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BITRE | Working paper 74

It is important to understand the prevailing pattern of congestion. The same total

congestion cost can disguise considerably different congestion costs per kilometre.

For instance, Melbourne is characterised by a high but concentrated level of

congestion around a relatively small central area near the CBD. Here, the external cost

of congestion (and the efficient charge) was estimated to be around $1.26 per vehicle

kilometre travelled (BTCE 1996a, p. 74). In contrast, the congestion in Sydney is more

evenly spread from the CBD to the Parramatta area. The external cost of congestion

per kilometre is lower than that of Melbourne, but prevails over a greater area.

Congestion in central London is six times that of a typical UK city (TfL undated). Of the 22

French-European administrative regions,

60 per cent of congestion occurs in the

The variation in congestion across a Ile-de-France region, corresponding

city has implications for the levying of roughly to the metropolitan area of

charges.

Paris. 80 In Australia, the three eastern

seaboard cities—Sydney, Melbourne

and Brisbane—account for over 80 per

cent of the estimated $9.4 billion annual cost of traffic congestion (BTRE 2007, p. xv).

Between cities the shape and dispersion of congestion varies, with implications

for estimating the cost of congestion and the structure of the charges necessary

to internalise that cost. Thus, caution is required when defining the congestion

‘problem’ in terms of a single monetary value. While it is important to understand the

burden imposed by congestion, it is also essential to understand the pattern of that

congestion. A concentrated pattern has a strong bearing on the feasibility of applying

congestion charges—particularly, area-based congestion charges.

5.4 Charge-setting options

Time costs are the major component of congestion costs and hence the optimal

congestion charge will be determined, in part, by the value ascribed to time. However,

there is no fixed value of time—it will vary between road users and, for each user, by

time of day and function of the trip. Factors external to the road user, such as traffic

conditions, which can vary between segments of the network and times of day/week/

year, also impact on the optimal congestion charge.

Hence, it is challenging to set charges to optimise capacity. Anderson and Mohring

observed that we lack the information that is essential for planning ‘optimal road

networks and prices for their use’:

We really know very little about what travellers are willing to pay to save travel time.

The little we do know derives almost entirely from the choices wage earners make

between auto and mass transit for commuting journeys. We know next to nothing

about what wage earners are willing to pay to save time on non-work trips. We also

know next to nothing about the relationship between the incomes of wage-earning

members of a household and the amounts that its non-wage earning members are

willing to pay to save travel time (Anderson and Mohring 1997, p. 9).

80. The region is relatively densely populated, having around 11 million, or 17 per cent of the population of ‘metropolitan’

(European) France and just over 2 per cent of the land space.

108

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