Road pricing reform – a getting started idea

03 Oct 2017

David Hensher and Michiel Bliemer

While it is recognised through numerous inquiries and research related activities that road pricing reform is necessary if we are ever to tame traffic congestion to ‘acceptable’ levels, and the theory is well established on how to price travel under congested conditions, the challenge has always been on how to get started in a way that can demonstrate the merits of a reform scheme without having to have a total system implementation. We have seen congestion charging at a cordon level (e.g., City of London, Stockholm CBD and Milan), and area wide pricing in Singapore, but we have struggled to find a way of introducing a scheme for an entire metropolitan area where much of the congestion is spread around.

The challenge has always been on how to get started. In simple terms, we need to secure buy in from the population at large and especially car and truck users. This means a reform plan that can offer financial benefits as well as travel time savings. Typically it is assumed that gaining travel time savings means paying more but is this always the case?

With digital technology now widely available (via smart phones) to disrupt the way we deliver improved transport infrastructure and services, we have a real opportunity to offer a trial that is essentially an opt in (or opt out) pilot that offers attractive incentives to car (and truck) users to move some amount of travel out of the more severely congested times of the day (including switch some travel to public transport or switching destinations to have shorter and/or less congested trips) so as to relieve the system of congestion, especially severe congestion. We are able to do this without implementing it over the entire travelling population, but to give individuals travellers a choice such that they can see a benefit to themselves while contributing to improving the performance of the network as a whole. Over time we might expect more travellers to take advantage of the scheme and opt in. What do we have in mind?

We start with a smartphone App that can be used to establish, for each person, the typical travel times associated with trips between specific origins and destinations (an OD pair) for each time of day. Users can refine starting times to suit their ability to be time-flexible. This will show where travel time gains, in real time, are on offer by specific times of day. This may involve small adjustments in trip commencement times (e.g., 10 mins) or larger adjustments, depending on the specific OD pair. Importantly, travel times are not only based on historical travel times but also on real time information and is applicable to each specific traveller, so it is personalised and relevant information. Clearly this App must be fully functional before we can proceed to the next steps.

  1. The reform proposal involves reducing registration charges according to time of day (moving out of peak and even shoulders or some finer granularity of time periods). One must do this for at least three months of a year’s travel to be eligible for a discount on registration fees.
  2. We can tailor the registration fee reduction to establish enough incentive to trade a lower registration fee with moving to less congested times of day which deliver improved travel times. What we have here is a combined benefit of a reduced registration fee and travel time savings. We understand that not everyone will opt in for many reasons (including they must travel at a particular time of day); although we know from studies we have undertaken previously that there are sufficient travellers who can switch time of day if the incentives are enough to merit it.
  3. To compensate for the loss of registration revenue, the fee will increase if someone stays in the ‘peak’ period or other periods deemed to be the ones to encourage some switching out of. The adjustment in the registration fee would be on some sliding scale to recognise levels of traffic congestion.

Importantly, the loss of registration revenue can be recouped by a higher charge for those who continue to travel in the peaks. Such evidence will require controls through GPS or other similar data capture technology.

We suggest a trial in a major city such as Sydney. While we admit that if there are only a small number of participants opting in, for example 1,000 participants from all over the city and not concentrated around a certain area, there may not be much of a difference on the roads at a particular time of day, but that is not the point – a specific participating individual who switches to another time of day will observe a noticeable personal time savings (even if many others switch to that same time of day, but over other parts of the road network) as per advice from the real time information provided on the smartphone App. An alternative way of proceeding is to concentrate on specific bottleneck roads (typically bridges or tunnels) with thousands of participants in order to measure a difference in travel times. Maybe the trial should target harbour bridge/tunnel crossing traffic or users or similarly congested roads? But this is not necessary to show a time benefit to a participant which can be the basis of promoting the scheme to specific contexts where time savings will be noticeable, and hence overall levels of traffic congestion are reduced.

We do, however, recognise that such a peak (or high congested time) avoidance scheme (which has been trialled in the Netherlands, but involving giving money directly to travel outside the peak, and not adjusting the registration charge) has to be made fraud proof. Travellers must turn on their GPS on their phone while they are travelling in order to see when they are driving? If they turn their phone off then the data will show up as questionable, such that the person becomes ineligible.

The scheme we are proposing, however, would need to know the OD pairs with departure time, travel times and mode (for individuals). Speed data1 is desirable in order to build the App and determine realistic travel times for different departure times. This can be extracted from mobile data that does not require the GPS to be turned on (at least not in urban and suburban areas where mobile coverage is good) provided the mobile operators are willing to provide the data and have the capability of processing the data into trips with mode detection. However, this does not prevent people leaving their smart phones at home (or getting a second mobile), but since that would require changing their telephone number and operator, we doubt that too many people would do that.

In time, with buy in we can start looking towards a distance-based charging scheme (by time of day) with discounted registration fees. This is an ongoing approach we are working on, as are other researchers proposing a distance based system (that is not differentiated by time of day initially) using odometer readings to track registration reduction entitlements.




  1. Michiel Bliemer and Mark Raadsen of ITLS have built such an App in the Netherlands together with a company that makes travel time predictions on road networks using loop detectors. This is not easy to do in Australia since there are much fewer loop detectors available here. TomTom and others have speed data available that they use for their own navigation devices. These so-called ‘speed profiles’ can be bought. Such data is needed in order to build the App. Alternatively, one could use speed data from a model, but that is likely not accurate enough.