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Countdown timers impact driver behavior significantly and are widely used at signalized intersections in many countries. Literature shows potential vehicle class-specific temporal and spatial variations in driver behavior in the presence of timer. Therefore, first, this paper analyzed the temporal, spatial, and vehicle class-specific impacts of timer on driver behavior in heterogeneous traffic conditions based on variations in acceleration. Second, a Long Short-Term Memory model was developed to model vehicle discharge, incorporating the heterogeneity of traffic and impacts of timer. The performance of the model was compared with that of the Intelligent Driver Model using field trajectory data from three signalized intersections in Kerala, India. The model accurately predicts the following behavior with mixed spacing errors of 0.24 to 0.35 and an average mean squared error of spacing of 1.23. The results were better than, or comparable to, results from recent data-driven car-following models and significantly better than IDM. [ABSTRACT FROM AUTHOR]

The article analyses the transportation sector in India with respect to the changing energy mix. A key objective is to contribute to the policy debate on electrification of the transportation sector. The article attempts to serve multiple sub-objectives. The aggregate size of vehicle fleet in operation is estimated. A vehicle survival model is calibrated using primary data collected from the field. Then, based on the extant literature, certain mobility-related parameters are estimated. Using these data passenger mobility is calculated. The estimate for passenger-km travelled in India obtained from the approach is thus a fairly correct estimate for the same. The values are in sharp contrast to some of the earlier studies. Further, future mobility is projected using an S-shaped curve. The mobility data is used to estimate the current energy demand and the consequential carbon emissions. Lastly, the e-vehicle penetration pathways for the future are modelled based on different scenarios. Based on the assumed scenarios, the future demand for the energy and the expected emissions for different electricity mixes are calculated. The adopted approach thus gives a set of plausible future scenarios of the Indian transportation sector making the study a valuable tool for the policymakers and managers. We conclude that the e-vehicle push may not give the desired environmental outcome unless the energy mix is drastically changed. [ABSTRACT FROM AUTHOR]