The Transportation Analytics Market is expected to grow from USD 10.5 Billion in 2020 to USD 27.6 Billion by 2024, at a Compound Annual Growth Rate (CAGR) of 21.6% during the forecast period.

Major competitors in the transportation analytics as IBM, Xerox, SAP, Space-Time Insight, Predikto, TSS-Transport Simulation Systems, Caliper Corporation, Tiger Analytics, T-Systems and Cyient.

The transportation industry is undergoing a dramatic transformation. Over the past few years, consumer preferences have become a driving factor in every aspect of business operations, from supply chain management to last-mile delivery. As consumer expectations continue to evolve, the industry will bring more revolutionary technologies to market to meet these demands. With many transportation companies hyper-focused on safety, compliance, and innovation, technology will become even more central to their business strategy in 2020. In particular, the availability of automation technology, the onset of 5G, and new opportunities for data analysis will bring many opportunities if companies are willing to jump on them.

13 October, 2020: IBM and Vodafone Idea Limited (VI) announced that IBM Services has been selected to help the leading telecom operator embrace open source at scale across the enterprise by implementing the Big Data Platform on open source Hadoop framework. As VIL's strategic technology partner, IBM is leading the end-to-end implementation and management of the Big Data Platform.  IBM is responsible for program management, consulting, system integration, infrastructure services, application operations, and maintenance support. Additionally, IBM is helping in enhancing network security. The IBM team's expertise is integral to supporting VIL achieve a reduction in the overall cost of data analytics. The insights from advanced data mining is empowering employees and partners in faster decision making and elevating the omnichannel, digital-first experience, for end customers.

In 2020, the industry has experienced the rise of 5G, which will drive the framework for the connected roadway. The increased bandwidth of 5G will allow for the placement of advanced sensors on roadways and traffic signals. The sensors will kick-start real-time data collection that allows for living 3-D maps, affording a safe environment for autonomous vehicles.

Future Transportation analysts

From smarter fleet telematics to  video intelligence, transportation technology is constantly advancing. But the driving force behind all of these technologies remains the same: fleets need to be safer, more productive, and as cost efficient as possible. To that end, fleet management solutions are progressing into new territory. Current  fleet maintenance management technologies are making excellent use of engine data, parts tracking, and other important information to monitor truck health and catch faulty or worn parts before they cause an expensive breakdown and excessive downtime for the driver. This is made all the more valuable by machine learning, which enables massive amounts of data to be analyzed effectively without requiring back-office staff to invest hours of manual labor. 

Trimble’s Fault Code Monitoring is a prime example of exactly this. A telematics device collects data from an engine’s electronic control module. This information includes everything from oil pressure to coolant levels, and it’s quickly analyzed to identify any indicators of potential fault. With that information in hand, fleets can ensure trucks receive preventative maintenance and needed repairs—instead of emergency roadside assistance. As machine learning continues to advance, expect to see the transportation industry further embrace predictive models and machine learning. This method of processing and interpreting data with a future-focused mindset has untold potential. From fleet safety and maintenance to driver retention, predictive analytics has plenty more to offer—and we intend to unlock those benefits. Trimble is committed to continuing to develop and deliver industry-leading solutions that make use of AI and machine learning.

In March 2020 the Innovate UK and Centre for Connected and Autonomous Vehicle part funded collaborative R&D project, HumanDrive, came to a close. The HumanDrive project developed an autonomous vehicle, which, in November 2019, completed a 230-mile drive from Cranfield to Sunderland, which was the UK’s longest autonomous journey to date. One of the primary outputs from the Human Drive project was the development of an Advanced Control System (ACS) (by Nissan and Hitachi), that was designed such that the autonomous vehicle would emulate a natural, human-like, driving style.       

The market is segmented into by application traffic management, logistics management, planning and maintenance, and other applications. By type it divided into Descriptive, Predictive and Prescriptive. Region wise it has contains North America, Europe, Asia-Pacific and Rest of the world. North America and Europe are anticipated to be the key regions over the forecast period owing to early adoption of transportation analytics solutions. Asia Pacific is anticipated to be the fastest growing regional market driven by growing smart city and smart transportation initiatives undertaken in the region.

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