Abstract
Unexpected delay on freeways is the prime cause of dissatisfaction in road users. Increasing traffic, adverse environmental conditions, accidents, time, season, location and many more factors influence travel time and cause delay. There is no direct method to estimate delay. It is calculated from trip time estimates. Thus, it is a very big challenge for transportation professionals to develop a model that accurately estimates the trip time for a trip at a particular time, by a specific mode of transport. Subsequently, the reliability of the delay calculated from those trip time estimates is often doubtful. Further, the measurement of delay using the trip time data is another big thing. This paper is a step toward measuring the delay in an accurate way using travel time reliability measures. The study was conducted on the two modes of public transportation (City bus and Auto) in an urban corridor of length 16.3 km, in Hyderabad city, India. In this study, a license plate survey was conducted for data collection, travel time-based statistical analysis was employed for estimation of trip time and by making use of travel time measures, the delay was measured. The approach was validated graphically to portray its accuracy.
Highlights
On the urban outer freeways of large cities, the expectations are to travel close to the speed limit or free-flow travel
There are various types of measures widely applied in assessing traffic performances such as planning time (PT), planning time index (PTI), buffer time (BT), buffer index (BI), frequency of congestion (FOC), standard deviation (SD), coefficient of variation (CV), misery index (MI), etc
Of the above-mentioned measures, only a few are considered in this research, as it is confined to the measurement of PT and delay only
Summary
On the urban outer freeways of large cities, the expectations are to travel close to the speed limit or free-flow travel. Travel time on a given road stretch varies over time and is influenced by various factors (Hojati et al, 2016) These measures are further used for various applications such as the ATIS, to design time schedule for transit system management, freight movers, policy making and transportation planning (Kwon et al, 2011). If the travel time and delay can be estimated accurately, travelers can adjust their mode choices, trip patterns and expectations (Emam and Al-Deek, 2006) Information on both the cost and reliability of transportation modes are necessary to make policies and estimate the benefits to be gained from improving reliability or shifting the users to more reliable transportation modes (Nam et al, 2006)
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