Microscopic Traffic Characterization of Light Rail Transit Systems at Level Crossings

The movement of the light rail vehicles (LRVs) is highly interrupted at level crossings during peak hour times, especially when the intersections are not regulated by a coordinated signal system. Traffic modelling ensures better understanding and interpretation of complex traffic interactions. This study is aimed at modelling light rail transit (LRT) system operational characteristics at level crossings in Addis Ababa City using VISSIM software. The studied scenarios at Sebategna (All Way Stop Controlled, AWSC) and CMC (Roundabout) level crossings are the baseline without LRT scenario, the actual scenario with collected LRV headways, twice arrival frequency scenario, signalized actual LRV arrival, and signalized twice actual LRV arrival. The relative comparisons among the tested scenarios depicted that significant travel time savings can be achieved in some approaches if more green time is offered to nonconflicting phases during a light rail crossing. Overall, the average additional delays at level crossings increase from the base scenario with increasing light rail crossing frequencies, and delay at the level crossing is the second important variable that contributes to the variability of train travel time at peak hours. If it is a must for an intersection to have a rail road to pass through the median, different options should be verified based on the trade-off between the operational cost of the level crossing and the cost incurred if it is grade separated.

Macroscopic Traffic Flow Characterization for Stimuli Based on Driver Reaction

The design and management of infrastructure is a significant challenge for traffic engineers and planners. Accurate traffic characterization is necessary for effective infrastructure utilization. Thus, models are required that can characterize a variety of conditions and can be employed for homogeneous, heterogeneous, equilibrium and non-equilibrium traffic. The Lighthill-Whitham-Richards (LWR) model is widely used because of its simplicity. This model characterizes traffic behavior with small changes over a long idealized road and so is inadequate for typical traffic conditions. The extended LWR model considers driver types based on velocity to characterize traffic behavior in non lane discipline traffic but it ignores the stimuli for changes in velocity. In this paper, an improved model is presented which is based on driver reaction to forward traffic stimuli. This reaction occurs over the forward distance headway during which traffic aligns to the current conditions. The performance of the proposed, LWR and extended LWR models is evaluated using the first order upwind scheme (FOUS). The numerical stability of this scheme is guaranteed by employing the Courant, Friedrich and Lewy (CFL) condition. Results are presented which show that the proposed model can characterize both small and large changes in traffic more realistically. Doi: 10.28991/cej-2021-03091632 Full Text: PDF