The Iowa Driving Simulator: an immersive research environment

Kuhl, Jon G.; Evans, D. F.; Papelis, Yiannis; Romano, Richard; Watson, G. S.

doi:10.1109/2.391039

Cited by 59 publications

(21 citation statements)

References 3 publications

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“…The motion generation process of a driving simulator is traditionally implemented through dynamics modeling of a vehicle and real-time computation of motion equations derived from a vehicle dynamics model [1][2][3][4][5]. The modeling process of dynamics is crucial for the development of a driving simulator to achieve realistic simulation of the complex motion of a vehicle.…”

Section: Introductionmentioning

confidence: 99%

An interactive data-driven driving simulator using motion blending

Cha

Yang

Han

2008

Computers in Industry

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Section: Introductionmentioning

confidence: 99%

An interactive data-driven driving simulator using motion blending

Cha

Yang

Han

2008

Computers in Industry

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“…Investigation of driver behaviour modelling research demonstrated that the majority of high-fidelity traffic simulators utilise the macroscopic simulation method (Kuhl et al, 1995;Cremer, 1995;Papelis & Bahauddin, 1995). Predominantly, this method exploits mathematical models -often originated from fluid dynamics -that treat vehicles as particles in a homogenous flow.…”

Section: Macroscopic Simulation Approachmentioning

confidence: 99%

Artificial Intelligence Rationale for Autonomous Vehicle Agents Behaviour in Driving Simulation Environment

Charissis¹,

Papanastasiou²

2008

Advances in Robotics, Automation and Control

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In recent times, in-vehicle notifications have proliferated with a focus on the exhibition of technological prowess rather than the fulfilment of actual driving needs. In effect, information portrayed by automotive infotainment devices, while useful, is often ignored by the driver due to field of view limitations associated with traditional instrumentation panels. Not surprisingly, under poor visibility conditions and at motorway-level driving speeds, such systems do not effectively present useful information to the user. Contemporary Head-Up Display (HUD) experiments have focused on adapting the aviation-specific characteristics of HUDs to driver-specific needs, obsolescing functionality and simplifying operations where necessary. The more mature approach of these preceding works has revealed that although in-vehicle HUD technological advances have overcome most implementation issues, the related user-centred interface design is in its infancy prohibiting the HUD's unique features from being successfully exploited. Towards addressing this issue, in previous work, we have designed and implemented a functional prototype of a Human Machine Interface (HMI). Specifically, the proposed HMI system introduces a novel design for an automotive HUD interface, which aims to improve the driver's spatial awareness and response times under low visibility conditions. Particular emphasis has been placed on the prioritisation and effective presentation of information available through vehicular sensors, which would assist, without distracting, the driver in successfully navigating the vehicle. In order to evaluate the effectiveness of the proposed HUD system, we developed a driving simulator based on an open source racing program. Leveraging an open source solution has resulted in manageable levels of incurred expenses whilst allowing us to deliver a flexible simulation application for HUD evaluation. This chapter discusses the artificial intelligence (AI) as developed for the agent vehicles of our open source driving simulator. The simulator was explicitly designed to measure driver's performance when using the proposed HUD interface and compares its effectiveness to traditional instrumentation techniques. Intuitively, human cognition complexity poses the largest challenge for creating a model of life-like driver's behaviour for any type of traffic flow. Presuming that specific driving characteristics apply to all human drivers, as dictated by common sense, an attempt was made to form a generic reaction Open Access Database www.i

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“…There is also considerable work on using virtual environments for driving simulation [14,3] and methods for modeling the vehicle behaviors and navigable paths [27,7,29].…”

Section: Traffic Simulationmentioning

confidence: 99%

Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatiotemporal Data

Sewall

Berg

Lin

et al. 2011

IEEE Trans. Visual. Comput. Graphics

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We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatio-temporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e. the dynamic motions of multiple cars over time) in between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur.

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The Iowa Driving Simulator: an immersive research environment

Cited by 59 publications

References 3 publications

An interactive data-driven driving simulator using motion blending

An interactive data-driven driving simulator using motion blending

Artificial Intelligence Rationale for Autonomous Vehicle Agents Behaviour in Driving Simulation Environment

Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatiotemporal Data

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