Optimization of airport bus timetable in cultivation period considering passenger dynamic airport choice under conditions of uncertainty

An airport bus service, which is newly introduced in a multi-airport region, commonly leads to a gradually increasing market share of airports until a new state of equilibrium is reached. With the goal of speeding up and enlarging the increase in market share, this paper proposes a timetable optimization model by incorporating reactions of airport-loyal passengers to bus service quality. The simulation part of the model, which uses cumulative prospect theory to formulate discrete airport choices, results in predicted passenger demand needed in the optimization part. Then a genetic algorithm for multi-objective optimization problems called NSGA-II is applied to solve the model. To illustrate the model, the “Lukou airport-Wuxi” airport bus in China is taken as an example. The results show that the optimized timetables shorten the cultivation period and impel the market share to grow rapidly.     

Routing aspects of electric vehicle drivers and their effects on network performance

This study investigates the routing aspects of battery electric vehicle (BEV) drivers and their effects on the overall traffic network performance. BEVs have unique characteristics such as range limitation, long battery recharging time, and recuperation of energy lost during the deceleration phase if equipped with regenerative braking system (RBS). In addition, the energy consumption rate per unit distance traveled is lower at moderate speed than at higher speed. This raises two interesting questions: (i) whether these characteristics of BEVs will lead to different route selection compared to conventional internal combustion engine vehicles (ICEVs), and (ii) whether such route selection implications of BEVs will affect the network performance. With the increasing market penetration of BEVs, these questions are becoming more important. This study formulates a multi-class dynamic user equilibrium (MCDUE) model to determine the equilibrium flows for mixed traffic consisting of BEVs and ICEVs. A simulation-based solution procedure is proposed for the MCDUE model. In the MCDUE model, BEVs select routes to minimize the generalized cost which includes route travel time, energy related costs and range anxiety cost, and ICEVs to minimize route travel time. Results from numerical experiments illustrate that BEV drivers select routes with lower speed to conserve and recuperate battery energy while ICEV drivers select shortest travel time routes. They also illustrate that the differences in route choice behavior of BEV and ICEV drivers can synergistically lead to reduction in total travel time and the network performance towards system optimum under certain conditions.     

交通可达性对居住地选择的影响--以成都市为例

为了解新型城镇化战略下大城市中心区居民外迁至卫星城时的居住地选择行为特征及偏好，选取卫星城居住地周边学校、医院、商业设施、轨道交通车站及到中心区交通可达性作为主要变量。根据家庭成员组成特征将样本家庭划分为5类，对比分析不同家庭居住地选择行为特征及偏好。结合家庭社会经济属性形成了一套包含8种情景的正交设计组合问卷，对成都市中心区居民进行意愿调查，并建立Logit模型对居住地选择行为进行分析。结果表明，学校、医院等主要服务设施的交通可达性及家庭自身属性均对中心区居民外迁行为存在显著影响，同时定量分析各变量对居民选择外迁意愿的影响程度，最后提出有助于中心区人口疏解到卫星城的交通政策和措施建议。     

A day-to-day route flow evolution process towards the mixed equilibria

This study investigates a travelers’ day-to-day route flow evolution process under a predefined market penetration of advanced traveler information system (ATIS). It is assumed that some travelers equipped with ATIS will follow the deterministic user equilibrium route choice behavior due to the complete traffic information provided by ATIS, while the other travelers unequipped with ATIS will follow the stochastic user equilibrium route choice behavior. The interaction between these two groups of travelers will result in a mixed equilibrium state. We first propose a discrete day-to-day route flow adjustment process for this mixed equilibrium behavior by specifying the travelers’ route adjustment principle and adjustment ratio. The convergence of the proposed day-to-day flow dynamic model to the mixed equilibrium state is then rigorously demonstrated under certain assumptions upon route adjustment principle and adjustment ratio. In addition, without affecting the convergence of the proposed day-to-day flow dynamic model, the assumption concerning the adjustment ratio is further relaxed, thus making the proposed model more appealing in practice. Finally, numerical experiments are conducted to illustrate and evaluate the performance of the proposed day-to-day flow dynamic model.     

Spatial transferability assessment of a composite walkability index: The Pedestrian Index of the Environment (PIE)

This paper analyzes the transferability of a composite walkability index, the Pedestrian Index of the Environment (PIE), to the Greater Montréal Area (GMA). The PIE was developed in Portland, Oregon, and is based on proprietary data. It combines six urban form variables into a score ranging from 20 to 100. The measure introduces several methodological refinements which have not been applied concurrently in previous efforts: a wide coverage of the different dimensions of the urban form, together with the use of a distance-based decay function and modelling-based weighing of the variables.This measure is applied to the GMA using local data in order to evaluate the feasibility of its transfer (the possibility of locally replicating the measure). It is then included in a series of mode choice models to assess its transferability (the capacity of the measure to describe walkability and predict mode choice in another urban area). The models, segmented by trip distance or trip purpose, are estimated and validated against observed trip data from the 2013 Origin-Destination survey.Significant positive correlation is found between the PIE and the choice of walking for short trips, for all purposes as well as for four specific trip purposes. The inclusion of the PIE also improves the accuracy of the modelling process as well as the prediction of the choice of walking for short trips. The PIE can therefore be used in the GMA, and potentially in other metropolitan areas, to improve the modelling of travel behavior for short trips.     

Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data

This paper explores how we can use smart card data for bus passengers to reveal individual and aggregate travel behaviour. More specifically, we measure the extent to which both individual and bus routes exhibit habitual behaviour. To achieve this, we introduce a metric called Stickiness Index to quantify the range of preferences of users that always select to travel on the same route (high stickiness) to those with a more varied patterns of route selection (low stickiness). Adopting a visual analytic and modelling approach using a suite of regression models we find evidence to suggest that stickiness varies across the metropolitan area and over a 24-h period wherein higher stickiness is associated with high frequency users where there is substantial variability of route travel times across all alternatives. We argue that our findings are important in their capacity to contribute to a new evidence base with the potential to inform the (re)-design and scheduling of a public transit systems through unveiling the complexities of transit behaviour.     

Preferences for shared autonomous vehicles

Shared autonomous vehicles (SAVs) could provide inexpensive mobility on-demand services. In addition, the autonomous vehicle technology could facilitate the implementation of dynamic ride-sharing (DRS). The widespread adoption of SAVs could provide benefits to society, but also entail risks. For the design of effective policies aiming to realize the advantages of SAVs, a better understanding of how SAVs may be adopted is necessary. This article intends to advance future research about the travel behavior impacts of SAVs, by identifying the characteristics of users who are likely to adopt SAV services and by eliciting willingness to pay measures for service attributes. For this purpose, a stated choice survey was conducted and analyzed, using a mixed logit model. The results show that service attributes including travel cost, travel time and waiting time may be critical determinants of the use of SAVs and the acceptance of DRS. Differences in willingness to pay for service attributes indicate that SAVs with DRS and SAVs without DRS are perceived as two distinct mobility options. The results imply that the adoption of SAVs may differ across cohorts, whereby young individuals and individuals with multimodal travel patterns may be more likely to adopt SAVs. The methodological limitations of the study are also acknowledged. Despite a potential hypothetical bias, the results capture the directionality and relative importance of the attributes of interest.     

Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services

Despite some substantial limitations in the simulation of low-frequency scheduled services, frequency-based (FB) assignment models are by far the most widely used in practice. They are less expensive to build and less demanding from the computational viewpoint with respect to schedule-based (SB) models, as they require neither explicit simulation of the timetable (on the supply side), nor segmentation of OD matrices by desired departure/arrival time (on the demand side).The objective of this paper is to assess to what extent the lack of modeling capabilities of FB models is acceptable, and, on the other hand, the cases in which such approximations are substantial and more detailed SB models are needed. This is a first attempt to shed light on the trade-off between (frequency-based) model inaccuracy and (scheduled-based) model development costs in the field of long-distance (e.g. High-speed Rail, HSR) service modeling.To this aim, we considered two modeling specifications estimated using mixed Revealed Preferences (RP) and Stated Preferences (SP) surveys and validated with respect to the same case study. Starting from an observed (baseline) scenario, we artificially altered the demand distributions (uniform vs. time-varying demand) and the supply configuration (i.e. train departure times), and analyzed the differences in modal split estimates and flows on individual trains, using the two different model specifications.It resulted that when the demand distribution is uniform within the period of analysis, such differences are significant only when departure times of trains are strongly unevenly spaced in time. In such cases, the difference in modal shares, using FB w.r.t. SB, is in the range of [0%, +5%] meaning that FB models tend to overestimate HSR modal shares. When the demand distribution is not uniform, the difference in modal shares, using FB w.r.t. SB, is in the range of [−10%, +10%] meaning that FB models can overestimate or underestimate HSR modal shares, depending on timetable settings with respect to travelers’ desired departure times. The differences in on-board train flow estimates are more substantial in both cases of uniform and not uniform demand distribution.     

须家河组近水平软硬相间地层中斜坡破坏及处理对策

针对成自泸高速公路重点叙述了须家河组地层的地层特征,归纳了容易发生在须家河组近水平软硬相间地层中的斜坡破坏类型。在此基础上,分析破坏发生原因及其对工程的危害性和工程应对策略。通过工程实例具体说明在该类地质条件下进行地质选线和工程治理设计的原则。     

中小城市居民出行特征片区差异性分析——以浙江省长兴县为例

由于城市规模的差异,中小城市的出行需求与大城市存在较大区别,且由于区域发展进程的不同,中小城市内部也多呈现明显的片区差异。以浙江省长兴县中心城区居民出行调查数据为基础,在城区总体居民出行特征框架下,从出行次数、出行目的、出行距离、出行方式和出行时耗等方面分析各片区居民出行特征的差异,并以此挖掘片区的发展症结。最后以优化出行结构为目的,从用地规划、非机动交通环境营造、公共交通优化和小汽车管控等四个方面对中小城市的交通发展提出对策。