Open AccessTimetable and Headway Adherence Assessment using the Gini Coefficient and the Lorenz Curve
Author(s) -
Neïla Bhouri,
Sneha Lakhotia,
Maurice Aron,
Geetam Tiwari
Publication year - 2021
Publication title -
wseas transactions on computer research
Language(s) - English
Resource type - Journals
eISSN - 2415-1521
pISSN - 1991-8755
DOI - 10.37394/232018.2021.9.16
Subject(s) - lorenz curve , headway , gini coefficient , schedule , computer science , operator (biology) , statistics , econometrics , mathematics , simulation , inequality , mathematical analysis , biochemistry , chemistry , repressor , transcription factor , economic inequality , gene , operating system
Adherence to the schedule is of prime importance in public transport. This paper presents a specific application of the Gini coefficient, well known indicator in economics, for the headway adherence assessment. The paper shows that Lorenz curve, which is usually used to define mathematically the Gini coefficient, is a good indicator of the users' waiting time when it is based on the bus schedule. When it is computed on the basis of the ratio of observed headway to the schedule, it is a powerful visual tool that can be used by operators to detect the existence of irregularities on a bus line at a glance. An equation gives, in an idealistic case, the impact of any single traffic disturbance on the Gini coefficient, making this coefficient comprehensive. A detailed analysis is developed, based on the bus proportions according to the headway adherence level. These proportions are obtained from new indices coming from the derivative of the Lorenz curve. The values of these indexes alert the operator of any adherence disturbance. The examination of the Lorenz curve takes more time, but is worthwhile, giving the types of the irregularities The application of these indicators is carried on real-time data from the New Delhi bus network.