EV35 — Congestion Pricing Outcomes: Evidence from Operational Schemes

Executive Summary

This evidence note synthesises quantitative outcomes from five operational congestion pricing/road user charging schemes across multiple jurisdictions. The data demonstrates that congestion pricing is a proven economic instrument capable of delivering measurable reductions in vehicle trips, generating sustained revenues for transit and sustainable mobility investment, and maintaining public acceptance over extended operating periods. These outcomes support the use of congestion pricing as a governance tool to manage emerging Autonomous Vehicle (CAM) deployment and maintain traffic efficiency in city centres.

---

1. Stockholm Congestion Tax (Sweden)

Implementation Timeline: Trial period: 3 January 2006 – 31 July 2006 Permanent scheme: 1 August 2007 – present

Traffic Reduction

Metric	Value	Notes
Initial traffic reduction	20–25%	Recorded during trial and first permanent year
Vehicle volume reduction (daily)	~20,000 vehicles	Immediate effect on first day
Long-term sustainability	Sustained / increased slightly	Effects persisted and slightly strengthened over time when controlling for external factors

Congestion & Travel Time

• Travel time and queuing reduction: 30–50% on bottleneck links
• Variability reduction: 30–50% reduction in travel time variability

Environmental Outcomes

• CO₂ emissions (Stockholm County): 2–3% reduction
• Vehicle emissions: 10–14% reduction in the Central Business District

Revenue & Acceptance

• Public acceptance trajectory: Initial trial period experienced significant opposition; public support shifted dramatically post-implementation through experience effects
• The scheme became politically viable for permanent status partly due to demonstrated benefits and improved public acceptance

Sources

• OECD: Long-Term Effects of the Swedish Congestion Charges
• ITS Deployment Evaluation: Stockholm traffic reduction
• ResearchGate: Stockholm congestion charging overview of effects
• Transport Portal: Stockholm congestion charges—5 years on

---

2. London Congestion Charge (United Kingdom)

Implementation Timeline: 17 February 2003 – present Western Extension: 19 February 2007 – 4 January 2011 (withdrawn due to stakeholder opposition)

Traffic Reduction

Metric	Value	Period	Notes
Initial traffic reduction	~20%	2003–2004	Approximately 20,000 vehicles per day
Private vehicle reduction	39%	2002–2014	Cumulative decline in private cars entering zone
Long-term (10-year) traffic reduction	10%	2003–2013	Reduction from baseline
Vehicle kilometres reduction	11%	2000–2012	London-wide impact

Congestion & Travel Time

• Travel speeds: Increased by 30% in charging zone
• Trip times: Decreased by 14%
• Traffic delays: Reduced by 25%

Modal Shift

• Bus ridership increase: 29,000 additional bus passengers during morning rush hour (first year)
• Transport mode distribution: Shift to public transit (buses), taxis, motorcycles, bicycles, and walking

Financial Outcomes

Metric	Value	Notes
Annual revenue (2017–18)	£229.8 million	4.3% of TfL’s total annual revenue
Operating costs	£57.7 million (25%)	Annual system operation expenses
Net annual income	£155.9 million	After operating costs
Cumulative gross revenue (2003–2013)	£2.6 billion	10-year total
Public transport investment (2003–2013)	£1.2 billion	From congestion charge revenue
Bus network improvement	£960 million	Subset of public transport investment

Safety Outcomes

• KSI (kill and severe injury) crashes: 14% reduction in charging zone

Sources

• ITS Deployment Evaluation: London 20% traffic reduction
• Transport for London: Impacts Monitoring Report (2nd Annual)
• TfL: 4th Annual Monitoring Report
• TfL: Congestion Charge publications and reports
• ITS Deployment Evaluation: 10-year outcomes

---

3. NYC Central Business District Tolling Program (United States)

Implementation Timeline: 5 January 2025 – present

Traffic Reduction

Metric	Value	Period	Notes
First week reduction	7.5%	Week 1 (vs. 2024 baseline)	Measured from launch
Daily vehicle entries reduction	11%	Jan–Nov 2025	Average 71,500 fewer vehicles per day
Peak reduction	Up to 475,000–560,000 vehicles/day	Operational period	vs. baseline of 583,000

Congestion & Travel Time Improvements

Route	Travel Time Improvement
Manhattan–New Jersey river crossings	30–40% faster
Crosstown (east–west)	20–30% faster
North–south avenues	Up to 20% faster
Average speed in CBD	8.2 to 9.7 mph (+15%)

Public Transit Benefits

• Lincoln Tunnel (bus trips): 17% reduction in average trip time
• Holland Tunnel (bus trips): 48% reduction in average trip time

Financial Performance

Metric	Value	Notes
2025 net revenue goal	$500 million	After expenses
2025 projected net revenue	$548.3 million	By end of year
Toll rates (current)	$9 day / $2.50 night	Starting rate
Planned toll escalation	$12 (2028), $15 (2031)	Scheduled increases

Economic Impact

• Neighborhood visits (south of 60th St): +3.4% vs. 2024
• Manhattan-wide visit growth: +1.4% vs. 2024
• Assessment: Fears of economic drain not supported by early data

Air Quality Impacts (Mixed Results)

• Positive: Statistically significant PM 2.5 decreases in Manhattan (satellite data)
• Negative externality: Substantial increases in eastern boroughs (Queens, Brooklyn) indicating traffic rerouting effects

Legal/Political Status (as of March 2026)

• Federal opposition and litigation (February 2025); program continues under legal challenge

Sources

• MTA: Central Business District Tolling Program
• RPA: Congestion Pricing research—faster all around
• NBER: Impact of NYC Congestion Pricing Program
• Congress.gov: Legal challenge documentation

---

4. Singapore Electronic Road Pricing (ERP) System

Implementation Timeline: Precursor (Area Licensing Scheme): 1975–1998 Modern ERP system: 1 September 1998 – present

Traffic Reduction

Metric	Value	Notes
First-day reduction (morning rush)	17%	Launch impact (1998)
Sustained initial reduction	10–15%	First months of ERP system
Expressway traffic reduction	15%	During ERP operational hours
Restricted Zone traffic reduction	16%	Dedicated restricted zone
Morning peak reduction	~14%	Rush hour specific

Speed Improvements

• Expressway speeds (during ERP hours): Increased from 35 to 55 kph

Environmental Outcomes

• CO₂ emissions reduction (1998–2008): 103 kilotons estimated reduction

Financial Outcomes

Metric	Value	Notes
ERP annual revenue (1999)	US$39.5 million	Lower than previous manual system (ALS/RPS combined)
Revenue vs. previous system	33% less	Trade-off: reduced revenue for improved operational efficiency

Modal Shift & Complementary Investment

• Public transit growth: Increased bus and train ridership through complementary investment in PT networks
• Active transport: Investment in bicycling and walking networks
• Overall mobility strategy: Combined pricing with transit-oriented development

Sources

• EDF: Singapore traffic factsheet
• CMAP: How Singapore improved traffic with congestion pricing
• ITF-OECD: Congestion control in Singapore
• WEF: Road pricing in Singapore

---

5. Milan Area C (Italy)

Implementation Timeline: Ecopass (pollution charge): 2 January 2008 – 31 December 2011 Area C (congestion charge): 16 January 2012 – present

Traffic Reduction

Metric	Value	Period	Notes
Within Area C (restricted zone)	30–38.45%	2012–2021	Sustained reduction over 10 years
First year reduction	34.3%	By 30 April 2012	Against 2011 baseline
6-month average (2015)	28.6% fewer cars	2015 vs. 2011 (Ecopass period)
Daily vehicle entries (2021)	81,181	2021	Down from 131,898 (2011)
Outside restricted zone	6% reduction	First 2 months	Spillover effect

Public Transport Benefits

• Bus average speed improvement: ~10% higher during morning peak (8–9 am)
• Service reliability: Reduced congestion improved operational consistency

Revenue & Allocation

Use Category	% of Net Revenue	Notes
Public transport improvement	62%	Inside and outside Area C
Sustainable mobility projects	22%	New initiatives and infrastructure
Operating costs	16%	System administration and maintenance

Environmental Outcomes

• Black carbon reduction: ~30% in the restricted zone
• General pollutants: No appreciable effect on most pollution levels (air quality improvements limited)

Sources

• C40 Cities: Milan Area C case study
• ScienceDirect: Evaluating congestion limitation policies in Milan (2025)
• HAL: Ecopass and Area C comparison
• IEEP: Social aspects of Milan low-emission zones

---

6. Gothenburg Congestion Charge (Sweden)

Implementation Timeline: Trial period: 2012–2013 Permanent operation: January 2013 – present

Traffic Reduction

Metric	Value	Notes
Average cordon traffic reduction	10–12%	Across toll cordon during charged hours
Average travel time reduction	9%	On arterial roads with congestion

Congestion & Speed

• Congestion index reduction: From 160% to 80% on congested links
• Speed improvements: Significant gains on arterial network

Traveler Adaptation

• Mode shift: Commuters shifted to public transport
• Discretionary trip changes: Reduced frequency and destination changes by discretionary travelers

Economic & Social Analysis

Metric	Value	Notes
Net annual surplus	€20 million	Annual social benefit
Investment payback period	~1.3 years	Financial recovery
Social surplus payback	<4 years	Including broader benefits

Acceptance & Attitude Change

• Initial public opposition reversed through experience effects (similar to Stockholm pattern)
• Attitudes shifted positively as citizens experienced congestion benefits

Sources

• Springer: Gothenburg congestion charges—cost–benefit analysis
• Transport Portal: Gothenburg congestion charge effects, design and politics
• ITF-OECD: Long-term effects of Swedish congestion charges
• ScienceDirect: Why experience changes attitudes to congestion pricing

---

Synthesis: Key Outcomes Across Schemes

Traffic & Congestion Reduction

Range of effectiveness: 7.5–38% traffic reduction depending on scheme design and measurement scope

Scheme	Traffic Reduction	Duration	Notes
Stockholm	20–25%	Long-term sustained	Trial + 19 years permanent
London	10–20% initially, 10% sustained (10yr)	Long-term sustained	23 years operation
NYC CBDTP	7.5–11%	Early (1 month–11 months)	Very recent launch
Singapore ERP	10–17%	Sustained (27+ years)	Longest operating scheme
Milan Area C	28–38%	Sustained 10+ years	Strong sustained impact
Gothenburg	10–12%	Sustained (13+ years)	Small city context

Revenue Generation

Schemes with strong revenue performance:

• London: £229.8 million annual (2017–18); £1.2–2.6 billion cumulative investment in public transit
• NYC CBDTP: $500–548 million net annual (2025); expected to scale with planned toll increases
• Stockholm & Gothenburg: Revenue allocated to transport investment; net economic surplus demonstrated

Key insight: Revenue generation is sufficient to fund complementary transport improvements, creating positive feedback for political sustainability.

Modal Shift & Complementary Policy

All schemes show measurable public transit ridership increases, but effect size depends on transit quality:

• London: +29,000 bus passengers AM peak (year 1)
• Singapore: Paired with PT system expansion; increased bus/train ridership
• Milan: Public transit speed improvements (10%) due to reduced congestion

Public Acceptance & Political Longevity

Paradox of reversals:

• Stockholm, Gothenburg: Initial opposition → post-implementation support (experience effect)
• London: 20+ years continuous operation despite political challenges
• NYC CBDTP: Legal/federal opposition despite strong traffic and economic outcomes

Critical factor: Transparent communication of benefits and visible improvements in traffic flow correlate with acceptance reversal.

---

Implications for CAM Governance

1. Congestion Pricing as a Demand Management Tool

The evidence demonstrates that congestion pricing is a proven, effective instrument for reducing vehicle miles traveled (VMT) and managing urban traffic. VMT reductions of 10–38% are achievable and sustained across diverse urban contexts (global cities, mid-sized cities, different regulatory environments).

2. Revenue Sustainability for Transit Investment

Revenue generation is substantial and sustained, enabling cities to fund:

• Public transit improvements (London: £960 million bus investment)
• Sustainable mobility infrastructure (cycling, walking, micromobility)
• System operations and maintenance

This creates a virtuous cycle: pricing → revenue → transit quality → higher acceptance.

3. Transferability to CAM Management

Congestion pricing frameworks can be adapted to manage autonomous vehicle deployment by:

• Differentiating tolls by vehicle type (occupied vs. empty deadheading)
• Time-of-day pricing to incentivize off-peak AVs
• Cordon-based charging to protect city centres from congestion externalities
• Revenue dedication to transit subsidies or AVs restricted to shared fleets

The Stockholm and Milan examples show that pricing schemes remain effective and publicly acceptable over 10+ year horizons, suggesting congestion pricing can be a long-term CAM governance framework.

4. Design Lessons from Operational Schemes

Design Element	Success Factor
Clear cordon boundaries	Milan, London, Stockholm all use precise geographic definition
Transparent revenue allocation	Milan’s documented allocation (62% PT, 22% sustainability, 16% ops) increases acceptance
Complementary PT investment	Singapore, London model shows pricing effectiveness tied to transit alternatives
Gradual implementation	Trial periods (Stockholm, Gothenburg) allow public adaptation and build acceptance
Regular monitoring & reporting	London’s annual reports (2003–2008) documented benefits and maintained credibility

---

Data Quality & Confidence Notes

Scheme	Data Confidence	Caveats
Stockholm	High	Long-term follow-up; peer-reviewed evaluations; 19+ year dataset
London	High	Annual monitoring reports (2003–2008); TfL data; academic evaluations
NYC CBDTP	Medium	Very recent implementation (Jan 2025); preliminary data; legal challenges ongoing
Singapore	Medium–High	Long operating history but less recent published evaluation; diverse metrics
Milan	High	Recent peer-reviewed evaluations (2024–2025); 13+ year operational dataset
Gothenburg	High	Cost–benefit analysis; attitude change research; Swedish transport authority data

Methodological Notes

• VMT/traffic reduction figures derived from cordon counts, loop detectors, or household surveys; subject to boundary definitions
• Revenue figures reported by transport authorities; subject to exchange rate variation (Stockholm, Gothenburg in SEK; Milan in EUR)
• Modal shift data varies by scheme; some derived from household travel surveys (London), others from transit authority counts
• NYC CBDTP outcomes preliminary due to January 2025 launch and ongoing political/legal contestation

---

Conclusion

Congestion pricing is an economically proven, operationally implemented governance tool across six major jurisdictions spanning North America, Europe, and Asia. The convergence of evidence on traffic reduction (7.5–38%), sustained revenue generation, and maintained public acceptance over 10–27 year periods establishes congestion pricing as viable foundation policy for CAM deployment governance.

Cities can adapt existing congestion pricing frameworks to manage autonomous vehicles through differentiated pricing, revenue dedication to shared mobility, and complementary transit investment. The experience of London, Stockholm, and Milan demonstrates that properly designed and transparently communicated pricing schemes achieve both traffic management and political sustainability objectives.

---

References & Sources

Primary Evaluation Documents

1. OECD (2018). Long-Term Effects of the Swedish Congestion Charges. https://www.oecd.org/content/dam/oecd/en/publications/reports/2018/10/long-term-effects-of-the-swedish-congestion-charges_41933a53/d944f94b-en.pdf

2. Transport for London. Central London Congestion Charging: Impacts Monitoring Reports (Annual, 2003–2008). https://tfl.gov.uk/corporate/publications-and-reports/congestion-charge

3. MTA (2025). Central Business District Tolling Program. https://www.mta.info/project/CBDTP

4. Metropolitan Transit Authority & Research Partners. Impact of New York City’s Congestion Pricing Program. NBER (2025). https://nber.org/digest/202506/impact-new-york-citys-congestion-pricing-program

5. Moulin et al. (2025). “Evaluating the effectiveness of two congestion limitation policies in Milan: Charge increase and vehicle type.” Transportation Policy, 165. https://www.sciencedirect.com/science/article/pii/S0967070X25000630

6. Transport Portal Sweden. The Gothenburg Congestion Charge: Effects, Design and Politics. https://www.transportportal.se/swopec/CTS2014-25.pdf

7. ITF-OECD (2020). Congestion Control in Singapore. https://www.itf-oecd.org/sites/default/files/docs/congestion-control-singapore.pdf

Supporting Data & Case Studies

8. C40 Cities. Milan’s Area C: Reduces Traffic Pollution and Transforms City Center. https://www.c40.org/case-studies/milan-s-area-c-reduces-traffic-pollution-and-transforms-the-city-center/

9. RPA. Congestion Pricing: Getting Around Faster All Around. https://rpa.org/news/lab/congestion-pricing-getting-around-faster-all-around

10. U.S. Department of Transportation ITS Deployment Evaluation Program. Multiple case studies (Stockholm, London, Singapore). https://www.itskrs.its.dot.gov