主講人：姜宇
丹麥技術大學（Technical Universityof Denmark）副教授
題 目:
(1) Integrated Public Transport Planning
(2) Incorporating Personalization and Bounded Rationality into Stochastic Transit Assignment Model
地 點：建設工程學部 土木綜合實驗四號樓526室
時 間：2021年12月29日（周三）上午，9：30 -11：30
主持人：鐘紹鵬
主辦單位：大連理工大學交通運輸學院
歡迎各位師生及有意向赴丹麥和歐洲留學的同學積極參加!
姜宇教授簡介：姜宇博士現為丹麥技術大學副教授，山東大學本科，新加坡國立大學碩士，香港大學博士，牛津大學、蘭卡斯特大學、香港大學博士后。姜宇博士目前專注于未來公交的，優化模型的開發與其算法方面的研究，主要研究興趣包括公交系統優化、交通網絡設計、多目標優化、元啟發式算法、機場運行規劃、基礎設施彈性及脆弱性。他用于研究交通問題的數學方法處在世界領先水平，已在交通領域國際頂級期刊發表SCI索引論文20 余篇。谷歌學者引用1091次，H-index為16，I10-index為18，單篇最高引用超過150次。
丹麥技術大學簡介：丹麥技術大學，又譯丹麥科技大學，是世界頂尖的理工大學之一，也是北歐地區最好的工科大學，在世界范圍內享有盛譽，同時也是世界上最古老的科技大學之一，是丹麥培養高級工程技術人員的最主要學府，是歐洲卓越理工大學聯盟、北歐五校聯盟成員之一，坐落于丹麥首都哥本哈根北部的孔恩斯靈比（Kongens Lyngby）。2017年美國US News世界大學排名中，其工學位列世界第18，歐洲第4，北歐第1；泰晤士高等教育排名，其工學位列世界第31，歐洲第9，北歐第1；在2015年世界大學學術排名（ARWU），其工學位列世界第38，大歐洲（含英國）第6，北歐第1。2022年US News世界大學排名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.
