Enterprises in the transportation sector are increasingly leveraging ICT solutions to improve their overall efficiency and deliver world-class services. These solutions have not only facilitated the development of next-generation intelligent transportation systems, they have also enabled the provision of informed, secure, cost-effective, convenient and greener mobility.
Enterprises in the sector are deploying new advanced technologies such as artificial intelligence (AI), machine learning (ML), internet of things (IoT), cloud and big data in order to improve decision-making, enable real-time monitoring and simplify traffic management. These solutions are the backbone of autonomous vehicles, aerospace travel and on-demand taxi services such as Uber and Ola cabs. However, concerns related to cybersecurity and high costs associated with running and maintaining a vast IT set-up still need to be addressed.
A look at the key ICT solutions being leveraged by transportation enterprises…
AI and ML
AI and ML technologies are enabling stakeholders in the sector to efficiently utilise modern computing and communication technologies. According to industry reports, the global market for AI in transportation is expected to reach $3.5 billion by 2023. The use of AI/ML in transportation helps reduce traffic congestion and accidents, lower carbon emissions and ensure passenger safety.
For instance, with the help of AI/ML, Uber ensures efficiency in several areas of operation, including transportation and mobility, driver-partner navigation and customer support. Uber’s Map Services team uses ML models to predict errors in its existing estimated time of arrival (ETA) system. In addition, it makes corrections based on the errors predicted. According to Uber, the adoption of the ML model has significantly increased its ETA prediction accuracy.
Some use cases of AI are:
- Self-driving vehicles: AI ensures real-time data transmission and processing in driverless vehicles. The ability of AI to manage and process data and optimise connectivity makes autonomous vehicles safer and more widely acceptable.
- Traffic management solutions: AI/ML technologies are used in traffic management and decision-making systems. With the help of AI/ML, stakeholders enhance and streamline traffic management and make roads smarter. Besides, AI’s predictive abilities enable the identification of physical and environmental conditions that can lead to heavier traffic flow and congestion.
- Delay predictions: At present, flight delays are one of the most common problems faced in air transport. With data lake technology and computer vision, continuous monitoring of airplanes can be carried out, eliminating unplanned downtime. Further, AI/ML components can process real-time airplane data, historical records and weather information to provide on-route efficiency.
- Route optimisation: The vehicle routing problem can be addressed by applying ML-powered route optimisation software. ML technologies can identify an optimal route to depots for multiple customers while minimising the road costs and number of vehicles. For instance, Valerann, an Israeli-British start-up, has developed a smart road system. The AI algorithm deployed in the system leverages wireless sensors integrated in roads to track road conditions and predict the situation on highways.
According to industry reports, the value of IoT in the transportation market is set to grow from $135 billion in 2016 to $328 billion in 2023. By leveraging IoT solutions, enterprises are able to optimise costs and increase fleet productivity. IoT devices equipped with GPS-enabled sensors provide valuable information such as travel time, directions to the destination, vehicle volume and traffic movement. These devices are deployed in traffic congestion control systems, telematics systems within motor vehicles and remote vehicle monitoring systems.
Furthermore, IoT-enabled predictive asset management can help avoid issues such as frequent breakdown of vehicles and failures in transport networks as IoT systems constantly monitor the health parameters of vehicles to help identify potential problems in advance. These devices can be installed at bus stations to collect and transmit data regarding the ETA. Besides, intelligent transport logistics solutions can be used to track cargo condition and location in real time; automate scheduling, placement and delivery; and proactively manage vehicle capacity. Moreover, IoT can be used for automating toll collection and implementing dynamic toll pricing.
Enterprises in the transportation sector have started leveraging cloud computing to store data related to ridership, traffic status and toll collection on a secure dashboard. The data can be collated to provide real-time insights on fare collection, passenger count, etc. Some of the use cases of cloud computing are:
- Public transportation: To ensure smooth operations, public transportation systems across the world use cloud computing. For instance, some cities monitor and forecast traffic in order to make transit easier and keep track of delays and passenger count to inform citizens.
- Railroads and airlines: Private transportation companies are leveraging cloud technology to manage passengers and vehicle routes. With the help of these technologies, enterprises in airlines and railroads inform travellers of delays and available seats using real-time data.
- Vehicle health monitoring: Vehicles in the sector are mostly strained to meet tight schedules, which raises concerns about their operational health. In order to address this issue, transportation companies can install sensors at vehicles’ critical components that constantly feed data to a cloud-powered analytical tool. As the value of a sensor exceeds the defined threshold, the vehicle can be scheduled for repairs.
Big data analytics enables conversions of the enormous amount of data generated by connected devices and sensors, on or off the vehicles, into actionable insights. With the help of insights on travel patterns, authorities can tailor communication for riders through their preferred communication channels. This includes communicating information about changes in any service on a route that a customer frequents, weather-related events that might impact service and alternative routes in such cases.
Leveraging big data technologies, enterprises in the sector can ensure operational efficiency and flexibility, reduce fuel consumption, and provide better customer experiences while improving safety in transportation. Information from sensors installed on vehicles can be analysed at a much faster rate and at a granular level using big data. For instance, in case of delivery address changes, the system allows companies to quickly and easily calculate the best route to the new destination.
In June 2020, the National Highways Authority of India went fully digital with the launch of a cloud-based and AI-powered big data analytics platform, Data Lake and Project Management Software. With advanced analytics, Data Lake software will forecast delays and provide advance alerts. This system will expedite the decision-making process, ensuring correct and timely decisions.
Challenges and the way forward
While the deployment of advanced technologies ensures transport efficiency and safety, they typically entail a high cost. Besides, challenges related to the integration of these solutions with the existing IT infrastructure, and skill development of the existing workforce to use new-age ICT solutions are hampering their adoption. Meanwhile, cybersecurity has emerged as a key area of concern with regard to technology adoption in the transportation industry.
Challenges notwithstanding, ICT adoption in the transportation industry is poised to grow considerably as the country moves towards a smart transport medium. With the growing demand for on-board entertainment and surveillance and security, ICT has become central to customer satisfaction and safety. Going forward, this trend will only gain momentum with the increasing reliance on automation. That said, future transport services need to be safer, smarter and greener, and ICT will play a critical role in achieving these objectives. s
By Shikha Swaroop