Demand-responsive toll pricing
Demand-responsive toll pricing is designed to reduce congestion by dynamically charging drivers based on observed demand to use a roadway. In theory, the price all road user pay, internalizes the external costs they impose on other drivers and mitigates the adverse environmental effects the impose on society (Button and Verhoef, 1998). In practice, road pricing has proliferated under various designs and contexts, but in North America, it has only been successfully implemented on individual facilities. Internationally, area-wide strategies have gained acceptance in London and Singapore . Demand pricing is a nascent design that has been made possible through advances in technology and warranted by the rising costs of congestion. It reduces congestion by making single-occupant vehicle travel more costly, thus encouraging different transportation modes and travel during off-peak periods. Many have proposed that using toll revenues to improve highway capacity and transit service in the corridor and elsewhere will improve public opinion .
- Goal: Increase the efficiency of automobile traffic
- Goal: Increase the funds available to develop, operate and maintain automobile roads
- Goal: Decrease the rate of fluctuation in automobile transportation use between peak and off-peak periods
- Goal: Decrease average automobile transportation commute times
- Goal: Decrease the rate of environmental damage from automobiles
- Goal: Decrease the rate of automobile use
- Goal: Increase the rates of automobile transportation user comfort, convenient and satisfaction
- Goal: Increase the funds available to develop, operate and maintain urban bus service
- Goal: Increase the rates of bus transportation user comfort, convenience and satisfaction
High occupancy toll (HOT) lanes are one way facility-based demand-responsive tolling systems have been successfully implemented in the United States. Drivers of single-occupant vehicles are permitted to use HOV lanes by paying a toll that varies throughout the day as a function of the measured demand for that lane. By encouraging a more efficient use of the road, some drivers will be incented to use alternate modes of transportation, travel during off-peak hours, or use a less congested route. Revenues that are collected can be used to fund transit and highway transportation improvements in the corridor which will further improve travel times and the local political feasibility of the project.
Trade-offs of implementing this demand responsive tolling may include:
- Facility tolls (i.e. HOT lanes)that allow travel on adjacent lanes without barriers and on free alternative routes will cause traffic diversion, which may lead to increased congestion in other locations (Parry, 2000; de Palma and Lindsey, 2011)
- If toll revenues aren't fairly distributed, congestion pricing will create inequitable outcomes for travelers who can't afford tolls (King,Manville, and Shoup, 2007)
- If alternative modes' (i.e. transit) level of service aren't improved after implementing congestion pricing,travel times on those modes will become congested, reducing travel times and forcing lower-income drivers and transit riders to use a slower forms of transportation (Schaller, 2010)
- Difficulties with enforcement will require new technologies and additional costs, particularly for designs that don’t include physically separated lanes (de Palma and Lindsey, 2011; Halvorson and Buckeye, 2006)
If answered yes, the following questions indicate superior conditions under which the policy is more likely to be appropriate:
- Are congestion's impacts great enough for there to be relative gains realized through congestion pricing?
- How should congestion be measured?
- Are there underutilized HOV lanes that can be converted to HOT lanes?
- Is funding sufficient to install a new toll system or upgrade the existing system?
- What is the current level of public acceptance that could be expected before project implementation?
- Who are the political leaders who can be the project's champions to guide its implementation and improve its chances for success?
The following questions should be considered when determining how to implement this policy:
- What is the optimal price drivers should be charged to minimize congestion and maximize an efficient use of existing infrastructure?
- Should DRT congestion pricing be facility-based or area-based?
- Should DRT congestion pricing reflect other variables such as vehicle type and weight?
- How should toll lane facilities be designed (i.e.Should barriers separate tolled lanes from untolled lanes?)
- How should toll revenues be fairly redistributed to maximize political and public support for congestion pricing?
- How should toll revenues be spent by localities to improve traffic performance?
- Which technologies are the most effective for managing a demand responsive congestion pricing program?
- Has adoption of: Limited. Demand responsive tolling has grown in popularity in recent years. In the United States, the only instances where DRT has been successfully adopted are on high occupancy/toll lanes (HOT)
- For governance level(s): Local
Demand responsive tolling has had limited use domestically internationally. In practice, high occupancy/toll (HOT) lanes in the United States are the only instances in which dynamic tolling schemes have been successfully implemented.
Notable entities who have implemented this policy include:
- Advocates - Bus Transportation Assumption: If transit travel times are reduced or if toll revenues are spent on improving bus transit facilities
- Advocates - Mass Transportation Assumption: If rail travel times are reduced or if toll revenues are spent on improving rail transit facilities
- Constituent Groups - Commuters Assumption: If SOV commuters' value of time exceeds their value for money and if tolled lanes facilitate faster travel times
- Constituent Groups - Local Residents Assumption: If toll revenues are spent on local services
- Government Agencies - Economic Development Assumption: If the congestion pricing reduces the costs of congestion
- Government Agencies - Highways Assumption: If demand responsive tolling successfully reduces congestion
- Government Agencies - Transportation Assumption: If demand responsive tolling successfully reduces congestion
- Associations - Automobile Manufacturers Assumption: If a large amount of people switch to other modes or drive significantly less
- Constituent Groups - Local Businesses Assumption: If congestion pricing raises monetary freight and employee travel transportation costs
- Constituent Groups - Local Residents Assumption:: If congestion pricing raises their monetary costs of commute or the relative reductions in travel time are insignificant
- Electeds - Local Legislators Assumption: If public support for demand responsive tolling is low
- Electeds - Local Executives Assumption: If public support for demand responsive tolling is low
- Electeds - State and Provincial Legislators Assumption: If public support for demand responsive tolling is low
- Electeds - State and Provincial Executives Assumption: If public support for demand responsive tolling is low
- Buckey, K., & Munnich, L. (2004). Value Pricing Education and Outreach Model: 1-394 MnPASS Community Task Force. Transportation Research Record: Journal of the Transportation Research Board, (1864), 80-86.
- Ecola, L., Light, T., 2009. Equity and congestion pricing: A review of the Evidence. Technical Report, Rand Transportation, Space, and Technology <http:/www.rand.org/pubs/technical_reports/TR680/> (05.07.09).
- Gardner, L., Boyles, S., & Waller, S. (2011). Quantifying the benefit of responsive pricing and travel information in the stochastic congestion pricing problem. Transportation Research Part A: Policy and Practice, 45(3), 204-218. doi:doi:10.1016/j.tra.2010.12.006
- Halvorson, R., & Buckeye, K. (2006). High-Occupancy Toll Lane Innovations: I-394 MnPASS. Public Works Management & Policy, 10(3), 242-255. doi:DOI: 10.1177/1087724X06288331
- King, D., Manville, M., & Shoup, D. (2007). The political calculus of congestion pricing. Transport Policy, 14(2), 111-123. doi:doi:10.1016/j.tranpol.2006.11.002
- K., B., & E., V. (1998). Introduction. In Road Pricing, Traffic Congestion and the Environment. Cheltenham: Edward Elgar Publishing Limited.
- Palma, A., & Lindsey, R. (2011). Traffic congestion pricing methodologies and technologies. Transportation Research Part C: Emerging Technologies, 19(6), 1377-1399. doi:10.1016/j.trc.2011.02.010
- Parry, I. (2002). Comparing the efficiency of alternative policies for reducing traffic congestion. Journal of Public Economics, 85, 333-362.
- Perez, B., & Stamm, H. (2011). Evaluation and Performance Measurement of Congestion Pricing Projects. National Cooperative Highway Research Program 684. Transportation Research Board.
- Shoup, D. (2005). The high cost of free parking. Chicago: Planners Press, American Planning Association.
- Zmud, J., & Arce C (2008). Compilation of Public Opinion Data on Tolls and Road Pricing. National Cooperative Highway Research Program Synthesis 377. Transportation Research Board
- Online TDM Encyclopedia Transportation Demand management strategies created by Victoria Transportation Policy Institute
- FHWA Congestion Pricing Website - A resource provided by the Federal Highway Administration that provides links to dozens of articles, primers, and examples of the use of congestion pricing in the United States
- Virginia Department of Transportation Congestion Pricing - A resource from the Virginia Department of Transportation that provides information on congestion pricing, other states' experiences with it, and a brief a video that describes its history and its future
- Automated fare collection systems
- Demand-responsive parking pricing
- Dynamic parking pricing systems
- High occupancy vehicle lane designations
- License plate monitoring systems