planning for first &last mile connectivity...
TRANSCRIPT
PLANNING FORFIRST &LAST MILE CONNECTIVITY
FOR MASS TRANSIT USERSCase Study- Delhi MRTS
By Anannya DasTransport Planning Department (2013-15)
School of Planning & Architecture
Need & Importance of LMC
Structure of Presentation
Public Transportation Scenario- Delhi
MRTS Delhi & Station Typology
LMC Trip Characteristics Study
Case Station Study
Scenario Development & Evaluation
Conclusion & Recommendation
Approach to LMC
OBJECTIVE & METHODOLOGY
STUDY OBJECTIVE
1. To assess the importance of first &last mile connectivity for an efficienturban MRTS
2. To review global best practices inplanning for Last mile connectivityto urban mass transit systems
3. To assess the existing last mileconnectivity environment , trippattern & attitudinal behaviour ofMass transit Users
4. To Develop Last Mile access choicemodel
5. To evolve alternative strategies forenhancing last mile connectivity formetro user at case station
6. To recommend Approach &guidelines for last mile connectivity
METHODOLOGY
Stage I – Assessing the Study
Stage II – Assessing the Study Area
Stage III – Quantitative evaluation ofTrip Characteristics
Stage IV – Development ofMathematical model
Stage V – Providing Solutions
NEED & IMPORTANCE OF LMC
NUTP , 2006Focus on MASS TRANSIT Avg. Catchment
Recommendedservice Range
LAST MILE CONNECTIVITY COVERAGE w.r.t DELHIMETRO STATIONS
There are areas beyond walkable distance fromMRTS station
Note: In practice both first mile & last mile are synonymously used
If there are no provision of sustainable modeswithin this range people start depending on
private modes of transport
Thus to access from those area, people dependon auxiliary or feeder modes
ThusUnavailability of LMC options acts as deterrent to
use of Mass transport
LITERATURE STUDY
PARIS
SEOUL
HONGKONG
LONDON
SINGAPORE
SAN FRANSISCO
MELBOURNE
• Multiple modes availability• Extensive network• Less waiting time• Seamless travel between
MRT & LMC modes• Reduction in pollution
Findings for LMC requirement
Seoul MRTS NetworkSingapore Cycle network for
LMC
DELHI
Popu
latio
n (l
akhs
)
POPULATION GROWTH TREND DELHI 2011
Source: Statistical abstract of Delhi2014,
PER CAPITA INCOME DELHI
1995 – Rs 19,0002013- Rs. 40,000i.e. 100% increase- capacity to buys
pvt vehicleincreasing rapidly
VEHICLE GROWTH TREND 2014
Source: Statistical abstract of Delhi 2014, IUT 2014
2014 : 3,90,000 veh /million pop- Highest registered vehicles compare to global cities
INCREASE IN ROAD NETWORK IN DELHI
Source: State of Environment Report for Delhi 2010
AIR POLLUTION
Source: SAFAR, 2015
627,426 premature deaths/year in Indiadue to air pollution
http://www.topnews.in/law/files/delhi-pollution.jpg
PUBLIC TRANSPORTATION SCENARIO IN DELHI
MRTS(25 lakhpeople)
BRTS Suburban-Rail
MASS PUBLICTRANSPORTATION
PRIVATEMODES
2 WHEELER
IPT
AUTO CYCLERICKSHAW
MAIN HAUL• 192.7 km• 138 stations• 3000 daily trips• 3-4 min frequency
LAST MILE- FEEDER BUSES• 117 bus• 24 stations (17% of all)
MAIN HAUL• 140 kms• Loop rail
CURRENT SCENARIO
FUTURE SCENARIO
LAST MILE- WALKING60% area within 5 mins walking
LAST MILE- CYCLE• “Hire a cycle” scheme Vishwavidyalaya• Cycle Sharing
+
+
+• Annual travel demand in
increasing at the rate of 9.5%IN DELHI
• Share of Mass transit is belowdesired range
• Modal split growing opposite• Ideal for Delhi – Mass transit
should be at least 75% (>10million population)
TRANSPORT DEMAND FORECAST BY RITES 2020Mode Daily Trips 2021 Modal share %
Car 5953694 23.3
2w 4751593 18.6
Auto 1184732 4.6
Bus 8377185 32.8
Metro 5128868 20.1
Intracity Train 131317 .5
Total 25527388 100
DELHI
CAR
Decongesting Delhi, IUT 2014
MODAL SPLIT DELHI 2014
PCTR- 1.56TRAVEL DEMAND Delhi- 26
million trips
MRT/BRT72 lakh49%
66%
39%
102%
72%
Ride
rshi
p
MRTS DELHI
• OPERATION HOURS : 5:30 am - 00:00 hrs (17 hrs)• DAILy 000 trips at 3-4 min frequency• ROUTE LENGTH: 192.7 kms connecting 138 stations
Daily Avg. Ridership Growth 2010- 2014
CHANGE IN MRTS RIDERSHIP PATTERN 2010 - 2014
This change in Ridership depends onCharacteristics of stations
CHARACTERISTICS OF STATIONS
Mixed PSP IndustrialCommercialResidential
HighDensity
MidDensity
LowDensity
VeryHigh
Ridership
HighRidership
MidRidership
LowRidership
VeryLow
Ridership
DENSITY
LANDUSE
RIDERSHIP
Develop a matrix based on stationcharacteristics where certain set of stations
represent similar characteristicsOBJECTIVE
HIGHDENSITY
MIDDENSITY
LOWDENSITY
Residential
Commercial
PSP
Industrial
Mix
STEP 1- LANDUSE & DENSITY Step 2- LANDUSE & RIDERSHIP
HIGH DENSITY MID DENSITY LOW DENSITY
4001-8000 8001-16000 16001-40000 4001-8000 8001-16000 16001-40000 4001-8000 8001-16000 16001-40000RESIDENTIAL
COMMERCIAL
PSP
INDUSTRIAL
MIX
TOTAL
HIGHRIDESRHIP
MIDRIDERSHIP
LOWRIDERSHIP
RESIDENTIALCOMMERCIALPSPINDUSTRIALMIXTOTAL
Step 3 - STATION MATRIX w . r . t LANDUSE & DENSITY & RIDERSHIP
EVOLVING STATION TYPOLOGY
Note: Staions in the matrix excludes stations w.r.t special /Occasional/CBD /Industrial Area Stations
Distribution of station w.r.t landuse, density & Ridership
Note: The matrix consists of mid value stations within the category
Case Station Identification & Data Collection
TRIPCHARACTERISTICS
Overall Delhi
Across Metro Stationsof different character
w.r.t Landuse &Ridership
Across Tripproducing &
Trip attractingAreas
Source : UNEP Data 2014,SPA TP Thesis
9 stations
Hauz Khas & Noida
User Characteristics
Trip Characteristics
User Attitudinal Survey
Station Area Inventory
Transport Supply StatusQuantitative
Qualitative
Walkability
SURVEY TOOLS
• Survey Formats• Questionnaire
Survey• TVC at Station
• Ranking & rating• CAI Walkability
App
DETAILED STUDY LOCATIONTrip Characteristics , User Characteristics,
Availability of modes 9 locations
Transport Supply Status, User AttitudinalSurvey Hauz Khas, Noida
Walkability, Station Area, TVC Hauz Khas
S U R V E Y S
S A M P L ES T U D Y
17Days
700samples
LMC TRIP CHARACTERISTICS
9 cardinalZones
Green Mode Public Transport Carbon Mode
43% 28% 29%
Use of private vehicles isalmost same all over Delhi
Stations at TripTRIP
Length Time Cost
Attracting areas 0.9 8 16
Producing areas 1.2 9 20
DELHI NCR
UNEP Data 2014
ACROSS 9 STATIONS
Trip producing areas haslonger trip lengths
TRIP CHARACTERISTICS across USER GROUPSATL (km) ATT (min) ATC (Rs)
Female 1.5 6.5 22
Male 2.8 12 21
Regular Trip maker 2 8 18
Ocassional Trip maker 2.7 15 27
Though ATL & ATT of male is moreATC is similar for both
Regular trip maker tends to spendless time and cost for a lesser distance
w.r.t to occasional trip maker
LMC Trip Attributes at Case Stations
NOIDA SECTOR 15HAUZ KHAS
Station Mode
Supply Attributes
Location Supply Distance(m) Frequency
Avg.Passenger
pick up
Pick uptime (min)
WaitingTime (min)
HAUZ KHASDTC Bus Bus bay 50 5 5 1 -
Feeder Bus No designatedlocation 10 15 20 13 11-13
NOIDA 15 DTC Bus Bus Stop 100 5 3 - 5 1 -
Hauz khas is one ofthe 17 station with
feeder bus
OCCUPATION OF USERS
TRANSPORT SUPPLY STATUS
LMC Modal Split
STATISTICAL TEST OF TRIP ATTRIBUTES
DESCRIPTIVESTATISTICS
MEAN
STANDARDDEVIATION
COEFFICIENTOF
VARIATION
On Mean AcrossStations
Ratio OF LASTMILE TRIP TOTOTAL TRIP
ANOVA TEST
S U M M A R Y S T A T I S T I C A L T E S T S
HAUZKHAS
Length
Time
Cost
SIMILARSIMILAR
DIFFERENTDIFFERENT
VARIATIONVARIATION
NO VARIATIONNO VARIATION
Mean At Trip end
Mean By User
DIFFERENTDIFFERENTMean By Mode
SIMILARSIMILAR
NOIDA
Residential
Institutional
FINDINGS
LONGER LMCLONGER LMC
SHORT LMCSHORT LMC
LMC Trip Attribute Across Case Stations
Dense job distributionaround Noida stationSource: Primary survey 2015
NO
IDA SECTOR 15
HAU
Z KH
ASLast Mile Trip Length
Access &Dispersal trip are
similar
Dispersal tripare shorter
Last Mile Trip Time
Longer waitingtime
Most trips arewithin 6 mins
of travel
Last Mile Trip Cost
Service Area Determination of Modes
Range WALK AUTO BUS GRAMIN SEVA RICKSHAW 2W CARPrimary Catchment 0 - 1. 5 km 44 5.8 0.5 19.8Secondary Catchment 1.5 - 3 km 11.0 2.4 0.6 0.5 0.9
3 - 5 km 8.7 2.4 2.4 1.0
% Distribution of Trip as per Service Range of Mode
MODES (km) (min)Walk 0.8 8Cycle 2Auto >3 15Bus >4 15PVT 6 20
TRIP RATIO ANALYSISMode of
travelATL ATT
LMC % MAIN HAUL % LMC % MAIN HAUL %Walk 2 98 10 90Bus 16 84 22 78IPT 9 91 15 85PVT 16 84 22 78
SERVICE RANGE OF MODES
*Note: Entire table sums upto 100%
BA
C
D
A B
DC Pedestrian
Network Length= 2.8 km
NOTE: Representation (not to scale)
Pedestrian flow
Source: Author, 2015
Location
Physical infrastructureSpeed
(m/sec) LOSWidth(mts)
length(mts)
Frequentobstruction
A 1.5 100 Y 0.60 FB 1.5 200 Y 0.90 EC 2 180 - 1.10 DD 1 80 - 0.90 E
Avg. 0.90 E
WALKABILITY ASSESSMENT AT HAUZ KHAS
Existing Situation Assessment – Primary catchment Area
WALKING DEPENDS UPON
LOS Improvement required
Source:User preferencesurvey, 2015
An empirical Study conducted at various station also shows that people walk more at areas with better pedestrianinfrastructure
Avg Indian condition has LOS CSource: Dr. Purnima Parida , Scientist, CRRI, 2009 & Primary survey at 7 stations, 2015
HAUZ KHAS METRO CATCHMENT AREA
HAUZKHASEXIT
BUSSTO
P
Choked traffic in front of Staion
Feeder Bus & Auto waiting topickup passenger
Gramin Sewa queueblocking DTC Bus Stop
Too long queue depictsunmatched demand supplystatus
AUTOBUS
CAR
Source: Author, 2015
HAUZ KHAS METRO AREA
46% trips
12% trips
20%trips
22% trips
Feeder BUS
DTC BUS
GRAMIN SEWA
PT ROUTES WITHIN 5.5 KM RADIUS OF HAZU KHASSTATION
Source: User preference survey, 2015
NOTE: Representation (not to scale)
SATISFACTION OF LAST MILE MODE CHOICE14 % BUS USERS 40% AUTO USERS
• Unmatched demand supply status• Long waiting time acts as a deterrent to use of
service
Mode Location Supply Hours ofoperation
Frequency/15 min
Avg. Passengerpick up
DTC Bus Bus bay 16 5 5Feeder - 10 16 1 20Auto - - - 130 150
Need for Improvement
Auto users are leastsatisfied with fare
Thus an option to increase availability of buses might lead to shift of auto users dissatisfied with High fares
not satisfied with availability &waiting time
Existing Situation Assessment – Secondary catchment Area
SHIFT POSSIBLE
?
COper
Persongm/km
PM 2.5per
persongm/km
1.3.05
2.40.054
COper
Persongm/km
PM 2.5per
persongm/km
00
0.120.0006
VS
How
58% 39%
70%27%
Carbon modes Sustainablemodes
80 person1 person
2 person
Underlying FACT : A user will only shift if he has option within his range of travel
Bus & Auto
EXPECTED MODAL SHIFT
Thus
LOSImprovement
by
SERVICE RANGE GRAPH SERVICE RANGE GRAPH
EMPIRICAL STUDY SAYSPeople walk more at areas with betterpedestrian infrastructure
Thus there can be a Probability of shift ofusers from Auto to walk within 1.5 km ifwalkability of the area is improved
Development of Last mile access choice model equations
reducing waiting time through improvingfrequency of to check probability for shiftfrom Auto to Sustainable public transportmode Bus.
EMPIRICAL STUDY SAYSRidership increases with increase inservice availability
LMC Modal Split at Hauz Khas
Walk & Auto
% Tr
ips
% Tr
ips
LAST MILE ACCESS CHOICE MODEL
U (Auto) = 16.071+ 0.219(Time) + 0.513(Cost) + 0.319(W_Time)Model
DataShare
S_Time S_Cost S_W Utility Walk Auto
75% 2.17 32 0.66 1.03173.70
%26.30
%
25% 2.12 31.7 0.79 0.90771.20
%28.80
%
Here Share of Walk to Auto is73.7 : 26 and data mismatch is5% (73.7%-69.7%).
U(Bus) = -0.003+ (-0.07)(Time) + (-0.11)(Cost) + (0.261)(W_Time)
DataShare
Model
S_Time S_Cost S_W Utility Walk Auto
75% -1.81 28.9 -8.4 -0.8629.70
%70.30
%
25% -1.4 30 -9 -0.8529.80
%70.20
%
Share of Bus to Auto is 30: 70 anddata mismatch is very less i.e.11%. (29.7%-40.9%).
Validation
ModeCount
UserRatio
ModelRatio
Walk 44 30.30% 26.30%
Auto 101 69.70% 73.70%
Validation
ModeCoun
tUserRatio
ModelRatio
Bus 55 59.10% 70.30%
Auto 38 40.90% 29.70%
Equation 1Probability of shift from Auto to Walk
Equation 2Probability of shift from Auto_Bus
Secondary catchment Area
Primary catchment Area
BAU Transit ConnectivityOption T1 Option T2 Option T3
Auto 52 39 37 29Walk 25 25 25 25
Bus 14 27 29 37Gramin sewa 3 3 3 3Pvt. Veh 6 6 6 6
100 100 100 100
BAU IMPROVED WALKABILITYOption W1 Option W2 Option W3
Auto 52 44.4 43.5 43.8
Walk 25 32.6 33.5 33.2Bus 14 14 14 14Gramin sewa 3 3 3 3Pvt. Veh 6 6 6 6
100 100 100 100
SCENARIO BUILDING
INCREASING WALKABILITYWITH EQUATION 1
OPTION Speed w.r.t S_Time S_Cost S_W UtilityShare
Walk Auto
Existing LOS E - - - - 69% 31%
Option W1 LOS D -4.31 -26 -1 0.827 69.6% 30%
Option W2 LOS C -3.5 -34 -1 0.985 72.8% 27.2%
Option W3 LOS A,B -2.9 -34 -1 0.978 72.7% 27.3%
DEVELOPMENT OF IMPROVED TRANSITCONNECIVITY WITH EQUATION 2
OPTION Reduction inwaiting time S_Time S_Cost S_
W UtilityShare
Bus AutoExisting - - - - - 26% 74%
Option T1 15% 6 -34 8.4 -0.715 32.9% 67.1%Option T2 30% 6 -28 5 -0.523 37.2% 62.8%Option T3 60% 6 -18.7 1.3 0.317 57.9% 42.1%
MODAL SPLIT OPTIONS MODAL SPLIT OPTIONS
Pedestrian infrastructure improvement Service & Frequency Improvement
The share of bus increases with decrease in waiting time
SCENARIO 2SCENARIO 1
33.5 % 29% 37%Walk BusUsers
33.5%
29%
SCENARIO BUILDING
SCENARIOS
IMPROVED TRANSIT CONNECIVITYSCENARIOS
37%
IMPROVED WALKABILITYSCENARIOS
COMPOSITE 1
COMPOSITE 2
COMPOSITE OF WALK &TRANSIT
Thus 5 modal split options
SCENARIO EVALUATION
Reduction ofemission levels can
measuredtranslating modal
split w.r.t emissioncoefficients as givenin the CMP toolkit
,2015 by IUT
Improvement in scenarios led to reduction inmotorized modes and increase in
sustainable modes
Immediateinfluence
area
Walking LOSpedestrian
amenities &Design standard
Reduced waitingtime by 30%
Reduced waitingtime by 60%
ImprovedWalkability nwaiting time
ImprovedWalkability nwaiting time
=
=
5 MODALSPLIT
OPTIONS
Secondaryinfluence
area
1
2
3
4
5
12
3
4
5
5
OP
TI
ON
S
SCENARIOS
Source emission calculation:• Vehicle occupancy is taken as per survey• Emission coefficient is considered from CMP Toolkit
Impr
oved
Wal
kabi
lity
Impr
oved
Tran
sit c
onne
ctiv
ity
Impr
oved
Wal
kabi
lity
& Tr
ansit
BUS 37%
BUS 29 %
Walk 33 %
Walk 33 %
Emission level w.r.t Scenario 1
Emission level w.r.t Scenario 2
Emission level w.r.t Scenario 3
Scenario Evaluation w.r.t Emission Reduction
Share of mechanized modes increase carbonemissions directly
Year Ridership PM 2.5 (gm/km) CO (gm/km)
2015 38,171 1581 46,0662020 68,434 70% 70%2025 1,07,432 160% 160%
At BAU, considering same trend of modal split forfuture, the emission level for 10 years from nowwill grow up to 160 times higher
ScenarioShare of
NonCarbonModes
Share ofCarbonmodes
Emissions
PM 2.5(gm/km)
Co(gm/km)
Walkability 33 67 -13% -12%
Transit A 25 75 -23% -16%
Transit B 25 75 -36% -24%
Composite A 33 67 -36% -27%
Composite B 33 67 -49% -36%
REDUCTION IN EMISSION WITH DEVELOPEDSCENARIOS
EMISSION IN BAU SCENARIO
5
4
3
2
1
5
Option 5 gives 36%emissionreduction
Scenario Evaluation w.r.t Emission Reduction
How to achieve this?
Area level intervention
PLANNING FOR PEDESTRIAN NETWORK WITHIN PRIMARY CATCHMENT AREA
WALKABILITY IMPROVEMENT- PLANNING INTERVENTION
Existing OD based demand
Missing links
Current Walking pattern
Demography distribution
Evaluating identified networkby Graph Theory
Identifying commercial,recreational and residentialareas
PEDESTRIAN NETWORKIDENTIFICATION CRITERIA
Increase in network from 2.8 km to 11.2 km
Networklink(e)
nodes(v)
Beta index(link/nodes)
Gammaindex
AlphaIndex
Existing 12 9 1.3 57 0.31Proposed 34 14 2.4 94 0.91 HIGH
Connectivity Index
All three indexes of Connectivity measure, namely Beta, Gamma andAlpha index show higher values for recommended network, thusindicating it as a better network.
Shimbel’sindex
Associatenumber
Mean Associateno
Existing 32 6 6
Proposed 31 4 3.6 LOW
Accessibility index gives a decrease in both Shimbel’s index and associatenumber shows a lower value for recommended network. The meanassociate number is also reduced by 40%, thus indicating network withimproved levels of accessibility
Accessibility Index
Graph Theory
ACCESSIBILITY(lower index is better)
CONNECTIVITY(higher index is better)
Existing Network2.8 km
Recommended Network11.2 km
WALKABILITY IMPROVEMENT- PLANNING INTERVENTION
FEEDER ROUTE IDENTIFICATIONCRITERIA
Existing OD based demand
Catchment populationservice
Existing service gaps
Present Bus usersTarget users
TRANSIT CONNECTIVITY IMPROVEMENTPLANNING INTERVENTION
Planning For Feeder Bus Services within Secondary Catchment Area
The physical performance of the transit is evaluated based on current practice standards
Capacity MINI Bus 22Speed 15 kmphLoad factor/Day 0.7Vehicle utilization (km/bus/day) 160 - 180FU/day/route 0.9Operating cost (km/Bus/Day) Rs. 25 - 30Person/Bus/yr 8Fare (current) 5km & >5km Rs 5 & Rs 10
PRACTICE STANDARDS
which gives an improved frequency of 5 mins, improvedfleet size from 24 and which suggests that it can serve 80%
of users compared to 20% in the existing system
TRANSIT CONNECTIVITY IMPROVEMENTPLANNING INTERVENTION
Physical Evaluation of FEEDER TRANSIT SERVICES
Financial performance of Feeder Transit services
Operational Profit Evaluation
26feederbuses
90%user
Current10 feeder
Current20%
Considering same fare/kmIncreasing service standards
leads to profit in spite of- increasing buses- Reducing route lengths
Profit
MODAL SPLIT
LMC Recommendations
SERVICE RANGE
SUPPLY/ 1000 user
RECOMMENDED feederGUIDELINES
800 m Walk, Cycleupto 1.5 Walk , cycle, Rickshaw, E rickshaw
1.5 - 3 km Rickshaw, E rickshaw, Auto, Feeder3 - 5 km Auto, Feeder Bus
Beyond 3.5 km Private vehicles
Auto 21%Auto 140Bus 19Gramin sewa 4
SERVICE RANGE
SUPPLY/ 1000 user (Low density High Ridership Stations
Route Network 3- 8 kmfrequency 5 – 7 minsBus: metro 1 : 2Capacity 22VU (km/bus) 160- 180Fare Rs10 (<5km), Rs 20(>5km)
RECOMMENDED feeder GUIDELINES
RECOMMENDATION
Modal SplitAuto 20-25Walk 30- 35Bus 33-38Gramin sewa 3-5Pvt. Veh 4-6
100
MODAL SPLIT for (Low density High Ridership Stations
Developmentof Last Mile
access choicemodel
StationcatchmentArea Audit
ImprovementIdentification
Applicationof Model toIdentify Best
Strategy
2 3 4 5ExistingDemand
assessment
1Planning
InterventionIn Catchment
Area
6
LMC APPROACH RECOMMENDED
STATION AREADEVELOPMENT
LAST MILE MODALSPLIT
PRIMARY STATIONAREA
SECONDARYSTATION AREA
Operation Integration(synchronization of time)
Physical Integration(Route synchronization)
Information Integration
Fare Integration(One smart card)
MULTIMODALINTEGRATION
CONCLUSION
Improvement inMODAL SPLIT
LMC improvement Impactat Hauz Khas Station area
FEEDER SYSTEM
USER BENEFIT ASSESSMENT Feeder Services
TRANSPORT SUPPLY & METRO INTEGRATION@ 5 MIN INTERVAL• 2 metro (approx.)• 1 feeder bus• 2 min Waiting Time• 45 Auto• 2 Gramin sewa vehicle
Frequencyincrease Fleet size Financial
GainUser
servedWaiting
timedecrease
TRANSIT CONNECTIVITY IMPROVEMENT
Improvement of Multimodal Integration
Existing RecommendedNo of routes 1 4User served 20% 90%Fleet size 10 26
Frequency 15 min 5 minWaiting Time 8 min 2 min
52%
6%
14%
25%
3%
33%
21%6%
37%
Increase inpedestrianNetwork
All Residential &Recreationalconnected
Maximum walkingdistance to metro
is 800 mts
WALKABILITY IMPROVEMENTCONCLUSION
MAIN LINE HAUL OFTRAVEL
Any Questions ?