Advances in Model-Based Traffic Vision

Model based vision allows use of prior knowledge of the shape and appearance of specific objects to be used in the interpretation of a visual scene; it provides a powerful and natural way to enforce the view consistency constraint. A model based vision system has been developed within ESPRIT VIEWS: P2152 which is able to classify and track moving objects (cars and other vehicles) in complex, cluttered traffic scenes. The fundamental basis of the method has been previously reported. This paper presents recent developments which have extended the scope of the system to include (i) multiple cameras, (ii) variable camera geometry, and (iii) articulated objects. All three enhancements have easily been accommodated within the original model-based approach

Model-based vehicle detection and classification using orthographic approximations

This paper reports the current state of work to simplify our previous model-based methods for visual tracking of vehicles for use in a real-time system intended to provide continuous monitoring and classification of traffic from a fixed camera on a busy multi-lane motorway. The main constraints of the system design were: (i) all low level processing to be carried out by low-cost auxiliary hardware, (ii) all 3-D reasoning to be carried out automatically off-line, at set-up time. The system developed uses three main stages: (i) pose and model hypothesis using 1-D templates, (ii) hypothesis tracking, and (iii) hypothesis verification, using 2-D templates. Stages (i) & (iii) have radically different computing performance and computational costs, and need to be carefully balanced for efficiency. Together, they provide an effective way to locate, track and classify vehicles.

An Integrated Traffic and Pedestrian Model_based Vision System

The paper describes a novel integrated vision system in which two autonomous visual modules are combined to interpret a dynamic scene. The first module employs a 3D model-based scheme to track rigid objects such as vehicles. The second module uses a 2D deformable model to track non-rigid objects such as people. The principal contribution is a novel method for handling occlusion between objects within the context of this hybrid tracking system. The practical aim of the work is to derive a scene description that is sufficiently rich to be used in a range of surveillance tasks. The paper describes each of the modules in outline before detailing the method of integration and the handling of occlusion in particular. Experimental results are presented to illustrate the performance of the system in a dynamic outdoor scene involving cars and people.

The importance of the diurnal and annual cycle of air traffic for contrail radiative forcing

Air traffic condensation trails, or contrails, are believed to have a net atmospheric warming effect(1), although one that is currently small compared to that induced by other sources of human emissions. However, the comparably large growth rate of air traffic requires an improved understanding of the resulting impact of aircraft radiative forcing on climate(2). Contrails have an effect on the Earth's energy balance similar to that of high thin ice clouds(3). Their trapping of outgoing longwave radiation emitted by the Earth and atmosphere (positive radiative forcing) is partly compensated by their reflection of incoming solar radiation (negative radiative forcing). On average, the longwave effect dominates and the net contrail radiative forcing is believed to be positive(1,2,4). Over daily and annual timescales, varying levels of air traffic, meteorological conditions, and solar insolation influence the net forcing effect of contrails. Here we determine the factors most important for contrail climate forcing using a sophisticated radiative transfer model(5,6) for a site in southeast England, located in the entrance to the North Atlantic flight corridor. We find that night-time flights during winter (December to February) are responsible for most of the contrail radiative forcing. Night flights account for only 25 per cent of daily air traffic, but contribute 60 to 80 per cent of the contrail forcing. Further, winter flights account for only 22 per cent of annual air traffic, but contribute half of the annual mean forcing. These results suggest that flight rescheduling could help to minimize the climate impact of aviation.

The impact of traffic emissions on atmospheric ozone and OH: results from QUANTIFY

To estimate the impact of emissions by road, aircraft and ship traffic on ozone and OH in the present-day atmosphere six different atmospheric chemistry models have been used. Based on newly developed global emission inventories for road, ship and aircraft emission data sets each model performed sensitivity simulations reducing the emissions of each transport sector by 5%. The model results indicate that on global annual average lower tropospheric ozone responds most sensitive to ship emissions (50.6%±10.9% of the total traffic induced perturbation), followed by road (36.7%±9.3%) and aircraft exhausts (12.7%±2.9%), respectively. In the northern upper troposphere between 200–300 hPa at 30–60° N the maximum impact from road and ship are 93% and 73% of the maximum effect of aircraft, respectively. The latter is 0.185 ppbv for ozone (for the 5% case) or 3.69 ppbv when scaling to 100%. On the global average the impact of road even dominates in the UTLS-region. The sensitivity of ozone formation per NOx molecule emitted is highest for aircraft exhausts. The local maximum effect of the summed traffic emissions on the ozone column predicted by the models is 0.2 DU and occurs over the northern subtropical Atlantic extending to central Europe. Below 800 hPa both ozone and OH respond most sensitively to ship emissions in the marine lower troposphere over the Atlantic. Based on the 5% perturbation the effect on ozone can exceed 0.6% close to the marine surface (global zonal mean) which is 80% of the total traffic induced ozone perturbation. In the southern hemisphere ship emissions contribute relatively strongly to the total ozone perturbation by 60%–80% throughout the year. Methane lifetime changes against OH are affected strongest by ship emissions up to 0.21 (± 0.05)%, followed by road (0.08 (±0.01)%) and air traffic (0.05 (± 0.02)%). Based on the full scale ozone and methane perturbations positive radiative forcings were calculated for road emissions (7.3±6.2 mWm−2) and for aviation (2.9±2.3 mWm−2). Ship induced methane lifetime changes dominate over the ozone forcing and therefore lead to a net negative forcing (−25.5±13.2 mWm−2).

Cognitive process modelling of controllers in en route air traffic control

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes.

Parameterization of contrails in the UK Met Office Climate Model

Persistent contrails are believed to currently have a relatively small but significant positive radiative forcing on climate. With air travel predicted to continue its rapid growth over the coming years, the contrail warming effect on climate is expected to increase. Nevertheless, there remains a high level of uncertainty in the current estimates of contrail radiative forcing. Contrail formation depends mostly on the aircraft flying in cold and moist enough air masses. Most studies to date have relied on simple parameterizations using averaged meteorological conditions. In this paper we take into account the short‐term variability in background cloudiness by developing an on‐line contrail parameterization for the UK Met Office climate model. With this parameterization, we estimate that for the air traffic of year 2002 the global mean annual linear contrail coverage was approximately 0.11%. Assuming a global mean contrail optical depth of 0.2 or smaller and assuming hexagonal ice crystals, the corresponding contrail radiative forcing was calculated to be less than 10 mW m−2 in all‐sky conditions. We find that the natural cloud masking effect on contrails may be significantly higher than previously believed. This new result is explained by the fact that contrails seem to preferentially form in cloudy conditions, which ameliorates their overall climate impact by approximately 40%.