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|Title: ||Traffic assignment based on activity travel data: a case study|
|Authors: ||RAMAEKERS, Katrien|
|Issue Date: ||2008|
|Citation: ||Belgian Conference on Operations Research, Brussels, Belgium - 17/1/2008 - 18/1/2008.|
|Abstract: ||Modelling traffic patterns has always been a ma- jor area of concern in transportation research. The four-step model has been the primary tool for fore- casting future demand of regional transportation services. The framework uses trips as an indepen- dent entity of analysis. This, however, leads to a number of serious limitations. Therefore, the orig- inal four-step models were replaced by tour-based systems. In a tour-based model, trips are explic- itly connected in tours, i.e. chains that start and end at the same home or work base. Neverthe- less, these models did not escape criticism either. It was claimed by several researchers that very lim- ited insight was o®ered into the relationship be- tween travel and non-travel aspects. This is where activity-based models come into play. The major idea behind activity-based models is that travel de- mand is derived from the activities that individu- als and households need or wish to perform. Travel should therefore be modelled within the context of the entire agenda, as a component of an activity scheduling decision. Because of the use of an activity-based model, a better traffic assignment module can be developed and as a result of this, the impact of transport on environment, traffic safety and health can be pre- dicted more accurately. A custom tool, PARROTS (PDA system for Activity Registration and Recording of Travel Scheduling) was developed to collect both activity data and GPS data. This tool is currently deployed in a survey that is carried out on 2500 households in Flanders. Two types of data are collected us- ing PARROTS: activity-travel diaries inputted by the respondents and location data logged by a GPS receiver. Activity-travel diaries and route information that are collected via GPS are linked and inves- tigated. By jointly investigating activity-travel di- aries and route choice information, a richer route- choice dataset is obtained. This enables investiga- tion of the route-choice process in the context of the activities and their attributes. Much research is going on both in the ¯elds of traffic demand modelling and traffic assignment. In the past, both research ¯elds have been developing independently. It is clear that by coupling traffic demand modelling and traffic assignment a power- ful tool can be obtained. The traditional approach towards the integration of traffic demand models and traffic assignment consists of aggregating travel demand in origin-destination matrices and subse- quently assigning these OD matrices to the trans- portation network. Activity-based models can pre- dict traffic demand by predicting activity-travel di- aries for the individuals within the studied popula- tion. The traffic demand can be derived from the requirement to travel from one activity location to the next. It is clear that aggregating the traffic de- mands resulting for all individuals in OD matrices yields an enormous loss of information. Indeed, it does seem reasonable to assume that on an indi- vidual level, the context of a trip plays a role in how an individual chooses a certain route. E.g. if the purpose of a trip is to go to work, the fastest route might be preferred. However, a route with a beautiful scenery might be preferred for leisure time trips.|
|Notes: ||Davy Janssens, Transportation Research Institute, Hasselt University, Belgium Tom Bellemans, Transportation Research Institute, Hasselt University, Belgium Elke Moons, Transportation Research Institute, Hasselt University, Belgium Geert Wets, Transportation Research Institute, Hasselt University, Belgium|
|Type: ||Conference Material|
|Appears in Collections: ||Research publications|
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