Eds: Disclaimer: The following press release comes to you under an arrangement with Business Wire India. PTI takes no editorial responsibility for the same.) Bangalore, Karnataka, India & Munich, Germany – Business Wire India Trusted Platform Modules (TPM) enable secured remote software updates, disc encryption and user authentication. Hence, they are crucial for connected industrial, automotive and other embedded devices. To further facilitate seamless integration in Linux-based systems, Infineon Technologies AG (FSE: IFX / OTCQX: IFNNY) now provides its leading OPTIGA™ TPM 2.0 solution with a comprehensive TSS* host software implementing the latest FAPI standard. Infineon has developed the open-source software jointly with Intel Corporation and Fraunhofer Institute for Secure Information Technology SIT. By using Infineon’s plug-and-play OPTIGA TPM 2.0, IoT system integrators can significantly improve the security of connected products. Software integration with TSS-FAPI does not require specific skills in low-level security specifications and reduces source code development by a factor of up to 16. Therefore, expenses and time to market can be reduced. Additionally, manufacturers can accelerate the process for certifying their industrial devices according to the IEC 62443 standard for industrial applications, which requires hardware-based safety from level 4 upwards. The FAPI specification has been released recently as an international standard by the Trusted Computing Group (TCG). The specification is implemented in the TSS stack1 together with the associated tools and plug-ins. The TSS stack is open-source software, which allows seamless integration of the TPM 2.0 in Linux-based systems. This includes the support of typical Linux software for device authentication, data encryption, software updates and remote device management. In addition, the FAPI enables the native support of the PKCS#11 standard as a generic interface for user authentication, single sign-on and e-mail encryption/signing. The FAPI provides a default configuration for cryptographic functionalities, system integration and automated processing of security mechanisms according to the latest state-of-the-art and industrial best-practices. The OPTIGA TPM acts as a vault for sensitive data in connected devices and lowers the risk of data and production losses due to cyberattacks. Infineon’s TPMs are certified by independent certification bodies according to Common Criteria, an international set of guidelines and specifications developed for evaluating information security products. The TSS stack including the recent FAPI has been verified with the Infineon TPM portfolio to achieve compliance and interoperability. Availability Application developers can use the OPTIGA TPM SLB 9670, OPTIGA TPM SLI 9670 and OPTIGA TPM SLM 9670 Iridium boards and TSS Quickstarter offered by Infineon to get started right away. Board and source code packages for the Infineon AURIX™ as well as for Arduino microcontrollers are available now.

The Global Continuous Integration Tools (CI) Market is anticipated to rise at a considerable rate over the estimated period between 2020 and 2027. The Global Continuous Integration Tools (CI) Market Industry Research Report is an exhaustive study and a detailed examination of the recent scenario of the Global Continuous Integration Tools (CI) industry.

Continuous integration is a software development practice in which developers regularly unite their codes changed into a central fount, automated builds and tests are being processed. The main objective of continuous integration (CI) is to discover quick address bugs.

Growing demand for continuous integration (CI) tools in all industry verticals, high demand of automation in the development process of software, and rising productivity with the help of continuous integration (CI) tools are the factors driving the growth of the continuous integration (CI) tools market. Traditional integration methods and customers attraction towards the software updates are the factors restraining the growth of continuous integration (CI) tools market.

Major Key Players Covered In This Report: Atlassian, AWS, Cloudbees, IBM Corporation, Jetbrains, Micro Focus, Microsoft Corporation, Oracle, Puppet, Red Hat

The study conducts SWOT analysis to evaluate strengths and weaknesses of the key players in the Continuous Integration Tools (CI) market. Further, the report conducts an intricate examination of drivers and restraints operating in the market. The report also evaluates the trends observed in the parent market, along with the macro-economic indicators, prevailing factors, and market appeal with regard to different segments. The report predicts the influence of different industry aspects on the Continuous Integration Tools (CI) market segments and regions.

The global Continuous integration tools (CI) market is segmented on the basis of, deployment model, and size. On the basis of deployment model, market is segmented as on premises, on cloud. On the basis of size, market is segmented as SMEs, large enterprise.

The research on the Continuous Integration Tools (CI) market focuses on mining out valuable data on investment pockets, growth opportunities, and major market vendors to help clients understand their competitor’s methodologies. The research also segments the Continuous Integration Tools (CI) market on the basis of end user, product type, application, and demography for the forecast period 2020–2027. Comprehensive analysis of critical aspects such as impacting factors and competitive landscape are showcased with the help of vital resources, such as charts, tables, and infographics.

This report strategically examines the micro-markets and sheds light on the impact of technology upgrades on the performance of the Continuous Integration Tools (CI) market.

Continuous Integration Tools (CI) Market Segmented by Region/Country: North America, Europe, Asia Pacific, Middle East & Africa, and Central & South America

Highlights of the report:

A complete backdrop analysis, which includes an assessment of the parent market
Important changes in market dynamics
Market segmentation up to the second or third level
Historical, current, and projected size of the market from the standpoint of both value and volume
Reporting and evaluation of recent industry developments
Market shares and strategies of key players
Emerging niche segments and regional markets
An objective assessment of the trajectory of the market
Recommendations to companies for strengthening their foothold in the market

The Insight Partners is a one stop industry research provider of actionable intelligence. We help our clients in getting solutions to their research requirements through our syndicated and consulting research services. We are a specialist in Technology, Healthcare, Manufacturing, Automotive and Defence.

Overview of the Automotive Driving Simulator Market

The global automotive driving simulator market encompasses a wide range of hardware and software platforms used to replicate real-world vehicle dynamics in a controlled, virtual environment. Driving simulators are used across motorsport engineering, passenger vehicle development, ADAS (Advanced Driver Assistance Systems) validation, and driver training programs.

Market research covering the 2019–2026 forecast period examined the competitive landscape, manufacturing methodologies, application segments, and regional dynamics shaping this industry.

Key Manufacturers and Market Participants

The report identified several prominent players in the global automotive driving simulator space, including:

• Ansible Motion – A UK-based developer of high-fidelity dynamic driving simulators used in motorsport and OEM vehicle programs.
• Cruden – A Netherlands-based company offering full-motion professional driving simulators for racing and automotive R&D applications.
• DALLARA – An Italian motorsport constructor that has expanded into simulator technology for race car and road car development.
• Mechanical Simulation – Known for its CarSim and TruckSim vehicle dynamics software, widely used in simulation-based ADAS and autonomous vehicle development.
• Moog – A US-based manufacturer of motion control systems that supplies motion platforms for high-performance driving simulators.

These companies compete across hardware motion platforms, real-time vehicle dynamics software, and integrated turnkey simulation environments.

Market Segments

By Product Type

Automotive driving simulators are broadly categorized by the degree of motion and immersion they provide:

• Fixed-base simulators – Lower cost, suitable for software validation and basic driver training.
• Full-motion simulators – Incorporate hydraulic or electric motion platforms for realistic force feedback; used in high-end OEM and motorsport R&D.
• Driver-in-the-loop (DIL) simulators – The most sophisticated class, enabling real-time interaction between a human driver and a virtual vehicle model.

By Application

• Motorsport and racing team development
• OEM vehicle dynamics and chassis development
• ADAS and autonomous vehicle validation
• Driver training and licensing programs
• Road safety research

Market Drivers and Opportunities

Several factors are contributing to growth in the automotive driving simulator market:

• ADAS and autonomous vehicle development: Simulation reduces the cost and risk of validating safety-critical systems by replacing or supplementing physical road testing.
• Regulatory and safety requirements: Increasingly stringent vehicle safety standards push OEMs to invest in virtual testing environments earlier in the development cycle.
• Motorsport investment: Formula 1 teams and other racing organizations use advanced simulators extensively for car setup and driver preparation, driving demand for high-fidelity systems.
• Cost reduction in vehicle development: Virtual prototyping with simulators reduces the need for expensive physical prototypes during early design phases.
• Driver training scalability: Fleet operators and licensing authorities can train and assess drivers more consistently using simulator-based programs.

Industry Chain and Supply Structure

The automotive driving simulator industry chain spans several layers:

• Upstream suppliers: Motion platform actuator manufacturers, visual display system providers (LED walls, projectors), computing hardware vendors, and force-feedback steering and pedal system makers.
• Simulator integrators: Companies like Cruden and Ansible Motion that combine hardware and software into complete systems.
• Software platform developers: Providers of real-time vehicle dynamics models (e.g., Mechanical Simulation’s CarSim), environment rendering engines, and sensor simulation tools.
• End users: Automotive OEMs, Tier 1 suppliers, motorsport teams, research institutions, and government transport agencies.

Regional Market Dynamics

The report examined regional trends across major automotive markets. Europe has historically been a strong adopter of driving simulator technology, driven by its Formula 1 presence and a concentration of premium OEMs in Germany, Italy, and the UK. North America represents a significant market through both automotive R&D investment and defense/training applications. Asia-Pacific is a growing region, with expanding automotive production in China, Japan, and South Korea increasing simulator adoption for both development and regulatory compliance.

Challenges and Limitations

• High upfront cost: Full-motion, high-fidelity simulators require significant capital investment, limiting adoption to well-funded OEMs, racing teams, and research organizations.
• Motion cueing fidelity: Replicating all aspects of real vehicle dynamics—particularly sustained lateral and longitudinal forces—remains an engineering challenge due to physical platform travel limits.
• Integration complexity: Combining real-time vehicle models, visual systems, and motion platforms requires deep multi-disciplinary engineering expertise.
• Simulator sickness: Latency and perceptual mismatches can cause discomfort in extended simulator sessions, affecting usability for driver training programs.

Summary

The global automotive driving simulator market is being shaped by the convergence of motorsport engineering, ADAS development, and autonomous vehicle validation requirements. Key players such as Ansible Motion, Cruden, DALLARA, Mechanical Simulation, and Moog each address different segments of this market—from high-fidelity driver-in-the-loop platforms to real-time vehicle dynamics software. As regulatory pressures and development costs continue to push OEMs toward virtual testing, the market is expected to see sustained investment through the mid-2020s.

This article is based on a market summary originally published by marketanalyst24.com in July 2019. Figures and forecasts should be verified against current market data before use in business decisions.

What Are Automotive Driving Simulators?

Automotive driving simulators are systems that reproduce vehicle dynamics, road environments, and driver feedback in a controlled setting. They range from desktop software tools used by automotive engineers to full-motion, multi-axis platforms used in professional motorsport, commercial driver training, and road-safety research. Key simulator categories identified in the market include:

• Modular Design Simulators – configurable systems built from interchangeable hardware and software components, suited for research environments where test scenarios change frequently.
• Multi-Station Driving Simulators – setups supporting multiple concurrent users, common in large training academies or testing facilities.
• Bus Simulators – purpose-built platforms replicating the dynamics and visibility challenges of heavy passenger vehicles.
• Physical Simulators – high-fidelity platforms with full-motion actuators and realistic cockpit environments used in motorsport and advanced R&D.

Primary End-User Applications

Demand for driving simulators is distributed across several end-user segments:

• Entertainment – arcade and consumer-grade simulators, as well as location-based experiences.
• Training Institutions – driving schools, fleet operators, and military organisations using simulators to reduce on-road training costs and risk.
• Transport Authorities – government and regulatory bodies employing simulators for driver assessment, road-safety research, and policy evaluation.
• Automotive R&D – OEMs and Tier-1 suppliers using high-fidelity simulators to develop and validate vehicle dynamics, ADAS systems, and human-machine interfaces before physical prototypes exist.

Key Market Players

The competitive landscape includes a mix of specialist simulation vendors and diversified engineering companies. Notable players identified in HTF MI’s research include:

• Ansible Motion – UK-based manufacturer known for its Kinematic Driver-in-the-Loop (DIL) simulators used in vehicle dynamics and ADAS development.
• Cruden – Netherlands-based provider of professional driving simulators for motorsport, automotive OEMs, and research institutions.
• Dallara – Italian motorsport engineering firm that has expanded into simulator development, leveraging its racing expertise.
• Mechanical Simulation – developer of CarSim, TruckSim, and BikeSim software, widely used for vehicle dynamics modelling and simulation.
• Moog – global manufacturer of motion control hardware including the actuation systems that underpin many high-end driving simulators.
• Oktal (Sogeclair Group) – French company specialising in driving simulation software and integrated simulator platforms for research, training, and certification.

Market Growth Drivers

Several converging trends are fuelling investment in automotive driving simulation:

• ADAS and autonomous vehicle development – validating self-driving algorithms requires billions of simulated miles; simulator hardware provides a physical loop for sensor-fusion testing.
• Regulatory pressure on road safety – governments in multiple regions are tightening driver licensing standards and encouraging simulator-based pre-road assessment.
• Cost and risk reduction in training – simulators eliminate fuel, vehicle-wear, and accident-risk costs associated with on-road instruction for commercial vehicle operators.
• Advances in real-time rendering and motion actuation – improvements in graphics fidelity, latency, and motion cueing make modern simulators far more representative of real driving than earlier generations.
• Growing motorsport investment – Formula 1 teams and other motorsport organisations rely heavily on simulator testing to refine car setups between races.

Regional Landscape

Market activity is distributed globally, with distinct regional dynamics:

• North America – Strong demand from defence, commercial fleet training, and automotive OEM R&D, particularly in the United States.
• Europe – Home to several leading simulator vendors and automotive manufacturers driving high simulator adoption; Germany, France, and the UK are key markets.
• Asia-Pacific – Rapid growth driven by expanding automotive industries in China, India, Japan, and South Korea, along with increasing government investment in road-safety infrastructure.
• Middle East & Africa / Central & South America – Emerging demand, primarily from government transport authorities investing in driver training infrastructure.

Challenges Facing the Market

Despite strong growth drivers, several challenges constrain wider adoption:

• High capital cost – high-fidelity, full-motion simulator platforms can require significant upfront investment, limiting accessibility for smaller organisations.
• Simulation sickness – latency and inadequate motion cueing can cause discomfort in users, reducing the duration and effectiveness of training sessions.
• Transfer of training validity – the degree to which simulator experience translates to improved real-world driving performance varies by platform quality and training programme design.
• Rapid technology change – fast-moving sensor and software ecosystems mean simulator platforms can become outdated quickly, increasing lifecycle costs.

Relevance to DevOps and Engineering Teams

For DevOps engineers working in the automotive or embedded software space, driving simulators represent a critical part of the continuous integration pipeline for autonomous and ADAS software. Simulator platforms such as those from Mechanical Simulation integrate with software-in-the-loop (SIL) and hardware-in-the-loop (HIL) test environments, enabling automated regression testing of vehicle control algorithms at scale. CI/CD pipelines for autonomous driving stacks increasingly treat simulator runs as a first-class test stage, using tools such as containerised simulation environments to parallellise scenario coverage across cloud or on-premise compute clusters.

Source and Further Reading

The market overview above is based on a research summary published by HTF Market Intelligence (HTF MI), a market research and consulting organisation. Their full report — Global Automotive Driving Simulators Market Research Report — covers detailed financial data, competitive profiles, supply-chain analysis, and forecasts across the segments described above. Contact HTF MI directly for report access and custom research enquiries.

What Is an Automotive Driving Simulator?

An automotive driving simulator is a hardware-and-software system that replicates the dynamics of a real vehicle in a controlled, virtual environment. Engineers, researchers, and drivers use simulators to evaluate vehicle handling, test advanced driver-assistance systems (ADAS), validate control software, and train drivers — all without the cost, risk, or logistical overhead of on-road or on-track testing.

Modern simulators range from desktop software tools to large-scale motion platforms with multi-screen visual systems and force-feedback steering and pedal rigs. The fidelity required — and the budget available — determines which category of simulator is appropriate for a given application.

Key Vendors in the Automotive Driving Simulator Market

Several specialist companies and engineering firms compete in this space, each offering different combinations of motion platforms, visual systems, and vehicle-dynamics software:

• Mechanical Simulation — Best known for its CarSim, TruckSim, and BikeSim vehicle-dynamics software packages, widely used in both OEM and supplier engineering workflows.
• Ansible Motion — A UK-based specialist producing high-bandwidth, compact motion platforms (the Delta Series) targeted at automotive OEMs and motorsport teams that need high-fidelity dynamic response.
• Cruden — A Dutch company offering full-mission driving simulators for motorsport, OEM vehicle development, and driver training, including its Panthera simulator platform.
• Dallara — Primarily a racing car constructor, Dallara has invested in high-performance driving simulators used for Formula racing development and driver coaching.
• Moog — A diversified motion-control company whose simulation division supplies electric and hydraulic motion platforms used across automotive, aerospace, and defence simulators.
• Oktal — Part of the Sogeclair Group, Oktal provides SCANeR simulation software and integrated simulator systems for ADAS validation, autonomous-vehicle testing, and driver training.

Simulator Types and Categories

Automotive driving simulators are commonly segmented by their visual and motion capabilities:

Simple (Fixed-Base) Automotive Driving Simulators

Fixed-base simulators provide a vehicle cockpit, steering wheel, pedals, and a software-rendered driving environment but do not physically move the platform. They are the most affordable entry point and are widely used for driver training, HMI evaluation, and early-stage software testing where motion cues are not critical.

Single-Screen Active (Motion) Simulators

These systems add a motion platform — typically a Stewart platform or similar parallel kinematic mechanism — to a single forward-facing display. The motion system generates heave, pitch, roll, surge, sway, and yaw cues to supplement the visual scene, improving immersion and the realism of dynamic manoeuvres.

Multi-Screen (Three-Screen or Dome) Active Simulators

High-end simulators combine wide field-of-view visual systems — three or more screens, or curved projection domes — with high-bandwidth motion platforms. These configurations are used for advanced vehicle-dynamics research, ADAS/autonomous system validation, and professional motorsport development where peripheral vision and accurate motion fidelity are essential.

Primary Application Areas

• Vehicle dynamics development — Chassis, suspension, and powertrain engineers use simulators to evaluate handling behaviour and refine control parameters before physical prototypes are built.
• ADAS and autonomous vehicle validation — Safety-critical scenarios that are difficult or dangerous to reproduce on track (emergency braking, lane-departure events, sensor failure modes) can be run thousands of times in simulation.
• Driver training and assessment — Fleet operators, law-enforcement agencies, and motorsport academies use simulators to train drivers in hazardous conditions without risk.
• Ergonomics and HMI evaluation — Interior designers and UX teams use simulator environments to assess how drivers interact with infotainment, instrument clusters, and controls.
• Motorsport performance engineering — Racing teams use high-fidelity simulators for track familiarisation, setup optimisation, and driver-in-the-loop tyre and aerodynamic modelling.

Market Drivers and Restraints

Growth Drivers

• Rising investment in ADAS and autonomous driving technologies requires extensive simulation-based validation to satisfy safety standards such as ISO 26262 and UN ECE regulations.
• Electrification of vehicle powertrains creates new dynamics engineering challenges — simulators allow rapid iteration of motor calibration and regenerative braking strategies.
• Cost and time pressures in vehicle development programmes make simulator-based front-loading attractive compared with expensive physical prototype builds and track time.
• Growing adoption in driver-training applications across commercial vehicle fleets and public safety organisations.

Challenges and Restraints

• High capital cost of full-motion, high-fidelity systems limits adoption to well-funded OEMs, Tier 1 suppliers, and motorsport teams.
• Motion sickness and simulator adaptation effects can limit session durations and require careful platform tuning.
• Maintaining accurate, up-to-date vehicle and tyre models demands sustained investment in model development and correlation.
• Integration complexity when coupling simulator platforms with proprietary OEM software toolchains (e.g., MATLAB/Simulink-based control system models).

Geographic Landscape

Adoption is concentrated in regions with strong automotive OEM and motorsport ecosystems. Europe — particularly Germany, the UK, Italy, and the Netherlands — hosts both major simulator vendors and high-spending OEM customers. North America is a significant market driven by automotive R&D investment and defence/training simulation budgets. Asia-Pacific, particularly China, Japan, and South Korea, represents a growing segment as domestic OEMs increase investment in ADAS and EV development programmes.

Summary

The automotive driving simulator market spans a wide range of technologies — from low-cost fixed-base software tools to multi-million-dollar full-motion domes — serving use cases from driver training to autonomous-vehicle validation. Vendors such as Mechanical Simulation, Ansible Motion, Cruden, Dallara, Moog, and Oktal each occupy distinct niches within this ecosystem. As vehicle electrification, autonomy, and safety regulation continue to intensify, demand for high-fidelity simulation is likely to grow across the automotive value chain.

What Is an Automotive Driving Simulator?

Automotive driving simulators — commonly called sims — are a category of human-machine interface (HMI) systems designed to replicate the conditions a driver encounters behind the wheel. A well-engineered simulator reproduces:

• Driver perspective — field of view, mirrors, instrument cluster
• Motion and physics — vehicle dynamics, road surface feedback, inertial forces
• Vehicle interior and exterior environment — cabin acoustics, weather, traffic scenarios

Simulators are used across automotive engineering for driver behavior research, ADAS (Advanced Driver Assistance System) validation, vehicle dynamics tuning, and increasingly as a core development tool for autonomous vehicle software.

Market Snapshot

According to the source report covering the period 2018–2023, the global automotive driving simulator market was under cost pressure, with analysts projecting a negative compound annual growth rate (CAGR) of approximately -2.64% over that period. The report examined market volume and value across four primary regions:

• North America
• Europe
• China
• Japan

This negative CAGR reflects the cost dynamics discussed below rather than a decline in simulator adoption per se — high validation costs were identified as a key constraint on market expansion during this window.

Market Drivers

The primary driver identified in the source report is paradoxical: the high cost of validating simulation outputs increases the total cost of ownership (TCO) for simulator platforms. While this is simultaneously listed as a challenge, it also drives demand for better simulation toolchains — organisations that invest in simulation do so to reduce the even higher cost of physical prototype testing and real-world validation cycles.

Market Challenges

A notable challenge — and opportunity — is the emergence of augmented reality (AR) head-up displays (HUDs) and head-mounted displays (HMDs) as lower-cost alternatives to full-motion simulator rigs. These technologies allow OEMs and Tier 1 suppliers to introduce driving simulation solutions at a fraction of the capital expenditure required for traditional dome or hexapod-based systems, potentially disrupting the high-end simulator segment.

Key Market Trends

The most significant trend shaping the market is the use of automotive driving simulation algorithms as a foundation for autonomous vehicle (AV) development. Simulation environments allow AV stacks to be exposed to billions of scenario miles that would be impractical or unsafe to run on public roads. This use case has substantially raised the strategic importance of simulation software and hardware platforms within automotive R&D budgets.

Key Vendors in the Automotive Driving Simulator Market

The source report identifies the following companies as leading manufacturers in this space, analysed across product portfolio, geographic focus, business segments, and SWOT profile:

• Ansible Motion — specialist in driver-in-the-loop (DIL) simulators for vehicle dynamics research
• Cruden — provider of high-fidelity motion simulators for automotive and motorsport applications
• DALLARA — motorsport engineering firm with simulator capability
• Mechanical Simulation — known for vehicle dynamics software (CarSim, TruckSim)
• Moog — industrial motion platform and actuation systems supplier
• OKTAL (Sogeclair Group) — specialist in virtual testing and driving simulation software

What a Full Market Report Typically Covers

Commercial automotive driving simulator market reports in this category generally provide the following analytical layers:

• Historical market size data and multi-year forecasts segmented by product type, application, and region
• Market share, volume, and production capacity analysis at global, regional, and country level
• Supply chain analysis covering producers, distributors, and end-users
• Import/export dynamics and regulatory factors by region
• Competitive landscape with SWOT profiles of leading players
• Segment-level CAGR breakdowns
• Investment feasibility and ROI analysis for new market entrants

Why Simulation Matters for Modern Automotive Engineering

Driving simulators sit at the intersection of safety engineering, software validation, and human factors research. For DevOps and platform engineering teams working in automotive software development, the simulator is effectively a continuous integration environment for vehicle software — a closed loop where ADAS algorithms, firmware, and sensor fusion stacks can be tested against synthetic but physically accurate scenarios before any hardware-in-the-loop (HIL) or real-world testing phase begins.

Key use cases include:

• Regression testing of ADAS feature branches against a library of edge-case scenarios
• Driver behavior research to inform HMI design
• Vehicle dynamics model calibration prior to physical prototype build
• Autonomous driving policy training and validation in synthetic environments
• Safety case evidence generation for homologation

Summary

The automotive driving simulator market as described in this 2019 snapshot was navigating a tension between rising strategic importance — driven by autonomous vehicle development — and the persistent cost barriers of high-fidelity simulation hardware. AR/HMD technologies were beginning to offer lower-cost alternatives, while established vendors like Ansible Motion, Cruden, and Moog continued to serve high-end OEM and motorsport customers. For engineering teams, understanding the simulator landscape is increasingly relevant as simulation-first development pipelines become standard practice in automotive software delivery.