Remote measurement of diesel locomotive emission factors and particle size distributions

A technique for analysing exhaust emission plumes from unmodified locomotives under real world conditions is described and applied to the task of characterizing plumes from railway trains servicing an Australian shipping port. The method utilizes the simultaneous measurement, downwind of the railway line, of the following pollutants; particle number, PM2.5 mass fraction, SO2, NOx and CO2, with the last of these being used as an indicator of fuel combustion. Emission factors are then derived, in terms of number of particles and mass of pollutant emitted per unit mass of fuel consumed. Particle number size distributions are also presented. The practical advantages of the method are discussed including the capacity to routinely collect emission factor data for passing trains and to thereby build up a comprehensive real world database for a wide range of pollutants. Samples from 56 train movements were collected, analyzed and presented. The quantitative results for emission factors are: EF(N)=(1.7±1)×1016 kg-1, EF(PM2.5)= (1.1±0.5) g·kg-1, EF(NOx)= (28±14) g·kg-1, and EF(SO2 )= (1.4±0.4) g·kg-1. The findings are compared with comparable previously published work. Statistically significant (p<α, α=0.05) correlations within the group of locomotives sampled were found between the emission factors for particle number and both SO2 and NOx.

On-road driving studies to understand why drivers behave as they do at regional rail level crossings

Improving safety at rail level crossings is an important part of both road and rail safety strategies. While low in number, crashes between vehicles and trains at level crossings are catastrophic events typically involving multiple fatalities and serious injuries. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles with eye and head tracking, provide researchers with the opportunity to further understand driver behaviour at such crossings in ways not previously possible. This paper describes a study conducted to further understand the factors that shape driver behaviour at rail level crossings using instrumented vehicles. Twenty-two participants drove an On-Road Test Vehicle (ORTeV) on a predefined route in regional Victoria with a mix of both active (flashing lights with/without boom barriers) and passively controlled (stop, give way) crossings. Data collected included driving performance data, head checks, and interview data to capture driver strategies. The data from an integrated suite of methods demonstrated clearly how behaviour differs at active and passive level crossings, particularly for inexperienced drivers. For example, the head check data clearly show the reliance and expectancies of inexperienced drivers for active warnings even when approaching passively controlled crossings. These studies provide very novel and unique insights into how level crossing design and warnings shape driver behaviour.

Understanding pedestrian behaviour at railway level crossings : is there a need for more research?

Aim Collisions between trains and pedestrians are the most likely to result in severe injuries and fatalities when compared to other types of rail crossing accidents. Currently, there is a growing emphasis towards developing effective interventions designed to reduce the prevalence of train–pedestrian collisions. This paper reviews what is currently known regarding the personal and environmental factors that contribute to train–pedestrian collisions, particularly among high-risk groups. Method Studies that reported on the prevalence and characteristics of pedestrian accidents at railway crossings up until June 2012 were searched in electronic databases. Results Males, school children and older pedestrians (and those with disabilities) are disproportionately represented in fatality databases. However, a main theme to emerge is that little is known about the origins of train–pedestrian collisions (especially compared to train–vehicle collisions). In particular, whether collisions result from engaging in deliberate violations versus making decisional errors. This subsequently limits the corresponding development of effective and targeted interventions for high-risk groups as well as crossing locations. Finally, it remains unclear what combination of surveillance and deterrence-based and education-focused campaigns are required to produce lasting reductions in train–pedestrian fatality rates. This paper provides direction for future research into the personal and environmental origins of collisions as well as the development of interventions that aim to attract pedestrians’ attention and ensure crossing rules are respected.

A large scale quantitative study of pedestrian railway level crossing behaviour : deliberate violations, errors and deterrence

Every year a number of pedestrians are struck by trains resulting in death and serious injury. While much research has been conducted on train-vehicle collisions, very little is currently known about the aetiology of train-pedestrian collisions. To date, scant research has been undertaken to investigate the demographics of rule breakers, the frequency of deliberate violation versus error making and the influence of the classic deterrence approach on subsequent behaviours. Aim This study aimed to to identify pedestrians’ self-reported reasons for engaging in violations at crossing, the frequency and nature of rule breaking and whether the threat of sanctions influence such events. Method A questionnaire was administered to 511 participants of all ages. Results Analysis revealed that pedestrians (particularly younger groups) were more likely to commit deliberate violations rather than make crossing errors e.g., mistakes. The most frequent reasons given for deliberate violations were participants were running late and did not want to miss their train or participants believed that the gate was taking too long to open so may be malfunctioning. In regards to classical deterrence, an examination of the perceived threat of being apprehended and fined for a crossing violation revealed participants reported the highest mean scores for swiftness of punishment, which suggests they were generally aware that they would receive an “on the spot” fine. However, the overall mean scores for certainty and severity of sanctions (for violating the rules) indicate that the participants did not perceive the certainty and severity of sanctions as very high. This paper will further discuss the research findings in regards to the development of interventions designed to improve pedestrian crossing safety.

Study of a geo-multicast framework for efficient message dissemination at unmanned level crossings

Collisions among trains and cars at road/rail level crossings (LXs) can have severe consequences such as high level of fatalities, injuries and significant financial losses. As communication and positioning technologies have significantly advanced, implementing vehicular ad hoc networks (VANETs) in the vicinity of unmanned LXs, generally LXs without barriers, is seen as an efficient and effective approach to mitigate or even eliminate collisions without imposing huge infrastructure costs. VANETs necessitate unique communication strategies, in which routing protocols take a prominent part in their scalability and overall performance, through finding optimised routes quickly and with low bandwidth overheads. This article studies a novel geo-multicast framework that incorporates a set of models for communication, message flow and geo-determination of endangered vehicles with a reliable receiver-based geo-multicast protocol to support cooperative level crossings (CLXs), which provide collision warnings to the endangered motorists facing road/rail LXs without barriers. This framework is designed and studied as part of a $5.5 m Government and industry funded project, entitled 'Intelligent-Transport-Systems to improve safety at road/rail crossings'. Combined simulation and experimental studies of the proposed geo-multicast framework have demonstrated promising outcomes as cooperative awareness messages provide actionable critical information to endangered drivers who are identified by CLXs.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Video analytics for the detection of near-miss incidents on approach to railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand causal factors that contribute to these accidents, the Cooperative Research Centre for Rail Innovation is running a project entitled Baseline Level Crossing Video. The project aims to improve the recording of level crossing safety data by developing an intelligent system capable of detecting near-miss incidents and capturing quantitative data around these incidents. To detect near-miss events at railway level crossings a video analytics module is being developed to analyse video footage obtained from forward-facing cameras installed on trains. This paper presents a vision base approach for the detection of these near-miss events. The video analytics module is comprised of object detectors and a rail detection algorithm, allowing the distance between a detected object and the rail to be determined. An existing publicly available Histograms of Oriented Gradients (HOG) based object detector algorithm is used to detect various types of vehicles in each video frame. As vehicles are usually seen from a sideway view from the cabin’s perspective, the results of the vehicle detector are verified using an algorithm that can detect the wheels of each detected vehicle. Rail detection is facilitated using a projective transformation of the video, such that the forward-facing view becomes a bird’s eye view. Line Segment Detector is employed as the feature extractor and a sliding window approach is developed to track a pair of rails. Localisation of the vehicles is done by projecting the results of the vehicle and rail detectors on the ground plane allowing the distance between the vehicle and rail to be calculated. The resultant vehicle positions and distance are logged to a database for further analysis. We present preliminary results regarding the performance of a prototype video analytics module on a data set of videos containing more than 30 different railway level crossings. The video data is captured from a journey of a train that has passed through these level crossings.

In-vehicle railway level crossing warning systems : can intelligent transport systems deliver?

Intelligent Transport System (ITS) technology is seen as a cost-effective way to increase the conspicuity of approaching trains and the effectiveness of train warnings at level crossings by providing an in-vehicle warning of an approaching train. The technology is often seen as a potential low-cost alternative to upgrading passive level crossings with traditional active warning systems (flashing lights and boom barriers). ITS platforms provide sensor, localization and dedicated short-range communication (DSRC) technologies to support cooperative applications such as collision avoidance for road vehicles. In recent years, in-vehicle warning systems based on ITS technology have been trialed at numerous locations around Australia, at level crossing sites with active and passive controls. While significant research has been conducted on the benefits of the technology in nominal operating modes, little research has focused on the effects of the failure modes, the human factors implications of unreliable warnings and the technology adoption process from the railway industry’s perspective. Many ITS technology suppliers originate from the road industry and often have limited awareness of the safety assurance requirements, operational requirements and legal obligations of railway operators. This paper aims to raise awareness of these issues and start a discussion on how such technology could be adopted. This paper will describe several ITS implementation cenarios and discuss failure modes, human factors considerations and the impact these scenarios are likely to have in terms of safety, railway safety assurance requirements and the practicability of meeting these requirements. The paper will identify the key obstacles impeding the adoption of ITS systems for the different implementation scenarios and a possible path forward towards the adoption of ITS technology.

Evaluation of emerging intelligent transport systems to improve safety on level crossings : an overview

Safety at railway level crossings (RLX) is one part of a wider picture of safety within the whole transport system. Governments, the rail industry and road organisations have used a variety of countermeasures for many years to improve RLX safety. New types of interventions are required in order to reduce the number of crashes and associated social costs at railway crossings. This paper presents the results of a large research program which aimed to assess the effectiveness of emerging Intelligent Transport Systems (ITS) interventions, both on-road and in-vehicle based, to improve the safety of car drivers at RLXs in Australia. The three most promising technologies selected from the literature review and focus groups were tested in an advanced driving simulator to provide a detailed assessment of their effects on driver behaviour. The three interventions were: (i) in-vehicle visual warning using a GPS/smartphone navigation-like system, (ii) in-vehicle audio warning and; (iii) on-road intervention known as valet system (warning lights on the road surface activated as a train approaches). The effects of these technologies on 57 participants were assessed in a systematic approach focusing on the safety of the intervention, effects on the road traffic around the crossings and driver’s acceptance of the technology. Given that the ITS interventions were likely to provide a benefit by improving the driver’s awareness of the crossing status in low visibility conditions, such conditions were investigated through curves in the track before arriving at the crossing. ITS interventions were also expected to improve driver behaviour at crossings with high traffic (blocking back issue), which were also investigated at active crossings. The key findings are: (i) interventions at passive crossings are likely to provide safety benefits; (ii) the benefits of ITS interventions on driver behaviour at active crossings are limited; (iii) the trialled ITS interventions did not show any issues in terms of driver distraction, driver acceptance or traffic delays; (iv) these interventions are easy to use, do not increase driver workload substantially; (v) participants’ intention to use the technology is high and; (vi) participants saw most value in succinct messages about approaching trains as opposed to knowing the RLX locations or the imminence of a collision with a train.

Effects of driver familiarity and prolonged or intermittent right-side failure on level crossing safety

This paper investigates the adverse effects of familiarity and human factors issues associated with the reliability of low-cost warning devices at level crossings. The driving simulator study featured a repetitive, low workload, monotonous driving task in which there were no failures of the level crossing (control) or prolonged or intermittent right-side failures (where the device reverts to a safe failure mode). The results of the experiment provided mixed support for the familiarity hypothesis. Four of the 23 participants collided with the train when it first appeared on trial 10 but safety margins increased from the first train to the next presentation of a train (trial 12). Contrary to expectations, the safety margins decreased with repeated right-side failure only for the intermittent condition. The limited head movement data showed that participants in the prolonged failure condition were more likely to turn their head to check for trains in the right-side failure trials than in earlier trials where there was no signal and no train. Few control participants turned their head to check for trains when no signal was presented. This research highlights the need to consider repetitive tasks and workload in experimental design and accident investigation at railway level crossings.

Near-miss event detection at railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand the causal factors of these accidents, a video analytics application is being developed to automatically detect near-miss incidents using forward facing videos from trains. As near-miss events occur more frequently than collisions, by detecting these occurrences there will be more safety data available for analysis. The application that is being developed will improve the objectivity of near-miss reporting by providing quantitative data about the position of vehicles at level crossings through the automatic analysis of video footage. In this paper we present a novel method for detecting near-miss occurrences at railway level crossings from video data of trains. Our system detects and localizes vehicles at railway level crossings. It also detects the position of railways to calculate the distance of the detected vehicles to the railway centerline. The system logs the information about the position of the vehicles and railway centerline into a database for further analysis by the safety data recording and analysis system, to determine whether or not the event is a near-miss. We present preliminary results of our system on a dataset of videos taken from a train that passed through 14 railway level crossings. We demonstrate the robustness of our system by showing the results of our system on day and night videos.

Multiscale features and information extraction of online strain for long-span bridges

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

A sensitivity analysis of train speed and its effect on railway capacity

Increasing train speeds is conceptually a simple and straight forward method to expand railway capacity, for example in comparison to other more extensive and elaborate alternatives. In this article an analytical capacity model has been investigated as a means of performing a sensitivity analysis of train speeds. The results of this sensitivity analysis can help improve the operation of this railway system and to help it cope with additional demands in the future. To test our approach a case study of the Rah Ahane Iran (RAI) national railway network has been selected. The absolute capacity levels for this railway network have been determined and the analysis shows that increasing trains speeds may not be entirely cost effective in all circumstances.

Investigations of ultrafine particles emitted by ships and other transport modes in the port of Brisbane

This research measured particle and gaseous emissions from ships and trains operating within the Port of Brisbane, and explored their influence on ambient air composition at a downwind suburban measurement site. The ship and train emission factor investigations resulted in the development of novel measurement techniques which permit the quantification of particle and gaseous emission factors using samples collected from post-emission exhaust plumes. The urban influence investigation phase of the project produced a new approach to identifying influences from ship emissions.

Isolation of microvascular endothelial cells from cadaveric corneal limbus

Limbal microvascular endothelial cells (L-MVEC) contribute to formation of the corneal-limbal stem cell niche and to neovascularization of diseased and injuries corneas. Nevertheless, despite these important roles in corneal health and disease, few attempts have been made to isolate L-MVEC with the view to studying their biology in vitro. We therefore explored the feasibility of generating primary cultures of L-MVEC from cadaveric human tissue. We commenced our study by evaluating growth conditions (MesenCult-XF system) that have been previously found to be associated with expression of the endothelial cell surface marker thrombomodulin/CD141, in crude cultures established from collagenase-digests of limbal stroma. The potential presence of L-MVEC in these cultures was examined by flow cytometry using a more specific marker for vascular endothelial cells, CD31/PECAM-1. These studies demonstrated that the presence of CD141 in crude cultures established using the MesenCult-XF system is unrelated to L-MVEC. Thus we subsequently explored the use of magnetic assisted cell sorting (MACS) for CD31 as a tool for generating cultures of L-MVEC, in conjunction with more traditional endothelial cell growth conditions. These conditions consisted of gelatin-coated tissue culture plastic and MCDB-131 medium supplemented with fetal bovine serum (10% v/v), D-glucose (10 mg/mL), epidermal growth factor (10 ng/mL), heparin (50 μg/mL), hydrocortisone (1 μg/mL) and basic fibroblast growth factor (10 ng/mL). Our studies revealed that use of endothelial growth conditions are insufficient to generate significant numbers of L-MVEC in primary cultures established from cadaveric corneal stroma. Nevertheless, through use of positive-MACS selection for CD31 we were able to routinely observe L-MVEC in cultures derived from collagenase-digests of limbal stroma. The presence of L-MVEC in these cultures was confirmed by immunostaining for von Willebrand factor (vWF) and by ingestion of acetylated low-density lipoprotein. Moreover, the vWF+ cells formed aligned cell-to-cell ‘trains’ when grown on Geltrex™. The purity of L-MVEC cultures was found to be unrelated to tissue donor age (32 to 80 years) or duration in eye bank corneal preservation medium prior to use (3 to 10 days in Optisol) (using multiple regression test). Optimal purity of L-MVEC cultures was achieved through use of two rounds of positive-MACS selection for CD31 (mean ± s.e.m, 65.0 ± 20.8%; p<0.05). We propose that human L-MVEC cultures generated through these techniques, in conjunction with other cell types, will provide a useful tool for exploring the mechanisms of blood vessel cell growth in vitro.