Data Collection and Sampling issues -Preparing Low Carbon Mobility Plan

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1 Department of Civil Engineering/TRIPP Indian Institute of Technology Delhi Data Collection and Sampling issues -Preparing Low Carbon Mobility Plan K. Ramachandra Rao, G. Tiwari, Sudeep Grover UNEP Workshop, Apr 2012

2 Outline Background Sampling Data collection Data needs for LCMP City profile/structure Transport network inventory Public/para-transit system/nmt Traffic conditions Travel demand modelling Environmental conditions Alternative scenario development Case study Ludhiana: A choice experiment for Low Carbon Mobility options 2 Data collection and sampling issues

3 Background Data collection is one of the essential part of any planning exercise Most of the transportation planning models are data hungry Challenge lies in identifying the data needs and sampling sizes within the allocated budgets while preparing the CMP/LCMP Need to look at the data requirements and sampling strategies for LCMP Data collected for generating information would be used for decision making 3 Data collection and sampling issues

4 Sampling Plans The selection of a proper sample is an obvious prerequisite to a sample survey A sample is defined to be a collection of units which is some part of a larger population and which is specially selected to represent the whole population Sampling is often done for reasons of cost and practicality A sampling plan is just a method or procedure for specifying how a sample will be taken from a population Methods of sampling: Simple Random Sampling Stratified Random Sampling Variable fraction stratified random sampling Cluster Sampling Multi-stage sampling Systematic sampling 4 Data collection and sampling issues

5 Sampling methods 5 Data collection and sampling issues

6 Sampling methods 6 Data collection and sampling issues

7 Sampling methods 7 Data collection and sampling issues

8 Target population The target population is the complete group about which one would like to collect information. The elements of this group may be people, households, vehicles, geographical areas or any other discrete units The definition of the target population will, in many cases, follow directly from the objectives of the survey 8 Data collection and sampling issues

9 Data collection and survey process 9 Data collection and sampling issues

10 Data collection methods Documentary searches Observational surveys Household self-completion surveys Telephone surveys Intercept surveys Household personal interview surveys Group surveys In-depth surveys IT Wireless technology 10 Data collection and sampling issues

11 LCMP Data required Description LCMP CMP Geographical location Location Climatic condition Total land area Land area Growth pattern Identification of notified areas Regional linkages Population growth trend Demography Number and size of HH Age-sex pyramid Population by social group* Socio-economic data Population by income/expenditure at zone Vehicle ownership by social group 11 Data collection and sampling issues

12 City profile: demography - sampling Age sex pyramid: A population pyramid, also called an age structure diagram, is a graphical illustration that shows the distribution of various age groups in a population which forms the shape of a pyramid when the population is growing 12 Data collection and sampling issues

13 City structure: mix intensity - sampling Data required Description LCMP CMP Land use pattern Map Population density Disaggregated at the level of study Mix intensity Land consumption by land use Determined by job-housing ratio or balance in a zone or level of study 13 Data collection and sampling issues

14 Transport Network Inventory Pedestrians - population Data required Description LCMP CMP Footpath Intersections Access 14 Width Single sided/both side Continuity Encroachment by other activity/vehicles Pavement condition Lighting Clear markings Signalized crossing Level/raised crossing Traffic calming tools like speed breakers Intermediate crossing sections Crossing distance Barrier free access to bus stops Barrier free access to footpaths

15 Transport Network Inventory NMV - population Data required Description LCMP CMP Lanes Intersection treatment Parking Cycle lanes/tracks Width of cycle lanes/tracks Both sided/single sided Encroachment by other activity/vehicles Lighting Pavement condition Signalized intersections Traffic calming tools Traffic calming for access to properties Number of parking Distance of parking from PT stop Parking charges 15 Data collection and sampling issues

16 Transport Network Inventory Para-transit Autos and Cycle Rickshaws - population Data required Description LCMP CMP Para-transit (auto rickshaw and cycle rickshaw) Restricted / non-restricted Number of parking by specification of parking areas Distance of formal parking from bus stop Distance between parking stations Parking charges 16 Data collection and sampling issues

17 Transport Network Inventory- Public Transport (Bus) - population Data required Description LCMP CMP Infrastructure Dedicated bus lanes (type and description) Average speed on different roads Number of bus stops Bus stop inventory Average distance between bus stop Bus stop Location of bus stop with respect to junction Passenger amenities on bus stop Number of bus terminals 17 Data collection and sampling issues

18 Transport Network Inventory- Personal Motorized Vehicles - population Data required Description LCMP CMP Road infrastructure Intersections Parking ROW Number of lanes Average speed on different roads Road encroachment Lighting Type of intersection- signalized/unsignalized Turning time from each direction Signal phasing Existence of Area Traffic Control System Type of Signal Operation Ownership type Parking regulations Number of parking 18 Data collection and sampling issues Parking charges by mode

19 Public Transport Systemsample/population Data required Description LCMP CMP Type of ownership Number of bus by type of bus (standard, mini, low floor), fuel used and age Fleet usage detail Fleet utilization rate Vehicular kilometer Percentage occupancy- peak hour and average Total passengers per day Route inventory Number of bus routes Route detail Headway on different routes Average route speed Service reliability Operation cost per km Tax levied Cost and fare Fare structure Revenue per km 19 Profit/loss Data collection and sampling issues

20 Para-transit System- Auto, Cycle Rickshaw and Shared Auto - population Data required Description LCMP CMP Fleet usage detail Route detail Cost and fare Type of ownership Number of para-transit by type (shared, personal autos and cycle rickshaw), fuel used and age Vehicular kilometer Route inventory for share auto Average waiting time for auto, cycle rickshaw and shared auto Operation cost per km Tax levied Fare structure Revenue per km Profit/loss 20 Data collection and sampling issues

21 Traffic Study- Condition, Safety And Security - sample Data required Description LCMP CMP Traffic count Delay and Queue length Screen line by modes At intersection by modes Queue length by mode Delay by mode Travel speed by mode Number and location By victim mode of injury/fatalities on road By impacting vehicle Reported crimes Disaggregated by mode 21 Data collection and sampling issues

22 Modelling Travel Demand- Household Survey - sample Data required Description LCMP CMP Personal information Transport infrastructure rating for different modes Age Gender Occupation Monthly income Vehicle ownership and age of vehicle Monthly expenditure on transport Perception about Safety Perception about security Perception about comfort 22 Data collection and sampling issues

23 Modelling Travel Demand- Household Survey - sample Data required Trip making information Description LCMP CMP Trip purpose Trip origin and destination Travel distance Mode used Access and egress mode Access and egress public transport stop Distance to access and egress public transport stop Travel time to access and egress Average waiting time to board Public transport Total travel time Total travel cost Average mileage if PMV used Fuel used 23 Data collection and sampling issues Reason for using the mode used

24 Environmental Condition & City Budget Analysis - sample Data required Description LCMP CMP Air quality levels NOx, CO2, CO, SOx concentration by location Noise levels By location Investment trends in transport on different modes Tax policies for different modes Percentage of subsidy granted Fuel price Previous years trend 24 Data collection and sampling issues

25 Data for Developing Alternate Scenarios - sample Data required Socioeconomic profile New development areas Proposed projects Description LCMP CMP Population growth Economic growth- per capita income/household income Vehicle ownership trend Economic sector growth Location Area Land use plan Number of residential population Number of Jobs ear of completion Type of project Location Project profile Purpose of project Current status 25 Target year of completion Data collection and sampling issues Likely impacts of project on travel pattern, traffic

26 Case study Ludhiana Sampling strategy: stratified random sampling Data collection method: personal- paper questionnaire User preferences to the Low carbon modes Walk Bicycle Bus transit Electric vehicles Two-wheeler Car Stated preference study 26 Data collection and sampling issues

27 Determining sample size: parameters Margin of Error: The margin of error is the amount of error that you can tolerate. If 90% of respondents answer yes, while 10% answer no, you may be able to tolerate a larger amount of error than if the respondents are split or Lower margin of error requires a larger sample size. Confidence level: The confidence level is the amount of uncertainty you can tolerate. Suppose that you have 20 yes-no questions in your survey. With a confidence level of 95%, you would expect that for one of the questions (1 in 20), the percentage of people who answer yes would be more than the margin of error away from the true answer. Response percentage: This is the percentage of people who give a particular answer to a question in a survey. If 98% of people select an answer there is not much room for error. However, if 45 or 55% select a particular answer, we don't have a clear majority and the chance for error gets bigger. 27 Data collection and sampling issues

28 Sample size for given population Margin of Error (%) Confidence level(%) Response Ratio(%) Sample Size Data collection and sampling issues

29 Population vs sample Parameter Population (Census 2011) SIZE (n) 16,13, Sample SEX RATIO (%) 54.2 : : LITERAC 85.38% (city), 82.5 % ( district) Undergraduate 32.4 % Literate 100 % 29 Data collection and sampling issues

30 Personal attributes Income Distribution (%) Annual Family Income Gender( %) Sex(M/F) Male Female Upto 1 lakh lakh lakh < 6 lakh Education(%) Data collection and sampling issues

31 Vehicle Ownership One Two Three Car 2W Bicycle Jobs Held (%) Average daily Distance Commuted(%) <5 km 5-15 km km Data collection and sampling issues >25 km

32 Present Mode of travel(%) Primary Reason For Travel(%) Data collection and sampling issues

33 Study design Four choice cards for choosing desired mode. Card 1 Effect of providing independent lanes for buses, bicycles and walking Card 2 Better transit policy in addition to the above Card 3 Policy against cars in addition to the above Card 4 IC engine vehicles vs. electric vehicles 33 Data collection and sampling issues

34 Summary of choices (%) Option Car 2W Bus Auto/ Taxi Present Mode Used Card 1 (Lanes for Bus,Cycle,Walk) Card 2 (Card 1 + Better Buses) Card 3 (Card 2 + Policy against Cars) Bicycle Walk Option Car Electric Car Card 4 (Electric Vehicles) 2W Electric 2W Data collection and sampling issues

35 References Hensher, D.A, Rose, J.M., Greene, W. H., (2005) Applied Choice Analysis A primer, Cambridge University Press Keller, G. (2009) Statistics for Management and Economics, Eighth Edition, Cengage Learning Richardson, A.J., Ampt, E.S., Meyburg, A.H. (1995) Survey Methods for Transport Planning, 1 st Ed, Eucalyptus press, Melbourne Ortuzar, J.D., Willumsen, L.G. (2011) Modelling Transport, 4 th Ed, John Wiley, Chichester 35 Data collection and sampling issues

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