International Journal of Traffic Management in Transportation Network (p: 3107-9504)

Smart Mobility and Planning Framework for Religious Tourism Management during Pitra Paksha Mela in Gaya, Bihar

Samad Shaheen — 2026-04-30

Pitra Paksha (fortnight of the ancestors) happens every year in the city of Gaya during the month of Bhadrapada or September and October as per the Hindu (lunisolar) calendar. This ritual of pind daan (offering homage to departed ancestors) includes Vishnupad temple, the sacred Phalgu River, Pretshila Hill, Mangla Gauri Temple and other places. Approximately 0.8 to 0.9 million pilgrims from all over the nation, as well as from outside, arrive in the city during this time. This number is twice the population of Gaya. Tourists stay for either a single day, or for three or for seventeen days. This results in two of the most prominent problems—accommodation and traffic. Due to insufficient accommodation in hotels, guest houses, and dharamshalas (a rest house for pilgrims), which get filled up quickly, people have to stay in temporary accommodation, such as on rent, in tents, at public schools, and so on. Traditional methods of crowd management and infrastructure are no longer sufficient to handle the scale of the event effectively and efficiently. A technology-driven approach can revolutionize the management of this important place of pilgrimage, making it more organized while enhancing the overall experience of pilgrims. Through a review of available literature along with case studies of sites that manifest similar religious congregations, this paper intends to (1) explore the present state of management of accommodation and transportation in the city of Gaya, and (2) suggest technological measures towards management of accommodation and transportation in the city of Gaya during Pitra Paksha. This is the first of its kind research related to Pitra Paksha in Gaya, which provides smart-technology oriented management of accommodation and transportation for better management of the city as well as for enhancement of pilgrimage experience.

Calibration of VISSIM Parameters for Modeling Heterogeneous Traffic Conditions at Intersections in Kathmandu

Aashish Manandhar — 2026-01-02

Kathmandu’s intersections, characterized by heterogeneous traffic conditions, present unique challenges in traffic modeling. Dominated by motorcycles, these intersections feature diverse vehicle types, exhibit side-by-side vehicle stacking, variable lane widths, and the absence of lane markings and road discipline. In Nepal, microsimulation models are typically developed using trial-and-error methods and are not properly calibrated to such conditions. This study proposes an automated calibration approach for microscopic traffic simulation models, providing calibrated parameter values tailored to local traffic conditions. Three intersections were modeled using VISSIM, a microscopic simulation tool. Sensitivity analysis was conducted using Latin Hypercube Sampling (LHS) and two-level ANOVA testing to identify nine sensitive calibration parameters. Optimization using a bi-level genetic algorithm minimized the error between the simulated and field traffic flow and queue-length data. This resulted in the following sensitive calibration parameters with the recommended range of values—minimum look ahead distance (10−20), look back distance [minimum (15−18.71) and maximum (107.94−150)], average standstill distance (0.3−1.5), safety distance part [additive (0.1−0.5) and multiplicative (0−1)], minimum clearance (front/rear) (0.49−0.73), and minimum lateral distance [standing (0.2−0.41) and driving (0.6−0.9)]. When validated against the videographic survey data, the outputs appear similar to the findings from Indian studies. However, the tolerance levels of the outputs suggest that we need our values rather than Indian values. This methodology and the outputs are expected to significantly reduce the time and effort required for calibrating VISSIM models in similar traffic environments.

Modelling Tanker Transportation Demand in Nigeria’s Crude Oil Market

Kenneth O. Okeke — 2026-02-03

Tanker shipping is a critical component of Nigeria’s crude oil export system and is largely driven by global economic conditions and shipping market dynamics. This study models tanker transportation demand in Nigeria’s crude oil market using annual time series data spanning 1990–2019. An auto-regressive distributed lag-unrestricted error correction model (ARDL-UECM) is employed to account for mixed orders of integration and to estimate both short-run dynamics and long-run elasticities. Tanker transportation demand is specified as a function of World GDP per capita, Brent and Bonny Light crude oil prices, global tanker fleet capacity, freight rates, piracy incidents, tanker accidents, ship turnaround time, and world population. The results confirm the existence of stable long-run equilibrium relationship among the variables. World GDP per capita emerges as the dominant determinant of tanker transportation demand, with a 1% increase in global GDP per capita leading to an estimated 2.55% increase in tanker transportation demand in the long run. In contrast, piracy incidents, tanker accidents, freight rates, and ship turnaround time exert negative but statistically weak effects, indicating that their effects operate through lagged and broader market mechanisms rather than direct short-run responses. Diagnostic tests, including the CUSUM and CUSUM of squares, confirm both parameter and variance stability of the estimated model. The study contributes to maritime economics literature by providing a unified ARDL-based tanker demand model that integrates global macroeconomic forces, shipping market dynamics, and Nigeria-specific operational risks, offering valuable insights for maritime policy, port efficiency planning, and tanker market forecasting.