城市综合交通体系规划回顾与展望

回顾改革开放以来中国城市综合交通体系规划在规划定位、规划目标、内容体例、技术方法、规划实施等方面的实践和探索。总结规划编制工作的基本特点:以问题为导向、融合城市总体规划、提倡以人为本理念、广泛应用定量技术方法。指出规划编制和实施过程中存在的不足:规划地位和作用认识不清、价值理念与实际行动脱节、规划实施评估环节缺失、规划管理体制机制缺乏、相关法规技术标准陈旧。结合城市交通发展新趋势,展望未来城市综合交通体系规划的重点方向:强化多规融合、强调以人为核心的规划、加强规划评估和滚动编制、加强技术创新与行业规范、深化政策保障机制研究。     

Integrating mesoscopic dynamic traffic assignment with agent-based travel behavior models for cumulative land development impact analysis

A number of approaches have been developed to evaluate the impact of land development on transportation infrastructure. While traditional approaches are either limited to static modeling of traffic performance or lack a strong travel behavior foundation, today’s advanced computational technology makes it feasible to model an individual traveler’s response to land development. This study integrates dynamic traffic assignment (DTA) with a positive agent-based microsimulation travel behavior model for cumulative land development impact studies. The integrated model not only enhances the behavioral implementation of DTA, but also captures traffic dynamics. It provides an advanced yet practical approach to understanding the impact of a single or series of land development projects on an individual driver’s behavior, as well as the aggregated impacts on the demand pattern and time-dependent traffic conditions. A simulation-based optimization (SBO) approach is proposed for the calibration of the modeling system. The SBO calibration approach enhances the transferability of this integrated model to other study areas. Using a case study that focuses on the cumulative land development impact along a congested corridor in Maryland, various regional and local travel behavior changes are discussed to show the capability of this tool for behavior side estimations and the corresponding traffic impacts.     

振华启东船厂产能升级布局规划

振华启东船厂前身为成立于2007年的道达船厂,针对厂区内各功能模块之间的能力匹配问题凸显、部分设施破损、部分设施严重制约厂区生产能力的问题,通过厂区现状平面布局、工艺流程系统梳理,根据企业发展定位和关键生产要素潜能制定科学合理的规划目标,以生产设施产能分析计算分析为理论支撑,提出一套各区域产能相匹配且适应未来规模化、精益化、规范化、安全化发展的产能升级布局规划方案,达到各功能模块布局合理、生产能力匹配、生产工艺流畅、生产设施规范的目的。针对既有港区的产能升级规划,采用以定量计算为支撑的规划方法,可供类似工程参考与借鉴。     

地铁与市郊铁路过轨运营下列车开行方案研究

在分析地铁与市郊铁路过轨运营特点的基础上,以乘客节省的总旅行时间最大化和地铁运营企业增加的总费用最小化为目标函数,建立了过轨运营下列车开行方案双目标规划模型,并设计了基于模糊数学规划的求解算法.以某两条轨道交通线路为算例,研究过轨运营开行方案并对相关参数进行灵敏度分析.研究结果表明,地铁与市郊铁路过轨运营既可节省乘客总旅行时间又可增加运营企业收益,且过轨客流需求越大、过轨站换乘时间越长、过轨方缴纳的过轨费用越少、过轨列车运营组织方案越合理,过轨运营效果越显著.     

The vulnerability of the environment to spills of dangerous substances on highways: A diagnosis based on multi criteria modeling

Highways and freeways are the main infrastructure channel used to transport cargo in Brazil. This cargo often includes dangerous chemical products which can, in the event of an accident, negatively impact the environment. The development and implementation of tools for the rapid diagnosis of environmental vulnerability in the transportation of dangerous goods has been studied. However, for highways and freeways there is a lack of studies based on environmental attributes, and not just based on statistical data which demands a specific period for collection and analysis and only after that the implementation of preventive measures. Thus, evaluation grounded on multiple criteria embedded in Geographic Information System (GIS) has significant potential for the practical implementation of risk management of road transportation of dangerous goods. This study has determined the environmental vulnerability of route BR 050, specifically the segment between the cities of Uberlândia and Uberaba in the state of Minas Gerais, where multi criteria analysis has been efficient in determining the most vulnerable areas. The main attributes analyzed were the drainage density, soil type and geology, determining that in case of an accident with dangerous substances the regional environment would be immediately affected, and so endorsing the use of this tool in many segments involved in environmental management of highway enterprises.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.     

Human-like autonomous car-following model with deep reinforcement learning

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through these interactions, an optimal policy, or car-following model that maps in a human-like way from speed, relative speed between a lead and following vehicle, and inter-vehicle spacing to acceleration of a following vehicle is finally obtained. The model can be continuously updated when more data are fed in. Two thousand car-following periods extracted from the 2015 Shanghai Naturalistic Driving Study were used to train the model and compare its performance with that of traditional and recent data-driven car-following models. As shown by this study’s results, a deep deterministic policy gradient car-following model that uses disparity between simulated and observed speed as the reward function and considers a reaction delay of 1 s, denoted as DDPGvRT, can reproduce human-like car-following behavior with higher accuracy than traditional and recent data-driven car-following models. Specifically, the DDPGvRT model has a spacing validation error of 18% and speed validation error of 5%, which are less than those of other models, including the intelligent driver model, models based on locally weighted regression, and conventional neural network-based models. Moreover, the DDPGvRT demonstrates good capability of generalization to various driving situations and can adapt to different drivers by continuously learning. This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.     

A planning tool for evaluating vehicles miles travelled and traffic safety forecasts of growth management scenarios: A case study of Baton Rouge and New Orleans

This study describes an adaptable planning tool that examines potential change in vehicle miles travelled (VMT) growth and corresponding traffic safety outcomes in two urbanized areas, Baton Rouge and New Orleans, based on built environment, economic and demographic variables. This model is employed to demonstrate one aspect of the potential benefits of growth management policy implementation aimed at curbing VMT growth, and to establish targets with which to measure the effectiveness of those policies through a forecasting approach. The primary objective of this research is to demonstrate the need to break with current trends in order to achieve future goals, and to identify specific policy targets for fuel prices, population density, and transit service within the two study regions. Models indicate based on medium growth scenarios, Baton Rouge will experience a 9 percent increase in VMTs and New Orleans will experience 10 percent growth. This translates to corresponding increases in crashes, injuries and fatalities. The paper provides forecasts for planners and engineers to consider an alternative future, based on desired goals to reduce VMTs and therefore improve safety outcomes. A constrained-forecast model shows a cap on VMTs and crash rates is achievable through policy that increases fuel prices, population density and annual transit passenger miles per capita at reasonable levels through a growth management approach.     

交通模型的价值

在既有规划编制导则中,已经明确交通模型和交通需求分析是综合交通体系规划、轨道交通线网规划的重要工作内容。交通模型的价值并非仅仅体现在预测结果和精度上,更在于编制过程中对交通特征和供需关系的分析,对战略方案、系统方案的指导、解释、论证的作用上。但在现实规划编制中,模型的地位和价值在丧失,日益成为项目成果中的摆设品,难以支撑交通需求深入分析,并与战略构思、方案制定相脱节。与此同时,规划实践、大数据、交通模型的发展趋势,亟须重新审视模型的价值,提升模型精细化的定量分析水平。最后,从机制保障、应用推广、功能拓展、科研攻关等方面,提出促进模型价值提升的相关建议。     

城市大型医院周边道路交通问题剖析及改善对策——以深圳市为例

为了合理科学组织医院周边及内部交通,避免重现目前深圳大型医院周边普遍存在的交通拥堵、停车困难、进院车辆排队、的士乘坐不便等交通问题,以深圳市为例,分析现状大型医院周边存在的道路交通问题和产生原因,提出完善周边道路交通设施、大力发展公共交通、合理规划医院布局、建立科学有效的交通组织体系等改善对策.