ICECC 2023 Fukuoka

1. Kelvin J. A. Ooi*, K. S. Lee, M. A. S. Bhuiyan
Department of Physics, Xiamen University Malaysia
kelvin.ooi@xmu.edu.my

4.  Public health and environmental
concern due to road transport
exhaust emissions
 People living in urban areas are at
higher health risk
 Technological improvements and
policy settings does not keep pace
with the increase of travelling
demand
 Particularly in developing countries
where emissions regulation were
inadequate

5.  Malaysia has one of the lowest public transportation users
level among Asia.
 Initiation of the Green Technology Master Plan (2017–2030)
 Increase the overall public transport modal share to 40% by
the year of 2030.

7. Determine the fuel consumption
of vehicles within study area
Perform modal shift using
PCU and passenger load
factors
Determine the fuel consumption of
vehicles at 20%, 30% and 40%
public transport modal share
Greenshield’s macroscopic stream models to
determine the change in traffic flow parameters
associated with modal shift
Evaluate the effectiveness
of mitigation strategy

8. *Data obtained from Halcrow Report

9.  Travelling Fuel Consumption
 Congestion Fuel Consumption (Idling)
 Idle Time Estimation
𝐹𝐶𝑗 𝐿 ℎ 𝑟 =
𝐽𝑜𝑢𝑟𝑛𝑒𝑦 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑘 𝑚 𝑃 𝐶𝑈
𝐹𝑢𝑒𝑙 𝐸𝑐𝑜𝑛𝑜𝑚𝑦 𝑘 𝑚 𝐿
× 𝑇𝑟𝑎𝑓𝑓𝑖𝑐 𝐹𝑙𝑜𝑤 𝑃𝐶 𝑈 ℎ 𝑟
𝐹𝐶𝑖 𝐿 ℎ 𝑟 = 𝐹𝐶0 L s × 𝐼𝑑𝑙𝑒 𝑇𝑖𝑚𝑒 𝑠 𝑃 𝐶𝑈 × 𝑇𝑟𝑎𝑓𝑓𝑖𝑐 𝐹𝑙𝑜𝑤 𝑃𝐶 𝑈 ℎ 𝑟
𝐼𝑑𝑙𝑒 𝑇𝑖𝑚𝑒 𝑠 𝑃 𝐶𝑈 = 𝐷𝑗𝑖 𝑚 𝑃 𝐶𝑈 ×
1
𝑣𝑓 𝑚 𝑠
−
1
𝑣𝑐 𝑚 𝑠

10.  Adapting data into Greenshield’s model
Transportation
mode
Passengers/
vehicle
Car 1.55
Motorcycle 1.2
Bus 18.4

13.  Ong et. al [*]: 6% savings on 10% shift to public
transportation.
 Our model:
 5.9% savings on first 10% shift to public transportation
 7.46% savings on next 10% shift
 8.35% savings on next 10% shift
 6% savings come from the reduction of vehicles travelling on
the roads.
 Additional savings comes from the multiplier effect originating
from reduction of traffic congestion and idle time!
*Ong, H. C et al, (2011). A review on emissions and mitigation strategies for road transport in
Malaysia. Renewable and Sustainable Energy Reviews, 15(8), 3516–3522.

14.  Traffic forecasting and Fuel consumption models to inform
governmental policies on public transportation.
 More than 20% fuel consumption reduction leading to
mitigation of Greenhouse gases emissions.
 Shows the dynamics of multiplier effect of
i. Reducing number of vehicles on the road
ii. Reducing congestion and hence lowering idle-fuel burning
 Reduce total fuel consumption by 21%, which is equivalent to
0.6 million liters per year.