Designing a User Interface for Improving the

2010 13th International IEEE Annual Conference on Intelligent Transportation Systems Madeira Island, Portugal, September 19-22, 2010

TC6.5

Designing a User Interface for Improving the Awareness of Mining Vehicle Operators David Orchansky, Stewart Worrall, Andrew Maclean, Eduardo Nebot Australian Centre for Field Robotics University of Sydney NSW 2006, Australia

Abstract— Vehicle accidents are a major concern in open pit mines around the world. Factors such as visibility, fatigue and human error are the cause of many collisions in surface mines. These factors have a direct impact in the awareness of the vehicle operators. Intelligent transportation systems can address these factors and consequently benefit vehicular safety. Technology has the potential to effectively aid the operator in the tasks of driving and positively contribute in the overall safety of the mine. However, the design and implementation of these systems and their user interfaces is not trivial. This paper presents a strategy for improving the driver’s awareness and introduces the design of a user interface that helps the operator in the process of decision making. The system infers the presence of nearby threats and high risk situations and communicates this information to the operator in a combination of audio-visual cues. This paper presents an overview of the mechanism designed to infer high risk situations. Experimental results obtained from real-life operation of the system in several mine sites in Australia and overseas demonstrated how the information provided can enhance the operator’s awareness and contribute to an improvement in vehicle safety.

I. INTRODUCTION Vehicle-related accidents are the primary cause of fatalities and serious accidents in open cut mines across the world. Vehicle-to-vehicle collisions and accidents that result from the inappropriate interaction between drivers and personnel are very frequent. The occurrence of each of these accidents is the product of a combination of factors which include individual and team actions [32]. From the driver’s perspective, the main factors that affect the driving tasks can be grouped into three major categories: impaired visibility, fatigue and human error. Impaired visibility comprises all of the obstructions that reduce or block the visual contact of the vehicle’s surroundings. Vehicle design, adverse weather conditions (i.e. rain, fog, dust, snow, darkness, sun glare, etc.) or road design (i.e. sharp corners, stockpiles) can be detrimental to the visibility of other vehicles and personnel in the vehicle’s surroundings [39]. Impaired visibility also affects the ability to assess the conditions of the road (i.e. road width, lane orientation, perception of ice or snow on the road, etc.). Fatigue is highlighted as the most critical contributing factor of vehicle accidents in the mining industry, being the direct cause of hundreds of serious injuries and fatalities every year [22][35]. Fatigue affects the alertness and 978-1-4244-7658-9/10/$26.00 ©2010 IEEE

Fig. 1. The result of two vehicle accidents that occurred in Queensland mines during 2009 [27][28].

performance of drivers by increasing the reaction time and impairing the judgment capabilities, leading to a higher risk of motor and cognitive errors [36]. The human factor, also known as human behavior or human error, is a factor that involves errors made in the “perceptual-cognitive-motor” chain. At different degrees, driver behavioral error contributes to the occurrence of almost every vehicle accident [32][14]. Typical problems that involve human error include driving deliberately at inappropriate speeds [30] and engaging in distracting activities such as handling equipment while driving [24][8][9]. The common feature of these major categories of factors is that they all impair the driver’s awareness. When these factors are not properly addressed the consequences can be catastrophic, as illustrated in Figure 1. Safety management plays an essential role in identifying and addressing existing risks in the mine. The traditional approach based on the establishment of detailed safety rules of operation has proved to be insufficient for avoiding vehicle accidents. Furthermore, the introduction of more rules to cover every aspect of mining is not the solution for producing a safer workplace [19]. The human element present in the operation of a vehicle cannot be eliminated through the use of rules alone and, if the operator is missing crucial information, there is a higher risk of accidents. For this reason it is necessary to aid the driver to create and maintain a high level of awareness. Post-accident reports often remark the lack of a warning system being used during the incident. These reports usually conclude with the recommendation of incorporating a system that helps drivers to avoid similar accidents [34][26][32][30][13][37]. Moreover, it is estimated that almost every fatal collision in American mines that involved 1435

mining equipment between the years 1999 and 2003 could have been avoided if only a reliable proximity system had been installed [33]. Currently available technology has a great potential for effectively aiding the operator in the tasks of driving in a proactive way and positively contribute in the overall safety of the mine [30][25][7]. A broad variety of sensing technology such as lasers, radars, cameras, GPS, brain-wave sensors, RFID and others, can be integrated with supporting information to infer risk factors. This supporting information can be in the form of road maps, rules, speed profiles, etc. Knowledge about these risk factors can be used to enhance the driver’s awareness and consequently, contribute in accident prevention. In this paper we present the design of a novel humanmachine interface that aids the vehicle operator by improving his/her situation awareness. This improvement in awareness is achieved by transferring knowledge about the current situation to the driver. The different elements that compose the interface and the mechanism for threat risks inference are described in this paper. We present experimental results obtained during the implementation and deployment of the interface in several mines in Australia and overseas. II. S ITUATION AWARENESS & I NTERFACES The driver’s fundamental objective is to transport material or other resources from one area to another area in the mine [17]. In order to accomplish this task in a safe manner the operator has to “be aware of what is happening around and understand what the perceived information means in a time frame”, as the situation awareness model states [10]. From this perspective, the role of in-vehicle systems is to assist the vehicle operator in performing the everyday tasks by providing critical knowledge that otherwise cannot be accessed. Some examples of the elements that the driver needs to know while operating the vehicle include: • The location and relative distance (time or space) of other agents in proximity (fixed and mobile agents) • The road’s layout (road’s width, direction) and its conditions (icy, wet, etc.) • The vehicle’s position on the lane (driving on the center of the road or too close to the edge) • The driving dynamics within the current area (is the driver in a haul road or a slow speed area?) • Its own level of fatigue (and the presence of other fatigued drivers nearby) Different types of user interfaces can be used to transfer this knowledge to the driver. Among them, visual interfaces are usually the most popular choice for presenting information from an in-vehicle system. Different devices such as LCD screens, head-up displays and LED indicators can be used to present visual information. Visual displays are very effective when the message to be communicated is complex, long, will be referred to later, deals with spatial location and does not require immediate action [23][16]. Vision is the most important source of information for the driver [18], and therefore the main concern with visual interfaces is that

they should not overload the visual channel already occupied in the driving tasks [31][2]. The use of the auditory modality in human-machine interfaces is particularly useful in domains where the operator requires the visual sense to process and perform the other tasks. Audio stimuli are also better than any other modality for attracting the operator’s attention, which can lead to improved response times [23]. In the case of in-vehicle systems, sound alarms and voice messages can provide a significant benefit by allowing the driver to maintain a continuous visual contact with the road and the possible obstacles that may appear [1]. Haptic or vibratory interfaces can provide information to vehicle operators through the sense of touch. When compared to visual displays, the communication of particular events to drivers using for example vibrating elements mounted in the seat, can reduce the operator’s workload and can improve the visual attention [12][4]. Despite the benefits that haptic interfaces can provide in an in-vehicle application, they might not be suitable for mining applications due to the already existing amount of vibration in the operator’s cabin. Brain-machine interfaces are devices that allow humans to interact with artificial devices by measuring neuronal activity of a few neurons or large cell assemblies [15]. Computerbrain interfaces can stimulate the brain through artificially generated electrical signals to communicate different information. Brain signals can also be mapped to different aspects of the human brain, providing information about human behavior, workload, alertness, emotions, etc. In the near future brain-machine interfaces could revolutionize the way we interact with machines. III. T HE I NTERFACE D ESIGN The strategy for interfacing with the vehicle operator is based on the communication of a combination of visual and auditory cues. Audio-visual interfaces can provide a significant benefit for in-vehicle applications by allowing operators to simultaneously acquire and process essential data, thus improving the driver’s attention and increasing the overall performance [29][20][6][3][11]. The combination of visual and audio modalities enables the system to provide information that is both complex and relatively urgent [20]. While visual information is better for supporting long-term projection, sound alarms are better for supporting the shortterm projection to indicate, for example, that an immediate action should be performed [11]. The interaction between the operator and the system is based on the premise that drivers must have, at all times, the freedom to decide and perform whatever action they choose. From this premise we derive two basic behaviors or functionalities that the interface has to respond to: 1) “The operator queries the status of the current situation” 2) “The system notifies the presence of a dangerous situation” These two functionalities are addressed by providing a continuous visual representation of the current situation on

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perceive that they are approaching them or if there are other vehicles approaching the same intersection. By presenting a highlighted intersection on the screen the operator can assess the possibility of risk ahead of time. B. Inference of High Risk Situations

Fig. 2. Sketches that depict the transformation of a real situation into its visual representation.

the screen and by triggering a set of audible alarms that notify the presence of a danger. A. The Visual Screen The main screen of the interface consists on an egoreferenced view of the location of the operator’s vehicle in the mine. When compared to north-up or world referenced maps, ego-referenced maps require less mental transformations and less mental effort [38]. The screen provides a representation of the real situation (Figure 2a) by using a combination of basic drawings (Figure 2b). These drawings show the position and heading of other agents nearby, the layout of the roads in the area where the driver is located and the location of intersections and other context areas. The 2-D view design allows the operator to visualize the presence of agents (i.e. vehicles or personnel) located in the front and in the back of the vehicle and enables the operator to easily estimate the distance to these agents. A fixed radius circle in the middle of the screen serves as a reference to simplify the distance estimation. The closest agent is plotted in a distinctive color in order to emphasize where the closest threat is located. The roads on the screen serve as a guide for driving and also provide a simple way for estimating the relative distance to other agents when considering the environment constraints. During operation, the driver’s position is always plotted in the center of the screen facing forward, while all other elements (i.e. roads, agents, etc.) move around. To effectively improve driver’s awareness, the system has to adapt its own behavior according to the current context [39]. In general terms we can identify two distinctive type of context within any mine site: high speed areas and slow speed areas. In high speed areas (such as haul roads), vehicles generally drive uniformly within one lane at relatively high speeds and maintain a significant distance to vehicles in front and behind. This is in contrast to slow speed areas where the motion of the vehicle is characterized by unstructured movements. Some examples of slow speed areas include the crusher area, the loading area, the parking lot and intersections. By showing upcoming contexts on the screen the driver can identify areas of high risk and prepare a change of behavior ahead of time. For example, intersections are areas that present a very high risk and drivers often cannot

A high risk situation is defined as the combination of risk factors and their statuses that, in specific conditions, have the potential of causing a collision. These risk factors are determined by state information from the vehicle (e.g. the vehicle’s speed), the operator (e.g. the level of fatigue) or the surrounding environment (e.g. the position of another vehicle, the distance to the edge of the road, etc). Only when all the risk factors specified in a high risk situation take place simultaneously, it can be considered a dangerous situation. For example, a light vehicle driving at 60 km/h can be considered acceptable in a haulage road. However, if the vehicle was a haul truck, then the speed could be considered unacceptable, and therefore it could be a high risk situation. Furthermore, if the area is a slow speed area, then no matter what type of vehicle it is, the situation can be considered of high risk. In this simple example we combined several risk factors (the vehicle type, speed, and current context) and their statuses (i.e. heavy vehicle, 60 km/h, slow speed area) which define a high risk situation. The method for inferring the occurrence of high risk situations is based on the use of a set of rules. Each rule is composed of one or more conditions and an output alarm. Each condition is composed of a variable, a value, and a comparison sign. For example, if we want to evaluate whether the speed of the vehicle is exceeding 40 km/h, then the variable of the condition will be ’speed’, the value will be ’40’, and the sign will be ’>’. This condition can be read as “speed > 40 km/h”. The output alarm defines a distinctive sound and a specific image that can be associated to a particular danger. When all the conditions of a rule are fulfilled, the rule is considered to be active and the alarm of the rule is triggered (the sound is raised and the image is displayed on the screen). Some other examples of variables are the agent’s speed, heading, relative position to other agents, current context, etc. This threat inference method enables the use of a broad variety of evidence before triggering an alarm. The direct benefit is a reduction in the amount of unnecessary alarms. Unnecessary alarms can annoy the driver and can be detrimental for the driver’s awareness. In systems that are perceived as annoying, operators will not respond in the same way as the design intended to. Operators may respond slower, ignore alarms, disable the system, or even react with anger (i.e. break the system) [11][23]. Furthermore, systems with a high rate of false alarms distract the driver, negatively affect the operator’s confidence and acceptance of the system, and impair the operator’s response [11][5][21][30]. For example, by using context information, rules can be configured to differentiate when vehicles are driving in slow speed areas and haul roads. This way the system can avoid triggering unnecessary alarms, for example, when driving close to ve-

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hicles parked in the parking lot area. Rules can be configured to address a large variety of high risk situations. Typical situations include: • Detection of operators driving at high speed • Notification to drivers when breaching distance to vehicles while driving in a convoy • Warning the driver when approaching a dangerous area IV. AGENTS I NTERACTION The audio-visual interface described in this paper is part of a cooperative safety system developed by the Australian Centre for Field Robotics (ACFR) in conjunction with AcuMine Pty Ltd and CRC Mining. The functionallity of the underlying system is based on the exchange of state information between different agents in the mine. These agents include mobile and fixed resources such as haul trucks, loaders, light vehicles, personnel, base stations, etc. Upon reception of the information, each agent can infer the presence of a threat or high risk situations. Data logged in each vehicle is periodically collected in a central server located in the base station via wireless communication. This information is later on used for generating performance reports and for reviewing past driving situations. Each agent is equipped with a computer containing a GPS for determining position and a dual-radio communication system for interacting with other agents. The dual-radio configuration combines a 2.4 GHz radio that links the different agents on a mesh network allowing for multiple hops, and a 433 MHz radio used for redundancy and robustness. The long range radio allows agents to communicate through the mesh at a distance above 1.5 km for each hop, as long as these nodes have line-of-sight between each other. The shortrange radio provides communication over a shorter range (approximately 500m) but with fewer line-of-sight limitations, allowing to exchange information with agents located behind corners, stockpiles, or behind any other obstacle. Due to the fact that weather factors do not affect radio communications, agents can interact with other agents far in advance before approximation on a 360 ◦ angle of view. Figure 3 shows an overview of the interaction between vehicles, personnel and infrastructure. The position and other vehicle state information obtained from the system is then broadcasted to the other agents. The system uses only standard GPS resolution which requires a minimum of 3 satellites in view for 2D/3D positioning, which is available in most open pit mines [40]. Experimental data indicates that the GPS precision in the majority of open pit mines is in the order of 3 to 10 meters most of the time. Reasonably flat mines usually present a high availability of GPS reception throughout the whole mine. However, covered areas and deep areas in the mine might suffer from greater precision error or unavailability of GPS coverage. Some of the key benefits of the system include high scalability, ease of deployment, and good adaptation for the mining domain. The display is mounted on the vehicle’s cabin near the dashboard. When the vehicle is turned on, the system is powered up and the interface shows the main screen (i.e. the

Fig. 3.

Diagram of the interaction between agents.

position of the vehicle in the mine, the roads, context areas and other agents nearby, etc). The graphical representation of the situation presented on the screen is updated several times a second. The list of rules are constantly evaluated and when required, the sound alarm is triggered. V. D EPLOYMENT The interface was constructed using a 4.3” LCD screen with touch panel capabilities and integrated speakers. User input was only required for adjusting the volume and brightness levels. The scale of the map presented on the screen was configured to show 240 meters to each side of the vehicle (left and right) and 135m to the front and back of the vehicle. The diagram of the roads and the layout of the context areas were generated using GPS positions previously recorded by vehicles driving around the mine. During the experimental phase of the system the following three rules were configured: 1) Driving over the speed limit 2) Breaching a safe distance to a vehicle in front 3) Breaching a safe distance to a vehicle behind The distance rules only applied to the case where the operator was driving in a convoy situation (i.e. another vehicle is located either in front or in the back and heading on the same direction). The sound alarm in each rule consisted of a different configuration of tones. The sound used for the speed rule was a single beep and, in the case of the the distance rules the sound used was a double beep with different pitches (high pitch to indicate that a vehicle was in front and low pitch to indicate that a vehicle was located behind). The system was installed in haul trucks and light vehicles from three sites around Australia and overseas. Each of these sites contained distinctive features and particular challenges that had to be taken into account. One of the sites was a relatively small quarry that operated only during daytime. In this site the fleet consisted of 10 vehicles, including heavy vehicles, light vehicles and loaders. Direct visual contact between vehicles was sometimes

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affected by stockpiles and other terrain characteristics such as corners with different grading, hills and berms. The second site selected for installation was a relatively flat open-cut iron mine. In this mine the main sources of visual impairment included high berms along the roads, high stockpiles in slow speed areas, obscurity during night shifts and dust. In addition, complex maneuvers were frequently performed in congested areas such as the loading area and the crusher area. The third site where the system was deployed was a large copper mine. In this mine the distinctive factors that commonly impaired the driver’s awareness included the geometry of the roads and, during winter time, a combination of heavy snow with strong winds that reduced the visitibilty. In addition, sharp corners and intersections of roads converging at different gradients commonly blocked the operator’s visual field. Vehicle operators frequently don’t have sufficient knowledge of what is happening ahead of them due to the complex road layout.

Fig. 4.

Enhancing awareness in low visibility conditions

Fig. 5.

Visualization of vehicles covered by high berms.

VI. E XPERIMENTAL R ESULTS After several weeks of continuous use of the system in the large copper mine (site 3), a preliminary evaluation of the effectiveness of the system was performed. The purpose of this evaluation was to determine the level of understanding and satisfaction that the drivers had towards the system. The evaluation consisted of 15 multiple-option questions where the operators had to select a subjective rating about different aspects of the interface such as understandability of the information presented and improvement in awareness. The evaluation was completed by 28 out of 92 operators that were trained in the use of the system. Every operator that completed the evaluation indicated that the system allowed them to know their position in the mine; that they were able to perceive other vehicles in close proximity; that the provision of sound alarms was appropriate; and above all, that they felt more safe with the system. The improvement in operator’s awareness was also corroborated by collecting direct observations from real situations while driving with the system in each of the sites. For instance, Figure 4 depicts a situation where a light vehicle is following a heavy vehicle on a haul road. The visual contact with the vehicle in front is completely obstructed by dust suspended on the air. In a situation like this one, the driver can observe the presence of a truck driving less than 70m (or more precisely 53m) in front of his vehicle with a brief look at the screen. Stockpiles and high berms along the haul roads are major visual impairments. Figure 5 illustrates the sequence of events that took place when a light vehicle was approaching the entrance of a loading area. As depicted in the Figures, a heavy truck initially hidden from the view of the operator suddenly appears from behind a berm and converges into the same road as the light vehicle. The information on the screen, in combination with the sound notifications allowed both drivers to detect the existence of a threat far in advance.

Figure 6 illustrates the need of having access to the information on the interface, even when driving in clear weather conditions. The graphical representation of the roads and context areas located ahead allowed the driver to overlook what was happening beyond the truck in front. Another typical case is illustrated in Figure 7. In this example a truck located directly in front of the vehicle cannot be seen by the driver due to the curvature and gradient of the road. In addition, the operator cannot perceive the intersection located ahead on the road. The information presented on the screen summarizes the whole situation by indicating the presence of an intersection and, at the same time, that two vehicles are already present in the intersection.

Fig. 6.

A view of the display showing an intersection ahead.

Occasionally when driving in congested areas such as the crusher area (Figure 8), understanding the events that

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driver’s attention without annoying the operator. The proposed strategy and interface design presented in this paper demonstrated to be capable of improving the driver’s awareness and vehicle safety. VIII. F UTURE W ORK

are taking place can be very demanding, especially during night operations. In such cases, the whole situation can be transformed into a simplified visual represenatation. In this situation for example, the image presented on the screen indicates that the driver is located inside a slow speed area (more specifically the crusher area), there is a truck parked in front (id 1482, located 41 meters in front), and there is a second vehicle currently leaving the crusher area. The awareness of the whole situation can be acquired at a glance.

Many improvements can be incorporated into the process of threat inference. Future research will be focused on the integration of alternative sources of information such as radar information, received signal strength indication (RSSI) and fatigue measurements. These sources of information will allow the system to improve the reliability of threat inference and to detect other important dangers such as the distance to the edge of the road and other obstacles nearby, and measuring the level of fatigue of drivers. In future iterations it will become essential to define metrics for measuring the improvement of situation awareness and to perform measurements of these metrics in the field and/or during simulations. Comparative data of the number of crashes and near-misses before and after the deployment of the system can provide an indication of the improvement of driver’s performance and vehicle safety. However, due to the fact that accidents are unplanned events, this comparisson will require to collect data from an extended period of time (e.g. in the order of three or more years) with and without the system installed. Despite the fact that vehicle operators did not perceive any annoyance during the field tests, it will be critical to monitor the level of annoyance of the sound alarms, particularly when handling a large set of rules. Alternative ways of interfacing with the vehicle operator will also be evaluated. Head-up displays, vibratory interfaces and brain-computer interfaces will become more accessible in the near future and should improve the interaction with the driver. In addition, alarms can combine abstract sounds with voice messages to further improve the notification of risks.

VII. C ONCLUSION

R EFERENCES

The experimental results obtained from direct observations and from the operators feedback reflected the importance of having an in-vehicle system fitted in mining vehicles. The interface proved to be capable of transforming information that was previously inaccessible to the operator into visual and audible cues which enabled the operator to proactively assess real situations. In situations of impaired visibility the information provided by the display allowed operators to perceive vehicles located behind stockpiles, blind corners and adverse environmental conditions. Each of the visual elements that composed the audiovisual interface played a key role in the process of improving awareness. The representation of the positions of vehicles nearby were essential for anticipating future interactions, while the representation of the slow speed areas became critical for providing a better understanding of the situation. In addition, the sound alarms were useful for catching the

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Fig. 7.

Approaching a dangerous intersection with two vehicles ahead.

Fig. 8.

A view of the screen when driving inside a context area.

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