Analysis to find minimum potential
savings by Carpooling
Gopi Padmanabhan, Student, MSc in GISc
Introduction
Approach
Abstract
esri. (n.d.). Iterate Field Values (ModelBuilder). Retrieved March 15, 2014, from ArcGIS Help 10.1
Jianling Li, P. E. (2007). Who Chooses to Carpool and Why? Retrieved March 15, 2014, from TEXAX A&M UNIVERSITY
Pearce, P. M. (2009). Investigating the Energy Saving Potential of Flexible Carpooling. Retrieved March 15, 2014, Flexible car pooling
Rob Perks, C. R. (2013, July). Driving Commuter Choice in America. Retrieved March 15, 2014, Natural Resources Defense Council
References
Carpooling reduces cost, pollution, stress, traffic congestion. A scenario of employees of same workplace, is considered, with minor
office schedule variations and friendly colleagues being advantageous for carpooling. The individual optimal commute routes are found
from captured individual employee residences to the office, to determine minimum potential savings. The potential reduction of distance is
determined by calculating overlapping route portions and accommodating persons in empty seats of cars and bikes.
817
258
376
209
0
500
1000
Bike Bus
Actual and Saved distance
(kms)
Actual (Kms) Savings (Kms)
46%
81%
0%
50%
100%
Bike Bus
Savings Percentage
This study results reveals the quantity of the minimum savings potential as expected and, the potential carpooling routes could also be
identified. The results points that the benefits can be reaped if more employees are located closer to each or other near the commute
route of colleagues.
The actual and saved distance is shown in graph. It is found that a minimum quantity of 376 bike kms and 209 bus kms and could be
saved if the carpooling is adopted. This is a savings or reduction of 46% and 81% for bike and bus respectively.
Results and Discussion
In daily life, employees commute usually from their homes to work place. Considering a single work place like an office / industry, the routes travelled
by its employees, usually start to converge, as they get closer to their work place and finally reach a single destination point. This convergence of
commute routes to same destination and also availability of vacant seats in their vehicles creates a potential for carpooling.
Road network data is captured from OpenStreetMap
and a network is built using it. Other dataset used is
employee residence locations and office location.
Employee commute routes are found to the office.
Segmentation is performed on the commute routes.
For each route segment the values such as number of
vehicles travelling and their types is calculated during
the segmentation. This segment information is then
used to calculate the number of vehicles that could be
avoided after accommodating all the passengers in
minimal number of vehicles. The number of vehicles
that could be avoided is multiplied by the route
segment length. The final result is then summarized
using the vehicle savings in each segment.

Analysis to find minimum potential savings by Carpooling

  • 1.
    Analysis to findminimum potential savings by Carpooling Gopi Padmanabhan, Student, MSc in GISc Introduction Approach Abstract esri. (n.d.). Iterate Field Values (ModelBuilder). Retrieved March 15, 2014, from ArcGIS Help 10.1 Jianling Li, P. E. (2007). Who Chooses to Carpool and Why? Retrieved March 15, 2014, from TEXAX A&M UNIVERSITY Pearce, P. M. (2009). Investigating the Energy Saving Potential of Flexible Carpooling. Retrieved March 15, 2014, Flexible car pooling Rob Perks, C. R. (2013, July). Driving Commuter Choice in America. Retrieved March 15, 2014, Natural Resources Defense Council References Carpooling reduces cost, pollution, stress, traffic congestion. A scenario of employees of same workplace, is considered, with minor office schedule variations and friendly colleagues being advantageous for carpooling. The individual optimal commute routes are found from captured individual employee residences to the office, to determine minimum potential savings. The potential reduction of distance is determined by calculating overlapping route portions and accommodating persons in empty seats of cars and bikes. 817 258 376 209 0 500 1000 Bike Bus Actual and Saved distance (kms) Actual (Kms) Savings (Kms) 46% 81% 0% 50% 100% Bike Bus Savings Percentage This study results reveals the quantity of the minimum savings potential as expected and, the potential carpooling routes could also be identified. The results points that the benefits can be reaped if more employees are located closer to each or other near the commute route of colleagues. The actual and saved distance is shown in graph. It is found that a minimum quantity of 376 bike kms and 209 bus kms and could be saved if the carpooling is adopted. This is a savings or reduction of 46% and 81% for bike and bus respectively. Results and Discussion In daily life, employees commute usually from their homes to work place. Considering a single work place like an office / industry, the routes travelled by its employees, usually start to converge, as they get closer to their work place and finally reach a single destination point. This convergence of commute routes to same destination and also availability of vacant seats in their vehicles creates a potential for carpooling. Road network data is captured from OpenStreetMap and a network is built using it. Other dataset used is employee residence locations and office location. Employee commute routes are found to the office. Segmentation is performed on the commute routes. For each route segment the values such as number of vehicles travelling and their types is calculated during the segmentation. This segment information is then used to calculate the number of vehicles that could be avoided after accommodating all the passengers in minimal number of vehicles. The number of vehicles that could be avoided is multiplied by the route segment length. The final result is then summarized using the vehicle savings in each segment.