University of Twente Student Theses
Effect of the road safety on the cyclists route choice : Do cyclists consider road safety when deciding on their route?
Yakuta, R. (2023) Effect of the road safety on the cyclists route choice : Do cyclists consider road safety when deciding on their route?
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| Abstract: | Netherlands has the highest number of bicycles per capita in Europe, and the government and municipalities are constantly working on the improvement of the cycling network. Municipalities use traffic simulation models to improve cycling networks, including the "Fiets Monitor" developed by Witteveen+Bos company. However, the model's "all-or-nothing" approach for trip assignment may not reflect cyclists' preferences accurately, and Witteveen+Bos is working on its improvement. The research will be focused on the city of Enschede and its cycling infrastructure. The research aims to examine the influence of the road safety on the cyclists route choice, taking into account the impact of environmental and external factors. The study will involve examining existing literature application, required data collection and utilising regression modelling to determine whether road safety should be regarded as a critical factor in route attractiveness. The research gap outlined within this study is that while the influence of environmental factors on cyclists' route choice has been researched, the safety aspect of route choice was not considered and requires further investigation. The safety of cyclists on the road is affected by various environmental factors such as road design, weather conditions, and traffic volume. Cycling safety can be measured by both objective safety (based on empirical data) and subjective safety (based on an individual's perception of safety). In this study, the objective safety was considered and road safety was defined as the probability of a crash occurring on a particular segment of the route, Negative binomial regression modelling was used to estimate the predicted number of crashes for each individual road segment. Several environmental factors that can affect the risk of cycling crashes, including speed limits, road function class, traffic volumes, pavement type, intersections, and safety islands were included in the road safety analysis. In this study, various data sources were used, including the "Fietselweek data" for cycling counts, the "BRON" database for road accidents involving cyclists, "OpenStreetMap" for infrastructural information, "Basisregistratie Grootschalige Topografie" for greenery distribution, "Wijken en Buurten" for information on neighborhoods, and "RUDIFUN1" for data on land use classes. The limitations and benefits of each data source were discussed, with a focus on accuracy and completeness. Negative binomial regression modelling was utilised to develop a safety performance function that can estimate the expected number of crashes. Meanwhile, logistic regression modelling was used to quantitatively analyse the influence of road safety on the cyclists' route choice. Python tools and packages were applied to execute all the modelling. To build a negative binomial regression model, required data was gathered and processed. The list of factors that influence road safety was outlined and factors were properly categorised. The categorization was based on previous studies and the most popular road segments associated with the risk factors identified. The first step of the negative binomial regression model was to process the data as dummy variables, followed by selecting an appropriate distribution for the model. The dispersion parameter was used to estimate over-dispersion in the data. The Empirical Bayes method was fyrther applied to improve the precision of estimates by incorporating prior information and correcting for the regression-to-mean bias. This study found that pavement type, road function classes, and the location of road intersections have a significant impact on cyclist safety. The road safety map showed that major road links and the ring road surrounding the city of Enschede have the highest predicted number of crashes. After the road safety was estimated a logistic regression model to analyse the influence of road safety on the overall network attractiveness was used. The segment approach and a logistic regression model were used to project the road safety effect on the route attractiveness. After, the route attractiveness maps of the network of Enschede were tested with and without consideration of the predicted number of crashes. Validation and verification procedures were executed to ensure the quality and accuracy of the results. Statistical tests such as Kolmogorov-Smirnov and Chi-square tests were applied to see if the road safety implementation has any significant influence on the road attractiveness. Furthermore, model key 4 performance indicators were checked to indicate if the road safety influenced the accuracy of the road attractiveness model. The impact of road safety on route segments' attractiveness was examined, and it was found that road safety had a minor effect on the overall network attractiveness. Statistical tests showed a difference between the datasets, but the difference was not significant enough to to considered. Overall, the addition of road safety data had a small effect on the model's predictions compared to other environmental factors. This study investigated the relationship between road design factors and cyclist safety in Enschede using statistical models. Results showed that certain factors significantly influenced cyclist safety on road segments, but used methodology showed that road safety had a minor influence on the attractiveness of road segments for cycling. The study concluded that according to the applied methodology, road safety does not significantly affect cyclists' route selection, but further research is necessary to investigate the relationship between road safety and route selection for cyclists using alternative methodologies or integrating additional factors. The recommendations suggest using more accurate and detailed data for analysis, conducting further research on other factors that influence cyclist safety and route choice decisions, incorporating alternative approaches to interpreting road safety, and exploring alternative methods for incorporating road safety into route attractiveness models. Additionally, the recommendations suggest examining other factors that may impact cyclists' safety and using the findings of this study as a starting point for future research. |
| Item Type: | Essay (Bachelor) |
| Faculty: | ET: Engineering Technology |
| Programme: | Civil Engineering BSc (56952) |
| Link to this item: | https://purl.utwente.nl/essays/94790 |
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