Leveraging AI for the benefit of Bangladesh’s road transport sector
Dr. Nasim Ahmed :
Bangladesh Economic Review 2024 published by the Ministry of Finance in June 2024 revealed that the contribution of the transport and communication sector to GDP was 7.34% and 7.29% in financial years 2021-22 and 2022-23 respectively and the rate of growth was 5.75% and 5.49% in corresponding financial years. Up to February 2024, the country’s highways were 22,476 kilometers, of which 18% were national highways, 22% were regional highways, and 60% were district roads.
Bangladesh Road Transport Authority (BRTA) issued 4,531,731 digital registration certificates up to March 2024 and earned Tk 2020.13 crore in 2022-23 revenue against the target of Tk 3054 crore. The target achievement was 66.15%. Up to March 2024, it earned Tk 1594.06 crore with a target achievement of 31.91%. In the financial year 2022-23, Bangladesh Road Transport Corporation (BRTC) accumulated Tk 631.78 crore as revenue with an operating surplus of Tk 41.71 crore. Till January of the financial year 2023-24, the revenue earning of BRTC was Tk 338.13 crore with an operating surplus of Tk 19.26 crore.
Transport sector experts and engineers opine that the road transport sector in Bangladesh has a greater prospect for the country’s socio-economic development with the use of artificial intelligence (AI). The revenue earning could have been doubled had the sector been supported by professional integrity, effective institutional capacities, and technology like AI. The risks associated with the transport sector, for instance, accidents, casualties, and death can be reduced with AI.
The use of AI can facilitate the road transport sector in major areas such astraffic management and congestion reduction, road safety, optimizing public transport systems, logistics, and freight management, infrastructure planning and management, environmental benefits, enhanced user experience, etc.
AI can optimize traffic signal timings based on real-time traffic conditions, reducing congestion and improving traffic flow. AI algorithms predict traffic patterns and suggest alternative routes, to alleviate congestion during peak hours or in case of accidents. AI operating systems can dynamically allocate lanes based on traffic density, ensuring better road space utilization.
It analyzes historical accident data and real-time traffic conditions to predict potential accident hotspots. AI-based systems can monitor driver behavior (e.g., fatigue, distraction) and provide alerts or interventions to prevent accidents. It can facilitate quicker response to accidents by automatically notifying emergency services and providing location data.
AI can optimize commercial vehicle routes and schedules based on passenger demand, reducing waiting times and improving service efficiency.
Its engineered predictive maintenance can monitor the condition of public transport vehicles and forecast potential failures, ensuring timely maintenance and reducing downtime. AI provides real-time updates to passengers about bus locations, arrival times, and delays, enhancing the user experience.
Also it can optimize logistics and supply chain operations by foreseeing demand, optimizing routes, and managing inventory more efficiently. It helps monitor and manage fleets of trucks, optimize routes, reduce fuel consumption, and ensure timely deliveries. It helps integrate electric vehicles into the transport network, optimize charging station locations, and manage energy demand.
AI analyzes data from various sources (for instance, traffic cameras, and sensors) to provide insights for infrastructure planning and development. It can monitor road conditions in real-time, identifying issues such as potholes or structural damage, and prioritizing maintenance activities.
AI can provide personalized travel recommendations based on user preferences, real-time traffic conditions, and available transport options. It can facilitate seamless and contactless ticketing systems for public transport, improving users convenience.
However, employing AI is not without challenges and technical hindrances. Effective AI systems require high-quality, real-time data. Ensuring data availability and accuracy can be difficult. Existing traffic management systems may not be equipped to handle the data requirements of AI-based solutions.
Poor road conditions and inadequate infrastructure may make it problematic to introduce AI technologies: for instance, automatic vehicles. Limited internet connectivity particularly the digital divide in many areas can affect the performance of AI systems. A shortage of skilled professionals with expertise in AI and related technologies is a problem. Integrating AI with existing transport systems and infrastructure can be complex.
Implementing AI in road transport raises regulatory and ethical issues, such as data privacy, cybersecurity, and the impact on employment. Unpredictable driving behaviors and non-adherence to traffic rules can pose challenges for AI systems designed for traffic management and safety.
AI offers transformative potential for road transport by enhancing efficiency, safety, and user experience. A multidimensional approach involving collaboration between government, industry, and substantial investment in infrastructure and capacity building, is required to reap the overall benefits of AI.
With the adoption of AI, Bangladesh’s road transport sector has a brighter prospect, if supported by government initiatives, and increased private sector participation. The country can significantly improve its road transport sector and services by addressing implementation challenges and leveraging AI technologies, contributing to economic and social development.
(The author is Associate Professor (PhD in Public Policy, Ulster, UK) Bangladesh Institute of Governance and Management (BIGM) (Affiliated with the University of Dhaka) Agargaon, Sher-e-Bangla Nagar, Dhaka.)