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Dr Susan Grant-Muller
Measuring ITS Policy
through KPIs
Susan Grant-Muller and Ben Kolosz
Dec 18th 2014
s.m.grant-muller@its.leeds.ac.uk
ITS and sustainability KPI’s
Assessing	
  the	
  Environmental	
  	
  and	
  Energy	
  
(E&E)	
  impacts	
  of	
  ITS	
  as	
  part	
  of	
  a	
  wider	
  
evalua>on	
  framework	
  
•  Can	
  ITS	
  generate	
  E&E	
  impacts?	
  
•  Do	
  stakeholders	
  think	
  these	
  are	
  important?	
  
•  How	
  can	
  we	
  capture	
  them?	
  
•  Where	
  do	
  they	
  sit	
  in	
  a	
  wider	
  evalua>on	
  
framework?	
  
The big issue…
Isn’t whether ITS has energy and carbon impacts,
but the size of these and how best to capture
them. For example….
ITS	
  scheme	
   S t u d y	
  
Context	
  
Reported	
  Carbon/Energy	
  Impacts	
  
Electronic	
  charging	
   UK	
  
London	
  
a)	
  2003-­‐	
  2006,	
  ↓	
  16%	
  	
  carbon	
  emissions	
  in	
  central	
  Zone	
  
b)	
  2007	
  western	
  extension	
  zone	
  ↓6.5%	
  by	
  2008	
  
Hard	
  shoulder	
  running/variable	
  
speed	
  limits	
  	
  
UK	
   M42:	
  ↓	
  4%	
  -­‐	
  10%.	
  Fuel	
  consump>on	
  ↓	
  4%.	
  Similar	
  findings	
  
from	
  studies	
  of	
  VSL	
  on	
  M25	
  
In-­‐vehicle	
  control	
  and	
  
performance	
  systems	
  	
  
USA,.	
  	
   normal	
   condi>ons.	
   ↓	
   5%	
   carbon	
   no	
   feedback/coaching,	
   ↓	
  
10%	
  carbon	
  with	
  feedback/coaching	
  
Eco-­‐driving	
  	
   Field	
  trials	
   ↓	
  average	
  10%	
  	
  carbon	
  emissions	
  
In	
  vehicle	
  (overridable)	
  speed	
  
control	
  
UK	
   Motorway	
  –	
  average	
  ↓	
  6%	
  benefit	
  CO2	
  
Other	
  road	
  types	
  –	
  lible	
  benefit	
  or	
  small	
  disbenefit	
  on	
  low	
  
speed	
  urban	
  roads.	
  20%	
  difference	
  in	
  emissions	
  between	
  
lowest	
  and	
  highest	
  emidng	
  drivers	
  
Dynamic	
  systems	
  	
  u>lising	
  RTTI	
  	
  
	
  	
  
simulated	
   ↓	
  10%-­‐20%	
  carbon	
  emissions	
  and	
  fuel.	
  Real	
  world	
  
experiments	
  -­‐	
  slightly	
  lower	
  findings	
  
Eco-­‐driving	
   NL	
   ↓	
  0.3%-­‐0.8%	
  fuel	
  consump>on	
  1999-­‐2004	
  
	
  	
  
In	
  vehicle	
  technology/other	
  
measures	
  
EU	
  
	
  	
  
↓	
  5%	
  -­‐	
  25%	
  	
  carbon	
  
	
  	
  
Platooning	
  and	
  road-­‐trains	
   Lab	
   ↓	
  Up	
  to	
  20	
  %	
  fuel	
  consump>on	
  and	
  carbon	
  emissions.	
  	
  	
  
Teleworking	
   UK	
   ↓	
  2.4	
  %	
  of	
  carbon	
  emissions	
  from	
  cars	
  by	
  2050	
  
Personalised	
  travel	
  planning	
   JP	
   ↓ 20% carbon emissions through changes to route/
•  Managing excess demand on parts of the system -
mitigates environmental impacts of congestion
•  Speed smoothing - reduces vehicle emissions by shifting
demand (e.g. to off peak) through economic measures.
•  Route management - supports adaptation during climate
extremes 	
  
•  Enforcement systems - maintain expected environmental
and other benefits from infrastructure improvements such
as dedicated lanes.
•  Driver behaviour - directly impacts on driver behaviour and
performance of the vehicle to reduce emissions
•  Trip substitution - demand reduction
Drivers	
  on	
  ITS	
  	
  E&E	
  impacts	
  (1):	
  
Further set of impacts arise from:
•  Constructing and maintaining the roadside infrastructure
e.g. gantry’s, roadside kit (and decommissioning)
•  Energy supply for ICT elements (VMS etc)
•  Datacentre/control centre for operation and traffic
management
•  Enforcement equipment
Drivers	
  on	
  ITS	
  	
  E&E	
  impacts	
  (2)	
  
Do Stakeholders believe E&E impacts matter?
General Methodologies to capture E&E impacts
•  Cost Benefit Analysis (CBA) and Cost Effectiveness
Analysis (CEA)
•  Multi-Criteria Analysis (MCA)
•  Ecological Footprint (EF)
•  Environmental Impact Assessment (EIA) and
Environmental Risk Assessment (ERA)
•  Standardised Environmental Management System (EMS)
•  Life Cycle Assessment (LCA) and Life-cycle Cost Analysis
(LCC)
•  Regional/Strategic Environmental Assessment (R/SEA)
Where do ITS E&E impacts sit in wider framework?
•  Need to capture both ITS benefits and costs
•  KPI should cover installing and running ITS + estimate of
impacts from changes in road user behaviour and choices
•  Need to consider specific indicators and measurement
covering local environment, global environment and energy
draw
•  E&E impacts are only one element of a broader
assessment – also need include (at a minimum) social,
safety, efficiency (travel time), reliability components
Specific indicators to capture ITS E&E impacts?
Kolosz (2013)
Criteria	
   Sub-group	
   Unit	
   Description	
  
Scheme Lifecycle
Emissions	
  
Environment	
   Kg CO2 Eqv.	
   Global warming potential of road-side ITS infrastructure from
production to disposal.	
  
Road User Emissions	
   Environment	
   t CO2 Eqv.
	
  
Global warming potential of vehicles using the highway.	
  
Kg of GWP covered
by IT Certificates	
  
Environment
	
  
Kg CO2 Eqv.	
   Global warming offset due to certified green operational standards.	
  
Kg of GWP per IT
task or resource	
  
Environment	
   Kg CO2 Eqv.	
   Global warming potential at the software level. Hardware (IT
equipment) if software consumption unavailable.	
  
Energy used per Task
or Resource	
  
Energy	
   kWh	
   Electricity consumed at the software level. Hardware (IT equipment) if
software consumption unavailable.	
  
Annual DCIE/PUE of
Data Center	
  
Energy
	
  
<Range 1 –
2.5> or <%>	
  
Power Usage Effectiveness (total facility energy / IT equipment
energy) or Data Center Infrastructure Efficiency (the reverse of the
PUE equation).	
  
Roadside Energy
Consumption	
  
Energy
	
  
kWh	
   The total energy consumption of the ITS scheme situated on the
highway. 	
  
Scheme Compliance	
   Social	
   %	
   The road users adherence to the ITS enforcement messages if
applicable (speed etc). 	
  
Safety	
   Social	
   <Range 0-2>	
   Killed and Seriously Injured Ratio.	
  
Scheme Cost
	
  
Economic
	
  
£ (or currency
applicable)	
  
The capital cost of the scheme. May also include operational,
maintenance and disposal cost if available.	
  
Recommendations for IRF KPI (minimum)
KPI 1: Changes in road user emissions (t CO2 Eqv).
KPI 2: Roadside energy consumption (KWh)
(scaled by size of scheme, e.g per km for scheme
comparison)
s.m.grant-muller@its.leeds.ac.uk
References
Grant-Muller S M and Usher M (2013) ‘Intelligent Transport systems: the
propensity for environmental and economic benefits’. Technological Forecasting
and Social Change, Vol 82, pp 149–166
Newman-Askins, R., L. Ferreira, and J. Bunker, Intelligent transport systems
evaluation: From theory to practice. 2003.
Kolosz, B. W. (2013). Assessing the Sustainability Performance of Inter-Urban
Intelligent Transport. Institute for Transport Studies. Leeds, University of Leeds.
PhD: 333
Kolosz, B.W.; Grant-Muller, S.M., "Appraisal and Evaluation of Interurban ITS: A
European Survey," Intelligent Transportation Systems, IEEE Transactions on ,
vol.PP, no.99, pp.1,18 doi: 10.1109/TITS.2014.2351253
Kolosz, BW and Grant-Muller S.M (2014). "Extending Cost-Benefit Analysis for the
Assessment of Inter-urban Intelligent Transport Systems". Environmental
Impact Assessment Review. doi:10.1016/j.eiar.2014.10.006
Thank you – any Questions?

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Measuring intelligent transport policy

  • 1. Dr Susan Grant-Muller Measuring ITS Policy through KPIs Susan Grant-Muller and Ben Kolosz Dec 18th 2014 s.m.grant-muller@its.leeds.ac.uk
  • 2. ITS and sustainability KPI’s Assessing  the  Environmental    and  Energy   (E&E)  impacts  of  ITS  as  part  of  a  wider   evalua>on  framework   •  Can  ITS  generate  E&E  impacts?   •  Do  stakeholders  think  these  are  important?   •  How  can  we  capture  them?   •  Where  do  they  sit  in  a  wider  evalua>on   framework?  
  • 3. The big issue… Isn’t whether ITS has energy and carbon impacts, but the size of these and how best to capture them. For example….
  • 4. ITS  scheme   S t u d y   Context   Reported  Carbon/Energy  Impacts   Electronic  charging   UK   London   a)  2003-­‐  2006,  ↓  16%    carbon  emissions  in  central  Zone   b)  2007  western  extension  zone  ↓6.5%  by  2008   Hard  shoulder  running/variable   speed  limits     UK   M42:  ↓  4%  -­‐  10%.  Fuel  consump>on  ↓  4%.  Similar  findings   from  studies  of  VSL  on  M25   In-­‐vehicle  control  and   performance  systems     USA,.     normal   condi>ons.   ↓   5%   carbon   no   feedback/coaching,   ↓   10%  carbon  with  feedback/coaching   Eco-­‐driving     Field  trials   ↓  average  10%    carbon  emissions   In  vehicle  (overridable)  speed   control   UK   Motorway  –  average  ↓  6%  benefit  CO2   Other  road  types  –  lible  benefit  or  small  disbenefit  on  low   speed  urban  roads.  20%  difference  in  emissions  between   lowest  and  highest  emidng  drivers   Dynamic  systems    u>lising  RTTI         simulated   ↓  10%-­‐20%  carbon  emissions  and  fuel.  Real  world   experiments  -­‐  slightly  lower  findings   Eco-­‐driving   NL   ↓  0.3%-­‐0.8%  fuel  consump>on  1999-­‐2004       In  vehicle  technology/other   measures   EU       ↓  5%  -­‐  25%    carbon       Platooning  and  road-­‐trains   Lab   ↓  Up  to  20  %  fuel  consump>on  and  carbon  emissions.       Teleworking   UK   ↓  2.4  %  of  carbon  emissions  from  cars  by  2050   Personalised  travel  planning   JP   ↓ 20% carbon emissions through changes to route/
  • 5. •  Managing excess demand on parts of the system - mitigates environmental impacts of congestion •  Speed smoothing - reduces vehicle emissions by shifting demand (e.g. to off peak) through economic measures. •  Route management - supports adaptation during climate extremes   •  Enforcement systems - maintain expected environmental and other benefits from infrastructure improvements such as dedicated lanes. •  Driver behaviour - directly impacts on driver behaviour and performance of the vehicle to reduce emissions •  Trip substitution - demand reduction Drivers  on  ITS    E&E  impacts  (1):  
  • 6. Further set of impacts arise from: •  Constructing and maintaining the roadside infrastructure e.g. gantry’s, roadside kit (and decommissioning) •  Energy supply for ICT elements (VMS etc) •  Datacentre/control centre for operation and traffic management •  Enforcement equipment Drivers  on  ITS    E&E  impacts  (2)  
  • 7. Do Stakeholders believe E&E impacts matter?
  • 8. General Methodologies to capture E&E impacts •  Cost Benefit Analysis (CBA) and Cost Effectiveness Analysis (CEA) •  Multi-Criteria Analysis (MCA) •  Ecological Footprint (EF) •  Environmental Impact Assessment (EIA) and Environmental Risk Assessment (ERA) •  Standardised Environmental Management System (EMS) •  Life Cycle Assessment (LCA) and Life-cycle Cost Analysis (LCC) •  Regional/Strategic Environmental Assessment (R/SEA)
  • 9. Where do ITS E&E impacts sit in wider framework? •  Need to capture both ITS benefits and costs •  KPI should cover installing and running ITS + estimate of impacts from changes in road user behaviour and choices •  Need to consider specific indicators and measurement covering local environment, global environment and energy draw •  E&E impacts are only one element of a broader assessment – also need include (at a minimum) social, safety, efficiency (travel time), reliability components
  • 10. Specific indicators to capture ITS E&E impacts? Kolosz (2013) Criteria   Sub-group   Unit   Description   Scheme Lifecycle Emissions   Environment   Kg CO2 Eqv.   Global warming potential of road-side ITS infrastructure from production to disposal.   Road User Emissions   Environment   t CO2 Eqv.   Global warming potential of vehicles using the highway.   Kg of GWP covered by IT Certificates   Environment   Kg CO2 Eqv.   Global warming offset due to certified green operational standards.   Kg of GWP per IT task or resource   Environment   Kg CO2 Eqv.   Global warming potential at the software level. Hardware (IT equipment) if software consumption unavailable.   Energy used per Task or Resource   Energy   kWh   Electricity consumed at the software level. Hardware (IT equipment) if software consumption unavailable.   Annual DCIE/PUE of Data Center   Energy   <Range 1 – 2.5> or <%>   Power Usage Effectiveness (total facility energy / IT equipment energy) or Data Center Infrastructure Efficiency (the reverse of the PUE equation).   Roadside Energy Consumption   Energy   kWh   The total energy consumption of the ITS scheme situated on the highway.   Scheme Compliance   Social   %   The road users adherence to the ITS enforcement messages if applicable (speed etc).   Safety   Social   <Range 0-2>   Killed and Seriously Injured Ratio.   Scheme Cost   Economic   £ (or currency applicable)   The capital cost of the scheme. May also include operational, maintenance and disposal cost if available.  
  • 11. Recommendations for IRF KPI (minimum) KPI 1: Changes in road user emissions (t CO2 Eqv). KPI 2: Roadside energy consumption (KWh) (scaled by size of scheme, e.g per km for scheme comparison)
  • 12. s.m.grant-muller@its.leeds.ac.uk References Grant-Muller S M and Usher M (2013) ‘Intelligent Transport systems: the propensity for environmental and economic benefits’. Technological Forecasting and Social Change, Vol 82, pp 149–166 Newman-Askins, R., L. Ferreira, and J. Bunker, Intelligent transport systems evaluation: From theory to practice. 2003. Kolosz, B. W. (2013). Assessing the Sustainability Performance of Inter-Urban Intelligent Transport. Institute for Transport Studies. Leeds, University of Leeds. PhD: 333 Kolosz, B.W.; Grant-Muller, S.M., "Appraisal and Evaluation of Interurban ITS: A European Survey," Intelligent Transportation Systems, IEEE Transactions on , vol.PP, no.99, pp.1,18 doi: 10.1109/TITS.2014.2351253 Kolosz, BW and Grant-Muller S.M (2014). "Extending Cost-Benefit Analysis for the Assessment of Inter-urban Intelligent Transport Systems". Environmental Impact Assessment Review. doi:10.1016/j.eiar.2014.10.006 Thank you – any Questions?