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The purpose of this paper is to estimate total emission during idling of vehicles and validate emission results from real-world data.

Motor Vehicle Emission Simulator (MOVES)2010b emission model is customised for developing country like India and a case study of the Ashram intersection in Delhi has been selected in order to measure the emissions of vehicles during idling.

Results show that 3.997 mg/m3 of hydrocarbon, 1.82 mg/m3 of NOx and 17.688 mg/m3 of carbon monoxide is emitted from the cars, trucks and buses, respectively, at Ashram intersection in one day. As there are 600 intersections throughout Delhi, a total of 2,398.055 mg/m3 of hydrocarbon, 1,087.068 mg/m3 of NOx and 10,612.612 mg/m3 of carbon monoxide is emitted from cars, trucks and buses in a day in all of Delhi.

Knowledge of idling emission and fuel loss is very little for Indian traffic condition during delays.

Heterogeneous traffic in Delhi is complex to understand due its typical composition, speed acceleration, cruising, deceleration and idling activity in flow. To arrive at accurate emission factor estimates and implement proper traffic demand management there is need to understand microscopic vehicle operation activity. The vehicular operations are easily quantified by understanding driving cycle of the particular vehicle in real world driving conditions. The purpose of this paper is to present a study on the understanding of driving conditions in India that are heterogeneous in nature.

To understand the heterogeneity, the driving cycle data were collected using GPS on different types of both motorised and non‐motorized modes of transport, e.g. car, auto rickshaw, bus, motorcycle and cycle rickshaw and bicycle on different traffic corridors in Delhi.

Research findings show that driving cycles differ for different types of vehicles. Therefore, each mode should be encouraged based on their average speed‐time sequence in any traffic mix. The real‐world driving cycle will be also useful for the understanding of fuel consumption and emissions in real‐world scenarios, in order to control vehicle emissions properly, achieve fuel efficiency and to obtain a more sustainable transport system.

This type of research has not been carried out previously in any Indian city.

There is gap in literature on understanding of the issues of following headway behaviour of the driver and a lack of sufficient data in different traffic conditions. The purpose of this paper is to find the effects of type of lead vehicle on following headway in mixed traffic condition in India on different category of roads and flow.

Real-world headway data were collected through video and extracted. Data were analysed using tools and statically approach was adopted to present the results in detail.

Results shows the impact of type of lead vehicle on driver following time headway behaviour under different level of traffic and types of road characteristics. It was found that driver following behaviour is affected by the type of lead vehicle. It also shows that drivers are inconsistent in their choice of headway.

This research has special strategic study area of India in typical two cities Silchar and Shillong of northeast region of India. The traffic characteristic and composition is quite different as compared to other cities of India. Therefore the study results cannot be generalized for whole India.

The result of the study has focused on impact of type of lead vehicle on following behaviour. This can be useful to safety reduction and changing the driver behaviour through education and display of information. However, the real application of this result is to be implemented by local transport and road managing authority to reduce accidents and increase safety of drivers.

In mixed traffic conditions, the impact of type of lead vehicle on following behaviour affects the safety of drivers and the accounting for such behaviour is never been explored in mixed traffic condition. If the study is implemented, it can be useful to simulation modeller and intelligent transport systems (ITS) to design and operate many in-vehicle systems for smooth traffic processes.