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Automotive Driving Simulator Market

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Automotive Driving Simulator Market report categorizes global market on the basis of technology, end-user, and applications - Global Industry Insights, Trends, Outlook, and Opportunity Analysis, 2017–2025
Automotive Driving Simulator Market Global Industry Insights, Trends,
Outlook, 2018–2026
Automotive driving simulators (sims) belong to the class of human machine interface
(HMI) that are prominently used to mimic the near-exact conditions prevalent during
driving. These find substantial applications in education & training institutions for vehicle
user training programs, and R&D activities for the pre testing of new vehicles, advanced
driving assistance systems and other technologies. This enables the users to utilize the
best potential of virtual reality for testing of practical applications by eliminating the risk
due to mishandling of the controls and physical damages.
Driver state monitoring system (DSMS) incorporation in these systems will
provide high growth prospects
DSMS is an electronic system used in vehicles to monitor the users’ inactiveness,
fatigue or drowsiness while driving. This helps in analyzing the driver’s mental and
physical state accurately in real time by synchronizing the system with the camera
installed directly focusing on the user’s face. Furthermore, the system also helps in
evaluating range of driver conditions that includes eye closure, eyelid distance, head
positions and yawning. Utilization of these systems for improvements in the vehicle
safety and user comfort, is expected to drive the automotive driving simulator market
growth.
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Availability and utilization of low cost simulators is expected to provide major
industry traction over the forecast period
Low cost affordable sims are featured with the ability to gain better audience for its
primary applications in evaluation and testing of vehicle technologies. Growth in the
hardware and software processes have in turn led to easy availability of these products.
Players in the market offer an extensive portfolio from low cost scales to expensive
high-fidelity products. Mitsubishi Electric Research Labs’ offering, which is a medium
fidelity simulator is among the most popular low priced offering. Owing to these factors,
they account for significant revenue share and are expected to witness strong growth
over the next few years, specifically for gaming applications.
Existence of semblance of lag between the actual response time for any input given by
the driver and the expected response time is expected to be the major industry growth
challenge. It induces an adaption burden phenomenon, which impacts the driver’s brain.
This syndrome is called simulator sickness or SAS. Users have reported symptoms of
headaches, disorientation and motion sickness, among few others.
U.S. held the largest industry share in 2016, is expected to present strong growth
prospects
North America held the largest automotive driving simulator market share in 2016,
primarily owing to the ongoing new vehicle projects for advanced technologies such as
autonomous vehicle development and connected cars for the future adoptions.
Moreover, government support to encourage the utilizations of these technologies to
avoid accidents and damage to lives and infrastructure will present potential growth
landscape for the industry growth. For instance, EU training directive in Europe has
proposed the usage of advanced automotive driving simulator for the training and
retaining of truck and bus drivers.
Key participants in the automotive driving simulator market include Ansible Motion,
OKTAL, Cruden, Mechanical Simulation, Dallara, and Moog. Industry is majorly
characterized by the intensive competitive scenario, with key players competing on
market grounds with competitive pricing strategies, technology advancements, quality,
and customer experience with high end performance. Proliferation of R&D activities for
development of autonomous cars by Google, Volvo, Tesla and many others is expected
to provide large demands for these systems for evaluation of their algorithms and
decision making processes.
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