Lane Density as Measure of Effectiveness of Multi lane Indian Highways under Heterogeneous Traffic Conditions Traffic Engineering (original) (raw)
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—The increment in the traffic flow demand has forced transport planners to increase the number of lanes of highways in order to provide better functional and operational facilities to the users. Measures of effectiveness (MOE) of a road system is one of the critical issues faced in highway planning and management. Level of service (LOS) is a qualitative measures describing the operational condition of a transportation facility. The LOS concept devised by US-HCM is unfit for direct implementation in Indian heterogeneous mixed traffic condition. This is mainly due to the heterogeneous traffic conditions and vastly unique driver behavior found on Indian highways. Thus a well-defined LOS criterion for heterogeneous traffic condition is utmost necessary. The vehicles prevailing under heterogeneous traffic vary widely in static and dynamic nature. An attempt has been made in this study to define the LOS criteria per lane basis on multilane highways in terms of traffic density, considering the distribution of traffic across the lanes. LOS being a classification problem has been obtained by Clustering technique in the present study. K-means clustering methods have been employed to classify LOS in six categories.
ROADWAY CAPACITY ESTIMATION FOR MULTI-LANE INTER-URBAN HIGHWAYS IN INDIA
Indian highways operate under markedly varied traffic and driving conditions when compared to the highways in other countries. Hence the capacity estimation methods developed elsewhere are not readily applicable in India. This paper focuses on estimation of roadway capacity for multilane interurban highways in India. For this purpose, two sections of 60 meter length were identified as study sections on NH-2 (Delhi-Mathura corridor), which is a four-lane divided national highway. The sections were so chosen as to take into consideration the effect of varying road geometry, pavement surface conditions and possible variations in traffic conditions. Only normal weekday traffic was considered. Traffic data consisting of classified traffic volumes, space mean speeds and free speeds of vehicles were obtained using videography technique in blocks of four hours each for 10 to 12 hours in a day to capture the effects of morning and evening peak hours as well as the heavy traffic plying primarily in the night-time. Speed-flow relationships on the study sections were then developed for the study sections and capacity flow was taken to be the traffic flow at half of the free flow speed at a section. Furthermore, recognising that the macroscopic statistical analysis of traffic data may not be able to fully capture the heterogeneities arising out of the mixed traffic conditions and lane indiscipline existing on Indian roads, microscopic simulation of the traffic on the study sections was attempted using VISSIM 6.0. The simulation model was calibrated and validated using the observed volumes, space mean speeds. Subsequently the capacity was estimated using the speeds and flows obtained using the simulation model. Subsequently, the highway capacities estimated using the above two methods were compared.
2020
Traffic congestion causes many socio-economic problems in developing nations. One of the main causes of traffic congestion can be attributed to poor design practices. In the last few years, Lahore city has expanded haphazardly where the allocation of resources was done based on political will instead of feasible design practices. This haphazard growth coupled with a poor design resulted in traffic congestion on the main roads of the city. In this study, simulations using different traffic management design strategies were carried out on major roads to check if traffic delays and Level of Service (LOS) can be improved. The most feasible designs based on the simulated results were proposed for the improvement of the existing infrastructure designs. These findings suggested that Akbar Chowk and Jinnah Hospital Intersection have greatly reduced the traffic delay time by 92.97% and 92.67%, respectively. Policymakers can utilize these simulated results for future design guidelines to accommodate the future growth of traffic on these arterial roads.