Dynamic choice of geographical area. : Method developed to select an analysis area from a bigger transport model.

Extensive transport models give lengthy calculation times. In order to reduce calculation times, a tool to cut out the influence area from a complete strategic transport model is developed. A Part Area Model (PAM) has new geographical definitions compared to the original transport model, but should give the exact same results. The scope of this paper introduces a new method to deal with superfluously long calculation times in transport models. Most of the more fundamental transport infrastructure decisions are supported by transport model analysis. Regional transport models have been established for five regional areas in Norway. A joint demand model is estimated for the country, but during the calibration work minor regional adjustments were made to the parameters. Even if there were defined regional areas for the transport models to limit the calculation time, the most extensive model still holds about 6000 zones. This gives unsuitably long calculation times. Efforts have also been made to make the most of the dual-core technology, but the calculation times still need to be reduced further. PAMs calculate the transport demand for fewer zones, the trip destinations and modal split for fewer origin-destination pairs, and contains a smaller transport network. This gives shorter calculation times, both in the network analysis phase and for each of the matrix calculations and adaptation

Before and after analysis of the bridge to Askøy

Askøy is an island near the city centre of Bergen, consisting of about 20 000 residents. Bergen is the second largest city of Norway consisting of about 250 000 inhabitants including the commuting area. Until the bridge “Askøybroen” was opened in December 1992, the only transport option between Askøy and Bergen was a ferry.Three travel surveys are used in this study, the first was carried out just before and the second just after the opening of the bridge. The third was carried out a few years later, giving the travel habits time to settle. The three travel surveys give us a rare opportunity to check out how the bridge influenced the travel patterns in real life, compared to how the changes were calculated in a typical four-step transport model.This paper describes problems in the transport model regarding several issues, among them how ferries are described and the relation between car-availability and car-density used in the model

Cycle traffic in the regional transport model of Norway

The regional transport model developed in Norway over the last 12 years will from now on be used also for urban transport. Can the transport model also be used to model changes in the demand for cycling in its current form? Is it enough to detail the coding of the transport network in more detail, or is it necessary to include bike‐specific variables in the demand model to achieve this? These two issues are addressed in this paper by going in depth in the modeled and actual travel patterns in an area south of Trondheim, where an infrastructure measure for cyclists is scheduled in 2014. The cycle measure is a bridge for pedestrians and cyclists, which will reduce the travel distance, and hilliness on the route between two districts. Data sources for the actual travel patterns is the national travel survey conducted in 2009 and 2010, with an enhanced range of Trondheim. This is compared with model calculations at a paramount level, within areas of mode choice, trip length distribution for the various modes of transport, within the private travel purposes represented in the travel survey. Moreover, a short time registration of cycle traffic is carried out on roads in the near‐by area of the scheduled bridge. In addition, two small surveys are conducted in the same period aimed at households and workers. Interviewees are asked to give information about their travel patterns over the two previous days. Trips that could potentially to use the new bridge are labeled specifically. In addition, they were asked about how the bridge could affect their travel patterns. The results suggest that the transport net must be coded in more detail than we have done up until now. Both experience reported in the literature and results from this study, indicates that hilliness should be included in the net coding and skimming of level of service data, both because it is an important explanation factor to the demand for cycle traffic, but also to improve the net assignment

Before and after analysis of the bridge to Askøy

Askøy is an island near the city centre of Bergen, consisting of about 20 000 residents. Bergen is the second largest city of Norway consisting of about 250 000 inhabitants including the commuting area. Until the bridge “Askøybroen” was opened in December 1992, the only transport option between Askøy and Bergen was a ferry. Three travel surveys are used in this study, the first was carried out just before and the second just after the opening of the bridge. The third was carried out a few years later, giving the travel habits time to settle. The three travel surveys give us a rare opportunity to check out how the bridge influenced the travel patterns in real life, compared to how the changes were calculated in a typical four-step transport model. This paper describes problems in the transport model regarding several issues, among them how ferries are described and the relation between car-availability and car-density used in the model

Evaluating the STRATMOD transport model: Case Trondheim

The purpose of this paper is to discuss the usefulness of the transport model ’STRATMOD’, a simplified transport model. Transport models are often complex and have long run-times which STRATMOD improves by aggregating travel matrices from a baseline strategic transport model, and using elasticities to calculate the effects of measures. The model is tested with a sensitivity analysis on input- elasticities, and by analysing the metro-bus project in Trondheim. The model is useful, especially when analysing public transport measures with improvements in quality factors. It is however a bit inaccurate in practical use, because of insecurities with input- elasticities, and difficulties in deciding what effect the planned measures will have for the quality factors of the public transport system as a whole

Cost Benefit Analysis for safety projects at sea – Does the method give the entire picture? Experience from analysis of the Stad sea tunnel

The method used for CBA of safety projects at sea should be altered to include direct and indirect costs related to precautions taken to avoid risk. This is one of the conclusions from a cost benefit analysis regarding a ship tunnel at Stad, carried out in 2007. Stad is a peninsula located on the western coast of Norway. A tunnel here would give seafarers the opportunity to pass by Stad regardless of the weather conditions and ship size. The waters surrounding Stad are difficult, and this stretch of sea is one of the most feared along the entire Norwegian coast. Interviews and two open meetings gave information about how the people and companies react to the current sailing conditions. Information gathered indicates that aspects of great importance to some of the stakeholders, are not captured by the prevailing CBA method. Today, the seafarers take precautions which would not be necessary if a tunnel was built. This represents costs today and savings should the tunnel be built, and thus the savings should be included in the assessment of the tunnel. Research should be carried out to go more thoroughly into the effects, and the method to assess safety projects at sea. New assessments for sea projects should be altered to take these effects into account

Refordeling av plikter (og aktiviteter) i familien når en av de voksne får endret transporttilbud til arbeid

En spørreundersøkelse fra et arbeidssted som flyttet fra periferien til sentrum av Trondheim, illustrerer hvilke effekter en tradisjonell transportmodell vil utelate, men en aktivitetsbasert modell vil fange opp. Ved å knytte teorien fra aktivitetsbasert tilnærming til en reell situasjon, kan man lettere kvantifisere effekter som ellers bare er beskrevet. Om effektene er betydelige, er det et argument for en utvikling av transportmodellene i retning av aktivitetsbaserte

Waiting Time Strategy for Public Transport Passengers

To overcome future challenges in urban transport, it is crucial that transport models and cost benefit analyses provide a better approximation of real travel costs for public transport trips; however, it is challenging to exemplify public transport’s generalized cost components. This paper focuses on waiting time as one component of generalized costs. Unlike other relevant components, waiting time is partly determined by an individual strategy. The open waiting time is also affected by line punctuality; delays prolong the actual waiting time unless the delay is normal and travelers have adjusted to this situation. It is quite common to use the assumption of random passenger arrivals at bus stops (as in the Norwegian regional transport model, RTM), to represent the total waiting time, both open and hidden. This study presents results from field registrations and surveys, as well as passengers’ actual waiting times and their waiting time strategies. The registrations were completed during morning rush hour in low-frequency services and in residential areas. The results show that passengers plan their arrivals at bus stops, which implies lower waiting times than normally assumed in transport models. The results published here indicate how transport models could be developed to better deal with low-frequency public transport services

Bybane i Bergen – beregninger og prosess

Transportmodellen for Bergen TASS 3, ble i 2001 og 2002 benyttet som beslutningsstøtte for konsekvensutredninger av en bybane i Bergensdalen, hovedkorridoren mot sør fra Bergen sentrum. I denne artikkelen presenteres tre forskjellige eksempler på beslutningsprosesser rundt hvilke forutsetninger som inngikk i transportanalysen og diskusjoner som fulgte etter at den var ferdig. Eksemplene illustrerer at forutsetninger i transportanalysen er et resultat av forhandlinger, hvordan usikkerhet knyttet til utviklingen av enkelte variabler påvirker forhandlingene, og hvordan politiske beslutninger legger premisser for forutsetningene. Eksemplene underbygger et behov for å dokumentere, ikke bare benyttede forutsetninger, men også argumentasjoner for å bruke dem

Waiting Time Strategy for Public Transport Passengers

To overcome future challenges in urban transport, it is crucial that transport models and cost benefit analyses provide a better approximation of real travel costs for public transport trips; however, it is challenging to exemplify public transport’s generalized cost components. This paper focuses on waiting time as one component of generalized costs. Unlike other relevant components, waiting time is partly determined by an individual strategy. The open waiting time is also affected by line punctuality; delays prolong the actual waiting time unless the delay is normal and travelers have adjusted to this situation. It is quite common to use the assumption of random passenger arrivals at bus stops (as in the Norwegian regional transport model, RTM), to represent the total waiting time, both open and hidden. This study presents results from field registrations and surveys, as well as passengers’ actual waiting times and their waiting time strategies. The registrations were completed during morning rush hour in low-frequency services and in residential areas. The results show that passengers plan their arrivals at bus stops, which implies lower waiting times than normally assumed in transport models. The results published here indicate how transport models could be developed to better deal with low-frequency public transport services