中美城市交通模型现况评估

交通需求模型预测未来一个区域内对交通系统的需求.这些模型是辅助交通官员与专家对重大交通项目投资和政策策略作出理性决定的重要工具.根据本刊2008年第1期对中国具有代表性的几个城市交通模型系统的示例介绍,对中国目前的交通模型研发、数据及应用进行总结,并比较了中美交通模型的差异.通过对现阶段中国交通模型建设和使用的深入了解,并结合已有研究和实际工作经验,对中关交通模型及其相关的工作进行系统性和前瞻性的讨论.     

全自动泊车系统的模型设计与仿真

全球汽车保有量的增多,直接造成城市交通的拥堵以及停车位空间的减小。随之而来的就是泊车安全性问题,新手驾驶员或疲劳驾驶人员如何能在不发生碰撞的情况下,快速安全地泊车入库,成为当下研究的热点。针对以上问题,本文将对全自动泊车系统展开研究。基于B样条曲线设计出泊车路径,基于滑模变结构与预瞄方式进行泊车路径的跟踪。最后通过搭建SIMULINK与CARSIM仿真模型进行联合仿真。     

道路运输车辆达标车型整车主动安全项目测试简析

道路运输车辆达标车型的实施,有效提升了道路运输车辆的安全性能。文章主要从电子稳定性控制系统、车道偏离预警系统、前向碰撞预警系统、自动紧急制动系统四个整车主动安全测试项目对道路运输车辆达标车型相应标准进行介绍,为道路运输车辆达标车型相关从业人员提供了主动安全整车项目试验参考。     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.     

Integrated Transport System of the South-Moravian Region and its impact on rural development

It is generally presupposed that the infrastructure and availability of services of general interest (like schools, medical care, social services and also public transport) impact on present demographic development in rural areas, namely depopulation and aging. Such services affect the quality of life of local people and sometimes they perform a vital necessity. It is possible to say that the absence of the mentioned services should be compensated by an effective system of public transport. In other case, especially those people who are not able to use individual cars due to the age, health, legal conditions or financial situation are bequeathed on an assistance of the family or neighbors or they stay cut off and excluded. This paper is aimed at the verification of the presupposition in the case of the South-Moravian Region – NUTS 3 region occupying the south-eastern part of the Czech Republic, bordering with Austria and Slovakia. The research method lies in analysis of the frequency, travel time and fare of public transport system and its comparison with demographic development in rural areas, especially in the peripheral ones. The results are discussed in view of the system of central places in the region and present urbanization processes like suburbanization, counterurbanization and reurbanization.     

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.     

Impacts of trade related sustainability strategies on freight transportation: Modelling framework and application for France

The circular and functional economies are being presented in the literature as potential strategies for future sustainable societies. In terms of the consequences for supply chains, they will promote a much more dispersed and diversified, local and network based usage of goods than the current economy, which is comparatively linear, concentrated, long distance oriented and scale economy based. A gap in the literature is the assessment of the effects of these systems on freight transport flows. In our paper, we present a first attempt at estimating this impact using freight transport scenario building and quantitative modelling. In order to translate the main parameters that characterize these systems into factors determining freight transportation volumes, we develop a framework based on a typology of goods categories describing functional and spatial proximity between producers and consumers. In order to simulate changes in the economy, we develop scenarios for the shifting of goods from one category to another and, additionally, include internalization policies that should guide their realization. We calculate the impacts on freight flows using a new interregional transport model for France that includes distribution chains and produces estimates of external costs of transport. Our results show that circular and functional economies could lead to a 2–5% reduction of air pollutant emissions and up to a 14–26% reduction if combined with the internalization of external costs. The scenario with ongoing mass production for differentiated demand is found to lead to a 5% increase of environmental impacts compared to the baseline.     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.     

An ontology-based framework to support performance monitoring in public transport systems

Managers of public transport systems have been facing for years the strategic challenge of maintaining high quality of transport services to improve the mobility of citizens, while reducing costs and ensuring safety and low environmental impact. A well-established way to evaluate the performance achieved by the system or by specific activities is to monitor Key Performance Indicators (KPI). However, existing management systems, which refer to flexible yet large and complex data models, provide a limited support to define and select relevant KPIs for the objectives at hand, and even the identification of whether and how the data model is capable to achieve a certain informative need is a critical and time-consuming task. This work is aimed to propose a framework to ease the development of a monitoring system in the public transport domain. The approach is based on the ontological representation of all the knowledge regarding indicators and their formulas, business objectives, dimension analysis and their relation with the Transmodel, the European reference data model for public transport information systems. On its top, a reasoning framework provides logic functionalities to interactively support designers in a set of common design tasks: the choice of the most suitable indicators for the performance monitoring needs at hand, the definition of new indicators and the identification of the minimal set of Transmodel modules needed to calculate them. A case study is included to discuss these applications, while an evaluation shows the feasibility of the approach.