The effects of road pricing - Feweb - Vrije Universiteit Amsterdam

3.3.5 Vehicle occupancy
Whereas congestion pricing and the derivation of optimal tolls have received ample attention,
the issue of carpooling has largely been neglected in the literature. For instance, Daganzo
(1982) made a first attempt to incorporate carpooling in equilibrium traffic assignment in
general networks, but the demand for carpools is assumed to be fixed. This means that the
model fails to include the mode choice behaviour of commuters. Yang and Huang (1999),
however, use a deterministic equilibrium mode choice model with overall elastic demand.
Their analysis concerns the carpooling and congestion pricing problem in a multi-lane
highway with HOV (high-occupancy vehicle) lanes. Numerical examples show the efficiency
of HOV lanes, first- and second-best pricing and their combinations. Despite the fact that the
model is highly simplified, the findings may be relevant for the design and operations of
combined congestion pricing and HOV lanes in practice, such as in California. They found
that marginal cost pricing provides the most efficient policy option under either elastic or
inelastic demand. Reserving one or more entire lanes for carpooling vehicles rarely reduces
total costs and nor does it improve social welfare, given marginal cost prices. Nevertheless,
conventional carpool lanes alone can be justified at reasonably high congestion levels.
Differentiation of tolls across commuting modes should be cautiously implemented. The
optimal uniform second-best toll is a weighted sum of the marginal external congestion costs
between non-carpooling and carpooling commuters.
3.3.6 Location choices
The effects of road pricing on transport and location patterns have been much discussed.
Simulation models for a typical city can be used to examine the impacts of road pricing on
transport and location patterns. The model city should then be calibrated to replicate typical
observed location and travel patterns. Model parameters, elasticities, functional forms, and so
on can be taken from land use and transport models estimated on observed data. This should
ensure that the conclusions are also applicable in reality. The first studies on this issue date
back to the 1970s when Solow and Vickrey (1971) look at traffic patterns, congestion costs,
and land use. They show that, without congestion tolls, the market value of land may be a
poor guide to land-use decisions, and lead to an overallocation of land to transportation.
Solow (1973) confirms this result by using a simulation model of urban activity including the
congestion costs of transportation. He shows that rents nearer the city are too low to properly
reflect the social worth of transportation costs in the absence of congestion tolls. This will
result in more land to be taken for use as roads than is socially desirable. It remains unknown
what the consequences are for location patterns. Another topical contribution from this period
compares a model of equilibrium land use patterns in the residential ring of an urban area with
an optimal one (Oron et al., 1973). They show that scarce resources can be saved by
households moving from the periphery to more central locations in a distorted situation with
suboptimal congestion tolls. Proper pricing of transportation will most probably lead to less
suburbanisation.
More recently, Eliasson and Mattsson (2001) have developed a simulation model of a generic
city to study the effects of general congestion pricing and more specific toll ring pricing. The
city, consisting of homogenous zones, contains four types of actors: households, employers,
shops, and service establishments. The location of households is determined by their value of
plot size and accessibility to workplace, shops and service establishments. Firms locate only
according to accessibility to households. Shops and service establishments locate according to
the accessibility to households with this difference – that they evaluate the expected number
of customers in each zone. They also take into account the proximity to working places and
the size of the plot. It would go too far to discuss all other assumptions of the model at this
point; rather we focus on the outcomes. It appears that the location effects of congestion
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