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Walking is being promoted as either a main mode of transportation or as a part of multimodal mobility. However, a rapid growth and development in urban areas has resulted in a drastic increase in human population as well as vehicular population in most of the metropolitans across the globe. Due to this, there is an unavoidable increase in conflicts between vehicular traffic and pedestrians often sharing the same road space. At an undesignated crossing, pedestrians wait for suitable inter-vehicular gap to cross the road. However, in order to reduce the waiting delay, pedestrians often take risk by accepting smaller gaps while crossing the road. It increases the probability of their collision with approaching vehicles. Apart from the frequency of crashes, the crash severity is also vastly governed by traffic flow characteristics. In this regard, it is a common belief that the reduction in speed of approaching vehicles can significantly bring down the severity of pedestrian crashes. On the other hand, vehicular movements also get obstructed due to the pedestrian activities carried out on the carriageway. During pedestrian crossing maneuvers, pedestrians often force the approaching vehicle(s) either to slow down or to change the lane which leads to reduction in the average speed of traffic stream. However, in case of pedestrians walking along the road, vehicles tend to shy away towards the center of carriageway to ensure the safe movements of pedestrians. Hence, pedestrians irrespective of crossing or walking along the road, eventually results in the reduction in speed as well as capacity of the road and sometimes prove to be a promising threat to safety of the road users. Therefore, in order to delve into the phenomena of pedestrian-vehicle interaction, one should need to study the mutual influences of pedestrian and vehicular movements on each other. In this background, this paper puts forward a detailed literature review on the assessment of pedestrian-vehicle interaction on urban roads. Findings of the paper are specific and infer the behaviors of both pedestrians and vehicles while sharing the same road space.

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Mixed traffic conditions in emerging countries like India make it difficult to adopt Level of Service (LOS) criteria given in Highway Capacity Manual (HCM) of developed nations. Present study aims at identifying alternative performance measure which will exhibit better compatibility to define LOS in context of urban mixed traffic. A total sixteen hours of traffic volume and speed data have been recorded by videography at selected road segment of a six lane divided urban arterial in Kolkata metropolis. Percentage Speed Reduction (PSR) from Free Flow Speed (FFS) has been identified as an alternative performance measure for LOS assessment as it is a good representative of overall mobility state and also found sensitive to prevailing traffic flow conditions on the road. FFS of individual vehicle category has been computed from the normal distribution curves fitted upon the speed data under free flowing condition. Kolmogorov-Smirnov (K-S) test which has been performed to check goodnessof-fit of these modelled curves, has shown satisfactory compatibility with the observed data. K-mean clustering has been adopted to classify the observed PSR data into sub groups and consequently Silhouette method has been used to validate these clusters. Finally, six LOS classes bounded by threshold values of PSR have been proposed.

Developing countries are facing challenges in sustaining urban traffic congestion due to rapid urbanization. In order to manage urban traffic, a traffic engineer first need to assess the current operational condition on urban roads. ‘Level of Service (LOS)’ is used to define the operational traffic condition within a traffic stream in terms of service quality that a facility is providing to its user. This paper proposes a novel approach to estimate ‘Speed Ratio’ by considering individual Free-Flow Speed (FFS) of different vehicle categories. This study also provides a comparison between FFS estimated using the methods given in Highway Capacity Manual 2010 and Indian-Highway Capacity Manual 2018. LOS criteria was developed using five clustering technique; K-means, K-medoids, Clustering Large Applications, Fuzzy-C Means and Hierarchical Agglomerative Clustering. Both internal and external cluster validation indices were used to find the optimal number of clusters and suitable clustering algorithms.