Road pricing is an effective economic instrument to reduce congestion, and to limit the growth in private vehicle travel demand. It has been successfully implemented in cities such as Singapore and London, resulting in substantial improvements in the urban environment and transport system. The largest barrier for ERP is public opposition by car users. However acceptance often increases after implementation. Important success factors are clear communication of the benefits to society and complementary policies regarding public transport and parking.
Road pricing is an economic instrument that
applies direct charges for the use of roads. It can serve three
purposes: 1) as a tax to manage travel demand, 2) as an incentive to
guide more efficient investment decisions, and 3) as a source of public
revenues, e.g. to finance roads and public transport (Lindsay, 2009).
Road pricing can be implemented in several ways, including (VTPI, 2010):
- Road tolls: a (usually fixed) fee paid for driving on a particular road
- Congestion pricing: a variable fee depending on the level of congestion in a certain area
- Cordon fees: a fee applied to a certain area, e.g. an urban centre
- Distance-based fees: a vehicle fee based on the number of kilometres travelled
- Electronic tolling, which bills a charges to users when passing a point on the road;
- Optical vehicle recognition, which uses an optical system to bill the user;
- GPS, which tracks the location of vehicles and bills based on the distance driven.
Feasibility of technology and operational necessities :
The largest barrier for ERP is probably political
and public acceptance, particularly before implementation (Gehlert et
al, 2008). In general vehicle users are considering themselves worse off
when charged for something previously perceived as being free of
charge. In addition, there may be a general distrust in government
agencies resulting in a fear that the instrument only serves to increase
public revenues (VPTI, 2010). In developing countries car drivers are
often a small but rich and politically influential minority, rendering
political support difficult (Mahendra, 2008). Stockholm is the only city
where road pricing was decided after a referendum, and after a trial
period Stockholm’s citizens voted for its permanent adoption (Harsman
and Quigly, 2010). However in cities where initial public acceptance was
low, acceptance has been found to increase after its implementation
(Gehlert et al., 2008; Mahendra, 2008).
To secure public support and successful implementation of road pricing or congestions the following issues need to be taken into account (Mahendra, 2008; VTIP, 2010; Pike, 2010):
In some cities the implementation of ERP on certain roads simply shifted traffic to non-priced roads, thereby hardly affecting overall congestion.
Singapore is the first city in the world implementing ERP in 1998, after using a paper system for over a decade. In-vehicle “charge units” communicate with overhead gantries at all charging points and the appropriate amount is deducted from a smart card. The charge is dependent on the level congestion, and is reduced when traffic speeds increase (Pike, 2010). The policy measure and electronic technology has successfully reduced congestion both in the passenger and freight transport sector (Hin and Subramanian, 2006). It has been successful mainly due to Singapore’s widely accessible public transport system, which is both road and rail-based, supporting a modal shift away from private vehicles. Singapore is considered to be a potential example for other Asian cities, where rapidly growing traffic volumes pose an acute problem.
To secure public support and successful implementation of road pricing or congestions the following issues need to be taken into account (Mahendra, 2008; VTIP, 2010; Pike, 2010):
- Clear communication about reasons behind the policy and the benefits to society, including congestion reduction and public health benefits;
- Implementation of complementary policies such as public and non-motorised transport, flextime, ride sharing and parking fees;
- Transparent decision about road pricing, and based on public trust;
- Variable but predictable fees based on the level of congestion;
- Convenient system, which is easy to understand for the user;
- Protection of privacy of the user;
- Development of a ‘knowledge culture’ among politicians and experts on alternative pricing mechanisms, based on systematic transport policy analysis;
- Use of public ERP revenues for public and non-motorised transport.
Status of the technology and its future market potential :
Electronic road pricing, that uses electronic or
optical tolling, is a mature technology. It has been successfully
implemented in cities such as Singapore, London and Stockholm, and for
highways, e.g. in Canada and the US (VPTI, 2010). Several countries in
the developed and developing world, including Indonesia and the
Netherlands, are considering ERP.In some cities the implementation of ERP on certain roads simply shifted traffic to non-priced roads, thereby hardly affecting overall congestion.
Singapore is the first city in the world implementing ERP in 1998, after using a paper system for over a decade. In-vehicle “charge units” communicate with overhead gantries at all charging points and the appropriate amount is deducted from a smart card. The charge is dependent on the level congestion, and is reduced when traffic speeds increase (Pike, 2010). The policy measure and electronic technology has successfully reduced congestion both in the passenger and freight transport sector (Hin and Subramanian, 2006). It has been successful mainly due to Singapore’s widely accessible public transport system, which is both road and rail-based, supporting a modal shift away from private vehicles. Singapore is considered to be a potential example for other Asian cities, where rapidly growing traffic volumes pose an acute problem.
Figure 1: Traffic jam in Jakarta
How the technology could contribute to socio-economic development and environmental protection :
In order to move to a more sustainable transport
system, a combination of strategies is required, also called the
Avoid-Shift-Improve approach, which 1) avoids or reduces the need for
unnecessary travel (Transport Demand Management), 2) shifts private
vehicle use to more sustainable modes, and 3) improves the environmental
performance of modes. ERP is considered an important and effective
instrument in the ‘Avoid’ strategy, i.e. limiting the growth in travel
demand, while also contributing to a modal shift.
Vehicle use has been shown to be rather sensitive to tolls, with price elasticity from -0.1 to -0.4 for urban highways, i.e. a price increase of 10% results in a 1-4% automobile use reduction. The impact is however highly case specific, and may depend on many factors such as the type of toll, the availability of alternatives and on consumer preferences. Estimates for impacts of road pricing on vehicle trips vary widely, from 3% to 15% (VPTI, 2010; Dalkmann, 1010). However even if total travel demand was affected only to a limited extent, road pricing could significantly reduce congestion if only a small share of total traffic shifted from peak to off-peak hours with estimates for several cities in the range of 10% to more than 30% (VPTI, 2010; Pike, 2010). In Singapore, the ERP has decreased road traffic by 25,000 vehicles in peak hours, and increased average road speeds by 20%. Bus travel and car-pooling also increased.
By reducing and spreading travel demand, the benefits of ERP include (see e.g. Pike, 2010; VTPI, 2010):
Vehicle use has been shown to be rather sensitive to tolls, with price elasticity from -0.1 to -0.4 for urban highways, i.e. a price increase of 10% results in a 1-4% automobile use reduction. The impact is however highly case specific, and may depend on many factors such as the type of toll, the availability of alternatives and on consumer preferences. Estimates for impacts of road pricing on vehicle trips vary widely, from 3% to 15% (VPTI, 2010; Dalkmann, 1010). However even if total travel demand was affected only to a limited extent, road pricing could significantly reduce congestion if only a small share of total traffic shifted from peak to off-peak hours with estimates for several cities in the range of 10% to more than 30% (VPTI, 2010; Pike, 2010). In Singapore, the ERP has decreased road traffic by 25,000 vehicles in peak hours, and increased average road speeds by 20%. Bus travel and car-pooling also increased.
By reducing and spreading travel demand, the benefits of ERP include (see e.g. Pike, 2010; VTPI, 2010):
- Congestion reduction, i.e. travel time savings
- Reduction of greenhouse gas emissions
- Air quality improvement
- Increased road safety
The costs and benefits of ERP can be looked at from different perspectives, as shown in Table 1.
Table 1: Costs and benefits of ERP to governments and users or society
Although the investment costs of ERP equipment are high, the cost-benefit ratio to the government is often positive – obviously depending on the level of user fees (Pike, 2010). A study for the ERP considered by the Jakarta government indicates a 4 years payback time (Dalkmann, 2010).
In Stockholm and Santa Clara County in California the benefits in terms of time savings were shown to substantially exceed the operating costs. In London and Stockholm no difference was found in economic growth and retail sales inside and outside the ERP perimeter (Pike, 2010).
Table 1: Costs and benefits of ERP to governments and users or society
| Benefits | Costs | |
| Government | Increased revenues | Investment and system operation |
| Users / society | Reduced travel time Better air quality Increased road safety | Increased vehicle travel costs |
Although the investment costs of ERP equipment are high, the cost-benefit ratio to the government is often positive – obviously depending on the level of user fees (Pike, 2010). A study for the ERP considered by the Jakarta government indicates a 4 years payback time (Dalkmann, 2010).
In Stockholm and Santa Clara County in California the benefits in terms of time savings were shown to substantially exceed the operating costs. In London and Stockholm no difference was found in economic growth and retail sales inside and outside the ERP perimeter (Pike, 2010).
References :
Gehlert, T., O. Nielsen, J. Rich, B. Schlag
(2008) Public acceptability change of urban road pricing schemes.
Proceeding of the institution of civil engineers – transport 161 (3)
111-121.
Hin, L., R. Subramaniam (2006) Congestion control of heavy vehicles using electronic road pricing: the Singapore experience. International Journal of Heavy Vehicle Systems 13 (1-2) 37-55.
Lindsay, R. (2009) Introduction to the Special Issue on Road Pricing and Infrastructure Financing. International Journal of Sustainable Transportation 3 (5-6), 285-292.
Mahendra, A. (2008) Vehicle restrictions in four Latin American cities: Is congestion pricing possible? Transport Reviews 28 (1), 105-133
Menon, G., S. Guttikunda (2010) Electronic Road Pricing: Experience & Lessons from Singapore. SIM-air Working Paper Series: 33-2010. Available at http://www.indiaenvironmentportal.org.in/files/ERP-Singapore-Lessons.pdf
Olszewski, P, L. Xie (2005) Modelling the effects of road pricing on traffic in Singapore. Transportation Research Part A 39 (7-9) 755-772.
Pike, E. (2010) Congestion pricing. Challenges and opportunities. International Council for Clean Transportation. Available at http://www.theicct.org/pubs/congestion_apr10.pdf
VPTI (2010) Road pricing. Online TDM encyclopedia. Available at http://www.vtpi.org/tdm/tdm35.htm
Harsman. B., J. Quigley (2010) Political and Public Acceptability of Congestion Pricing: Ideology and Self-Interest. Journal of policy analysis and management 29 (4) 854 – 871.
Dalkmann, H. (2010) Case study of a transport MRV NAMA: TDM Measures in Jakarta, Indonesia. Applicability of Post 2012 Climate Instruments to the Transport Sector (CITS) Project. Available at http://www.slocat.net/wp-content/uploads/2009/11/TRL-Jakarta-final-report.pdf
Author affiliation:
Energy research Centre of the Netherlands (ECN), Policy Studies
origin : http://climatetechwiki.org/technology/erp
Hin, L., R. Subramaniam (2006) Congestion control of heavy vehicles using electronic road pricing: the Singapore experience. International Journal of Heavy Vehicle Systems 13 (1-2) 37-55.
Lindsay, R. (2009) Introduction to the Special Issue on Road Pricing and Infrastructure Financing. International Journal of Sustainable Transportation 3 (5-6), 285-292.
Mahendra, A. (2008) Vehicle restrictions in four Latin American cities: Is congestion pricing possible? Transport Reviews 28 (1), 105-133
Menon, G., S. Guttikunda (2010) Electronic Road Pricing: Experience & Lessons from Singapore. SIM-air Working Paper Series: 33-2010. Available at http://www.indiaenvironmentportal.org.in/files/ERP-Singapore-Lessons.pdf
Olszewski, P, L. Xie (2005) Modelling the effects of road pricing on traffic in Singapore. Transportation Research Part A 39 (7-9) 755-772.
Pike, E. (2010) Congestion pricing. Challenges and opportunities. International Council for Clean Transportation. Available at http://www.theicct.org/pubs/congestion_apr10.pdf
VPTI (2010) Road pricing. Online TDM encyclopedia. Available at http://www.vtpi.org/tdm/tdm35.htm
Harsman. B., J. Quigley (2010) Political and Public Acceptability of Congestion Pricing: Ideology and Self-Interest. Journal of policy analysis and management 29 (4) 854 – 871.
Dalkmann, H. (2010) Case study of a transport MRV NAMA: TDM Measures in Jakarta, Indonesia. Applicability of Post 2012 Climate Instruments to the Transport Sector (CITS) Project. Available at http://www.slocat.net/wp-content/uploads/2009/11/TRL-Jakarta-final-report.pdf
Author affiliation:
Energy research Centre of the Netherlands (ECN), Policy Studies
origin : http://climatetechwiki.org/technology/erp
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