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Drive and Fly with AR Real Driving: An Augmented Reality Car Simulator with Realistic Sound and Physics

Using the power of augmented reality, you can do the impossible with this game. Here, you can spawn various cars and control them using just your phone. This is all thanks to the advanced technology and the developers at Enteriosoft who made this possible.

FIGURE 3. Experimental setup for the driving simulator study. Each participant performed four drives. Each drive took 12 min. At the end of each drive the participants were faced with a more complex situation: an ambiguous left turn situation with an oncoming car, the moment when they were about to take the turn.

ar real driving augmented reality car simulator

While next-generation AR HUDs will provide a fundamentally new driving experience, we currently do not know how to effectively design and evaluate user interfaces (UIs) in this space. With new AR HUDs capable of rendering images over large areas at varying depths, the visual and cognitive separation between graphical and real-world visual stimuli will be increasingly more difficult to quantify. As we move toward widespread use of next-gen AR HUDs in transportation, we need to better understand how to manage UI designs that are not simply atop the environment, but instead are an integrated part of the environment.

Regarding fidelity of driving simulation (i.e., visual stimuli, vehicle control, and motion), a wide range of driving simulator hardware has been used in empirical studies on AR applications depending upon the research questions addressed. The lowest fidelity settings are often a combination of desktop computers, monitors and game controllers (Neurauter, 2005; Kim and Dey, 2009; Weinberg et al., 2011; Charissis et al., 2013; Kim et al., 2013; Tran et al., 2013; Politis et al., 2014; Sharfi and Shinar, 2014; Tippey et al., 2014). For example, Sharfi and Shinar (2014) prototyped an AR visibility enhancement system for nighttime driving that highlights lane markers using a desktop computer, DEXXA game controllers, and a 126 60 cm monitor and found that augmented road edges have positive effects on drivers' confidence and workload while reducing their ability to detect unexpected obstacles. Other researchers have used medium fidelity driving simulators that typically consist of a fixed-based real car cab with wall projection screens (Tonnis and Klinker, 2006; Caird et al., 2008; Plavšic et al., 2009; Olaverri-Monreal et al., 2012; Saffarian et al., 2013; Schall et al., 2013; Wai-Tat et al., 2013; Bolton et al., 2015). Fu et al. conducted a user study in a driving simulator with a GM Saturn real-car cab on a fixed base (Wai-Tat et al., 2013). The user study showed that the proposed AR forward collision warning improved driving performance but induced risky driving behavior especially among young drivers. A few user studies have been conducted in a high-fidelity driving simulator with motion-based real car cabs with wide field of view projection screens, in-vehicle displays for mirrors and center console displays (Medenica et al., 2011; Lorenz et al., 2014). For example, Medenica et al. (2011) evaluated the usability of three navigation aids in a high-fidelity real-car cab atop a motion-base which is able to simulate vehicle motion for braking and accelerating. The user study showed benefits of a conformal AR navigation aid showing a virtual route hovering above the road against traditional map-view or street view navigation aids presented on a center console display. Lastly, SILAB (WIVW, 2019), a commercially available driving simulator, supports a flexible, wide range of simulation fidelity from desktop systems with gaming control inputs to multi-channel projected scenes with real vehicles placed on motion platforms. Similar to our work presented herein, SILAB supports physiological measurement, video capture of driver and passengers from arbitrary angles, eye tracking, real-time connection protocols (such as TCP/IP, UDP, and CAN bus), and support for secondary task integration. From materials available online, it is not clear if separate AR HUD hardware has been successfully integrated into SILAB. However, it is certainly plausible that the infrastructure as described would support such an endeavor.

For AR displays, most researchers have simulated AR HUDs by presenting AR graphics directly within driving scene (with no physical AR display; Caird et al., 2008; Kim and Dey, 2009; Plavšic et al., 2009; Charissis and Papanastasiou, 2010; Medenica et al., 2011; Dijksterhuis et al., 2012; Olaverri-Monreal et al., 2012; Kim et al., 2013, 2016; Saffarian et al., 2013; Schall et al., 2013; Wai-Tat et al., 2013; Lorenz et al., 2014; Politis et al., 2014; Sharfi and Shinar, 2014), while some installed in-house prototypes (Tonnis and Klinker, 2006; Langlois, 2013; Tran et al., 2013), aftermarket c, or head-worn displays inside driving simulators (Sawyer et al., 2014; Tippey et al., 2017). Generally speaking, from our experience, integrating graphics directly into the driving scene (via computer graphics or video) does not afford the same accommodative and/or cognitive switching (Gabbard et al., 2019) that a separate AR display does; an important component for research that wishes to faithfully examine the effects of AR HUDs on driver's visual attention. Moreover, home-made AR HUDs (e.g., using tablets and semi-transparent combiners) may suffer from ghosting and other visual artifact that can impact user study results unless extreme care is put into its construction.

Conformal graphics in driving simulators have been realized mostly by direct integration of AR graphics into computer-generated driving scene without separate displays (Caird et al., 2008; Kim and Dey, 2009; Plavšic et al., 2009; Charissis and Papanastasiou, 2010; Medenica et al., 2011; Kim et al., 2013; Schall et al., 2013; Wai-Tat et al., 2013; Lorenz et al., 2014; Politis et al., 2014; Sharfi and Shinar, 2014). The few instances found in literature that present conformal AR graphics use Wizard of Oz (Bolton et al., 2015), computer-vision-based object detection (Wu et al., 2009), and communication between driving simulation software and AR application (Tran et al., 2013). Lorenz et al. (2014) prototyped AR warnings for restricted lanes due to emergency situations by presenting green safe path or red dangerous path by integrating conformal graphics into the driving scene using the same rendering pipeline as the driving environment. Bolton et al. (2015) presented drivers with a seemingly autonomous driving scenario including pre-recorded navigation arrows visible through an optical see-through HUD which correspond with a specific driving scenario that were manually-triggered by researchers. Wu et al. (2009) played driving footage in front of a driving simulator and overlaid AR bounding boxes through the windshield to highlight detected road signs by computer-vision technology. Finally, Tran et al. developed a capability of presenting real-time conformal graphics via communication with driving simulation software that transmitted information about road geometry, other road actors and traffic signals. They presented AR graphics to visualize predicted path of oncoming traffic for left turn aid. However, details about the system configuration and software architecture were not reported (Tran et al., 2013).

The centerpiece of our driving simulator is the front half of a 2014 Mini Cooper automobile. The vehicle was donated from a major car insurance company that kindly removed the engine and transmission prior to delivery. Once delivered, we tested the electrical components and then completely disassembled the vehicle, including all trim, seats, airbags, dash components, and more until just the frame remained. The back half of the cab was removed and discarded, and the top half of the remaining cab was temporarily removed. The two cab halves were relocated into a lab, where the back-end of the bottom half was mounted on a frame with casters (the front-end of bottom half supported by original tires). The top half was the reattached and we then reassembled all the previously removed components (from supporting sub-structures to finished trim pieces) and tested the reassembled vehicle electrical systems.

The major computing components of our AR DriveSim communicate via UDP (yellow). A set of off-the-shelf and custom microcontrollers (brown) pass driving control inputs read from CAN bus (green) and other sensors to the AR DriveSim computer (orange). A control board (brown) further manages a DC motor to provide force feedback to the steering wheel. A separate computer (blue) renders 3D graphics on an AR HUD by synchronizing its virtual camera position in real-time with the AR DriveSim computer. A set of experimenter controls (black) assist in coordinating experiments.

Timing of AR HUD graphics' behavior is done through the use of MiniSim's road pad trigger events which, when driven over by participants, generate event specific network data traffic. For example, in the user study presented below, road pad triggers create data packets that inform the AR HUD software that the driver has encountered an augmented driving segment, and consequently begin rendering the desired AR HUD graphics. The data selected to inform the behavior of conformal graphics is adaptable as a callback mechanism to launch procedures defined in the AR HUD scene graph component. The MiniSim route table can also be configured to send position and orientation data on the nearest 20 dynamic scene objects (e.g., other vehicles, pedestrians, etc.). Such information can also be used to render real-time conformal graphics such visual pedestrian alerts and labels for nearby traffic.

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There were no differences in driving or risk-taking behaviors despite the fact that participants using the Screen-fixed display allocated less visual attention toward the graphic and therefore, presumably allocated more visual attention toward other elements relevant to the driving task. The lack of differences in driving behaviors can be explained in a study like this because we did not include events that were unexpected or unpredictable in our driving scenarios, which might be more likely to differentiate between HUD graphics. Surprise events (unexpected or unpredictable) require rapid responses and drivers using conformal AR HUDs are especially vulnerable to change blindness or display clutter that might hinder drivers particularly in the face of unexpected events because changes in the display may mask real-world changes. Driving measures are not as sensitive as other physiological measures (Wierwille and Eggemeier, 1993) and the allocation of visual attention can be an early indicator of degraded driving ability. Thus, measures such as glance behavior provide direction about display design even when driving performance measures do not differ. Regardless of the reason for the increased visual attentional allocation, this work suggests that we should be judicious when designing AR HUDs for vehicles.


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