No abstract

No abstract

Cost-Benefit analysis (CBA) is sometimes criticized for not taking account of induced demand due to planning policy or relocalization triggered by large infrastructure investments. There is also a notion among planers and decision makers that accounting for these effects can underestimate the relative merits of rail investments. In this paper we explore if induced demand from relocalization triggered by an infrastructure investment have any significant impact on the CBA outcome. A second aim is to investigate the robustness of the relative CBA ranking of rail and road investments with respect to the general planning policy in the region 25 years ahead. We use a large-scale integrated land-use and traffic model calibrated for the Stockholm region. We find that the induced demand from relocalization triggered by infrastructure investments has a very limited impact on the CBA outcome. This result is largely due to the fact that the population that relocates over 20-30 years is limited in comparison to the total population. Moreover, the uncertainty in the CBA outcome, and in particular the relative ranking of rail and road investments, caused by uncertainties in future land-use policies is limited. As expected, however, the CBA outcome of rail investments is to a larger extent dependent on stronger planning policy than road investments. The results underscores that the planning policy in the region have a considerably stronger impact on accessibility and total car use than individual road or rail investments. Only the largest road investment, a second bypass in the region, induces car use of the same magnitude as the impact of the planning policy in the region.

Tour generation is conventionally modelled separately according to tour purpose. Tours with different purposes are, however, in reality not generated independently of each other. For example, few travellers conduct more than three tours per day. In this paper, the conventional tour generation model is extended into estimation of a model that takes travellers' daily tour patterns into account. Results show that access to a car and a drivers' licence, having a job and presence of children in the household increase the probability of making many tours in one day. Furthermore, results show that accessibility is an important factor for the generation of non-mandatory tours, that weekends and holiday seasons are important determinants of when tour purposes are generated, that high income increases the probability of conducting business tours as well as tour patterns that include expensive activities, and that high income reduces the probability of conducting inexpensive activities such as visiting friends and family.

Connection trips is often an important part of long-distance travel, especially for air travel. Models of long-distance travel would therefore benefit from a more detailed representation of the connection part. In this paper it is however shown that most models of connection trips are stand-alone models not integrated with the model for main mode. Only a handful models that integrate connection trip modelling into a large-scale transport model for long-distance travel are found. The connection trip models are classified into different types using a typology developed within the paper. The typology identifies nine model types that differ in how access/egress mode choice and terminal choice are handled. The scarce literature on connection trip modelling within large-scale transport modelling systems call for more research regarding detailed representation of access/egress mode choice and terminal choice, especially regarding the trade-off between model complexity and detailed representation, as well as whether the detailed representation of connection trips should primarily be conducted within the public transport network assignment or on the demand modelling side.