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