浅谈城市道路交通管理规划方法与应用

该文以我国城市道路交通管理规划的现状为出发点,提出了城市道路交通管理规划是一项重要课题,阐述了交通管理规划的目的、基本内容及三个层次,论述了交通需求预测的分析方法及模型。最后结合兰州市道路交通管理规划的框架与实施情况,分析其主要成果及产生的社会经济效益。     

修正四阶段法在城市交通抗灾规划中的应用

根据地震环境下不同恢复阶段的社会经济活动及交通系统特性,对传统交通预测四阶段法———出行产生、出行分布、方式划分、交通分配的宏观模型进行了修正,讨论了不同模型的参数变化趋势,建议了参数的调整原则及方法,进而以修正四阶段法为基础进行震后交通需求预测。该方法简便易行,预测得到道路通行能力、流量、负荷度和平均运行时间等多个指标,为城市交通系统防灾规划提供决策依据。最后,结合我国东南沿海某城市的工程实践,有针对性的进行了应用和验证。     

The Impact of Travel Time Information on Travelers’ Learning under Uncertainty

In this work, laboratory experiment was conducted in order to evaluate the effect of feedback on decision-making under uncertainty, with and without provided information about travel times. We discuss the prediction of travelers’ response to uncertainty in two route–choice situations. In the first situation travelers are faced with a route–choice problem in which travel times are uncertain but some external information about routes’ travel times is provided. The second situation takes place in a more uncertain environment in which external information about travel times is not provided, and the travelers’ only source of information is their own experience. Experimental results are in conflict with the paradigm about traveler information systems: As a consequence of information, the propensity of travelers to minimize expected travel time is not necessarily increased. Providing travelers with static information about expected travel times reveals an increase in the heterogeneity of travelers’ choices and reduces the maximization rate.     

Demand for rail travel to and from airports

Rail access to airports is becoming increasingly important for both train operators and the airports themselves. This paper reports analysis of inter-urban rail demand to and from Manchester and Stansted Airports and the sensitivity of this market segment to growth in air traffic and the cost and service quality of rail services. The estimated demand parameters vary in an expected manner between outward and inward air travellers as well as between airport users and general rail travellers. These parameters can be entered into the demand forecasting framework widely used in the rail industry in Great Britain to provide an appropriate means of forecasting for this otherwise neglected market segment. The novel features of this research, at least in the British context, are that it provides the first detailed analysis of aggregate rail flows to and from airports, it has disaggregated the traditional generalised time measure of rail service quality in order to estimate separate elasticities to journey time, service headway and interchange, and it has successfully explored departures from the conventional constant elasticity position.     

A conceptual and methdological framework for the generation of activity-travel patterns

This paper develops a conceptual framework for the generation of activity and travel patterns in the context of more general structures and presents an integrated model system as a step toward development of an improved travel demand forecasting model system. We propose a two-stage structure to model activity and travel behavior. The first stage, the stop generation and stop/auto allocation models, consists of the choices for the number of household maintenance stops and the allocation of stops and autos to household members. The second stage, the tour formation model, includes the choices for the number of tours and the assignment of stops to tours for each individual, conditional on the choices in the first stage. Empirical results demonstrate that individual and household socio-demographics are important factors affecting the first stage choices, the generation of maintenance stops and the allocation of stops and autos among household members, and the second stage choices, the number of tours and the assignment of stops to tours. This revised version was published online in June 2006 with corrections to the Cover Date.     

Conformity: How VMT-speed distributions can affect mobile emission inventories

Transportation conformity is a US regulatory process that requires that transportation modeling be integrated with air quality modeling. Consequently, every change to either modeling process is undertaken with great scrutiny by the regional governments, who have to use the models for demonstrating conformity. This paper explores the "trip versus link debate," which stems from the fact that the standard travel demand models used by most metropolitan planning organizations are primarily link oriented, while the air quality models have been primarily trip oriented. Using the Sacramento region we examine the effects on mobile source emissions inventories when speed-VMT distributions are constructed using the trip and link-based philosophies. The results of our study indicate that trip-based VMT-speed distributions produce consistently lower emissions estimates than the link-based distributions. We use the results to assert that deciding between a trip-based or link-based conformity modeling process involves more than the technical difficulty of changesto the models or the potential political ramifications, it involves assessing which method will provide the most accurate estimates of regional motor vehicle emissions. We also examine ways to think about constructing mobile source emission inventories.     

Optimizing the locations of electric taxi charging stations: A spatial–temporal demand coverage approach

Vehicle electrification is a promising approach towards attaining green transportation. However, the absence of charging stations limits the penetration of electric vehicles. Current approaches for optimizing the locations of charging stations suffer from challenges associated with spatial–temporal dynamic travel demands and the lengthy period required for the charging process. The present article uses the electric taxi (ET) as an example to develop a spatial–temporal demand coverage approach for optimizing the placement of ET charging stations in the space–time context. To this end, public taxi demands with spatial and temporal attributes are extracted from massive taxi GPS data. The cyclical interactions between taxi demands, ETs, and charging stations are modeled with a spatial–temporal path tool. A location model is developed to maximize the level of ET service on the road network and the level of charging service at the stations under spatial and temporal constraints such as the ET range, the charging time, and the capacity of charging stations. The reduced carbon emission generated by used ETs with located charging stations is also evaluated. An experiment conducted in Shenzhen, China demonstrates that the proposed approach not only exhibits good performance in determining ET charging station locations by considering temporal attributes, but also achieves a high quality trade-off between the levels of ET service and charging service. The proposed approach and obtained results help the decision-making of urban ET charging station siting.     

城市轨道交通站点客流不确定性研究

为提高城市轨道交通站点客流预测的可靠性,在分析客流不确定性影响因素的基础上,基于ARIMA-GARCH模型,依据南京地铁珠江路站点客流数据对客流不确定性进行建模和预测,并从预测置信区间和无效覆盖率两方面与传统的时间序列进行对比分析,研究结果表明,ARIMA-GARCH能够较好地拟合客流波动情况,为城市轨道交通运营与管理提供理论依据。     

太原市可持续交通发展策略研究

针对太原市社会、经济、交通现状提出发展可持续交通的思想,并从交通管理体制、制定交通规划以及具体措施几个方面提出相应的策略以求交通发展能满足当代人和后代的交通需求,实现与资源、环境的协调发展。     

基于深度强化学习的车辆跟驰控制

针对自适应巡航控制系统在控制主车跟驰行驶中受前车运动状态的不确定性影响问题，在分析车辆运动特点的基础上，提出一种能够考虑前车运动随机性的跟驰控制策略。搭建驾驶人实车驾驶数据采集平台，招募驾驶人进行实车跟驰道路试验，建立驾驶人真实驾驶数据库。假设车辆未来时刻的加速度决策主要受前方目标车辆运动影响，建立基于双前车跟驰结构的主车纵向控制架构。将驾驶数据库中的驾驶数据分别视作前车和前前车运动变化历程，利用高斯过程算法建立了前车纵向加速度变化随机过程模型，实现对前方目标车运动状态分布的概率性建模。将车辆跟驰问题构建为一定奖励函数下的马尔可夫决策过程，引入深度强化学习研究主车跟驰控制问题。利用近端策略优化算法建立车辆跟驰控制策略，通过与前车运动随机过程模型进行交互式迭代学习，得到具有运动不确定性跟驰环境下的主车纵向控制策略，实现对车辆纵向控制的最优决策。最后基于真实驾驶数据，对控制策略进行测试。研究结果表明：该策略建立了车辆纵向控制与主车和双前车状态之间的映射关系，在迭代学习过程中对前车运动的随机性进行考虑，跟驰控制中不需要对前车运动进行额外的概率预测，能够以较低的计算量实现主车稳定跟随前车行驶。