Observations of truck-bicycle encounters: A case study of conflicts and behaviour in Trondheim, Norway

Pokorny, Petr; Pitera, Kelly

doi:10.1016/j.trf.2018.11.018

Cited by 18 publications

(22 citation statements)

References 18 publications

(25 reference statements)

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“…Some observational studies have investigated how cyclists and motorized vehicles actually interact in conflict situations (e.g. Bjørnskau, 2017;Pokorny & Pitera, 2019). For instance, Bjørnskau (2017) observed that although car drivers in Norway do not have to yield for cyclists who cycle on zebra crossings, most of them did.…”

Section: Introductionmentioning

confidence: 99%

Cyclists’ intentions to yield for automated cars at intersections when they have right of way: Results of an experiment using high-quality video animations

Vlakveld

Kint

Hagenzieker

2020

Transportation Research Part F: Traffic Psychology and Behaviou

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What will cyclists do in future conflict situations with automated cars at intersections when the cyclist has the right of way? In order to explore this, short high-quality animation videos of conflicts between a car and a cyclist at five different intersections were developed. These videos were 'shot' from the perspective of the cyclist and ended when a collision was imminent should the car or the bicyclist not slow down. After each video participants indicated whether they would slow down or continue cycling, how confident they were about this decision, what they thought the car would do, and how confident they were about what the car would do. The appearance of the approaching car was varied as within-subjects variable with 3 levels (Car type): automated car, automated car displaying its intentions to the cyclists, and traditional car. In all situations the cyclist had right of way. Of each conflict, three versions were made that differed in the moment that the video ended by cutting off fractions from the longest version, thus creating videos with an early, mid, and late moment for the cyclist to decide to continue cycling or to slow down (Decision moment). Before the video experiment started the participants watched an introductory video about automated vehicles that served as prime. This video was either positive, negative, or neutral about automated vehicles (Prime type). Both Decision moment and Prime type were between subject variables. After the experiment participants completed a short questionnaire about trust in technology and trust in automated vehicles. 1009 participants divided in nine groups (one per Decision moment and Prime) completed the online experiment in which they watched fifteen videos (5 conflicts Â 3 car types). The results show that participants more often yielded when the approaching car was an automated car than when it was a traditional car. However, when the approaching car was an automated car that could communicate its intentions, they yielded less often than for a traditional car. The earlier the Decision moment, the more often participants yielded but this increase in yielding did not differ between the three car types. Participants yielded more often for automated cars (both types) after they watched the negative prime video before the experiment than when they watched the positive video. The less participants trusted technology, and the capabilities of automated vehicles in particular, the more they were inclined to slow down in the conflict situations with automated cars. The association between trust and yielding was stronger for trust in the capabilities of automated vehicles than for trust in technology in general.

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Section: Introductionmentioning

confidence: 99%

Cyclists’ intentions to yield for automated cars at intersections when they have right of way: Results of an experiment using high-quality video animations

Vlakveld

Kint

Hagenzieker

2020

Transportation Research Part F: Traffic Psychology and Behaviou

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show abstract

“…Pavement markings could also prioritize intersections for cyclists through the implementation of a bike box. Bike boxes are advanced stop boxes that increase the visibility of cyclists and potentially reduce conflicts between vehicles and cyclists in right-hook situations [112][113][114]. The effects of the bike box have also been inadequately considered in the literature and they might be significant in terms of network-based BLOS studies.…”

Section: Traffic Enforcementmentioning

confidence: 99%

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

et al. 2020

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Research into the bicycle level-of-service (BLOS) has been extensively conducted over the last three decades. This research has mostly focused on user perceptions of comfort to provide guidance for decision-makers and planners. Segments and nodes were studied first, followed by a network evaluation. Besides these investigations, several variables have also been utilized to depict the users’ perspectives within the BLOS field, along with other cycling research domains that simultaneously scrutinized the users’ preferences. This review investigates the variables and indices employed in the BLOS area in relation to the field of bicycle flow and comfort research. Despite general agreement among existing BLOS variables and the adopted indices, several important research gaps remain to be filled. First, BLOS indices are often categorized based on transport components, while scarce attention has been paid to BLOS studies in trip-end facilities such as bicycle parking facilities. The importance of these facilities has been highlighted instead within research related to comfort. Second, the advantages of separated bike facilities have been proven in many studies; however, scarce research has addressed the challenges associated with them (e.g., the heterogeneity within those facilities due to the presence of electric bikes and electric scooters). This issue is clearly noticeable within the research regarding flow studies. Furthermore, network evaluation (in comparison to segment and node indices) has been studied to a lesser extent, whereas issues such as connectivity can be evaluated mainly through a holistic approach to the system. This study takes one step toward demonstrating the importance of the integration of similar research domains in the BLOS field to eliminate the aforementioned shortcomings.

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“…As shown by Pokorny and Pitera (2019a), cyclists adapt to the presence of trucks in intersections, for example by placing themselves in a position where the truck driver can see them at a traffic light. However, they also observed numerous situations where the cyclist passed the truck on the inside.…”

Section: Limitationsmentioning

confidence: 99%

“…One study from Norway investigated interactions between cyclists going straight ahead and right-turning trucks in four intersections (Pokorny and Pitera 2019a). In a traffic lightregulated intersection, it was found that the chosen waiting positions of both truck drivers and cyclists varied depending on other traffic already present.…”

Section: Introductionmentioning

confidence: 99%

Effects of training on truck drivers’ interaction with cyclists in a right turn

et al. 2020

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With encounters between trucks and cyclists still being a major safety issue and physical as well as technological improvements far from ubiquitous implementation, training truck drivers in anticipatory driving to improve their interaction with cyclists may be a way forward. After a baseline drive in an urban environment, truck drivers inexperienced with urban driving received a dedicated training on anticipatory driving, followed by another drive along the same route several weeks later. The drivers were also interviewed about their opinion about the training. The drivers’ behaviour changed from before to after training, resulting in a better speed management in general, and a more intensive monitoring of the cyclists. There were also some improvements with respect to the placement in relation to the cyclist, but this effect was limited mainly because truck drivers performed well already before the training. The observed results correspond well to the opinions and feelings about the training that were reported by the drivers in the interview. Thus, driver training can possibly be one contributor to an increase in safety in urban areas.

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Observations of truck-bicycle encounters: A case study of conflicts and behaviour in Trondheim, Norway

Cited by 18 publications

References 18 publications

Cyclists’ intentions to yield for automated cars at intersections when they have right of way: Results of an experiment using high-quality video animations

Cyclists’ intentions to yield for automated cars at intersections when they have right of way: Results of an experiment using high-quality video animations

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

Effects of training on truck drivers’ interaction with cyclists in a right turn

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