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).
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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.
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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.
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