  Travel time prediction is a well-renowned topic of research. It is primarily
influenced by traffic congestion, road conditions and route geometry. Among
them route geometry at any point is not investigated enough to find a sound
spatial dynamics of timing delays and quality of public transport. This study
investigates the reliability of travel time to build a new key performance
indicator of public transport network. We have introduced a suitable point wise
clustering followed by an adapted statistical significance analysis. The
outcome is an estimation of absolute delay at geometrical points independent of
the delay at bus station. This outcome serves as an incremental delay towards
overall delay. Our investigation suggests that this novel metric of delay time
contributes around 23.56% in overall delay. The proposed methodology (here in
known as Delay Time and Quality of Service (DT QS)) is capable of providing
novel insights which attracts attention among policy makers of public transport
operators. The novel insight is coined with assignment of high value to
level-of-service attributes. Moreover, the proposed technique is independent of
any assumption of normal distribution.
