The Bid-rent Land Use Model of the simple,efficient, elegant,and effective model of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. The financial, time, and staff requirements to develop these models has put them beyond the reach of most small to medium sized urban areas. This paper presents the land use allocation submodel of the Simple, Efficient, Elegant, and Effective model of land use and transportation (SE³M), an integrated land use and transportation forecasting model founded upon Economic Base Theory and Bid-rent Theory. The Bid-rent Land Use Model (BLUM) is an agent based, spatial competition model utilizing unique utility curves for willingness to pay and incomes for budget constrained abilities to pay for each agent. The model structure, estimation, calibration, implementation, and validation are presented. With a single year of land use data available, the validation approach used the Kappa Index of Agreement to spatially check model outputs against base year control data while controlling for agreement by chance. The U.S. territory of Guam is used as the case study/proof of concept implementation for this model framework. Once calibrated, BLUM could solve the spatial competition problem on Guam in less than two minutes of processing time with over 90% accuracy.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem

This paper proposes simple and direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem. It is only necessary to account for random variables independent of link flows by performing a simple transformation of the perceived link travel time with a normal distribution. At every iteration of a Monte-Carlo simulation procedure, the values of the random variables are sampled based on their probability distributions, and then a regular deterministic user equilibrium assignment is carried out to produce link flows. The link flows produced at each iteration of the Monte-Carlo simulation are averaged to yield the final flow pattern. Two test networks demonstrate that the proposed algorithms and the traditional algorithm (the Method of Successive Averages) produce similar results and that the proposed algorithms can be extended to the computation of the case in which the random error term depends on measured travel time.     

Impact of regional population density on walking behavior

Land use can influence walking (measured by the number of steps) and so the health of people. This paper presents the result of empirical research on the impact of regional population densities (inhabitants per inhabitable area) on the number of steps (all steps, both outdoors and indoors). With data collected from almost 11,000 respondents in 148 Japanese regions, we estimate polynomial regression models, the total number of steps being the dependent variable and densities being the main independent variable. Regional population density significantly affects the number of steps after controlling for individual and household attributes. The estimated population density that maximizes the number of steps is around 11,000?persons/km². Increasing densities, up to levels of around 11,000?inhabitants/km², could increase walking and consequently the health of inhabitants. The population density elasticity of the number of steps is 0.046–0.049 in a simple log linear regression model without a peak.     

北京地铁深基坑支护结构设计优化与施工

北京地铁9号线军事博物馆站北换乘厅南侧紧邻复兴路和既有1号线,附近管线众多,周边环境复杂,对地层扰动影响较高,地层中下部以黏土岩、砾岩为主,整体稳定性较好,原设计方案采取咬合桩止水及基坑底部换撑等加强措施。在保证施工安全的前提下,为了合理缩短工期、减少造价,结合实际工程经验对原设计方案进行了优化。和原设计方案相比,优化设计方案取消了咬合桩及换撑,对第4道支撑位置进行了调整,并更换了防水材料。同时,采用北京理正深基坑分析软件对优化设计前后的基坑开挖情况进行了对比分析。最后,在按优化设计方案施工的过程中进行严密的监控量测,并对监测数据进行了分析。最终给出以下建议:1)深基坑支护尽量不采取换撑的方式;2)设计方案要结合实际情况进行动态设计,要以软件计算作为参考依据;3)在基坑开挖过程中要进行严密的监控量测,并重视数据反馈。     

基于改进云模型的地铁站行人拥挤辨识方法

为降低城市地铁站内行人拥挤识别时多指标和多等级带来的不确定性和模糊性,采用改进云模型构建行人拥挤状态辨识模型。基于AHP-熵权法标定指标权重和行人拥挤状态等级,以标定的指标权重和各指标等级阈值作为输入,计算云数字特征值,采用正向正态云发生器,建立模板云和待识别云模型,计算两者之间的隶属度,根据最大隶属度原则辨识车站内各服务设施的行人拥挤状态,最后输出各服务设施的拥挤等级辨识结果。以宁波市鼓楼站为实证对象,对辨识结果进行实证分析。结果表明:采用四级行人拥挤状态划分方法合理可行。     

考虑湖盆摩阻效应的川藏铁路冰碛堰塞湖地震涌浪及溃决风险分析

川藏铁路沿线存在着众多冰碛堰塞湖,且大部分位于高烈度地震区,堰塞湖溃决洪水成为对线路方案起控制作用的灾害类型,而地震涌浪是导致冰湖溃决的主要诱因之一。目前湖泊地震涌浪计算公式一般忽略湖盆的摩阻效应,对水深较浅且糙率大的冰碛堰塞湖而言,计算值偏小。鉴此,通过开展不同水深、不同地震峰值加速度、不同糙率的振动台造波模型实验,研究湖盆摩阻效应对地震涌浪的影响。根据实验结果,建立考虑摩阻效应的地震涌浪计算公式,并利用漫溢型溃决临界水文条件提出了冰湖溃决判据;最后以川藏铁路帕隆藏布流域为例进行应用说明,从而建立一种与选线原则方案确定阶段精度要求相匹配的冰碛堰塞湖地震涌浪溃决风险评估方法。本文公式考虑湖盆摩阻效应,适用于水深较浅的冰碛堰塞湖,尤其是在大震强震情况下,其计算结果偏安全。     

青岛地铁蓄电池工程维护车车钩挂梁结构设计

文章分析了青岛地铁2号线蓄电池工程维护车出现车钩"低头"现象的原因,并给出了一种通过加装车钩挂梁结构以支撑车钩的解决方案。文章还对挂梁结构进行了强度校核,确保该结构满足实际工况需求。     

拱墩降温对大跨桥上连续式无砟轨道竖向位移影响分析

受季节和日照的影响,高墩大跨拱桥混凝土结构会出现膨胀现象,从而引起桥墩顶部竖向位移的变化。为了研究拱墩降温对高墩大跨拱桥上连续式无砟轨道竖向位移和高低不平顺的影响,根据桥上连续式无砟轨道的结构和受力特征,参考国内某大跨度上承式钢筋混凝土拱桥的实际参数,利用有限元方法,建立线-桥-墩一体化模型,分析拱墩降温对大跨拱桥上连续式无砟轨道的竖向位移和高低不平顺的影响。结果表明:拱墩降温引起的大跨桥上线路竖向位移较明显,设计时不可忽略;拱墩降温会引起线路高低不平顺,且对长波不平顺影响最严重;线路高低不平顺随降温幅度增加而增大,在年温差较大的地区目前不建议高墩大跨拱桥与连续式无砟轨道配合设计使用。     

海南北部老粘性土工程地质性质研究

海南岛北部沿海广泛分布老粘性土层,该土层埋藏适中、分布稳定,但常规勘察手段难以客观全面地揭示其工程地质性质.结合海南马村港口工程项目,综合分析该老粘性土层的时代成因、微观结构、化学成分及其物理力学性质,客观全面地揭示该土层的工程地质性质,为港口建设提供地质依据.