• 出版社/出版日：Mordor Intelligence / 2021年1月
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The vehicle analytics market was valued at USD 1.74 billion in 2020 and is expected to reach a value of USD 6.34 billion by 2026 at a CAGR of 24.3% over the forecast period from 2021 to 2026. Digitization has become an essential driver of innovation in the vehicle industry. With vehicles generating volumes of data in seconds, the opportunity to deliver superior customer experiences and business processes is becoming more significant than before. At present, cars account for at least 50 sensors designed to collect more detailed information, such as speed, emissions, distance, resource usage, driving behavior, and fuel consumption. The generated data gives the automotive industry stakeholders to use it for further analysis, create relation analysis, and enable better utilization.
– With the congestion of city streets and sidewalks, city planners face new safety challenges, such as distracted pedestrians, more bicyclists, and an increase in public transportation. Moreover, local government agencies and transportation departments are tapping video analytics solutions to analyze real-world data regarding traffic patterns and road conditions. The analysis of various parameters, areas with poor road conditions, and bottlenecks that create traffic delays can be identified. Thus, aiding in planning and prioritization of improvements. Moreover, the market is expected to grow, owing to the rising adoption of predictive analytics, which has been a logical upgrade for the end-users, who have adopted some means of automation and data collection solutions.
– The predictive analytics applications enable the end-users in evaluating prior patterns and driving behavior, arriving on the decision on the likelihood of various future possibilities. Apart from this, growth in the connected car industry is expected to provide a significant number of challenges, as well as opportunities to the automotive sector, including analytics, and it has been a massive impetus for innovations. Cars of the future are poised to present immense intelligence with dense connectivity. Also, vehicle connectivity allows the vehicles to interact, navigate, and collaborate without human mediation and enables analyzing collected data. By leveraging advanced sensors, enhanced connectivity, and big and high-speed data, predictive analytics can help eliminate vehicle accidents.
– The market is gradually getting fragmented due to the emergence of startups for the past one year. In January 2019, Carmen Automotive, a data analytics company serving automotive insurers and servicing centers, raised USD 730,000. Carmen’s predictive technology reads real-time data (battery life, fault codes, fuel efficiency, and mileage) via its proprietary hardware. In October 2019, Tactile Mobility, tactile virtual sensing, and data company headquartered in Haifa, Israel, secured USD 9 million. It provides tactile sensing and data analytics solutions for smart and autonomous vehicles, municipalities, and fleet managers. It uses machine learning to provide real-time insights into private cars and road conditions and driving safety.
– It was predicted that among all the mobility services, carpooling would occupy the maximum share by 2025 due to government regulations and awareness regarding reduced greenhouse gas emissions. However, due to the spread of COVID-19, it is expected that owned car usage is likely to surpass carpooling to stop the spread of the virus and maintain social distancing. This would further increase the amount of data being generated for vehicle analytics. However, the installation of vehicle analytics solutions in new cars would not witness significant growth. Due to the economic slowdown, the sales of automobile vehicles have suffered. According to J.D. Power, new car sales in April were off by 45% compared to 2019. Furthermore, researchers established that 445,600 fewer new cars were sold in April compared to their sales forecast.
Key Market Trends
Predictive maintenance is Expected to Hold Significant Share
– As automakers are continually assessing the vehicle part’s performance in real-time through sensors, it unlocks the opportunity toward a predictive maintenance approach. Using predictive maintenance, data can be pulled out from a majority of the vehicles of a given year and model, and that information can be compared with warranty repair trends. These trending issues are carefully observed and addressed, limiting the fallout from large-scale recalls, minimizing unnecessary wrench time, and potentially saving lives in the process. The Defense Innovation Unit (DIU) plans to bring predictive maintenance to the Navy, aimed at keeping naval, aircraft, and ground vehicles online and avoiding costly last-minute repairs. This will help in a greater understanding of a vehicle’s life and health since it is critical for the military.
– Moreover, vehicle breakdowns are one of the significant causes of road accidents. These breakdowns often occur due to human negligence in the timely service and maintenance of vehicles. Predictive analytics solutions inform the owner beforehand regarding the potential requirement of maintenance before a breakdown can occur. Data collected from the various sensors fitted in a car assists in carrying out predictive maintenance tasks. The market has growth potential as the demand for electric vehicles increases. In EV(s), variation in voltages during charging can damage the battery. Predictive analytics integrated with artificial intelligence (AI) facilitates the feedback and monitoring system for batteries to avoid unnecessary damage that assists in extending the lifespan of batteries.
– A recent study by the Technology & Maintenance Council and FleetNet America found that the cost of an unscheduled truck repair was USD 407 in the third quarter of 2019, 24% higher than mechanical maintenance in the same quarter in 2018. Five vehicle components accounted for 64% of all roadside repairs experienced by participating fleets, such as tires, brakes, lighting, power plants, and cooling systems. Frito-Lay North America, a PepsiCo unit, said its fleet began using predictive maintenance practices in 2017. These practices resulted in a measurable decrease in on-road breakdowns and spending and have reduced technician diagnostic time. Additionally, organizations relying on vehicles in daily operations, such as logistics and transport companies, are aware of keeping the vehicle downtime to a minimum.
– Uptake, an industrial artificial intelligence software company, considers underlying signal data, such as battery cranking voltage, transmitted in subsecond intervals when the truck starts. That information is combined with recent trending data and historical failures from that fleet. In May 2020, Verisk, one of the prominent data analytics provider, added Liability symbols to ISO Risk Analyzer Commercial Auto to help insurers improve loss ratios and price their commercial auto risks accurately. Using the new Liability symbols in ISO Risk Analyzer Commercial Auto can help decrease an insurer’s loss ratios through the combined power of Verisk’s loss costs data and machine learning capabilities.
Asia-Pacific is Expected to Register Highest Market Growth in the Forecast Period
– Asia-Pacific is the fastest-growing region since it is witnessing a growing dominance of connected and autonomous vehicles. Also, increasing the penetration of new technology companies making ways into the automotive industry is expected to lead to a new automotive analytics era. China laid out a plan to have at least 30 million autonomous vehicles within a decade until 2028 which is expected to drive automobile analytics demand. The government has been very active in terms of adopting technology to help policy implementation. China is also planning to ease quotas designed to boost the production of electric cars, in an attempt to help automakers revive its sales.
– In April 2020, Ideanomics announced that the Chinese State Council issued a Three-Year Action Plan for the Battle of the Blue Sky, accelerating the company’s Blue Sky Plan. Blue Sky Plan was the development of an eco-friendly transport system with higher fuel efficiency and lower emissions and included fines for pollution, carbon emissions, and water contamination. The plan consists of agreements of 24 provinces and cities to accelerate the adoption of new energy vehicles. Ideanomics’ Mobile Energy Global (MEG) group has already started working with seven of the priority regions. Many regions in China plan to promote conversion to electric vehicles (EVs). This presents a new opportunity for market vendors.
– In October 2019, the self-drive mobility platform, Zoomcar, announced that it launched India’s first vehicle agnostic Driver Score Tech Stack with the passenger car segment. The AI-powered algorithm with machine learning abilities tracks the car’s mechanical specifications, driving style of the consumer. It identifies grave events of driving and rates it on a scale of 0-100. In the case of rash driving, the scoring system can give real-time feedback to drivers, which helps them adjust their behavior accordingly. Zoomcar, within the first month, was able to reduce the accident rate by 20% and the maintenance and service cost by 25% with the help of Driver Score.
– In April 2020, Ping An Insurance announced that the “Ping An Auto Owner” app had surpassed 100 million registered users. The app which was launched by Ping An Property & Casualty Insurance Company of China, Ltd., has 25 million monthly active users and is one of the top-ranked auto service apps in China. About half of the app users are existing auto insurance customers of Ping An Property & Casualty. The app utilizes Ping An’s artificial intelligence (AI) and big data analytics technology in a platform to connect car owners to car dealers and other automotive service providers. Since the outbreak of the novel coronavirus in January 2020, the app has provided services to approximately 12.3 million users, with online self-service insurance claims accounting for 40% of the services.
Owing to the presence of significant players in the market, the competitive rivalry in the market is high. Some of the key players in the market are SAP SE, IBM Corporation, Cloudmade Ltd, Harman International Industries Inc., Genetec Ltd, and many more. Their ability to continually innovate the products by investing heavily in R&D has allowed them to gain a competitive advantage over their competitors, which has enabled them to gain significant market share over others.
– March 2020 – Genetec announced the availability of its next-generation mobile license plate recognition system. The new AutoVu SharpZ3 goes beyond traditional license plate identification and brings unique insight into vehicle analytics, situational awareness, and accuracy. It utilizes Intel’s latest machine learning and computer vision technology to unlock new insights through analytics.
– November 2019 – IBM partnered with ElectraLink and Western Power Distribution (WPD) to commence the Virtual Monitoring (VM) Data project. The project will investigate the feasibility of creating half-hourly load profiles for WPD customers, including those with electric vehicles and LCTs installed, which can be fed into a VM tool for WPD’s local network, using cognitive analytics, various data sets, and proof of concept models. It will use IBM’s advanced analytics services and IBM Watson Studio.
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1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview (Covers the impact due to COVID-19)
4.2 Industry Attractiveness – Porter’s Five Force Analysis
4.2.1 Bargaining Power of Suppliers
4.2.2 Bargaining Power of Consumers
4.2.3 Threat of New Entrants
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
5 MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Growing Adoption Of Vehicle Telematics
5.1.2 Advancements in Technology, Such as Artificial Intelligence and Predictive Analytics Leading to Applications in Vehicle Management
5.2 Market Restraints
5.2.1 High Cost of Solutions Limiting Adoption in High End Cars
6 MARKET SEGMENTATION
6.1 By Deployment
6.2 By Application
6.2.1 Predictive Maintenence
6.2.2 Safety and Security Management
6.2.3 Driver Performance Analysis
6.2.4 Other Applications
6.3 By End-user Industry
6.3.1 Fleet Owners
6.3.3 OEMs and Service Providers
6.3.4 Other End-user Industries
6.4.1 North America
6.4.4 Latin America
6.4.5 Middle East & Africa
7 COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 SAP SE
7.1.2 Cloudmade Ltd
7.1.3 Genetec Inc.
7.1.4 HARMAN International Industries Inc. (Samsung Electronics Co. Ltd)
7.1.5 IBM Corporation
7.1.6 Inquiron Ltd
7.1.7 Intelligent Mechatronic Systems Inc.
7.1.8 Teletrac Navman US Ltd
8 INVESTMENT ANALYSIS
9 FUTURE OF THE MARKET