A lightweight, modular robotic vehicle for the sustainable intensification of agriculture

This paper describes a lightweight, modular and energy efficient robotic vehicle platform designed for broadacre agriculture - the Small Robotic Farm Vehicle (SRFV). The current trend in farming is towards increasingly large machines that optimise the individual farmer’s productivity. Instead, the SRFV is designed to promote the sustainable intensification of agriculture by allowing farmers to concentrate on more important farm management tasks. The robot has been designed with a user-centred approach which focuses the outcomes of the project on the needs of the key project stakeholders. In this way user and environmental considerations for broadacre farming have informed the vehicle platform configuration, locomotion, power requirements and chassis construction. The resultant design is a lightweight, modular four-wheeled differential steer vehicle incorporating custom twin in-hub electric drives with emergency brakes. The vehicle is designed for a balance between low soil impact, stability, energy efficiency and traction. The paper includes modelling of the robot’s dynamics during an emergency brake in order to determine the potential for tipping. The vehicle is powered by a selection of energy sources including rechargeable lithium batteries and petrol-electric generators.

Autonomous vehicle path planning for persistence monitoring under uncertainty using Gaussian based Markov decision process

One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.

Young drivers' perceptions of road safety messages and a high performance vehicle advertisement : a qualitative exploration

While road safety messages that focus on physical threats have shown some effectiveness, messages that include social threats and gains/rewards may be an alternative approach to encourage safer driving behaviours. In addition to message frame and type, motor vehicle advertising exposure may also influence the persuasiveness of road safety messages. Using qualitative methods this preliminary study explored young drivers’ (N = 17, 11 males) perceptions of the persuasiveness of four anti-speeding messages and a fictional high performance vehicle advertisement. The majority of males perceived the social loss/gain-framed messages to be more persuasive (sense of responsibility and personal relevance themes), whereas females tended to perceive the physical loss/ gain-frame messages (social esteem theme) to be more persuasive. Males appeared to be, while females appeared not to be, persuaded by the vehicle advertisement. The findings suggest that a range of road safety messages may be required to reach and influence young drivers.

Autonomous hot metal carrier: Navigation and manipulation with a 20 tonne industrial vehicle

This paper reports work on the automation of a hot metal carrier, which is a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demonstrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. Finally, an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network are described.

Obstacle detection for a mining vehicle using a 2D laser

This paper discusses a number of key issues for the development of robust obstacle detection systems for autonomous mining vehicles. Strategies for obstacle detection are described and an overview of the state-of-the-art in obstacle detection for outdoor autonomous vehicles using lasers is presented, with their applicability to the mining environment noted. The development of an obstacle detection system for a mining vehicle is then detailed. This system uses a 2D laser scanner as the prime sensor and combines dead-reckoning data with laser data to create local terrain maps. The slope of the terrain maps is then used to detect potential obstacles.

Experiments and experiences with dependability for a large autonomous industrial vehicle

This paper describes the experiences gained performing multiple experiments while developing a large autonomous industrial vehicle. Hot Metal Carriers (HMCs) are large forklift-type vehicles used in the light metals industry to move molten or hot metal around a smelter. Autonomous vehicles of this type must be dependable as they are large and potentially hazardous to infrastructure and people. This paper will talk about four aspects of dependability, that of safety, reliability, availability and security and how they have been addressed on our experimental autonomous HMC.

Modeling and control of a robotic power line inspection vehicle

Power line inspection is a vital function for electricity supply companies but it involves labor-intensive and expensive procedures which are tedious and error-prone for humans to perform. A possible solution is to use an unmanned aerial vehicle (UAV) equipped with video surveillance equipment to perform the inspection. This paper considers how a small, electrically driven rotorcraft conceived for this application could be controlled by visually tracking the overhead supply lines. A dynamic model for a ducted-fan rotorcraft is presented and used to control the action of an Air Vehicle Simulator (AVS), consisting of a cable-array robot. Results show how visual data can be used to determine, and hence regulate in closed loop, the simulated vehicle’s position relative to the overhead lines.

Heavy vehicle crash characteristics in Oman, 2009-2011

In recent years, Oman has seen a shift in the burden of diseases towards road accidents. The main objective of this paper, therefore, is to describe key characteristics of heavy vehicle crashes in Oman and identify the key driving behaviours that influence fatality risks. Crash data from January 2009 to December 2011 were examined and it was found that of the 22,543 traffic accidents that occurred within this timeframe, 3,114 involved heavy vehicles. While the majority of these crashes were attributed to driver behaviours, a small proportion was attributed to other factors. The results of the study indicate that there is a need for a more thorough crash investigation process in Oman. Future research should explore the reporting processes used by the Royal Oman Police, cultural influences on heavy vehicle operations in Oman, and improvements to the current licensing system.

Shortest path and vehicle trajectory aided map-matching for low frequency GPS data

Map-matching algorithms that utilise road segment connectivity along with other data (i.e.position, speed and heading) in the process of map-matching are normally suitable for high frequency (1 Hz or higher) positioning data from GPS. While applying such map-matching algorithms to low frequency data (such as data from a fleet of private cars, buses or light duty vehicles or smartphones), the performance of these algorithms reduces to in the region of 70% in terms of correct link identification, especially in urban and sub-urban road networks. This level of performance may be insufficient for some real-time Intelligent Transport System (ITS) applications and services such as estimating link travel time and speed from low frequency GPS data. Therefore, this paper develops a new weight-based shortest path and vehicle trajectory aided map-matching (stMM) algorithm that enhances the map-matching of low frequency positioning data on a road map. The well-known A* search algorithm is employed to derive the shortest path between two points while taking into account both link connectivity and turn restrictions at junctions. In the developed stMM algorithm, two additional weights related to the shortest path and vehicle trajectory are considered: one shortest path-based weight is related to the distance along the shortest path and the distance along the vehicle trajectory, while the other is associated with the heading difference of the vehicle trajectory. The developed stMM algorithm is tested using a series of real-world datasets of varying frequencies (i.e. 1 s, 5 s, 30 s, 60 s sampling intervals). A high-accuracy integrated navigation system (a high-grade inertial navigation system and a carrier-phase GPS receiver) is used to measure the accuracy of the developed algorithm. The results suggest that the algorithm identifies 98.9% of the links correctly for every 30 s GPS data. Omitting the information from the shortest path and vehicle trajectory, the accuracy of the algorithm reduces to about 73% in terms of correct link identification. The algorithm can process on average 50 positioning fixes per second making it suitable for real-time ITS applications and services.

Driving simulator evaluation of the failure of an audio in-vehicle warning for railway level crossings

It is impracticable to upgrade the 18,900 Australian passive crossings as such crossings are often located in remote areas, where power is lacking and with low road and rail traffic. The rail industry is interested in developing innovative in-vehicle technology interventions to warn motorists of approaching trains directly in their vehicles. The objective of this study was therefore to evaluate the benefits of the introduction of such technology. We evaluated the changes in driver performance once the technology is enabled and functioning correctly, as well as the effects of an unsafe failure of the technology? We conducted a driving simulator study where participants (N=15) were familiarised with an in-vehicle audio warning for an extended period. After being familiarised with the system, the technology started failing, and we tested the reaction of drivers with a train approaching. This study has shown that with the traditional passive crossings with RX2 signage, the majority of drivers complied (70%) and looked for trains on both sides of the rail track. With the introduction of the in-vehicle audio message, drivers did not approach crossings faster, did not reduce their safety margins and did not reduce their gaze towards the rail tracks. However participants’ compliance at the stop sign decreased by 16.5% with the technology installed in the vehicle. The effect of the failure of the in-vehicle audio warning technology showed that most participants did not experience difficulties in detecting the approaching train even though they did not receive any warning message. This showed that participants were still actively looking for trains with the system in their vehicle. However, two participants did not stop and one decided to beat the train when they did not receive the audio message, suggesting potential human factors issues to be considered with such technology.

The expected and unexpected consequences of implementing energy efficient vehicle incentives

Completed as part of a Joint PhD program between Queensland University of Technology and the Royal Institute of Technology in Stockholm, Sweden, this thesis examines the effects of different government incentive policies on the demand, usage and pricing of energy efficient vehicles. This study outlines recommendations for policy makers aiming to increase the uptake of energy efficient vehicles. The study finds that whilst many government incentives have been successful in encouraging the uptake of energy efficient vehicles, policy makers need to both recognise and attempt to minimise the potential unintended consequences of such initiatives.

Design of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture

This thesis presents the design process and the prototyping of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture. Achieved by the joint operation of multiple autonomous vehicles to improve energy consumption, reduce labour, and increase efficiency in the application of inputs for the management of crops. The Small Robotic Farm Vehicle (SRFV) is a lightweight and energy efficient robotic vehicle with a configurable, modular design. It is capable of undertaking a range of agricultural tasks, including fertilising and weed management through mechanical intervention and precision spraying, whilst being more than an order of magnitude lower in weight than existing broadacre agricultural equipment.

General motor vehicle drivers' knowledge and practices regarding drink driving in Yinchuan and Guangzhou, China

Objective: Drink driving contributes to significant levels of injury and economic loss in China but is not well researched. This study examined knowledge, drink-driving practices, and alcohol misuse problems among general drivers in Yinchuan. The objectives were to gain a better understanding of drink driving in Yinchuan, identify areas that need to be addressed, and compare the results with a similar study in Guangzhou. Methods: This was a cross-sectional study with a survey designed to collect information on participants’ demographic characteristics and their knowledge and practices in relation to drinking and driving. The survey was composed of questions on knowledge and practices in relation to drink driving and was administered to a convenience sample of 406 drivers. Alcohol misuse problems were assessed by using the Alcohol Use Disorders Identification Test (AUDIT). Results: Males accounted for the main proportion of drivers sampled from the general population (“general drivers”). A majority of general drivers in both cities knew that drunk driving had become a criminal offense in 2011; however, knowledge of 2 legal blood alcohol concentration (BAC) limits was quite low. Fewer drivers in Yinchuan (22.6%) than in Guangzhou (27.9) reported having been stopped by police conducting breath alcohol testing at least once in the last 12 months. The mean AUDIT score in Yinchuan (M = 8.2) was higher than that in Guangzhou (M = 7.4), and the proportion of Yinchuan drivers with medium or higher alcohol misuse problems (31.2%) was correspondingly higher than in Guangzhou (23.1%). In Yinchuan, males had a significantly higher AUDIT score than females (t = 3.454, P < .001), similar to Guangzhou. Multiple regression analyses were conducted on potential predictors of the AUDIT score (age, gender, monthly income, education level, years licensed, and age started drinking). There were significant individual contributions of gender (beta = 0.173, P = .09) and age at which drinking started (beta = 0.141, P = .033), but the overall model for Yinchuan was not significant, unlike Guangzhou. Conclusions: The results show that there are shortfalls in knowledge of the legislation and how to comply with it and deficiencies in police enforcement. In addition, there was evidence of drink driving and drink riding at high levels in both cities. Recommendations are made to address these issues.

Predicting the speed of a Wave Glider autonomous surface vehicle from wave model data

A key component of robotic path planning is ensuring that one can reliably navigate a vehicle to a desired location. In addition, when the features of interest are dynamic and move with oceanic currents, vehicle speed plays an important role in the planning exercise to ensure that vehicles are in the right place at the right time. Aquatic robot design is moving towards utilizing the environment for propulsion rather than traditional motors and propellers. These new vehicles are able to realize significantly increased endurance, however the mission planning problem, in turn, becomes more difficult as the vehicle velocity is not directly controllable. In this paper, we examine Gaussian process models applied to existing wave model data to predict the behavior, i.e., velocity, of a Wave Glider Autonomous Surface Vehicle. Using training data from an on-board sensor and forecasting with the WAVEWATCH III model, our probabilistic regression models created an effective method for forecasting WG velocity.

Systematic literature review of incidence rates of low-speed vehicle run-over incidents in children

Aim: To systematically review the literature investigating the incidence of fatal and or nonfatal low-speed vehicle run-over (LSVRO) incidents in children aged 0–15 years. Methods: The following databases were searched using specific search terms, from their date of conception up to June 2011: Cochrane Library, Medline, CINAHL, Embase, AMI, Sociological Abstracts, ERIC, PsycArticles, PsycInfo, Urban Studies and Planning; Australian Criminology Database; Dissertations and Thesis; Academic Research Library; Social Services Abstracts; Family and Society; Scopus; and Web of Science. A total of 128 articles were identified in the databases (33 found by hand searching). The title and abstract of these were read, and 102 were removed because they were not primary research articles relating to LSVRO-type injuries. Twenty-six articles were assessed against the inclusion (reporting population level incidence rates) and exclusion criteria, 19 of which were excluded, leaving a total of five articles for inclusion in the review. Findings: Five studies were identified that met the inclusion criteria. The incidence rate in nonfatal LSVRO events varied in the range of 7.09 to 14.79 per 100,000 and from 0.63 to 3.2 per 100,000 in fatal events. Discussion: Using International Classification of Diseases codes for classifying fatal or nonfatal LSVRO incidents is problematic as there is no specific code for LSVRO. The current body of research is void of a comprehensive secular population data analysis. Only with an improved spectrum of incidence rates will appropriate evaluation of this problem be possible, and this will inform nursing prevention interventions. The effect of LSVRO incidents is clearly understudied. More research is required to address incidence rates in relation to culture, environment, risk factors, car design, and injury characteristics. Conclusions: Thevlack of nursing research or policy around this area of injury, most often to children, indicates a field of inquiry and policy development that needs attention.