| 1. |
- Moll, Sara, et al.
(författare)
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Modelling duration of car-bicycles overtaking manoeuvres on two-lane rural roads using naturalistic data
- 2021
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 160
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays, Spanish two-lane rural roads frequently accommodate sport cyclists. They usually ride on the shoulder or on the right edge of the lane, sharing the infrastructure with motorised vehicles. Due to the speed difference between road users, the most frequent and dangerous interaction is in overtaking manoeuvres. One key factor from a safety and traffic operation point of view is the overtaking duration. The main aim of this paper is to analyse how factors related to the road, the cyclists, and the overtaking manoeuvre influence the duration of overtaking to cyclists on two-lane rural roads. Naturalistic field data were obtained using instrumented bicycles. Seven groups of cyclists, formed by different numbers of cyclists riding in-line and two-abreast, rode along five rural roads with different geometric and traffic characteristics. A total of 1592 flying manoeuvres, in which drivers did not reduce their speed, and 192 accelerative manoeuvres were analysed. The overtaking duration, considering each overtaking strategy, was modelled using Bayesian statistics. Results showed that flying manoeuvres were more prevalent than accelerative. They were performed with higher speeds and lower lateral clearances and, therefore, presented lower overtaking durations. For both overtaking strategies, duration increased on wider roads and with a larger size of the group. The presence of an oncoming vehicle decreased the overtaking duration. However, other factors presented opposite effects on the duration depending on the overtaking strategy. The developed predictive models allow obtaining overtaking durations varying road and cyclist grouping characteristics. Results can be used by road administration to manage and propose some specific countermeasures to integrate the cyclists in a safe and efficient way on two-lane rural roads.
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| 2. |
- Rasch, Alexander, 1991, et al.
(författare)
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Drivers’ and cyclists’ safety perceptions in overtaking maneuvers
- 2022
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Ingår i: Transportation Research Part F: Traffic Psychology and Behaviour. - : Elsevier BV. - 1369-8478. ; 84:January, s. 165-176
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Tidskriftsartikel (refereegranskat)abstract
- Drivers overtaking cyclists on rural roads are a safety concern, as drivers need to handle the interaction with the cyclist and possibly an oncoming vehicle. Improving the maneuver’s outcome requires an understanding of not only the objective, measurable safety metrics, but also the subjective, perceived safety of each road user. Previous research has shown that the perceived safety of the cyclist is most at risk at the passing moment, when driver and cyclist are closest to each other. However, to develop safety measures, it is necessary to know how both road users perceive safety, by understanding the factors that influence their perceptions during the overtaking maneuver. This study measured the perceived safety of drivers in a test-track experiment in Sweden and the perceived safety of cyclists in a field test in Spain. For both drivers and cyclists, we developed Bayesian ordinal logistic regression models of perceived safety scores that take as input objective safety metrics representing the different crash risks at the passing moment. Our results show that while drivers’ perceived safety decreases when there is an oncoming vehicle with a low time-to-collision, cyclists’ perceived safety is reduced by a small lateral clearance and a high overtaking speed. Although our datasets are heterogeneous and limited, our results are in line with previous research. In addition, the Bayesian models presented in this paper are novel and may be improved in future studies once more naturalistic data become available. We discuss how our models may support infrastructure development and regulation, policymaking, driver coaching, the development of active safety systems, and automated driving by providing a possible method for predicting perceived safety.
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