport (PT) users. Thus, it becomes an integral part of the design and management of PT systems, but corresponding transit assignment models for improving the prediction of passenger ridership have yet to be developed. This work proposes a novel stochastic transit assignment model that predicts passenger ridership. Two new features are incorporated into a transit assignment model, namely, personalization and bounded rationality. Personalization refers to a personalized route-ranking methodology so that the app recommends paths with respect to a traveler’s preference considering various PT attributes. Bounded rationality is modeled over three route-choice strategies representing different levels of cognitive effort exercised by a traveler in selecting a path from the set of paths recommended by the app. The transit assignment model is formulated as a fixed-point problem. Because the mapping function of the fixed-point formulation is not necessarily continuous, the model constructs an approximated fixed point existing under certain measures of discontinuity. The method of successive averages is applied to solve the problem. Numerical studies are conducted to demonstrate the properties of the new transit assignment model, the effect of demand on the path choice probability, and the effect of passengers’ heterogeneity on the convergence of the algorithm. The results reveal that, with a personalized path recommendation, passenger’s preferences could stabilize the differences of path choice probability when adopting route-choice strategies relying on the path order. In addition, although the MSA may not always converge and oscillate, the fluctuation is below the derived measure of discontinuity, indicating that an approximated fixed point can be found.


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