Thanks for your comment Kelly. The point I was trying to make was that for a scheme to be effective, revenue should not be the driver. I think it would be fair to say that the scheme in Singapore is not revenue driven, and it is the most successful one. Nor is the Emissions Trading Scheme. But since revenue is a side effect, cynics can always say that revenue is the real motivation.
But I like the idea of a congestion dividend paid out of congestion charges.
Take all the money raised by the charge.
Split it out amongst the accounts where a plate was seen by a charge gantry (if they run it that way) regardless of time of use.
Some accounts wind up with a positive balance that can be withdrawn or used against RUC/licence renewal. Those that travel at peak times don't.
The payments would be lump sum with respect to time of travel so shouldn't affect those choices. And you could put a proportionately higher congestion dividend for charge accounts linked to a community services card (with lower dividends for others) in answer to perceived equity issues.
Nice piece! As you note though, the practical setting is likely somewhat different to the nice theoretical one models are based on. The reality is the objective is centred around revenue raising and demand mitigation at peak periods (to reduce pressures for future investment by roading authorities). Hence it’s not about reducing queuing times even if that might be a side effect of what’s proposed. I think your key paragraph is
“Moreover, decision-makers find it difficult not to load a scheme with multiple, potentially conflicting objectives, in particular revenue raising and allowing exemptions for certain interest groups.”
This is totally relevant and will be critical to the feasibility of any scheme. If it’s about revenue raising then it will be important to be upfront about it and design the scheme accordingly so it’s seen as fair. And let’s be honest - the driver is the need for revenue to finance roading and public transport initiatives.
Optimal scheme design seems very difficult to achieve in practice. You touched on some of the perception problems, but I think there are a few other real world divergences from the theoretical models. Effectively roading is a constrain based system (finite roading network, elastic car demand), with the added problem of non-linear chaotic traffic flow collapse (e.g. a slowdown at one point ripples across the system even when the total system isn't experiencing congestion bottlenecks). The scheduling cost of the system is also driven by constraints and may not be completely elastic hence amenable to price signals. For some actors in the system the scheduling costs may be unavoidable due to different constraints e.g. critical face to face meeting, doctor's appointment etc. This all suggests finding an ideal pricing model will be very challenging.
The extent to which users can effectively respond to prices signals is, in our view, critical to the success of a Time of Day Pricing scheme that seeks to control congestion. In the case of RAMP prices (i.e. prices that change say every 30mins over the peak period as in Singapore) the users need to keep to their 'slots' sufficiently reliably for the pricing scheme to achieve an efficient outcome. As you note, if user departure routines are disturbed sufficiently often, then it will be difficult to establish a stable pricing regime that encourages an efficient outcome. Such a system works in Singapore, but it is unclear whether it would work under local conditions, where our lives are arguably; 'less disciplined'. That issue among others is likely to be the subject of further work.
PS: we hope to issue a post shortly looking at implementational issues, although it will be at a high level.
And I think one reason it works well in Singapore is the set of roading network constraints is quite small due to the geography of Singapore. It turns that side of the problem much more into a forced-choice problem, reducing the total set of combinations that users can select from.
Thanks for your comment Kelly. The point I was trying to make was that for a scheme to be effective, revenue should not be the driver. I think it would be fair to say that the scheme in Singapore is not revenue driven, and it is the most successful one. Nor is the Emissions Trading Scheme. But since revenue is a side effect, cynics can always say that revenue is the real motivation.
I don't think anyone has ever done it.
But I like the idea of a congestion dividend paid out of congestion charges.
Take all the money raised by the charge.
Split it out amongst the accounts where a plate was seen by a charge gantry (if they run it that way) regardless of time of use.
Some accounts wind up with a positive balance that can be withdrawn or used against RUC/licence renewal. Those that travel at peak times don't.
The payments would be lump sum with respect to time of travel so shouldn't affect those choices. And you could put a proportionately higher congestion dividend for charge accounts linked to a community services card (with lower dividends for others) in answer to perceived equity issues.
Nice piece! As you note though, the practical setting is likely somewhat different to the nice theoretical one models are based on. The reality is the objective is centred around revenue raising and demand mitigation at peak periods (to reduce pressures for future investment by roading authorities). Hence it’s not about reducing queuing times even if that might be a side effect of what’s proposed. I think your key paragraph is
“Moreover, decision-makers find it difficult not to load a scheme with multiple, potentially conflicting objectives, in particular revenue raising and allowing exemptions for certain interest groups.”
This is totally relevant and will be critical to the feasibility of any scheme. If it’s about revenue raising then it will be important to be upfront about it and design the scheme accordingly so it’s seen as fair. And let’s be honest - the driver is the need for revenue to finance roading and public transport initiatives.
Very interesting
Interesting summary, thanks.
Optimal scheme design seems very difficult to achieve in practice. You touched on some of the perception problems, but I think there are a few other real world divergences from the theoretical models. Effectively roading is a constrain based system (finite roading network, elastic car demand), with the added problem of non-linear chaotic traffic flow collapse (e.g. a slowdown at one point ripples across the system even when the total system isn't experiencing congestion bottlenecks). The scheduling cost of the system is also driven by constraints and may not be completely elastic hence amenable to price signals. For some actors in the system the scheduling costs may be unavoidable due to different constraints e.g. critical face to face meeting, doctor's appointment etc. This all suggests finding an ideal pricing model will be very challenging.
Useful comment.
The extent to which users can effectively respond to prices signals is, in our view, critical to the success of a Time of Day Pricing scheme that seeks to control congestion. In the case of RAMP prices (i.e. prices that change say every 30mins over the peak period as in Singapore) the users need to keep to their 'slots' sufficiently reliably for the pricing scheme to achieve an efficient outcome. As you note, if user departure routines are disturbed sufficiently often, then it will be difficult to establish a stable pricing regime that encourages an efficient outcome. Such a system works in Singapore, but it is unclear whether it would work under local conditions, where our lives are arguably; 'less disciplined'. That issue among others is likely to be the subject of further work.
PS: we hope to issue a post shortly looking at implementational issues, although it will be at a high level.
And I think one reason it works well in Singapore is the set of roading network constraints is quite small due to the geography of Singapore. It turns that side of the problem much more into a forced-choice problem, reducing the total set of combinations that users can select from.
It would probably be even more a forced-choice problem in Wellington, though less so in Auckland. But not sure why that makes a difference…
Because it removes choices that may force changes in the scheduling side.