Transportmetrica最新文献_第4页

Distributive impacts of demand-based modelling 基于需求的模型的分配影响

Transportmetrica Pub Date : 2011-05-01 DOI: 10.1080/18128600903322333

K. Martens, E. Hurvitz

{"title":"Distributive impacts of demand-based modelling","authors":"K. Martens, E. Hurvitz","doi":"10.1080/18128600903322333","DOIUrl":"https://doi.org/10.1080/18128600903322333","url":null,"abstract":"Transport demand models play a crucial role in the distribution of transport facilities, and hence accessibility, over population groups. The goal of this article is to assess the distributive impacts of the widely-used four-step, demand-based, transport model. This article starts from the hypothesis that the consecutive application of the four-step model over a number of years, and successive investments in transport infrastructure consistent with the model results, will widen existing gaps between high-mobile and low-mobile groups, in terms of transport facilities and accessibility available to each group. A simplified four-step model is then developed to test the hypothesis under different policy scenarios. The results are mixed. In each scenario, gaps between high-mobile and low-mobile groups are increasing and decreasing at the same time. Against expectations, the distributive implications of demand-based modelling seem to depend on the situation and the focus of analysis. Given the unpredictable distributive impacts, it is suggested that explicit justice indicators be incorporated in transport modelling if it is to contribute to a more just distribution of transport facilities and accessibility over population groups.","PeriodicalId":49416,"journal":{"name":"Transportmetrica","volume":"7 1","pages":"181 - 200"},"PeriodicalIF":0.0,"publicationDate":"2011-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/18128600903322333","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59925202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Using principal curves to analyse traffic patterns on freeways 利用主曲线分析高速公路交通模式

Transportmetrica Pub Date : 2011-05-01 DOI: 10.1080/18128600903500110

J. Einbeck, J. Dwyer

引用次数: 17

Assessing planning decisions by activity type during the scheduling process 在调度过程中按活动类型评估计划决策

Transportmetrica Pub Date : 2011-03-22 DOI: 10.1080/18128602.2010.520276

Tomás Ruiz, M. Roorda

引用次数: 15

Developing a generic metric of terminal airspace traffic complexity 开发终端空域交通复杂性的通用度量

Transportmetrica Pub Date : 2011-03-21 DOI: 10.1080/18128602.2010.505590

Fedja Netjasov, M. Janić, V. Tosic

{"title":"Developing a generic metric of terminal airspace traffic complexity","authors":"Fedja Netjasov, M. Janić, V. Tosic","doi":"10.1080/18128602.2010.505590","DOIUrl":"https://doi.org/10.1080/18128602.2010.505590","url":null,"abstract":"This article develops a generic metric for measuring the complexity of a given terminal airspace (TMA). The metric includes static and dynamic complexity, both consisting of the complexity component for arriving and departing traffic. The main objective of the developed metric is as follows: evaluation of particular alternative solutions for airspace organisation and design and related air traffic complexity under the given circumstances, which could be used for planning purposes at the strategic and the tactical level. For this reason, the proposed metric reflects the expected complexity over a certain time period, rather than the current value of complexity. The main factors influencing complexity of a given TMA are: configuration of TMA, which implies among other factors, the number and length of arrival/departure trajectories, the airport(s) runway system capacity, air traffic volume, aircraft fleet mix, spatial distribution of traffic and the air traffic control separation rules. Unlike most other approaches, the one presented in this article disregards the air traffic controller workload issue from explicit consideration, but indicates the level of complexity which could influence the workload that he or she could be faced with under the specified circumstances. The output consists of complexity values dependent of the configuration, i.e. three-dimensional geometry of the given TMA and approach/departure trajectories in it, air traffic volume, aircraft fleet mix and the spatial distribution of traffic. The developed complexity metric has been applied to TMA traffic around London Heathrow Airport, UK.","PeriodicalId":49416,"journal":{"name":"Transportmetrica","volume":"7 1","pages":"369 - 394"},"PeriodicalIF":0.0,"publicationDate":"2011-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/18128602.2010.505590","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59925411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

A two-level multiple discrete-continuous model of time allocation to virtual and physical activities 虚拟和物理活动时间分配的两级多重离散连续模型

Transportmetrica Pub Date : 2011-03-21 DOI: 10.1080/18128602.2010.520138

Donggen Wang, Jiukun Li

引用次数: 27

Cellular automaton model with time gap dependent randomisation under Kerner's three-phase traffic theory Kerner三相交通理论下具有时间间隔依赖随机化的元胞自动机模型

Transportmetrica Pub Date : 2011-03-01 DOI: 10.1080/18128600903312789

B. Jia, Xingang Li, Tao Chen, R. Jiang, Ziyou Gao

引用次数: 43

A shock-fitting algorithm for the Lighthill–Whitham–Richards model on inhomogeneous highways 非均匀高速公路上lighhill - whitham - richards模型的激波拟合算法

Transportmetrica Pub Date : 2011-03-01 DOI: 10.1080/18128600903313936

Wen-jun Sun, S. Wong, Peng Zhang, Chi-Wang Shu

引用次数: 5

Passenger car units and saturation flow models for highly heterogeneous traffic at urban signalised intersections 城市信号交叉口高度异构交通的乘用车单元和饱和流模型

Transportmetrica Pub Date : 2011-03-01 DOI: 10.1080/18128600903351001

Padmakumar Radhakrishnan, Tom V. Mathew

{"title":"Passenger car units and saturation flow models for highly heterogeneous traffic at urban signalised intersections","authors":"Padmakumar Radhakrishnan, Tom V. Mathew","doi":"10.1080/18128600903351001","DOIUrl":"https://doi.org/10.1080/18128600903351001","url":null,"abstract":"Signalisation is a traffic control strategy to ease the competition by providing right-of-way in a cyclic manner to conflicting traffic at intersections. Saturation flow is a major component in the design of signals, and is influenced by a variety of factors like vehicle composition, intersection geometry and driver's behaviour. The highway capacity manual (HCM) has recommended a saturation flow model primarily for homogeneous conditions, with limited ability to address heterogeneity. But the traffic in many parts of the world is highly heterogeneous and hence, defining a unified saturation flow concept is a challenging task. The variability in vehicle types necessitates the use of passenger car units (PCUs). This article proposes a methodology to develop a saturation flow model based on dynamic PCUs by a microscopic analysis. Field data from intersections of three Indian cities – Jaipur, Bangalore and Trivandrum – is used for the study. PCU values are derived from the field data, by minimising the difference between the observed and the ideal flow profiles. A new saturation flow model is then developed using the regression method. The model is validated with the saturation flows collected from different locations. In addition, the flow predicted by the saturation flow model is used to estimate delay using the HCM and Webster's models, and these delays are compared to the observed delays. The proposed model resulted in lower error compared to the conventional flow estimation techniques.","PeriodicalId":49416,"journal":{"name":"Transportmetrica","volume":"7 1","pages":"141 - 162"},"PeriodicalIF":0.0,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/18128600903351001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59925246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 55

Multiclass first-order traffic model using stochastic fundamental diagrams 基于随机基本图的多类一阶交通模型

Transportmetrica Pub Date : 2011-03-01 DOI: 10.1080/18128600903251334

D. Ngoduy

引用次数: 116

Variable message sign operating strategies: simple examples 可变消息符号操作策略:简单示例

Transportmetrica Pub Date : 2011-02-12 DOI: 10.1080/18128602.2010.498004

Seungjae Lee, Sungwhee Shin

引用次数: 5