Market Overview
Predictive analytics is the practice of obtaining crucial information from existing data sets, in order to ascertain certain patterns and predict future outcomes and trends. It does not tell future or what will happen in the future rather it forecasts what might happen in the future with acceptable level of reliability. Predictive analytics has been largely used in transportation sector, where it provides valuable insights from data collected from numerous sources. These sources include vehicle location system, on-board sensors and data collection points embedded in fare and ticketing system, and scheduling and asset management system. Transportation predictive analytics and simulation software utilizes the extracted data to determine patterns and trends associated with transportation, in order to improve the efficiency of transportation operations.
The global transportation predictive analytics and simulation market is estimated to account for US$ 1,930.1Mn in terms of value by the end of 2019 and is expected to grow at a CAGR of 8.9% during the forecast period (2019-2027).
Market Dynamics- Driver
Growing popularity of IoT among consumers has increased the number of connected vehicles in the recent past significantly. OEMs are launching premium as well as mid-range cars with pre-installed sensors. These sensors enable automated driving capabilities, vehicle data tracking, and vehicle to safety pertaining to engine diagnostics and vehicle usage. Furthermore, connected cars can generate information related to traffic flow and density in real-time. This data can be obtained using transportation predictive analytics and simulation software, which facilitates better analysis of traffic flow.
The number of vehicles around the world has been increased significantly in the recent past. This mainly due to significant growth in transportation infrastructure. According to GOV.UK, 2019, all motor traffic increased by 0.8% from 2018. Increasing population in cities is exerting pressure on road networks, leading to overcrowded road networks, lack of safe public transportation modes, poor traffic management, parking issues, road safety concerns, and poor road conditions. Predictive analytics and simulation software for transportation collects the data from sensors embedded in vehicles and process it to produce meaningful insights. This analysis can help to manage the road traffic flow efficiently and reduce congestions on the roads.
North America region dominated the global transportation predictive analytics and simulation market in 2018, accounting for 31.3% share in terms of value, followed by Europe and Asia Pacific, respectively
Source: Coherent Market Insights
Market Dynamics-Restrain
Predictive analytics and simulation software is complex software to use, where it requires highly skilled operators. These operators should be able to process data refining and preparation, build predictive models, and integrate these models into application environment. Moreover, the problems sway between lack of skilled operators and availability of skilled operators at expensive price. This, in turn, is expected to restrain the market growth over the forecast period.
The data collected from wide range of systems and multiple sources are heterogeneous, high-dimensional, and highly noisy with complex interdependencies. Such expansive and diverse amount of data is challenging to process on real-time basis and convert it into useful insight for near-real operations or even for long-term process is extremely challenging. Moreover, low latency and data reliability, which is required to be translated into actionable intelligence to improve safety and for collision avoidance is expected to hamper the market growth over the forecast period.
Market Opportunities
Managing the transportation system of city is a challenging task, which includes road safety, parking management, reduction of traffic congestion, and vehicle-to-vehicle safety. Smart city projects are increasingly rapidly worldwide, owing to proactive government initiatives, growing digitization in various industrial verticals, and rapid adoption of IoT and big data. For instance, in 2016, the U.S. Department of Transportation invested around US$ 350 million for smart city and advanced transportation technologies. This, in turn, is expected to pose significant growth opportunities in the near future.
Many transit companies have been demanding data driven information. Companies such as Lyft and Uber use predictive analytics and simulation software where they can determine if the demand is the highest from specific region and whether the required number of fleet of cabs is available in that particular region. Companies sends message to driver in such situations so that they will reach specific area, so as to cater to the requirements.
Source: Coherent Market Insights
Market Trends
Introduction of IoT, the number of connected devices has been increased significantly and is expected to rise further during the forecast period. These devices create large amount of data, which can be analyzed and used for transportation sector. This data can be used to obtain valuable insights with the help of predictive analytics software, which has increased the demand for the same software.
A number of data analytics transport companies are developing microscopic simulation platforms, since microscopic simulation emphasizes on individual vehicles and their interactions, which in turn, helps traffic engineers and transport planners to evaluate the urban traffic system and suggest suitable infrastructure. For instance, Advanced Data Analytics in Transport (ADAIT) team piloted a microscopic simulation on their new smart motorway control system for Sydney M4, which is an arterial route in Sydney, Australia. The simulation showed that travel time savings can reach 40% during peak hours by adding an extra lane to existing route. This also means, it will save around US$ 22 million per annum on part of M4 alone and possibly over US$ 500 million per annum savings to the whole system in Sydney.
Segment information:
In global transportation predictive analytics and simulation market, by component of transport segment, roadways sub-segment dominated the global transportation predictive analytics market in 2018, accounting for 41.0% share in terms of value.
Source: Coherent Market Insights
Competitive Section
Key companies involved in the global transportation predicative analytics and simulation market are Cubic Corporation, T-Systems International GmbH, IBM Corporation, Tiger Analytics Inc., PTV Group, Cyient-Insights, Xerox Corporation, Predikto Inc. SAP AG, and Space-Time Insight.
Key Developments
Predictive analytics is the practice of obtaining crucial information from existing data sets, in order to ascertain certain patterns and predict future outcomes and trends. In transportation, predictive analytics and simulation software is used to determine traffic patterns and predict future outcomes and trends concerned with transportation. Predictive analytics has been largely used in transportation sector, where it provides valuable insights from data collected from numerous sources. These sources include vehicle location system, on-board sensors and data collection points embedded in fare and ticketing system, and scheduling and asset management system. This software provides various results to the transportation sector such as predictive maintenance, traffic optimization, network & capacity optimization, revenue optimization, and customer behavior. This software finds applications in different components of transport including railways, roadways, seaways, and airways as it can offer cost-saving operations for these components.
Market Dynamics
Growing popularity of IoT among consumers has increased the number of connected vehicles in the recent past significantly. OEMs are launching premium as well as mid-range cars with pre-installed sensors such as OBD-II, vehicle tracking, black box among others. These sensors enable automated driving capabilities, vehicle data tracking, and vehicle to safety pertaining to engine diagnostics and vehicle usage. Furthermore, connected cars can generate information related to traffic flow and density in real-time. This data can be obtained using transportation predictive analytics and simulation software, which facilitates better analysis of traffic flow. Moreover, now a days this data is used by insurance company to determine the driving pattern of the customers and to provide them a usage based insurance (UBI). Predictive analytics and simulation software for transportation offer cost-saving operations. Freight carriers in transportation sector require constant maintenance, which is the major reason behind increase in costs. Transpiration predictive analytics and simulation software provides predictive maintenance for vehicles by collecting data from sensors installed in vehicles and ascertaining which components are most likely to require immediate attention. Owing all these benefits the demand for transportation predictive analysis and simulation software is increasing globally.
Market Taxonomy
This report segments the global transportation predictive analysis and simulation market on the basis of component, simulation method, development model and component of transport. On the basis of component, the global transportation predictive analysis and simulation market is segmented into software and services. On the basis of simulation method, the market is segmented into microscopic, macroscopic, and mesoscopic. On the basis of development model, the market is segmented into on-premise, and cloud-based. On the basis of component of transport, the market is segmented into roadways, railways, airways and seaways.
Key features of the study:
Detailed Segmentation:
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