Integrating driving and traffic simulators for the study of railway level crossing safety interventions: a methodology

Safety at Railway Level Crossings (RLXs) is an important issue within the Australian transport system. Crashes at RLXs involving road vehicles in Australia are estimated to cost $10 million each year. Such crashes are mainly due to human factors; unintentional errors contribute to 46% of all fatal collisions and are far more common than deliberate violations. This suggests that innovative intervention targeting drivers are particularly promising to improve RLX safety. In recent years there has been a rapid development of a variety of affordable technologies which can be used to increase driver’s risk awareness around crossings. To date, no research has evaluated the potential effects of such technologies at RLXs in terms of safety, traffic and acceptance of the technology. Integrating driving and traffic simulations is a safe and affordable approach for evaluating these effects. This methodology will be implemented in a driving simulator, where we recreated realistic driving scenario with typical road environments and realistic traffic. This paper presents a methodology for evaluating comprehensively potential benefits and negative effects of such interventions: this methodology evaluates driver awareness at RLXs , driver distraction and workload when using the technology . Subjective assessment on perceived usefulness and ease of use of the technology is obtained from standard questionnaires. Driving simulation will provide a model of driving behaviour at RLXs which will be used to estimate the effects of such new technology on a road network featuring RLX for different market penetrations using a traffic simulation. This methodology can assist in evaluating future safety interventions at RLXs

Comparison of SimTraffic and VISSIM Microscopic Traffic Simulation Tools in Modeling Roundabouts

Abstract SimTraffic and VISSIM are two microscopic traffic simulation tools that are capable of modeling arterial roads with signalized intersections and roundabouts. This study compares the performance of the two simulation tools in modeling dual lane and triple lane roundabouts under different scenarios such as traffic volume, proportion of left turning movement, and proportion of trucks in the traffic flow. The two simulation tools did not show statistically significant difference in general. However; in the case of high traffic volumes, VISSIM showed higher average delays than those from SimTraffic compared to nearly identical results in the case of low traffic volumes

Evaluating safety at railway level crossings with microsimulation modeling

Safety at railway level crossings (RLXs) is a worldwide issue that increasingly attracts the attention of relevant transport authorities, the rail industry, and the general public. The differences in the operation characteristics of varying types of warning devices, together with differences in crossing geometry, traffic, or train characteristics, leads to different driver behaviors at crossings. The aim of this study was to use traffic microsimulation modeling based on field video recording data to compare the safety performance of varying conventional RLX warning systems. The widely used microsimulation model VISSIM was modified to produce safety-related performance measures, namely, collision likelihood, delay, and queue length. The results showed that RLXs with an active warning system were safer than those with a passive sign by at least 17%. Integration of surrogate measures in conjunction with traffic simulation models determined which safety approach was more efficient for specified traffic and train volumes

Removal of an atherogenic factor from the human diet

Call number: LD2668 .T4 1968 C4875Master of Scienc

Queue Discharge at Freeway On-Ramps Using Coordinated Operation of a Ramp Meter and an Upstream Traffic Signal

Ramp metering is an effective way of maintaining optimum traffic conditions and mitigating congestion on freeways. Several strategies for ramp metering exist in the literature. They are typically based on the freeway traffic parameters as control inputs to the ramp control logic. The ramp signal can be controlled in two ways, i.e., locally controlled (isolated ramp control) and coordinated ramp control. Coordinated ramp control refers to the ramp metering strategies in which several ramp meters connected to the freeway segment are dynamically controlled by considering traffic flows along all ramps. Coordinated ramp metering can play a vital role in freeway congestion mitigation on the ramps as well as normalize the traffic flow over the freeway. In this study, an alternate coordinated metering scheme that uses the state of the upstream traffic signal on arterial as the control input to the ramp meter is proposed. The proposed method aims to prevent long queues on the ramp with limited storage by taking feedback from the upstream traffic signal on the arterial, especially when the ramp has a small storage area for vehicles. Simulation results show a significant reduction in the queue length over the ramp using the proposed scheme. Additionally, the proposed scheme also benefits the arterial traffic. 2020 The Authors. Published by Elsevier B.V.All rights reserved.Scopu

Applications of brain imaging methods in driving behaviour research

Applications of neuroimaging methods have substantially contributed to the scientific understanding of human factors during driving by providing a deeper insight into the neuro-cognitive aspects of driver brain. This has been achieved by conducting simulated (and occasionally, field) driving experiments while collecting driver brain signals of certain types. Here, this sector of studies is comprehensively reviewed at both macro and micro scales. Different themes of neuroimaging driving behaviour research are identified and the findings within each theme are synthesised. The surveyed literature has reported on applications of four major brain imaging methods. These include Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Functional Near-Infrared Spectroscopy (fNIRS) and Magnetoencephalography (MEG), with the first two being the most common methods in this domain. While collecting driver fMRI signal has been particularly instrumental in studying neural correlates of intoxicated driving (e.g. alcohol or cannabis) or distracted driving, the EEG method has been predominantly utilised in relation to the efforts aiming at development of automatic fatigue/drowsiness detection systems, a topic to which the literature on neuro-ergonomics of driving particularly has shown a spike of interest within the last few years. The survey also reveals that topics such as driver brain activity in semi-automated settings or the brain activity of drivers with brain injuries or chronic neurological conditions have by contrast been investigated to a very limited extent. Further, potential topics in relation to driving behaviour are identified that could benefit from the adoption of neuroimaging methods in future studies

The influence of bus service satisfaction on university students' mode choice

The purpose of this study was to determine the relationship between bus service satisfaction and the transport mode of choice among university students in Qatar. The degree of bus service satisfaction was collected directly from questionnaire surveys, in which university students were asked questions in relation to their satisfaction with the bus service they used and their transport mode of choice. These questions were categorized into three factors according to confirmatory factor analysis: service at bus stops, service of busses, and service of drivers. Furthermore, the students were asked which mode of transport they used given the choice between public and private transport. This study presents a structural equation model to determine how much bus service satisfaction affects people's decisions about their transport mode. The results from the analysis showed that three key factors-namely, service at bus stops, service of busses, and service of bus drivers-were strongly correlated to the mode of choice. In particular, the bus stop was strongly associated with ease of use, shade, cleanliness, safety, and crowdedness level, while the bus itself influenced reliability, travel time, and frequency. Complying with traffic laws and the driver's attitude were also important contributors to the level of bus service satisfaction. Ultimately, this study will be beneficial for policy/decision-makers. It will allow them to determine what needs to be accomplished to encourage people to use public transportation.Scopu

Assessment of the taxi service in Doha

This research focuses on passengers' satisfaction of the taxi service in Doha, Qatar. Qatar is a rich developing country where taxis are widely considered as a public transportation service due to the limited use of the existing bus service and the profoundly dominant use of private car by expats and Qatari locals. The main objective of this research is to identify the quality attributes of the current taxi service. A descriptive analysis relating the demographic, accessibility, and trip purposes to taxi users in general in Doha with overall service satisfaction was conducted. A Structural Equation Model was used to assess the taxi service attributes that influence the users' perceived satisfaction. Two models were developed: one was a relationship between the demographic and satisfaction of the users while the other was between the trip time and the satisfaction of the users. The first model supports the premise that income is the greatest attribute in the demographic followed by marital status, age, and occupation. On the other hand, the latter model demonstrated that waiting time is the most contributing variable among the times spent by taxi users followed by walking from work to a station, journey time, and walking from home to a station. 2016 Elsevier Ltd.Scopu

Revealing the hidden features in traffic prediction via entity embedding

Models based on neural networks (NN) have been used widely and successfully in traffic prediction resulting in improved accuracy and efficiency in traffic flow, speed, passenger flow, and delay. Input data include continuous and discrete variables and these impact traffic changes both internally and externally. However, few studies have focused on discrete traffic-related variables in NN-based forecasting models. Inappropriate utilization of discrete variables may cause useful factors to become insignificant and lead to an inefficient forecasting model. In this paper, a NN-based model is used to predict traffic flow of a bike-sharing system in Suzhou, China. The model only uses external and discrete variables like weather, places of interest (POIs), and holiday periods. We applied both entity embedding and one-hot encoding for the data preprocessing of these variables. The results show that (1) Entity embedding can effectively increase the continuity of categorical variables and slightly improve the prediction efficiency for the NN model; and (2) The hidden relationship in variables can be identified through visual analysis, and the trained embedding vectors can also be used in traffic-related tasks.Scopu