Urban Transport Data Analysis Tool
Contents
1. Click on Filter Cities L iro Wa EDO T pT Of Neorg rm Blige pip de Primary City MM Chicago Peer Cities Accra Agra Ahmedabad Amritsar Amsterdam Athens Bangalore OOOOOOOO Filter Category City Population Current 2011 Operator p Value 5000000 Filter Cities X Axis Category 1 Data Item 1 The logic operator is the mathematical symbol that will define the value or the range of the filter category You can use one for a single value or both to enclose the category within a range e g Per Capita GDP gt 5000 5 000 000 lt City population gt 20 000 000 USER INSIRUCTIONS 33 Select Category l and the corresponding Data Item 1 from the list This will be the data item located in the horizontal axis of the scatter plot Select Category 2 and the corresponding Data Item 2 from the list This will be the data item located in the vertical axis of the scatter plot e Click on Proceed fanart Dntions repon Uptions Primary City Chicago Peer Cities Accra Agra Ahmedabad Amritsar Amsterdam Athens Bangalore Bangkok Filter Category City Population Current 2011 w Operator s w Value SW 0 Dperator 2 O Value 2 Em nr Filter Cities X Axis 00000000 Category 1 Data Item 1 Petrol price LC Current Category 2 Data Item 2 e A Results Report will be generated as shown below 342. 90042 Public Disclosure Authorized USER S MANUAL Os Copyright 9 2014 International Bank for Reconstruction and Development The World Bank 1818 H Street NW Washington DC 20433 All rights reserved The findines interpretations and conclusions expressed in this report are entirely those of the authors and should not be attributed to the World Bank and Energy Sector Management Assistance Program ESMAP Ihe World Bank does not guar antee the accuracy of the data included in the tool which have been collected only from secondary sources and these sources have been referenced The World Bank accepts no responsibility for any consequences of the use of these data ACKNOWLEDGMENTS his work was undertaken by the Transport Anchor of the World Bank with support from the Energy Sector Management Assistance Program ESMAP The World Bank team was led by O P Agarwal Senior Urban Transport Specialist and included Gouthami Padam Aroha Bahuguna and Salvador Pena Overall guidance for this work was provided by Jose Luis Irigoyen Marc Juhel Rohit Khanna Ivan Jacques and Sam Zimmerman The report also benefited from very useful sug gestions and comments made by peer reviewers Heather Allen Georges Darido Ajay Kumar Baher El Hefnawy and Ashok Sarkar The team thanks all of them for their input The work also benefited from comments from various other experts both within and outside the Bank including
3. Additionally the first sheet of the new Excel file will be a report called Status Across Indicators TRANSP RT Status Across Indicators www worldbank org transport Indicator Quintile cmemissonsperMillpop __ 5 NOemissonsperMillpop 4 Private Transport Energy Use per Pax KM 5 Public Transport Energy Use per Pax KM _ 4 RoadAocidentDeaths __ 6 Road Accident Deaths per Mill Pop 6 The indicator values of the main city and its peers are ranked The rankings are then divided into quin tile groups 20 percent each This report shows the quintile placement of the primary city across all the indicators reported A placement in the 1st top quintile indicates a positioning in the top 20 percent high rank for the indicator when compared with its peers A placement in the 5th bottom quintile indicates a positioning in the bottom 20 percent low rank for the indicator when compared with its peers This division into quintile groups is based solely on the ranking list of the indicators and places no qualitative judgment on the result By showing a high or low rank the report is not indicating Good or Bad this will change depending on the indicator selected and the judgment of the user Considering that at the moment not all data are available for all cities a mock guintile 6th guintile was created When a city is placed in the 6th no data quintile it indica
4. arrive at the best combination for analysis Report 1 will generate a new Excel file con taining the reports for all indicators chosen and one Status Across Indicators report that will show a thermometer view of the test city across all indicators Remember that this is a benchmarking tool to assess urban transport indicators of a city by comparing it with peers It will facilitate the analysis and diagnosis of the causes of the main issues affecting a city and combined with other sources of data and analytical work it will aid in the process of creating solutions for these issues INTRODUCTION I3 DAIA ANALYSIS IOOL MAIN PROCESS Start System Open Database Run Program Select a Test City By Range Select Cities Peer Group for Comparison 4 Combination By City A Single for Benchmark Select Graphic Style a Generate Report Print Metrics of cities ranking End System Select Indicator s The running of the data analysis tool is represented by the flowchart on the right The steps are described below and detailed instructions follow l The user starts the system i Database opens matrix ii The program runs in the background macros When generating the report i Aform prompts the user to enter the test city ii The user selects the main city to be tested The user then has the option of selecting the cities f
5. NRR TE p 1 EW Filter Cities Chart Type Bar Column Line Proceed The Delete button will delete any indicator that was added by mistake Select the indicator to delete from the list and click Delete Primary City Mass Transit Supply and Use Cairo Peer Cities Agra Selected Indicators Daily MT Ridershi Ahmedabad mi set Daily Ridership MTU Daily Ridership on Mass Transit Mill Amritsar Mass Transit Coverage Mass Transit Unit Coverage EESOROOOO MT Fare as share of Income P Capita Mass Transit Unit DOSOOOOO Bar Column Line gt 26 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL Choose the desired chart type Results Report Results Report Daily MT Ridership pop Daily MT Ridership pop Kolkata rai oma Z2 lt cron 023 03 aes w EC 025 oa a owe 0 10 0 04 c WOW 7 Leal o 0 1 0 2 03 0 4 0 5 0 6 0 7 os os Cairo Moscow Beijing shanghai Sao Paulo Seoul Delhi Kolkata Results Report Daily MT Ridership pop m Z2 mr 0 04 Cairo Moscow Beijing Shanghai Sao Paulo Seoul Delhi Kolksta e Click on Proceed Category Mass Transit Supply and Use Indicators Dail My Edern pop Jally Ridersnp Daily Ridership on Mass Transit Mill Length of Mass Transit Km Selected Indicators Bangalore Banc
6. Thierry Desclos Arturo Ardila Gomez and Shigeyuki Sakaki The financial and technical support by the Energy Sector Management Assistance Program ESMAP is gratefully acknowledged ESMAP a global knowledge and technical assistance pro gram administered by the World Bank assists low and middle income countries to increase their know how and institutional capacity to achieve environmentally sustainable energy solutions for poverty reduction and economic growth ESMAP is funded by Australia Austria Denmark Finland France Germany Iceland Lithuania the Netherlands Norway Sweden the United Kingdom and the World Bank Group Pij Rise UL AB z _ MB LI lias ll gn y m sie W zj Bi r s W ug di i aes Mmm wW 4 PE mi E FOREWORD he urban population in the developing world is expected to more than double by the middle of the twenty first century from 2 3 billion in 2005 to 5 3 billion in 2050 Large cities are growing very rapidly and services are struggling to keep up In particular some cities have been over whelmed by the increase in travel demand The result has been a turn to private vehicles an increase in fossil fuel consumption and a subse quent rise in greenhouse gas emissions and pollution levels This has also led to congestion making it increasingly difficult for goods and people to move from place to place as well as an increasing inci dence of road cras
7. job Barcelona City Population Current 2011 Operator 1 ee O8BOOOs8O0O0 Yv Value 1 5000000 Operator 2 Value 2 teres e Oe o Cim P proceed 9 Canel USERINSTRUCTIONS 2 e Anew Excel file will be generated containing the results of the report as shown below TRANSP RT Results Report www woridbank org transport pu Daily MT Ridership pop Rank Daily MT Ridership pop Primary City 0 124072035 Peer Cities Moscow oa a eijing 00 0418026003 a Shanghai 365569095 ao Paulo Ci 292853573 A 0 25161712 5 Delhi 0 103324373 4 oossoo 5 Sao Paulo Top Ranked Cities 0 852674733 1 Bottom Ranked Cities 0 124072035 6l Cairo is in the 5th Bottom Quintile of the cities compared Shanghai Beijing Moscow a oa E eo o o lt m Mb a WIG Ion Un Pe O M a a a a TAI Each report contains the following information The primary city The peer cities used in the comparison The value of the indicator for each city A ranking of each city The top ranked city and its value The bottom ranked city and its value The quintile in which the primary city is located VVVUVV VV A graph with the results Ihe basic features of the graph colors fonts etc can be customized by the user with Excel s chart options if needed 28 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL
8. the following e A one stop shop database Matrix containing Two types of reports can be generated i Reportl allows the user to easily choose a test city manually or automatically select the most relevant urban transport data for several cities around the world This database currently covers 144 data items for 93 cities in 42 countries Ihe data items were collected from secondary sources and can be broadly classified into categories such as demograph ics travel demand supply of urban transport infrastructure energy traffic safety air gual ity and macroeconomic data The user can easily update the database and add new cities by using the Update Form With the main matrix containing more than 160 columns this feature makes updating the database easier to manage If users want to add their city or if they feel that they have more recent data for any parameter for their city than what is in the tool they will be able to make changes to it before they generate a particular report However the actual data base will be locked and any update of the database will require additional verification by the tool administrator peer cities and generate a bar column or line chart graphing the indicators chosen ii Report 2 allows the user to generate a scat ter plot to better portray the relationship between two data items which a bar col umn or line report cannot do e Ihe user can select multiple indicators to
9. there was considerable variability and unreliability in the data it was necessary to develop an analytical method that accom modated this unreliability and yet generated acceptable results Therefore the tool does not try to compare cities based on absolute performance values Rather it tries to classify them based on their relative performance vis a vis peer cities It was recognized that the numerical scores may be viewed either as indexes of relative perfor mance ordinal score rather than a measure of absolute level of performance against some underlying value scale cardinal scale For example given the unreliability of the data it would be incorrect to consider that a score of 8 10 represents a level of performance that is twice as good as a score of 4 10 on some underlying value scale Instead a better interpretation given the constraints would be to consider a score of 8 10 as being worse than 9 10 and better than 7 10 which in turn is better than 6 10 and so on Such rank classification would lead to fewer errors even with relatively unreli able data It was therefore decided that a ranking method would be better than absolute numbers Further it would give more reliable results if all the cities that scored close to each other were grouped together into one grade and not assigned a strict merit ranking For this reason the tool first ranks the cities in the order of their absolute performance measure
10. transport related indicators for that city referred to as the test city with similar indicators for a large set of peer cities Such a comparison allows an under standing of where a city is doing well and where it is not vis a vis its peers and thereby suggests directions for remedial action The tool comprises a large set of data items for several cities and allows the user to make comparisons across selected indica tors and also choose the peer cities to compare against Thus there is a test city the city that is being subjected to diagnosis and peer cities chosen for the comparison The tool provides an output that compares the test city with the peers through graphs and charts 10 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL The UT DAT is a Microsoft Excel based tool and has been designed to be simple and user friendly The software allows the user to a input data for a test city b select a set of indicators to be used for the comparison c select a set of peer cities to compare against and d carry out the comparison and generate reports Indicators vs data items A comparison of performance is more mean ingful when it uses specific indicators derived through computations of one of more of the data items For example a comparison of public trans port ridership would not bemeaningful though a comparison of the share of the population using public transport would be useful Simil
11. 1k population Metro vehicles per 1k population 0 021159123 BRT vehicles per 1k population j Bl Jal S Slk a Sik 2 lela Solo ale LRT per 1k population USER INSIRUCTIONS I To update and or add data to an existing city Select the city to which data will be added or updated NYM UPDATE FORM TRANSPORT wneaw orldbhank org transport Chennai Copenhagen Curitiba Danang Delhi Number of metro stations 3 14 1 1 metropolitan area Number of BRT stations 3 14 1 1 metropolitan area Select the category of data to be updated ee a UPDATE FORM TRANSP RT iy eg category e gfficnanpotsuply nergy Geographic Macroeconomic Indicators Dir Public Transport Sub Category Public Transport Supply Length of public transit all public transport per 100k population Revenue and Costs Number of mass transit stations BRT metro and LRT 3 14 1 1 metropolitan a ea L Number of metro stations 3 14 1 1 metropolitan area Number of BRT stations 3 14 1 1 metropolitan area Number of LRT stations 3 14 1 1 metropolitan area Metra vehicles per 1k population LRT per 1k population 18 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL e Enter the corresponding values for each subcategory to Gegn afda UPDATE FORM TRANSPORT www worbdbank org transport Save Data New City Chennai Public Transport Supply O VY Ml po SubCategory oe
12. ALYSIS TOOL UT DAT USER S MANUAL Select the category for the type of indicator desired Indicators have been classified into several catego ries depending on what they measure Each category will have a subset of all the indicators available Air Ouality and Energy Use Mass Transit Supply and Use Safety Supply of Vehicles and Road Travel Distance and Time Amritsar Amsterdam City Population Current 2011 X Bar Column Line Cancel Filter Cities Chart Type Select the indicator from the indicator list Multiple indicators can be selected by holding down the SHIFT key or CTRL key Report Options Primary City Cairo w Peer Cities Category s Transit Mill IE L LAITH Selected Indicators Armedanau Amritsar Amsterdam EIEOOOROO City Population Current 2011 5000000 0 Wd Chart Type Bar Column Line Proceed Cancel USEMINSTRUCTIONS 25 e Click the Add button Indicators from different categories can be added as necessary by repeating the previous steps Primary City Gwg Cairo w Indicators Daily MT Ridership pop Peer Cities Daily Ridership MTU Daily Ridership on Mass Transit Mill Lenath of Mass Transit Km Selected Indicators Ahmedabad Amritsar Amsterdam Bangalore Bangkuk x Filter Category City Population Current 2011 Operator 1 Value 1 5000000 Operator 2
13. My Length of public transit all public transport per 100k population iF 220 Number of mass transit stations BRT metro and LRT 3 14 1 1 metropolitan o 0 26144654 Number of metro stations 3 14 1 1 metropolitan area 0 095071489 Number of BRT stations 3 14 1 1 metropolitan area _ ee _ ee Number of LRT stations 3 14 1 1 metropolitan area N 0 397998623 Metro vehicles per 1k population ooms d BRT vehicles per Ikpopulation U l w Jj URTpertkpopulation O S wY gb o k a e Click on Save Data EM UPDATE FORM TRANSP RT iy rir Category Public Transport Supply Length of public transit all public transport per 100k population 2 208438123 Number of mass transit stations BRT metro and LRT 3 14 1 1 metropolitan a 0 2614406594 Number of metro stations 3 14 1 1 metropolitan area 0 095071489 Number of BRT stations 3 14 1 1 metropolitan area Number of LRT stations 3 14 1 1 metropolitan area 0 397998622 Metro vehicles per 1k population 0 021159129 LRT per 1k population The Matrix will be updated with the data entered and all reports will correspond to the new values USER INSTRUIGCTHONS To add a new city to the Matrix e Click on New City TRANSP RT www iworldbank org transport Save Data New City Public Transport Supply Sub Category Length of public transit all public transport per 100k population Number of mass transit stations BRT metro and LRT 3 14 1 1 metrapolitan Number o
14. URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL TRANSP RT Results Report Generate Report www woridhank org ransport Daily public transport boardings i NE La ke Stations Metra rail Daily public transport boardings million Metro million Metra Vs Primary City Stations Metro rail em E eee S Peer Cities i ada cika 530 Palio kolkata 1 Sa TT en Cent ine in ATT 1 au Each report contains the following information Name of the primary city Names of the peer cities used in the comparison The value of the data items for each city A scatter plot graph with the results with the primary city location highlighted in a different color Ihe basic features of the scatter plot colors fonts etc can be customized with Excel s VW vv Vv chart options if needed os el a gt Sic TY ME NW a NY N A iH i n N UR e y Na x y G 7 Up kc NS No gt 103 yd I o i A gt cc Jl i N Swi sy gt y Urban Transport Data Analysis Tool UT DAT USER S MANUAL O THE WORLD BANK IBRD IDA WORLD BANK GROUP
15. a systematic diagnosis of the urban transport problems in a city before designing remedial measures It is hoped that cities and decision makers will find this tool useful in designing their policies and other interventions aimed at improving mobility in their cities Marc Juhel Rohit Khanna Sector Manager IWIIR Program Manager ESMAP TABLE OF CONIENIS Introduction Users Guide For The UI DAT Data Analysis Iool Main Process User Instructions Updating Adding Data Io The Matrix o update and or add data to an existing city lo add a new city to the Matrix Generating Reports Bar Column Line Generating Reports Scatter Plots 12 k5 14 lo 19 20 23 8 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL INTRODUCTION rbanization is a defining feature of this century This is es pecially true in the developing world where the total ur ban population is expected to more than double by the middle of the 21st century from 2 3 billion in 2005 to 5 3 billion in 2050 Overall population growth and increasing urbanization have led to the rapid growth of large cities which have been over whelmed by the sudden increase in travel demand Growing demands for urban travel have led to rapid motoriza tion For example in 1990 China had 5 5 million civil vehicles of which only 800 000 were privately owned By the end of 2012 it had 120 million civil vehicles of which 93 million were privately
16. arly the fare charged by public transport system would not mean much unless local income levels are also taken into account Therefore several indicators that would help measure urban transport performance in a city were identified These indicators derived from the raw data items collected were selected in such a way that they could be easily calculated from the available data and for ease of compari son across cities In all 30 indicators were selected and have been already computed in the tool for ease of use Shortcomings with regard to urban transport data Because most of the data collected for the tool came through secondary sources comparing transport data across multiple cities particularly across different countries and world regions is very difficult While some of the information is recorded in the annual statistics of public trans port agencies other data are not available from any single source and are usually scattered across several different sources Data vary greatly from one organization to another and from one city to another Even within a city data are usually scat tered among a large number of sources which do not always use the same definition for a given data item Data are also generally not available for the same year across all cities Apart from this several data items do not have a consistent basis for determination in all the cities M OJO PII AMO INTRODUCTION Il Because
17. aul 18 Bottom Ranked Cities 19 20 Shanghi 21 Cairo is in the 3rd Quintile of the cities compared HA b Mate os ESO JOENS CBTJGENONIT Ready USEMINSTRUCTIONS 21 e A form will pop up as shown below Peer cities These are the cities with which the test city will be compared They can be selected manually by clicking each box next to them or auto matically with filter categories Operator land 2 These are the mathematical symbols to define the value range of the filter category You can use one for a single value or both to enclose the category within a range Filter cities This action button will filter peer cities according to the filter cat egory selected and values chosen Indicators This is the list of indicators available according to the chosen cat egory They are the calculated data items and one or more can be selected at any time to generate reports 22 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL Selected indicators In this box the list of all selected indicators for the final report will appear Different indicators from several categories can be selected at any time Delete If an indicator was chosen by mistake selecting the box next to it and clicking Delete will eliminate it from the list of selected indicators Add This button is used to add indicators to the selected indicator list One or multiple indicators can be selected at any time by
18. ed more stringent emissions norms on all pollutants without first looking at the actual cause High energy consumption in a given city could be due to any number of system supply demand and performance related factors includ ing excessive trip making and trip lengths low public transport and non motorized transport opportunities low vehicle fleet fuel effi ciency and traffic congestion The precise mix of these factors will be different for each city based on its history geography government and socioeconomic characteristics This means that an a priori diag nosis to clearly identify the underlying causes of the visible symp toms would help in better targeting urban transport interventions In the absence of a proper up front diagnosis some proposed solutions may waste resources and even be counter productive Urban Transport Data Analysis Tool It is in this context that the Urban Transport Data Analysis Tool UT DAT has been developed to look at critical parameters relat ing to urban transport in a city and compare them with peer cities to identify the specific areas where each city performs better or worse This is analogous to a pathologist s report that helps a doctor diagnose a patients ailment more precisely before suggesting the right medication A diagnostic study will facilitate a diagnosis of the urban transport problems of a city so that remedial measures can be correctly targeted The UI DAT compares a series of
19. f metro stations 3 14 1 1 metropolitan area Number of BRT stations 3 14 1 1 metropolitan area Number of LRT stations 3 14 1 1 metropolitan area BRT vehicles per 1k population LRT per 1k population e Aform willpop up asshown below e Enter the New City name and click OK e Add data for that city in each category as explained on pages 11 12 UPDATE FORM 7 5 a oje o e m ro tb elm S G8 SEE m on 69 ha da cp Fa ele i G E b A 19 The Matrix will be updated with the data entered and all reports will correspond to the new values The new city will be available for use when generating reports 20 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL Generating Reports Bar Column Line e Keeping the Report 1 Graphs sheet active click on the Generate Report button Lb View Developer Add Home Insert Page Layout Formulas Data Review Cut ain w i R Calibri 11 T A FES r EJ Wrap Text R s Copy 7 amp a 5 aste sr DE w 4 w a he F Format Painter a PD m EN BS ESE bad Merge amp Center Clipboard i Font P Alignment ra U7 w fe B KG D E F G 1 www woridbank org f transport Generate Report 2 Average time of journey to work x Rank 3 minutes 4 Primary City 5 kama o a 7 4 6 Peer Cities 7 E SEO 3 10 11 Dell 12 13 14 Mum be 15 Top Ranked Cities 16 17 5ao P
20. g to each city are located Ihis matrix is available for viewing only and any modifications can be done only by authorized users Update Form This form is to be utilized by the user to enter data on the test city This form is also the means by which the user in charee of database mainte nance updates information in thematrix je AS AONE e Reportl Graphs e Report 2 Scatter Plots Report 1 Graphs This is the main part of the diagnostic tool it allows users to generate bar column or line reports using the available indicators Report 2 Scatter Plots This report is used to combine data items and generate scatter plots It is a valuable option to better portray the relationship between two data items when a bar or line report is not adeguate 16 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL Updating Adding Data to the Matrix e Pull up the Update Form by clicking on the Update Form tab at the bottom of the tool UPDATE FORM TRANSP RT wae aworkdbank ore transport Save Data New City Public Transport Suppl A y EE Sub Category Value Length of public transit all public transport per 100k population 2 208438123 Number of mass transit stations BRT metro and LRT 3 14 1 1 metropolitan a Number of metro stations 3 14 1 1 metropolitan area Number of BRT stations 3 14 1 1 metropolitan area Number of LRT stations 3 14 1 1 metropolitan area Bus fleet per
21. hes The net effect is a decrease in the health and well being of urban dwellers as well as the economic efficiency of the cities that they live in It is essential that the growing needs of urban mobility be met more efficiently There is an urgent need for planning for urban mobility that not only provides the required capacity to meet growing demand but does so in a manner that minimizes the energy used Mitigation efforts in most cities have addressed the symptoms rather than the underlying causes Cities have tried to deal with congestion by widening their roads or building mass transit systems with out first looking at whether the city needs additional road mass transit capacity or whether it needs other interventions like improved intersection design or improved road maintenance High energy consumption in a given city could be due to any number of supply demand and performance related factors such as excessive trip lengths poor integration among different modes of public transport low vehicle fleet fuel efficiency and highly congested traffic The precise mix of these factors will be different for each city based on its history geography government and local economy An effective diagnostic tool could clearly identify the underlying causes behind the visible symptoms and would help in better targeting of the urban transport interventions It is in this context that the Urban Transport Data Analysis Tool has been developed to allow
22. or comparison i Manually by selecting each city ii By range or indicators e g All cities with population lt 500K The user selects the indicator s to use as benchmark i Only one indicator iil Acombination of indicators The user selects the output option graph style that is most convenient bar column line By clicking on Proceed the user generates the report The report is printed and comparison finalized USER INSTRUCIIONS e Openthe UT Data Analysis Tool using Microsoft Excel 2007 or higher e Once opened enable the content of the file in order to allow macros to run properly File Home Insert Page Layout Formulas Data iA a p Calibri it Aa A Bae ou A 4f Format Painter BB I uUr Hr he Ar Clipboard J z i REVIEW WM a a Ans i eat ILE mg UT Diagi View Developer Macros E Wrap Text General w FU Formatting as Alignment z Number Particulate matteremissions million population Affordability index metro fare 40 12 per capita GDP Affordability index bus fare 40 12 per capita GDP 2 35 E 2 2 90 5 5 10 68 2 2 10 10 0 0 1 90 4 4 3 60 3 3 4 96 0 4 11 88 DIV 0 n DIV 0 9 62 1 0 em aria ami The file contains the following sheets e Matrix e Update Form Each sheet contains the following Matrix The matrix is where all the data pertainin
23. owned Similarly the number of motor vehicles in India went up from 21 3 million in 1991 to 141 8 million in 2011 The trend in most other developing countries is similar Such rapid motorization has led to increased consumption of energy especially nonrenewable energy as well as increased emis sion of Green House Gases GHG and other pollutants It has also led to congestion increasing the difficulty of moving goods and people from place to place as well as increasing the incidence of traffic accidents These have compromised the health and well being of the population as well as the economic efficiency of cit ies Therefore it is essential that the growing needs of urban travel be met more efficiently There is an urgent need for effective and efficient planning for urban transport planning that not only pro vides the required capacity to meet growing travel demand but does so in a manner that minimizes energy use and other negative aspects of excessive private vehicle use Unfortunately most cities have addressed the symptoms rather than the underlying causes Cities have tried to deal with conges tion by widening roads or building mass transit systems without INTRODUCTION 9 first looking at whether the city needs additional road mass transit capacity or whether it needs other interventions such as improved intersection design or improved road maintenance Similarly efforts to deal with air pollution have impos
24. rate Report b 2 Daily public transport boardings 3 zw Stations Metro rail 3 million Metro A Primary City 5 5 Peer Cities 300 7 8 3 5 2 KI Beijing 3 058 767123 13 p Shanghai 161835616 2 5 ii Wi 5 O O 12 Delhi 13 Kolkata 200 14 15 16 17 150 18 13 20 21 44 gt bi WET GDP Defistor 1960 2011 _ CPT1960 2011 Update Form mmm Ready ij 30 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL e Aform willpop up as shown below Primary City Amsterdam Athens Bangalore Bangkok i lt ET SI Dl S1 S1 Filter Category Operator Value Operator 2 Value 2 Filter Cities X Axis Category 1 Data Item 1 Category 2 Data Item 2 Primary city Peer cities Filter category Operator land 2 Vale l andl 2 Filter cities Here you will select the name of the city to be tested test city from the drop down menu These are the cities with which the primary city will be compared They can be selected manually by clicking each box next to them or automatically with filter categories If peer cities are not selected manually this is where peer cities will be automatically selected filtered These are the mathematical symbols to define the value range of the filter category You can use one for a single value or both to enclose the category within a range These a
25. re the desired range values for the filter category This action button will filter peer cities according to the filter cat egory selected and values chosen Category land 2 Data Items l and 2 Proceed Cancel Select the primary city scatter plot USEMINSTRUCTIONS 31 Indicators have been classified into several categories depending on what they measure Ihe indicator category will determine the type of data item that will be used in the report This is the list of data items available according to the category that was Chosen Their values will be placed along the X or Y axis of the This action button will generate the final report It will graph the val ues of the data items chosen Clicking Cancel will cancel the operation and reset all values After hitting Cancel the selected data items will be emptied Peer cities can be selected in two different ways gt By manually selecting the desired cities in the List Simply click inside the box next to each city ne a M ny ee MR I AUD Primary City Chicago Peer Cites JE a EF hmedabad Tmsterdaw hens angalore Bangkok Filter Category Operator Value Operator 2 Value 2 Filter Cities X Axis Category 1 Data Item 1 32 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL 2 By using filter categories Select the desired category to use as a filter Choose the logic operator from the list
26. s and thereafter groups them into five categories or quintiles based on their performance on each individual indicator The placement of the city in the top quintile Ist quintile indicates that the primary city is ranked in the top 20 percent for the selected indicator in comparison to its peers whereas a placement in the bottom quintile 5th quintile indi cates that the city isin the bottom 20 percent in comparison to its peers The tool lets users assess the cities performance across all the selected indicators based on such an analysis A detailed description on the use of this tool follows l An analogy may be made with the concept of utility functions or preference functions that underlie economics The economic rationale is that while there may indeed be significant variation in strength of preferences over different consumption baskets in terms of some underlying value scale it is cognitively extremely difficult to do more than assign relative ranks to the baskets Also as noted above cardinal valuations made by different individuals are not interpersonally comparable 12 URBAN TRANSPORT DATA ANALYSIS TOOL UT DAT USER S MANUAL USER S GUIDE FOR I HE UI DAT This manual contains step by step instructions for using the UI DAT It explains with examples how the outputs can be obtained and how the existing data can be updated Main Features The UT DAI is a multipurpose tool and its main features are
27. tes that the value for the indi cator selected has no data available for the main test city and thus cannot be compared to peers The indicator report will nevertheless show the graph and values of the peer cities with the main city showing a value of O OO USERINSTRUCTIONS 29 Generating Reports Scatter Plots This report is used to generate scatter plots if the user would like to compare the performance along one data item with changes in the value of another It is a valuable option to better portray the rela tionship between two data items which a bar column or line report cannot do The data will be displayed as a collection of points with the value of one data item determining the position of each point on the horizontal axis and the value of the other data item determining the posi tion on the vertical axis e While having the Report 2 Scatter Plots sheet active click on Generate Report Ee TA e UT Diagnostic Tool v7 New Report F Hame Insert Page Layout Formulas Data Review View Developer Add Ins FlowBreeze Flowchart Cut ain p EN T R Calibri aar T a 2 Sar Sp Wrap Text General r E ex g Copy z o 9 C 3 aste GEE t EEE z z su x 8 lt 0 Ot on lt 9 Format Painter a w a Ea Fae Merge amp Center k u n a 0 Com Clipboard fa Font Fa alignment z Number Tal F14 Fe A B c D E G 1 TRANSP RT nau veorldbank orp transgport Gene
28. using the CTRL key or SHIFT key Chart type These are the chart options for the final report For Report 1 a bar column or line chart can be selected Proceed This action button will generate the final report It will graph all indi Gators chosen and generate a new Excel file containing all reports Cancel Clicking Cancel will cancel the operation and reset all values After hitting Cancel the selected indicators will be emptied Select the primary city test city from the drop down menu This will be the city used to compare with peers Selected Indicators teres Gwrmwr gy ca lie cnet _ USEMINSTRUCTIONS 23 Peer cities can be selected in two different ways By manually selecting the desired cities in the list Simply click inside the box next to each city mom o O e cw coin Ci wed oma gt By using filter categories Select the desired category to use as a filter This can be income population area or any other data item Choose the logic operator from the list Click on Filter Cities LII SI IT IL u SSS pul i Bar C Column C Line Proceed Cancel The logic operator is the mathematical symbol that will define the value or the range of the filter category You can use one for a single value or both to enclose the category within a range e g Per Capita GDP gt 5 000 5 000 000 lt City population gt 20 000 000 24 URBAN TRANSPORT DATA AN
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