Strategic de-confliction in the presence of a large number of 4D trajectories using a causal modeling approach

This paper presents a strategic de-confliction algorithm based on causal modeling developed under the STREAM project and launched under the umbrella of the Single European Sky ATM Research (SESAR) Program. The basic underlying concept makes use of the enriched information included in the Shared Business Trajectories (SBTs) of the flights prior to takeoff (or in the Reference Business Trajectories (RBTs) if the flight is airborne) to allocate conflict-free trajectories in a traffic planning phase that should lead to an actual conflict-free scenario in the flight execution phase in the absence of flight and/or network uncertainties. The proposed approach could decrease the workload of the air traffic controllers, thus improving the Air Traffic Management (ATM) capacity while meeting the maximum possible expectations of the Airspace Users’ requirements in terms of horizontal flight efficiency. The main modules of the implemented system are also presented in this paper; these modules are designed to enable the processing of thousands of trajectories within a few seconds or minutes and encompass a global network scope with a planning horizon of approximately 2–3 h. The causal model applied for network conflict resolution and flight routing allocation is analyzed to demonstrate how the emergent dynamics (i.e., domino effects) of local trajectory amendments can be efficiently explored to identify conflict-free Pareto-efficient network scenarios. Various performance indicators can be taken into account in the multi-criteria optimization process, thus offering to the network manager a flexible tool for fostering a collaborative planning process.     

西部中小城市老城区交通改善研究

西部中小城市中心城区老城区特殊的地理背景,决定了其交通改善的特殊性。文章介绍了西部中小城市老城区综合交通系统现状和城市规划现状,分析了其特有的城市交通特点与存在的问题,从系统工程的角度提出了一系列交通改善措施。     

An empirical study of simulation-based dynamic traffic assignment procedures

Abstract

Under Intelligent Transportation Systems (ITS), real-time operations of traffic management measures depend on long-term planning results, such as the origin–destination (OD) trip distribution; however, results from current planning procedures are unable to provide fundamental data for dynamic analysis. In order to capture dynamic traffic characteristics, transportation planning models should play an important role to integrate basic data with real-time traffic management and control. In this paper, a heuristic algorithm is proposed to establish the linkage between daily OD trips and dynamic traffic assignment (DTA) procedures; thus results from transportation planning projects, in terms of daily OD trips, can be extended to estimate time-dependent OD trips. Field data from Taiwan are collected and applied in the calibration and validation processes. Dynamic Network Assignment-Simulation Model for Advanced Road Telematics (DYNASMART-P), a simulation-based DTA model, is applied to generate time-dependent flows. The results from the validation process show high agreement between actual flows from vehicle detectors (VDs) and simulated flows from DYNAMSART-P.     

Automatic identification of risky weather objects in line of flight (AIRWOLF)

Adverse weather conditions are hazardous to flight and contribute to re-routes and delays. This has a negative impact on the National Airspace System (NAS) due to reduced capacity and increased cost. In today’s air traffic control (ATC) system there is no automated weather information for air traffic management decision-support systems. There are also no automatic weather decision-support tools at the air traffic controller workstation. As a result, air traffic operators must integrate weather information and traffic information manually while making decisions. The vision in the Next Generation Air Transportation System (NextGen) includes new automation concepts with an integration of weather information and decision-making tools. Weather-sensitive traffic flow algorithms could automatically handle re-routes around weather affected areas; this would optimize the capacity during adverse conditions. In this paper, we outline a weather probe concept called automatic identification of risky weather objects in line of flight (AIRWOLF). The AIRWOLF operates in two steps: (a) derivation of polygons and weather objects from grid-based weather data and (b) subsequent identification of risky weather objects that conflict with an aircraft’s line of flight. We discuss how the AIRWOLF concept could increase capacity and safety while reducing pilot and air traffic operator workload. This could translate to reduced weather-related delays and reduced operating costs in the future NAS.     

Three-dimensional conflict count models for unstructured and layered airspace designs

This paper presents analytical models that describe the safety of unstructured and layered en route airspace designs. Here, ‘unstructured airspace’ refers to airspace designs that offer operators complete freedom in path planning, whereas ‘layered airspace’ refers to airspace concepts that utilize heading-altitude rules to vertically separate cruising aircraft based on their travel directions. With a focus on the intrinsic safety provided by an airspace design, the models compute instantaneous conflict counts as a function of traffic demand and airspace design parameters, such as traffic separation requirements and the permitted heading range per flight level. While previous studies have focused primarily on conflicts between cruising aircraft, the models presented here also take into account conflicts involving climbing and descending traffic. Fast-time simulation experiments used to validate the modeling approach indicate that the models estimate instantaneous conflict counts with high accuracy for both airspace designs. The simulation results also show that climbing and descending traffic caused the majority of conflicts for layered airspaces with a narrow heading range per flight level, highlighting the importance of including all aircraft flight phases for a comprehensive safety analysis. Because such trends could be accurately predicted by the three-dimensional models derived here, these analytical models can be used as tools for airspace design applications as they provide a detailed understanding of the relationships between the parameters that influence the safety of unstructured and layered airspace designs.     

Probabilistic multi-aircraft conflict detection approach for trajectory-based operation

Conflict detection (CD) is one of the key functions used to ensure air transport safety and efficiency. In trajectory-based operation (TBO), aircraft are provided with more flexibility in en route trajectory planning and more responsibility for self-separation. The high flexibility in trajectory planning enables random changes in pilot intent, thus increasing the uncertainty in trajectory prediction and CD. This study proposes a novel probabilistic CD approach for TBO in which the uncertainty of pilot intent is taken into account by quantifying the aircraft reachable domain constrained by the flight plan. First, a probabilistic model for aircraft trajectory prediction is developed using the truncated Brownian bridge method. Based on this model, a novel conflict probability estimation method is developed. Finally, the performance of the proposed probabilistic CD approach is demonstrated through an illustrative air traffic scenario.     

Connectivity-based optimization of vehicle route and speed for improved fuel economy

Traditionally, vehicle route planning problem focuses on route optimization based on traffic data and surrounding environment. This paper proposes a novel extended vehicle route planning problem, called vehicle macroscopic motion planning (VMMP) problem, to optimize vehicle route and speed simultaneously using both traffic data and vehicle characteristics to improve fuel economy for a given expected trip time. The required traffic data and neighbouring vehicle dynamic parameters can be collected through the vehicle connectivity (e.g. vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-cloud, etc.) developed rapidly in recent years. A genetic algorithm based co-optimization method, along with an adaptive real-time optimization strategy, is proposed to solve the proposed VMMP problem. It is able to provide the fuel economic route and reference speed for drivers or automated vehicles to improve the vehicle fuel economy. A co-simulation model, combining a traffic model based on SUMO (Simulation of Urban MObility) with a Simulink powertrain model, is developed to validate the proposed VMMP method. Four simulation studies, based on a real traffic network, are conducted for validating the proposed VMMP: (1) ideal traffic environment without traffic light and jam for studying the fuel economy improvement, (2) traffic environment with traffic light for validating the proposed traffic light penalty model, (3) traffic environment with traffic light and jam for validating the proposed adaptive real-time optimization strategy, and (4) investigating the effect of different powertrain platforms to fuel economy using two different vehicle platforms. Simulation results show that the proposed VMMP method is able to improve vehicle fuel economy significantly. For instance, comparing with the fastest route, the fuel economy using the proposed VMMP method is improved by up to 15%.     

城市平面交叉口汽车排放优化策略研究

文章针对城市平面交叉口交通污染严重的问题,分析城市平面交叉口交通及行为特性、影响机动车排放的相关因素,从平面交叉口交通规划、交通控制二个方面阐述汽车排放优化措施。     

Facing the realities of non-motorized transportation in developing countries

The objective of this paper is to assess issues concerning non-motorized transportation in developing countries. This assessment is done through an examination of three topics: a brief overview of the transportation picture in developing countries; a study of city size and city form vis-a-vis pedestrian movement; and, a look at the characteristics of non-motorized modes, including their capacities. An analysis and discussion attempt to sort out the crucial issues connected with pedestrian planning in particular, and non-motorized transport in general. It is concluded (1) that special attention be paid to space/time capacity/cost issues connected with non-motorized modes (2)that some of the low-cost intermediate technology modes be examined for possible inclusion in traffic streams (3)that land-use patterns need to be rearranged keeping in mind the limitations of non-motorized modes, and (4)that the extent to which physical trip-making can be substituted by telecommunication needs to be examined very critically. An agenda for action reflects these concerns.     

弯道诱发道路交通安全事故分析

道路交通安全关乎我们的切身利益,其诱发因素颇多,而弯道是交通安全事故高发地。文章从汽车行驶特性、不良视距、会车超车等方面入手,分析弯道诱因与交通安全事故间的内在关系,并提出了基于GPS、GIS信息系统工程的智能交通预警思路,为交通安全控制提供理论参考依据。     

Congestion avoidance in city traffic

The number of vehicles on the road (worldwide) is constantly increasing, causing traffic jams and congestion especially in city traffic. Anticipatory vehicle routing techniques have thus far been applied to fairly small networked traffic scenarios and uniform traffic. We note here a number of limitations of these techniques and present a routing strategy on the assumption of a city map that has a large number of nodes and connectivity and where the vehicles possess highly varying speed capabilities. A scenario of operation with such characteristics has not previously been sufficiently studied in the literature. Frequent short‐term planning is preferred as compared with infrequent planning of the complete map. Experimental results show an efficiency boost when single‐lane overtaking is allowed, traffic signals are accounted for and every vehicle prefers to avoid high traffic density on a road by taking an alternative route. Comparisons with optimistic routing, pessimistic routing and time message channel routing are given. Copyright © 2014 John Wiley & Sons, Ltd.     

Stochasticity of freeway operational capacity and chance-constrained ramp metering

The notion of capacity is essential to the planning, design, and operations of freeway systems. However, in the practice freeway capacity is commonly referred as a theoretical/design value without consideration of operational characteristics of freeways. This is evident from the Highway Capacity Manual (HCM) 2000 in that no influence from downstream traffic is considered in the definition of freeway capacity. In contrast to this definition, in this paper, we consider the impact of downstream traffic and define freeway operational capacity as the maximum hourly rate at which vehicles can be expected to traverse a point or a uniform section of a roadway under prevailing traffic flow conditions. Therefore freeway operational capacity is not a single value with theoretical notion. Rather, it changes under different traffic flow conditions. Specifically, this concept addresses the capacity loss during congested traffic conditions. We further study the stochasticity of freeway operational capacity by examining loop detector data at three specifically selected detector stations in the Twin Cities’ area. It is found that values of freeway operational capacity under different traffic flow conditions generally fit normal distributions. In recognition of the stochastic nature of freeway capacity, we propose a new chance-constrained ramp metering strategy, in which, constant capacity value is replaced by a probabilistic one that changes dynamically depending on real-time traffic conditions and acceptable probability of risk determined by traffic engineers. We then improve the Minnesota ZONE metering algorithm by applying the stochastic chance constraints and test the improved algorithm through microscopic traffic simulation. The evaluation results demonstrate varying degrees of system improvement depending on the acceptable level of risk defined.     

森林公园慢行交通系统规划分析

文章基于森林公园慢行交通系统的构成及特点,从宏观、中观、微观三个层面分析了森林公园慢行交通系统的研究框架,并以鹿寨香桥岩森林公园为例,探讨了森林公园慢行交通系统的规划与构建内容。     

A method for measuring accurate traffic density by aerial photography

Traffic density can be accurately measured by counting the number of vehicles within 1 km; however, it is often calculated between macroscopic traffic parameters using the fundamental equation because of difficulty of observing traffic density directly in the field. Measuring density in this way may be inaccurate and may bias the analysis because the relationship between these traffic parameters can vary across the study sites. The purpose of this study is to find a method for measuring traffic density from aerial photography that is easy and accurate, and for this purpose, we investigated whether the measuring length (i.e., the length of a section of roadway from which observations of traffic are simultaneously collected) can be shorter than 1 km and yet retain the same measured traffic density. We divided an aerial photograph into several 20‐m unit sections, counted the number of vehicles manually, and examined measured traffic density according to central limit theory. According to the results of this study, with the number of 20‐m unit sections for observing traffic density at 15 (the measuring length is 300 m), the measured traffic density was almost the same as the density of a representative section of 1 km. Copyright © 2014 John Wiley & Sons, Ltd.     

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters’ responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers’ behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief–desire–intention agent architecture.     

Single track line capacity model

The objective of the research described in this paper was to develop a model for computation of an ultimate capacity of a single track line and to provide a sensitivity analysis of this capacity to the parameters which influence it. The model is based in a concept of mathematical expectation of capacity and can be applied under saturation conditions i.e. a constant demand for service. It can serve for planning purposes, computation of single track line capacity on the base of which estimations are possible concerning a single track line performance under given conditions, as well as commercial time‐tables planning, decisions about a partial or complete construction of the second parallel track along the line in service, intermediate stations locations planning and the necessary facilities along the line under construction.

In the sensitivity analysis, the model allows a change of parameters upon which the capacity depends. These are: the length of the line segment which is considered to be bottleneck for calculation of capacity, traffic distributions per directions, train mix, train velocities and train spacing rules applied by the dispatching service when regulating the traffic on a line.     

Spatial structure and mobility

The aim of this paper is to contribute to a clearer understanding of the extent to which the spatial structure and planning of the residential environment can explain mobility, in general, and the choice of mode of transport, in particular, and what spatial planning and traffic management aspects play a significant role in this. The research showed that certain aspects of the planned environment do indeed have a clear impact on mobility. These effects are particularly apparent in trips made for shopping and social or recreational purposes. It is mainly personal characteristics that largely or almost entirely determine commuter traffic. An integral approach to the planning of residential areas is required to achieve any great changes in mobility. Only then may we expect spatial planning to have any significant impact on car use.     

Path flow estimator for planning applications in small communities

This paper presents an alternative planning framework to model and forecast network traffic for planning applications in small communities, where limited resources debilitate the development and applications of the conventional four-step travel demand forecasting model. The core idea is to use the Path Flow Estimator (PFE) to estimate current and forecast future traffic demand while taking into account of various field and planning data as modeling constraints. Specifically, two versions of PFE are developed: a base year PFE for estimating the current network traffic conditions using field data and planning data, if available, and a future year PFE for predicting future network traffic conditions using forecast planning data and the estimated base year origin–destination trip table as constraints. In the absence of travel survey data, the proposed method uses similar data (traffic counts and land use data) as a four-step model for model development and calibration. Since the Institute of Transportation Engineers (ITE) trip generation rates and Highway Capacity Manual (HCM) are both utilized in the modeling process, the analysis scope and results are consistent with those of common traffic impact studies and other short-range, localized transportation improvement programs. Solution algorithms are also developed to solve the two PFE models and integrated into a GIS-based software called Visual PFE. For proof of concept, two case studies in northern California are performed to demonstrate how the tool can be used in practice. The first case study is a small community of St. Helena, where the city’s planning department has neither an existing travel demand model nor the budget for developing a full four-step model. The second case study is in the city of Eureka, where there is a four-step model developed for the Humboldt County that can be used for comparison. The results show that the proposed approach is applicable for small communities with limited resources.     

Roadway determinants of bicyclist exposure to volatile organic compounds and carbon monoxide

Few studies have quantified relationships between bicyclist exposure to air pollution and roadway and traffic variables. As a result, transportation professionals are unable to easily estimate exposure differences among bicycle routes for network planning, design, and analysis. This paper estimates the effects of roadway and travel characteristics on bicyclist exposure concentrations, controlling for meteorology and background conditions. Concentrations of volatile organic compounds (VOC) and carbon monoxide (CO) are modeled using high-resolution data collected on-road. Results indicate that average daily traffic (ADT) provides a parsimonious way to characterize the impact of roadway characteristics on bicyclists’ exposure. VOC and CO exposure increase by approximately 2% per 1000 ADT, robust to different regression model specifications. Exposure on off-street facilities is higher than at a park, but lower than on-street riding – with the exception of a path through an industrial corridor with significantly higher exposure. VOC exposure is 20% higher near intersections. Traffic, roadway, and travel variables have more explanatory power in the VOC models than the CO model. The quantifications in this paper enable calculation of expected exposure differences among travel paths for planning and routing applications. The findings also have policy and design implications to reduce bicyclists’ exposure. Separation between bicyclists and motor vehicle traffic is a necessary but not sufficient condition to reduce exposure concentrations; off-street paths are not always low-exposure facilities.