Research Project

Strategies to Reduce Vehicular Pollution in Delhi

Geetam Tiwari and Sunil R. Kale

Project Details

Objectives
 
The project involves determination of driving cycle of different types of vehicles in varying traffic mix conditions representative of urban traffic in India. These driving cycles will be simulated with in-use vehicles on a chassis dynamometer and fuel  consumption and emissions will be measured. These data will be used to estimate fuel savings in alternate road plans, such as, creating exclusive bus lanes, bicycle lanes, flyovers, alternate signal cycle etc. because these are reflected in the driving cycle. This research is important because a large number of cities are planning strategies to improve traffic flow. Findings of the present study will be used to estimate fuel savings and emissions in different strategies. 
The specific objectives of the project are as follows: 
(a) Estimating the current status of emissions and fuel consumption of in–use vehicles in different driving conditions, and 
(b) Impact of different traffic management strategies on vehicular emissions and fuel economy 

Background 

One of the important components affecting ambient air quality in urban areas is emissions from vehicles. Several factors affect vehicular emissions, important among these are road traffic characteristics vehicle type and age variation, fuel used and maintenance. Road traffic in turn is influenced by road design, mode segregation, and on-road vehicle population by type. These parameters are time variant making the problem a continuously changing one. Models have been used or understanding homogeneous lane-following systems their current and future environmental impact. These  models fail in Indian conditions where heterogeneous traffic is the norm. Hence, in order to develop cost-effective air quality improvement plans, it is necessary to know not only the vehicle emission characteristics under standard conditions but also the vehicle operational characteristics in on-road scenarios. There is, therefore, a need to temporally and spatially quantify vehicular emissions. 

Methodology

Inventory of in-use vehicles:  Vehicles have been analyzed under six categories: Cars, taxi, two wheelers, three wheelers, buses, RTVs. Test Plan  For Delhi the candidate vehicles are 2-wheelers, 3-wheelers, car, and bus.  During limited hours light
and heavy commercial vehicles also operate on the roads.  These are not allowed during morning and evening rush hours.  These vehicles constitutes percentage of motorized vehicles on Delhi roads.
All 2-wheelers are powered by petrol engines 3-wheelers are mostly part by CNG there could be some that are powered by petrol engines.   Cars either by petrol and diesel engines and many small number of cars powered by LPG and CNG.  Vast majority of  buses powered by CNG engines and very few by diesel engines.
 
In the test plan it is proposed to measure vehicle and engine speeds with time.  The GPS units available commercially can record vehicle speed and locations at various sample frequencies.  From this data information about distance and direction can be calculated.  The engine speed can be recorded with a ad current pick up which required the engines with spark ignition type.  Using this technique the driving cycle for the four major vehicle categories listed above can be obtained.  On board data
collection can be done with a laptop.  The data so collected can be analyzed with various packages such as MATLAB, SPSS, SAS etc.   

Equipment selection and procurement 

A survey was conducted on commercially available GPS recording units.  These were assisted for suitability for the purpose described above.  All these manufacturers were contacted for obtaining details for demonstration.  Based on all of these the following measure attributes were identified for the GPS based recording system. 
 
Status of experiment 

Preliminary trials were performs with a car and these were satisfactory.  Detailed experimental metrics has been worked out which will include by vehicle type origin and destination and route.

Corridor Selection: The traffic network can be classified on the basis of two features   
1. Geographic- This feature includes Junction, Flyover, and Signal etc
2. Traffic- Traffic Volume, Speed etc

Three corridors of different characteristics are selected for the study.
These three corridors have been identified on the basis primarily different traffic management strategies.  
1.Ring Road 
2.BRT Corridor
3.Khel Gaon  
Ring Road: Ring road is an important arterial carrying intercity as well as intracity traffic. This covers 48 km and designed as a signal free corridor with most signalized junctions becoming grade separated intersections except for a small number of crossings in the last few years. Salient geometric features of Ring road are given in table 3.1. Table 3.1 gives traffic characteristics (volume, speed and density) of car, two wheelers, three wheelers and buses observed over last five years at Punjabi Bagh intersection, an important traffic junction on this corridor.

BRT Corridor:  BRT has been introduced in Delhi on a 14 km long corridor running from Ambedkar Nagar Junction to Delhi Gate. First six kilometre of this corridor has exclusive central lanes for buses and bicycle lanes on the left side. 
The corridor has been designed to give priority to buses and safe passage to bicyclists and pedestrians.  Table 3.2 give traffic characteristics (volume, speed, density)  of car, two wheelers, three wheelers and buses observed over last five years at Chiragh Delhi junction where BRT corridor has been introduced and ITO junction without exclusive lanes for buses over last five years. 

Khel Gaon marg This is an important arterial road and represents a typical arterial road having divided four lanes with signalized junctions.  It is a parallel corridor to BRT. In this corridor there was no separate length for any kind of transportation public or private. Traffic was flowing without any restrain of lanes. It also has flyover across it. In this corridor a preliminary studies will be done later. This corridor is around 6km in length.

Speed delay study was done on BRT and Ring Road corridors. 

Distance Data: First equal length of stretch was identified on both the corridors. Bus stops  and red lights were marked on both the corridors and their distances from either end of the corridor Travel Time Data: Time-delay data were collected manually. Travel Time Data tables were prepared corresponding to the corridors. Each table contains column for time spend on corridor between different points. 

In this phase the data is collected on the selected representative routes using GPS unit using car chasing technique. Before collecting data we have to determine the number of test runs is to be run. After determination GPS is calibrated.
    
GPS is installed on a car the speed–time data is to be collected using chase-car technique. This technique involves random selection of a vehicle in the traffic and survey vehicle simply has to follow the selected vehicle keeping approximately a constant distance during different modes of operation. The chasing procedure should be repeated depending upon number of test runs to obtain large amount of data.
The vehicle speed with respect to time should be measured and recorded on all the selected routes. On the selected routes, the data collection could be carried out during peak, off peak period, week days and weekends for varying traffic conditions.

Development of a drive cycle is based on micro-trips. Micro-trip is an excursion between two successive time points at which the vehicle is stopped. This part of motion consists of acceleration, cruise and deceleration modes. By convention, a period of rest is at the beginning and end of a micro-trip. The whole data has to be separated into number of micro-trips. That is the speed–time data collected for a particular stretch having n numbers of segments of different modes of vehicle operation are divided at each idle value.

Driving cycle is constructed using segregated micro trips as per methodology described in above sections

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