“IMPACT OF COMMON MOBILITY CARD ON TRAVEL PATTERN” CASE STUDY –DELHI #mobility as a service #ease the mobility Anshula Gumber School of Planning and Architecture, Delhi UP METRO Need of the Study Different Modes Different Fare Structures Hassle free and seamless travel Modern Technologies provide modern solutions • Facilitates multi-modal travel behavior. Commuters • Commuters just have to carry one card • Encourages faster boarding • Hassle free transaction. Enables commuters to enjoy the benefits of integrated fare policies. • Collection of real time data Transport Authorities • Complex fare schemes. • Help operators to balance peak • Expandable to the other and off peak patronage. services like toll payment, • Faster reconciliation of revenue congestion pricing in CBD with recorded data. areas, and parking and further for retail shopping. • It saves manhandling hours • Elimination of fake currency • Increases the accountability and from the economy. transparency of the transactions. • Increase the accessibility. • Enables the authorities to maintain the extra sum of money Literature Review London -Oyster Number Populati Cards/1000 Technology Additional SchemeAtlanta - MARTA Breeze Card TFL OysterTransport DublinCardmodes LUAS + NationalFunctions ITS of cards on served head used %of depositinformation to Boston - MBTACity Charlie Card Deposit MaximumToulouse- Pastel Fare TFLChicago Oyster - CTA43 Parameter Ventra8.17 5,263 Contactless Bus, Tube,Before Tram, LondonParis Docklands- Navigo Transit, RetailsAftermaximum and Concession fare for Houston million- METRO million Q Card card with RFID Light Railway (Metro),Netherlands the Emirates (Translink tourism)- OV Chipkaartchildren and students Number of cash transactions During the 1990’s to 2000, 30% of After the introduction of Oyster, the Los Angeles(2012) - LACMTA(2011) TAP Card and NFC Airline, London Overground and senior citizens bus journeys in London involved number of cash transactions on buses Miami - MDT EASY Card technology ,National Rail servicesEurope , Thames cash transactionsClippers River Bus services fell to just 1.4%. Montreal,London( Quebec -pounds)STM OPUS Card 5 12.5 40% Average 64% New Jersey - NJ TRANSIT Card Contactless Concession for 35 7.4 MTR, Light Rail, Tramways, Bus, HK Hong Kong (HK Dollar) card with RFID50 57 Transit, Retails, children88% and students million million 4,711 Ferry and Octopus and NFC parking and tourism and senior citizens (2018) (2018) Taxi technology North AmericaDelhi 50 60 83%Concession for Queues and ticket offices at Average ticket office queue time Average ticket office queuechildren time and was students underground stations Contactlesswas 129 seconds 78 seconds and senior citizens and EZ Link 17 5.7 card with RFID MRT, LRT, taxis, buses and road Transit, Retails, Singapore Armed PTENumber million of people million accommodated 2,935 15 people per minute 35 people per minute and NFC pricing parking and tourism Forces, Singapore (Singapore)at ticket(2018) gates (2018) technology Also, the deposit money charged is CivilhighAsia DefencewhenForce Boarding time approximately 2-3 seconds are saved per boarding in buses. and Singapore Police compare to the other global cities. Force Fraud and malpractices 2.5% of the total journeys made 1.5% of the total journeysThreemade type of cards: Delhi being the most populousHong Kongcity - OctopusPersonnalof all OV thecard, OV 14.3 11.7 This also Japanlead to – costPiTaPa savingAnonymous of card and ChipkaartRio de Janeiro – Rio Card Contactless above mentioned ones still lags behind. The card is million million 1,222 Train, Bus, tram and metro servicesapproximatelyTransit( Suicaand tourismup/Pasimo to £40m)single per useyear. card. The (Netherland card Mendoza(2017) – Red (2017)Bus not multifunctional. It is limitedSingaporeto Transit- EZproject Link. tookEven long intime Santiagos)Public transport – Transantiago usage In 2000 In 2005 Africa in implementation Peru, Lima- Tarjeta Public transitTransportit :33%is limited to onlyPublicbus Transportand :37%Metro.(2005-2014) Delhi 29.2 19 Private Transport:45% Private Transport:41% 1537 Contactless ThereCapeMetro, TownisRapidno – lineMyincentive ,DIMTSConnect ,DTCschemeTransit. Concessional Fares Metro Million Million(2 card There was 38% reductionfor incard traffic users and Durban – Muvo Card (One (2019) South019) America after the scheme. This furtherConcessional has also fares for Delhi One Johannesburg – Gautrain Goldreduced journey times. Weekdays and Ride) Lagos – ETC card Weekends Aim, Objective and Methodology AIM : To study the user Listing of public transport scenario in Delhi and finalizing the scope for further study behavior to ease the mobility using common mobility card Collection of Data Objectives: 1. To appreciate the types of smart card 2. To review the global best practices of using smart card for mobility. Primary data Secondary Data 3. To study the existing travel behavior of users. Socio-economic Data (Gender, Age, Vehicle Ridership Data by 4. To evaluate the travel behavior of non - ownership, Income, Educational Background, DMRC and DIMTS, users by expanding the smart card profession) DTC services Trip Characteristics (Trip Purpose, origin, Income generated by destination, Trip length, Trip cost and Trip Time, card (DMRC,DTC) 5. To estimate the economic benefits to Frequency of travel) users. Payment mode used and reason 6. To list out the financial benefits to Rating of intermodal parameters stakeholders Rating and Ranking of existing Card services Revealed Preference survey (PCA Analysis) Analysis of Data Multi –Criteria Decision making analysis for intermodal parameters Stated Preference survey, Design of Experiments Building up of Quantitative relationship between specific parameters By orthogonal analysis and indicators using various statistical tools Cojoint Analysis Policy Evaluating the economic benefits of the scenarios so generated Recommendations & Proposals Introduction: Study Area: Delhi Delhi Metro DTC AND DIMTS BUSES The DTC runs a fleet of 3,882 buses, of which Presently, the Delhi Metro network consists of 2,506 are low-floor non-AC buses, 1,275 are low- about 373 Km with 271 stations. floor AC buses and 101 green standard floor buses. Currently, there are 8 lines and the airport Besides, there are 1,672 cluster (orange) buses express line plying on city roads. Average Ridership of DMRC is 25.35 lakhs. Currently, bus fares in Delhi for non-AC buses are (Data as per RTI filed on 27/2/19) Rs 5, Rs 10 and Rs 15. There is a flat fare of Rs 5 Deposit is of Rs. 50 , so initial amount totals for travel in non-AC DTC and cluster buses for upto Rs. 150 travel up to five kms. Fare slab for travel in AC MetroMetro: : Average Monthly Daily Average ridership Ridership buses is between Rs 10 and Rs 25. Bus Passes are also available for students(Rs.100 28.00 28 27.61 per month), Normal Passes (Rs.800 per month for 27.50 27 Non AC and Rs. 1000 Per month for AC buses)and free pass for disabled persons and senior citizens. 2627.00 26.50 (Data as HT Times dated sept. 07, 2018) 25 25.90 26.00 Bus: Average Daily Ridership 24 25.38 25.35 25.50 46.77 43.47 23 50 38.87 42.25 Ridership (in lakhs) (in Ridership 35.37 2225.00 40 Ridership(in Lakhs) Ridership(in 2124.50 30 24.00 20 2015 2016 2017 2018 10 Jul-18 Jan-18 Sep-18 Oct-18 Jan-19 Feb-18 Dec-18 Jun-18 Apr-18 Nov-18 Aug-18 Mar-18 May-18 0 2012 2013 2014 2015 2016 Year (Data as(Data per RTI from filed DMRC on 27/2/19) Website) Clakhs) (in Ridership Year (Data from The Asian age article dated Oct 19, 2017) Introduction: Study Area: Delhi Primary Data Collection S.N Area Abutting o. Landuse 1 Nehru Place Institutional 2 Kashmere Gate Commercial 6 2 3 Anand Vihar Commercial 9 5 4 3 4 New Delhi Commercial 8 12 5 Old Delhi Commercial 10 11 7 6 Delhi Vishvidhalaya Institutional 1 7 Lajpat Nagar Commercial Metro Bus Number of 8 Connaught Place Commercial samples collected 9 Rajauri Commercial Captive X 200 10 Durgabhai Deshmukh Institutional Captive Captive 100 11 Hazarat Nizammuddin Commercial Captive Choice 50 Metro Bus12 Dwarka Mor Residential Cash Cash Choice Captive 50 Data was collected from different Cash DTC pass activity places having different landuse Choice X 50 Cash Card so to have a rich mix of characters of different commuters. Choice Choice 50 Card Cash Different samples were collected for X Captive 200 Card DTC pass different set of commuters as per the frequency of there travelling through X Choice 50 Card Card different mode. Data Analysis: Revealed Preference: Captive Riders Bus Metro Bus + Metro 3 3 2 2 2 t t t n n n 1 e e e 1 n n n Educational o o p o Employment 1 Educational p p Payment mode_Bus Payment mode m m 0 o m Reason 0 Age C o Educational Employment o Employment C Payment mode C d Gender n d -1 d 0 Age o n n Income c o Reason for not using in bus e Reason o -1 c Income Gender c Age S Income e e S -2 S -1 Gender -2 -3 -4 -3 -2 -1 0 1 2 3 4 5 -2 -2 -1 0 1 2 3 4 -3 -2 -1 0 1 2 3 4 First Component First Component First Component Variable PC1 PC2 PC3 Variable PC1 PC2 Variable PC1 PC2 PC3 Age 0.572 -0.016 0.074 Age -0.337 -0.397 Age 0.463 -0.333 0.197 Gender 0.301 -0.565 -0.231 Gender -0.398 -0.343 Gender 0.202 -0.678 -0.176 Educational Level 0.475 0.133 0.017 Educational Level 0.456 0.029 Educational Level 0.055 0.218 0.862 Employment -0.456 0.198 -0.529 Employment Status 0.447 0.099 Employment Status -0.436 0.286 -0.272 Status Income Level 0.31 -0.558 Income Level -0.276 -0.208 0.256 Income Level -0.123 -0.629 -0.36 Payment mode 0.41 -0.015 Payment mode 0.504 0.323 -0.146 Payment mode 0.296 0.099 -0.599 Reason 0.235 -0.634 Reason 0.471 0.391 -0.163 Reason for not -0.214 -0.467 0.416 using the card in Total Cumulative Total Cumulative bus variance(>60%) 67.5% variance(>60%) 73% Kaiser-Meyer-Olkin Measure 0.558 Kaiser-Meyer-Olkin Measure 0.576 Total Cumulative of Sampling Adequacy(>0.5) of Sampling Adequacy(>0.5) variance(>60%) 75.4% Kaiser-Meyer-Olkin Measure of 0.61 Income and Reason for Mode and Reason for not Sampling Adequacy(>0.5) not using the card in bus using the card in bus are Income and Reason for not using are related.