Erath, Alexander
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Quantifying the effect of street design on driving speed on urban roads
Reducing driving speed is a key factor in improving road safety and combating noise emissions. For this reason, more and more cities across the world reduce speed limits urban in roads to 30 km/h (20 mph). According measures are implemented in major urban areas in Europe (e.g. Paris, Brussels) and the U.S. (e.g. New York City, Seattle). For the implementation of speed reductions main roads are of particular interest. Main roads in urban areas are different from residential roads in several ways, including, but not limited to the type of trips, vehicular mix and the presence of public transport, and are therefore limited in design options to reduce speeds. The study at hand reports on a virtual reality study conducted in Switzerland using a driving simulator. To assess whether road design influences driving speed, participants were asked to drive through a series of main roads in VR with varying speed limits and street designs. Speed and lateral position were recorded; in a follow-up survey, participants stated their preferred speed along the same segments and were asked about risk aversion. Results indicate that only certain designs result in slightly lower driving speeds, while controlling for self-reported risk aversion and driving style. Given the characteristics of main roads, measures reducing the (perceived) lane width are promising, but require further investigation.
How relevant is the aggregation bias with regards to mode choice?
Most travel demand models used in practice still apply a four-step approach which describes travel demand in an aggregated manner. Aggregation bias refers to the assumption that group characteristics are shared by all the individuals who are members of that group as compared to an approach that evaluates travel behaviour on the level of individuals. The use of average values applied to aggregated populations across spatial zones and time periods distorts a model’s sensitivity to investment and policy alternatives (Castiglione u. a. 2015). Our paper examines the relevance and impact of aggregation bias with regards to trip- and tour-based mode choice. The paper starts with a short literature review and a theoretical description of the problem. The main part of the paper consists of two case studies which we have developed to quantitatively assess the relevance of the aggregation bias. The first case study is based on synthetic data that reflects typical rates of mobility tool ownership and travel times by different modes for a given travel relation in an urban, agglomeration and rural context in Switzerland. The relevance of the aggregation bias is assessed by different ways to consider mobility tool ownership and systematic adaptations of the considered travel times. The second case study is based on the implementation of an activity-based and disaggregated demand model for the German city of Halle based on which an aggregated model is derived that shared exact same transport network and overall travel demand. We use the two models to assess the relevance of the aggregation bias based on three scenarios with different transport planning measures.