Efficient toll plaza operations are critical to minimizing congestion and travel delay on high-volume highway corridors. This study investigates the operational performance of a major toll plaza on National Highway-75 (NH-75), India, using queueing theory–based analytical models. Field data were collected at the Neelmangala–Devihalli Toll Plaza, including traffic volume, time headway, arrival rates, service times, and space mean speeds under mixed traffic conditions. Statistical analysis confirms that vehicle arrivals follow a Poisson process, while service times exhibit a general distribution, justifying the application of both M/M/1 and M/G/1 queueing models. Key performance indicators such as system utilization, average queue length, and vehicle waiting time were derived to evaluate toll booth efficiency during peak and off-peak periods. The results indicate that congestion is primarily driven by high arrival rates during peak hours, limited toll booth capacity, and downstream lane merging constraints rather than insufficient roadway capacity. The analysis further demonstrates that the adoption of electronic toll collection (FASTag), optimized lane allocation, and selective booth expansion can significantly reduce average waiting times and improve throughput. This research highlights the practical applicability of queueing theory as a decision-support framework for diagnosing operational bottlenecks and guiding data-driven improvements in toll plaza planning and management on Indian highways.
Pandey et al. (Fri,) studied this question.