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【免费下载】TRANSIMS V3.0 的源码和技术说明文档!
[这个贴子最后由水寿松在 2005/03/13 00:02am 第 1 次编辑]
一种新兴的美国城市交通流量需求预测模型系统
孙晓端
背景
在过去的几年里,美国城市交通规划的重点已由原先的新建道路转变为对交通需求的有效管理,以及对现有道路设施的充分利用。这一转变是随着人们对于社会、环境以及经济方面问题的关注不断提高而产生的,同时人们也认识到面对日益增长的交通流量单纯解决交通拥堵问题只能是一种暂时的方案。
由于人们交通理念的转变,开发与运用出行控制措施(Travel Control Measures,TCM)已经得到交通运输规划部门的认同。这些措施其本身是极其复杂和综合性的,并且其影响到目前为止还不得而知。随着开始考虑采用TCM措施的美国城市区域数量的不断扩大,在最早基于出行的4阶段程序(Trip-based four-step procedure)基础上发展起来的传统交通需求预测及规划方法已经暴露出明显不足,无法解决通过实行TCM措施而引发的更为复杂的问题。人们出行行为模式与决定这些模式的态度、价值观念以及客观条件的局限等,这些关系在本质上都是极其复杂的。传统的预测方法不能在令人信服的理论框架下清楚地解释这些关系。
因而产生了一种基于行为的新的方法(activity-based approach),有可能针对当前的交通规划提供有效而实际的工具。它首先形成于20世纪70年代对人们出行行为的研究领域。基于行为的方法清楚地认识到人们对出行的需求源于对行为活动的需求,而这些行为在时间与空间上又是分散分布的。更进一步,这些方法还确定出某个人做出的一系列出行决定之间,内部又是相互关联的。认为基于出行的预测方法能够提供一个在理论与概念上都更令人信服的框架,并可在此框架下进行出行需求的模型建立,这一观点至今还存在着争论。
对基于出行的4阶段程序的评论
实际上目前美国所有预测乘客出行需求以及政策分析的工具,都是以4阶段程序为基础的。这种分析方法起源于20世纪50年代与60年代的战后发展时期,当时:
1、城市人口快速增长;
2、机动化不断发展,以及城市郊区开始蔓延。
当时交通规划的重点还是发展基础设施。所要着手解决的问题主要是考虑在哪里修建新的快速道路,以及需要建多少车道。正是由于这种直接规划交通的原因,那时预测程序的粗糙也是难以避免的。
然而,这种程序内部还包含了一些众所周知的不一致性。例如,区域范围小区出行产生和吸引的总量通常互不一致,还需要进行调整;用来进行出行分布和方式划分的出行时间矩阵与交通网络分配所得出的出行时间不一定相同。
而更为重要的,也是其中一个最大的问题是4阶段程序缺少以人们的行为特性为基础。例如,在一个典型的线性回归或交叉分类的出行产生模型中,家庭成员每天的出行数量只是家庭人口多少和该家庭所拥有车辆数量的函数。它并不能反映出人们所熟悉的行为事实,如生活方式(家庭人员的年龄,有无子女)以及就业状态对家庭出行模式的影响。
另外,4阶段程序归纳起来还有以下几种局限性:
1、以出行为基础的顺序结构;
2、缺少一天中某个时间的概念;
3、对于模型说明性变量大小的局限性;
4、对人们行为反应的局限性;
5、与大多数出行需求管理的结果无关;
6、出行的发生与交通拥堵及收费无关;
7、出行分布结果与系统变化没有完全关联;
8、不能确定车流量的发展变化;
9、其输入完全是城市土地利用、经济与社会人口统计学等外因。
众所周知,没有哪一种单一的模型能够适合所有的研究对象。对于某一类型的交通规划问题,采用基于出行的4阶段程序仍然不失为一种有效的手段与方法。然而,当前的实践还需要有其他的替代模型。对于决策者来说还需要扩展更多的解决交通规划的手段。
为何要采用基于行为的预测方法?
基于行为的预测方法能够清楚地认识到人们对行为活动的需求导致了对出行的需求。换言之,人们要到另一地点参与行为的需求或渴望导致人们做出出行的决定。因此,基于行为的预测方法针对人们出行行为潜在的决策过程为基础对出行需求进行预测。从这种意义上讲,基于行为的预测方法完全不同于4阶段程序方法的发展逻辑,4阶段程序是与统计学相关的而不是以人们的行为关系做为模型发展的驱动力。基于行为的预测方法还认为由于人们一天中的各种行为是相互联系的,因此实现这些行为的出行也是相互联系的。家庭成员每天的出行不可以单独进行分析。
尽管基于行为的预测方法早在20世纪70年代就由牛津大学的一群研究人员发明了,但是目前它仍然主要处于学术研究阶段,其中部分原因是它还不适合大型的密集投资项目的评估,但它却很适用于精确的、通常是小范围的交通政策措施。
除了交通规划方面发生的这种巨大变化以外,还有几个重要的发展值得注意:
1、基于行为研究成果的积累;
2、调查方法以及统计估计手段的进步;
3、计算机技术发展以及软件的应用(数据库,GIS等)。
所有这些方面的变化都促进了基于行为预测模型的发展。由于分析的复杂性,模型技术必须发展成为模拟技术。因此,在美国开发出一个基于行为的微观模拟模型,以满足对城市交通流量预测新的需求,这种需要要求对政策分析也是十分敏感的。
TRANSIMS:交通分析与模拟系统
TRANSIMS 是多线路出行模型改进计划的一部分,是由美国交通与环境保护部门发起资助的。位于洛斯阿拉莫斯市的美国国家实验室主持这项开发工作。
TRANSIMS 潜在的宗旨是研究人们的行为及其内在的相互作用,并由于受到交通系统的限制而产生的交通行为的实施。TRANSIMS 采用了先进的计算和分析技术,创建了一个完整的区域交通系统分析环境。这种模拟环境将包括由单独出行者所形成的区域人口,同时也包括有出行行为和计划的货物运输。
(作者工作单位:路易斯安娜大学,北京正大交通工程有限公司)
英文原文
An Overview of A New Modeling System for Urban Demand Forecasting in the United States
By
Xiaoduan Sun, Ph.D., & P.E.
Associate Professor
University of Louisiana at Lafayette
&
Technical Consultant
Beijing Zheng Da Traffic Engineering LTD.
Background
Over the past couple of years, the emphasis of transportation planning has shifted from the construction of new highways to the effective management of travel demand and efficient use of existing highway facilities in the United States. This shift has been brought about by rising social, environmental, and economic concerns coupled with a realization that building one';s way out of congestion is only a temporary solution to serving the increasing demand.
Due to the change of the philosophy, development and implementation of Travel Control Measures (TCM) have been embraced by the transportation planning community. These measures are sophisticated and complex in nature, the existing impacts of which are unknown. As increasing number of urban areas in the United States began considering TCMs, it is become apparent that traditional travel demand forecasting and planning methods, that are primarily derived from trip-based four-step procedures, are not able to address the complex questions raised by TCM implementation. Relationships among human travel behavior patterns and the attitudes, values and constraints that are determine these patterns are extremely complex in nature, and traditional forecasting methods do not explicitly model these relationships in a theoretically sound framework.
A new approach, which has potential of offering effective and practical tool for contemporary transportation planning, is the activity-based approach. It was first conceived in the travel behavior research arena in 1970s. Activity-based approach explicitly recognizes that travel demand is derived from the need to pursue activities that are dispersed in time and space. Moreover, these approaches also recognize the inter-dependence among decisions for a series of trips made by an individual. It has been argued that activity-based approach provides a theoretically and conceptually stronger framework within which travel demand modeling may be performed.
Critical review of the Trip-Based Four-Step Procedure
Practically all tools currently available in the U.S. for passenger travel demand forecasting and policy analysis are based on the four-step procedure. The procedure was developed in the 1950s and 1960s during the post-war expansion, when:
1、Urban population was rapidly growing,
2、Motorization was progressing, and Suburban sprawling was starting.
The emphasis in transportation planning at that time was infrastructure development. The issue at hand was where to build a new freeway and how many lanes were needed. Because of such straightforward planning contexts, coarse forecasting procedures sufficed at that time.
The procedure, however, contains several well-acknowledged internal inconsistencies. For example, the area-wide totals of zonal trip productions and attractions normally do not coincide with each other, requiring some adjustment; zone-to-zone travel time used as input to trip distribution and modal split are not necessarily consistent with travel times that are derived from the network assignment.
More importantly, lack of behavior foundation is one of the biggest problems with the four-step procedure. For example, in a typical linear-regression or cross-classification models of trip generation, number of household daily trips is only a function of household size and number of vehicles. This does not reflect the well-known behavioral fact that life-style (age, existence of children) and employment status affect households travel patterns.
Other limitations of the four-step procedure can be summarized in the following:
1、Trip-based, sequential structure,
2、Lack of the time-of-day dimension,
3、Limited size of explanatory variables
4、Limited behavior response,
5、Consequently unresponsive to most Travel Demand Management
6、Trip generation unresponsive to congestion and pricing,
7、Consequently the trip distribution is not fully responsive to system change,
8、In ability to address vehicle fleet mix evolution, and
9、Totally exogenous land-use, economic and socio-demographic input.
It is known that no single model is suited for all study objectives. The trip-based, four-step procedure continues to be an effective tool for certain type of transportation planning problems. Yet, current practice calls for alternative models. The array of transportation planning tools available to policy makers needs to be expanded.
Why Activity-Based Approach?
The activity-based approach explicitly recognizes the fact that the demand for activities produces the demand for travel. In other words the need or desire to engage in an activity at a different location generates a trip. The activity-based approach thus aims at the prediction of travel demand based on a though understanding of the decision process underlying travel behavior. In this sense the activity-based approach is entirely different from the approach for the development of four-step procedure where statisrtical association, rather than behavior relationships, drove model development. The activity-based approach also recognize that as the activities engaged in a day are linked to each other, trips made to pursue them are also linked to each other. Household daily trips can not be analyzed separately.
Although the activity-based approach was conceived in 1970s by a group of researchers at Oxford University, it largely remained in the academic research partly because of that the activity-based approach is not suited for the evaluation of capital-intensive large-scale projects, but better suited for refined, often small scale transportation policy measures.
Aside from this rather drastic change in transportation planning contexts, several important advances have taken place:
1、Accumulation of activity-based research results,
2、Advances in survey methods and statistical estimation methods, and
3、Advances in computation capabilities and supporting software (database, GIS, etc.)
All these changes have made the development of the activity-based models possible. Due to the complexity of the analysis, the modeling techniques have to be simulation. That is why an activity-based micro-simulation model has been developed in the United States to accommodate the need for a new demand for an urban travel forecasting model that is sensitive for policy analysis.
TRANSIMS: Transportation Analysis and Simulation Systems
The TRANSIMS is part of the multi-track Travel Model Improvement Program sponsored by the U.S. Department of Transportation and Environmental Protection Agency. Los Alamos National Laboratory is leading its development.
The underlying TRANSIMS theme is that individual behavior and their interactions, as constrained by the transportation system, generate the transportation performance. TRANSIMS employ advanced computational and analytical techniques to create an integrated regional transportation systems analysis environment. The simulation environment will include a regional population of individual travelers and freight loads with travel activities and plans.
For more information on Travel Model Improvement Program, please email iday@tamu.edu
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