The rapid advancements in information and communications technology (ICT) are helping the transportation industry switch to intelligent transportation systems, which have the potential to deliver a higher throughput on the existing transportation infrastructure, improve customer safety and reduce fuel consumption. These solutions also help address challenges such as capacity constraints, rising fuel costs and environmental pollution, as well as comply with strict emission norms.
Over the past few years, transportation enterprises have adopted several new technological tools such as radio frequency identification (RFID) and barcode scanners to maximise their supply chain efficiency. As per industry estimates, transportation companies using RFID are able to achieve nearly 100 per cent inventory, shipping, and receiving accuracy, 30 per cent faster order processing and 30 per cent reduction in labour costs. In the private vehicles segment, automobiles built after 2010 are equipped with a number of connected systems that enable the drivers to stream videos, view and use smartphone apps, navigate locations, request roadside assistance, unlock doors remotely, and find open parking spaces.
Today, next-generation ICT solutions such as cloud computing, internet of things (IoT), artificial intelligence (AI) and data analytics are allowing transportation companies to make more informed decisions about their operations. The vehicles are being equipped with powerful sensing, networking, communication and processing capabilities, which facilitate interaction with other vehicles, or exchange of data with external environments. These have made it possible to develop a range of innovative telematics services such as remote security and repair of vehicles.
IoT
IoT has the potential to transform the transportation industry. IoT devices can provide valuable information such as travel time, directions to the destination, vehicle volumes and traffic movements through GPS-enabled sensors. It can ensure effective fleet management by enabling intelligent tracking and monitoring of vehicles. Further, it can be used for streamlining transport logistics by tracking containers and packages through on-board sensors. This will minimise human intervention, prevent theft and product damage, and reduce fuel costs. It can also help reduce traffic congestion by automatically monitoring and controlling traffic lights, identifying structural problems in bridges, tunnels and roadways, determining traffic status and improving routing. Besides, it can play a key role in automating toll collection and implementing dynamic pricing of toll charges. In railways, IoT can be used in control and collision avoidance systems and for automatic scheduling and rerouting of trains. It can also help in smart parking by giving real-time information about parking status, thereby enabling organised parking and increasing utilisation of parking spaces. IoT can monitor vehicle carbon emissions as well.
IoT can also help enterprises communicate with drivers any time and anywhere, allowing them to be proactive in field repairs, maintenance, etc. Further, by leveraging IoT, city administrations can construct smart roads. The sensors installed on roads will be able to determine the number of cars in each lane and operate the traffic lights based on this information. These sensors can also be used to redirect traffic in response to an accident or other type of hazard.
Going forward, IoT is expected to play an enabling role in the autonomous vehicles segment by helping these vehicles adjust their speeds and directions depending on the information received from connected devices, vehicles as well as other external means.
Cloud computing
In the transportation industry, the key role of cloud computing is to bring the data on various parameters such as ridership, traffic status and toll collection on to a simple and secure dashboard. Transportation agencies using cloud platforms are able to gain access to this data in real time, thereby enabling them to make quick adjustments for better service delivery. Moreover, with the help of cloud solutions, the industry is able to save a considerable amount of time, which is otherwise spent on planning, procuring and deploying IT infrastructure to connect the embedded transportation devices, as in the case of traditional computing networks. For instance, UK-based firm Rolls-Royce is leveraging Microsoft Azure cloud-based services to enhance the performance of its plane engines, reduce fuel usage, improve maintenance, decrease downtime and improve the passenger experience. With companies increasingly relying on cloud technologies, customers can also enjoy better service uptime and reach their destinations in time.
Cloud is also helping transportation companies enhance their business performance by improving operational efficiencies, and creating innovative revenue and business models. Simpler and faster cloud-based processes can help enterprises achieve higher internal efficiency, reduce complexity, provide access to more and broader datasets, and expand their IT capacity as per the business volumes.
Data analytics
An unprecedented amount of data is being generated in the transportation industry through the IoT devices installed in vehicles, customers’ social media feeds about travelling experiences, etc. By using big data, this information can be turned into actionable insights. For instance, transport authorities can leverage big data to gain an accurate understanding of customer demand on different routes. Besides determining the frequency and size of vehicles on existing routes, they can use this data to efficiently plan future routes. This will help reduce customer wait time, thus leading to increased ridership. Further, the authorities can map customer journeys across multiple modes of transportation and plan additional services. For instance, food outlets can be opened at locations that are frequented by a large number of people at breakfast, lunch and dinner time. Big data can also play a significant role in predictive maintenance by enabling the authorities to forecast the maintenance requirements of vehicles.
AI
AI is making inroads into all segments of the transportation ecosystem, including private, public and cargo transportation, as well as in traffic management operations. In private transportation, AI is being used to design self-driving cars, which are theoretically more efficient than driver-operated vehicles. The first iteration of autonomous cars has already been introduced. These cars come with advanced active safety capabilities such as auto-braking, road sign understanding and lane deviation alerts.
In public transportation, small-scale autonomous bus trials have been initiated in countries such as Finland, Singapore and China. However, the variations in built-up structures, city infrastructure, road surfaces, and weather and traffic patterns are preventing the standardisation of such vehicles. Smart freight locomotives equipped with sensors are being developed for improving cargo transportation. The data from the sensors is fed into machine-learned analytic applications to enable real-time decision-making. With regard to traffic management, AI solutions are being used to convert traffic sensors into intelligent sensors, thereby helping predict and mitigate accidents.
Key challenges and the way forward
Next-generation technological solutions are significantly improving the way transportation businesses operate. They have increased passenger safety, improved productivity and reduced fuel consumption. Further, transportation enterprises are connecting all devices across a centralised cloud network, and capturing and sharing their mission-critical data to gain real-time visibility into their end-to-end operations.
However, as in other enterprise verticals, cybersecurity has emerged as a major concern for technology adoption in the transportation industry as well. As a growing number of city transportation systems such as traffic lights, road sensors, mass transit rail or bus, ports, and airport vehicles are getting connected to the network, cybercriminals are finding more opportunities to attack not only a city’s IT infrastructure, but also the operational technology infrastructure that runs its signalling and control systems. This implies that cybercriminals could potentially cause significant disruptions by remotely operating the city’s transportation infrastructure. Meanwhile, experts are cautioning against the large-scale use of AI in transportation since some of the pilot tests of self-driving vehicles have failed to generate the desired results. Another key challenge that enterprises face in the transportation industry with regard to managing their IT and telecom infrastructure pertains to the high costs of running and maintaining a large IT set-up. Since IT is not their core strength, these enterprises need a dedicated team to oversee their IT infrastructure. Enterprises in the transportation industry need to optimally utilise ICT solutions to improve their operational efficiency and make the future transport services safer, smarter and greener.
