Traffic
congestion
and Bike ShareCase study – Pune, Maharashtra, India
PRESENTED BY:
PARVESH KUMAR SHARAWAT
Case study
– Pune Pune is a city in the
western Indian state of Maharashtra
Radial city, mixed land use
Around 50% trips are less than 8 km
Average trip length is 6.1 km - suitable for cycling
Pune has a City-wide bus system which they are upgrading to a BRT system
Highest Public transport accessibility, safety and transportation performance index
Case Study- Pune
Cycling in Pune
Pune has a cycling culture –cycling across all income groups.
Second highest bicycle mode share (11%) among similar population cities
One of the lowest 3% bicycle accidents
Pune is already planning extensive cycling infrastructure for entire city so the question of safety while cycling gets addressed
Planning to invest in a city-wide Bike share system
Existing infrastructure
Infrastructure
audit - results
Existing cycle tracks either good or fair - from safety point of view
•Encroachment of cycle lane, kind of signage for cyclists, buffer zone type, height of cycle track, type of traffic calming ramps at intersection
Major partition of cycling tracks are comfortable to ride
•Pavement quality, slope of cycle track and shade quality
Coherence and directness aspect - existing cycle track shows poor results
•Marking for continuity, cycle track signage and barrier free cycle track
Cycle tracks are very attractive from design aspect
•Land use along footpath, cycle lane type and width of cycle track
Smart city – Bike share
system
Potential mode shift estimation process
Probability to shift –different cut off
points (0.5 to 0.9)
Modal shift for short and long trips
Extrapolation on city mode share
(updated from HH survey 2016)
Total modal shift –number of trips using City demographic
(2016 projected population)
Binary logistic regression
model
Multivariate
Univariate
Stepwise backward
User survey –socio-
economic, trip and
perception variables
User survey –willingness to
shift
Potential modal shift to Bike share system
Mode 0.5 cut off 0.6 cut off 0.7 cut off 0.8 cut off 0.9 cut off
Short
trips to
BS
Long
trips to
PT
Short
trips to
BS
Long
trips to
PT
Short
trips to
BS
Long
trips to
PT
Short
trips to
BS
Long
trips to
PT
Short
trips to
BS
Long
trips to
PT
Walk 99% 100% 92% 100% 69% 33% 42% 33% 8% 0%
Cycle 100% 93% 99% 93% 95% 58% 75% 51% 29% 0%
2wheeler 96% 90% 92% 91% 74% 62% 32% 38% 6% 0%
Car 100% 85% 91% 85% 61% 50% 30% 35% 0% 0%
PT 99% - 89% - 67% - 31% - 5% -
Auto 95% 75% 84% 75% 65% 17% 40% 17% 7% 0%
Total 98% 88% 91% 89% 71% 44% 40% 35% 9% 0%
New mode share including Bike share as mode choice
Mode Existing 0.5 cut off 0.6 cut off 0.7 cut off 0.8 cut off 0.9 cut off
Walk 47% 11.5% 14.0% 22.4% 32.1% 43.9%
Cycle 3% 0.1% 0.1% 0.3% 0.9% 2.3%
Bike share 0% 63.3% 59.2% 45.4% 25.4% 5.2%
Two wheeler 29% 4.6% 5.1% 10.8% 20.1% 28.1%
Car 6% 0.9% 1.1% 2.8% 3.9% 5.5%
PT 11% 18.8% 19.3% 16.2% 14.9% 11.0%
Auto rickshaw 4% 0.8% 1.2% 2.2% 2.9% 4.0%
New PCU (Mode shift to Bike Share)
Congestion reduction
Short trips
Access &
egress
Avg. occupancy
No. of trips
No. of vehicles
PCU savings
Current PCU
Potential decrease in
congestion – Bike share
Mode Avg. occupancy PCU
walk - -
cycle 1 0.5
2wheeler 1 0.5
car 1.25 1
bus 60 3
BRT 60 3
auto 2 1
Potential decrease in
congestion – Bike share
Potential decrease in
congestion – Bike share
Benefit Cut off (0.9)
Changes in
congestion
-1%
Parking demand
rationalization
1%
Potential decrease in
congestion – Bike share
Benefit Cut off (0.8)
Changes in
congestion
9%
Parking demand
rationalization
20%
Potential decrease in
congestion – Bike share
Benefit Cut off
(0.5)
Cut off
(0.6)
Cut off
(0.7)
Cut off
(0.8)
Cut off
(0.9)
Changes in
congestion
20% 21% 13% 9% -1%
Parking demand
rationalization
54% 52% 35% 20% 1%
Scope of future research
Thank
youThis Photo by Unknown Author is licensed under CC BY-SA