The impact of a child bike seat and trailer on the objective overtaking behaviour of motorized vehicles passing cyclists

IntroductionThe lateral clearance distance of a motorized vehicle while overtaking a cyclist is a key indicator of safety. This lateral clearance distance has never been measured for cyclists transporting a child. Therefore the aim of this study was to investigate the behaviour of motorized vehicles in overtaking cyclists with and without a child on the same bicycle.MethodsThe lateral clearance distance of the overtaking manoeuvres of motorized vehicles was measured using an instrumented bicycle when performing 19 cycling trips on one single road with two different types of cycling infrastructure (a bike lane and shared lane marking) in the Brussels Capital Region (Belgium). Mixed effect regression was used to examine the effect of cycling condition (cyclist without a child [control], cyclist with a child bike seat and cyclist with a child bike trailer) and secondary independent variables (i.e. cycling infrastructure, peak traffic hours and traffic density) on the lateral clearance distance.ResultsThe mean lateral clearance distance in ‘cyclists without child’ was significantly smaller (117.3 cm) than in ‘cyclists with child’ (128.8 cm) (95%CI [7.2;15.9]). Looking at ‘morning peak traffic hours’ (i.e. 7:00 to 9:00 a.m.) a cyclist with child bike seat was overtaken at greater lateral clearance distances than a cyclist with a child bike trailer or a cyclist without child (p=0.041). Furthermore, the percentage of passing manoeuvres under 100 cm was significantly higher in ‘cyclist without child’ (35.3%) in comparison to ‘cyclist with child bike seat’ (21.8%) and ‘cyclist with child bike trailer’ (21.8%) (Chi2=29.19, p<0.001). No significant differences were found between a shared lane marking and bike lane.ConclusionDrivers of motorized vehicles do adapt their overtaking manoeuvre when they overtake cyclists transporting a child, keeping greater and therefore safer lateral clearance distances. In morning peak traffic hours and/or crowded circumstances the child bike seat can be considered as the safest way to transport a child in terms of lateral clearance distance. In general, with 25.3% overtaking manoeuvres under 100cm, police should monitor compliance with the traffic rules with regard to cyclists, and motorists should be more aware of the overtaking traffic rules.     

How cyclist behavior affects bicycle accident configurations?

In many major cities, bicycle usage is on the increase and cycling safety is becoming a critical issue. Most of the existing studies are based on police data which understate both single-bicycle accidents as well as cyclist victims. In France, an estimation based on a road trauma database reveals that cyclists are 8 times more likely to be injured per hour spent on the road compared to motorists. To give a full picture of cycling accidents, as well as to understand how cyclist behavior interacts with other factors in causing accidents, we surveyed all injured cyclists in the period 2009–2011, as identified in a medical database of road trauma victims in a French territorial “départment” (the Rhône, capital city Lyon).Using classification methods we build a typology of 17 recurring configurations of cycling collisions and single-bicycle accidents: 7 concern utilitarian riding (commuting…), 3 concern recreational riding and 7 concern cycling as a sporting activity. A Multiple Correspondence Analysis (MCA) is then used to check the consistency of this typology, and to gain additional insight on road user behavior by projection of supplementary variables.External factors contributing to cycling accidents, such as “bad weather” (13%) or “riding at night” (14%), roadway configuration such as “cycling infrastructure” (16%) or “intersections” (25%), and cyclist behavior such as “alcohol consumption” (5%) or “speed” (25%) are discriminatory variables that interact in many accident configurations. This study shows how road user behavior-influences each step in the chain of events leading to an accident. In the discussion of study results, some recommendations are made to public authorities aimed at improving cyclist safety.     

Compensatory behaviour of visually impaired cyclists in everyday settings

This study investigated whether visually impaired cyclists, compared to cyclists without visual limitations, take other, potentially safer routes to destinations in their own living environment and whether they ride at a lower speed. In total, 19 matched pairs of a visually impaired cyclist and a normally sighted peer from the same neighbourhood recorded their everyday bicycle rides, using GPS action cameras. In addition, they completed an ‘assigned ride’, a ride for which only a starting and an ending point were provided by the researcher. A risk-assessment procedure showed that the route taken by visually impaired cyclists during this assigned ride was not less risky than the route taken by the normally sighted cyclists. Analysis of the everyday rides showed that, on average, cyclists with a visual impairment more frequently (i.e. for longer periods) cycled at a speed below 10 km/h compared to cyclists without visual impairment. Also, the visually impaired participants’ cruising speed was 1.4 km/h lower than that of their normally sighted counterparts. In conclusion, no evidence was found that visually impaired cyclists compensate strategically by taking different, potentially safer routes than normally sighted cyclists when riding in their own environment. They may (unconsciously) compensate tactically for their visual function limitations by riding at a lower speed when necessary. Mobility trainers in vision rehabilitation as well as road designers could apply these findings to optimise the cycling mobility of visually impaired people.     

Investigating cycling kinematics and braking maneuvers in the real world: e-bikes make cyclists move faster,brake harder,and experience new conflicts

Pedelecs (e-bikes), which facilitate higher speeds with less effort in comparison to traditional bicycles (t-bikes), have grown considerably in popularity in recent years. Despite the large expansion of this new transportation mode, little is known about the behavior of e-cyclists, or whether cycling an e-bike increases crash risk and the likelihood of conflicts with other road users, compared to cycling on t-bikes. In order to support the design of safety measures and to maximize the benefits of e-bike use, it is critical to investigate the real-world behavior of riders as a result of switching from t-bikes to e-bikes.Naturalistic studies provide an unequaled method for investigating rider cycling behavior and bicycle kinematics in the real world in which the cyclist regularly experiences traffic conflicts and may need to perform avoidance maneuvers, such as hard braking, to avoid crashing. In this paper we investigate cycling kinematics and braking events from naturalistic data to determine the extent to which cyclist behavior changes as a result of transferring from t-bikes to e-bikes, and whether such change influences cycling safety.Data from the BikeSAFE and E-bikeSAFE naturalistic studies were used in this investigation to evaluate possible changes in the behavior of six cyclists riding t-bikes in the first study and e-bikes in the second one. Individual cyclists’ kinematics were compared between bicycle types. In addition, a total of 5092 braking events were automatically extracted after identification of dynamic triggers. The 286 harshest braking events (136 cases for t-bike and 150 for e-bike) were then validated and coded via video inspection.Results revealed that each of the cyclists rode faster on the e-bike than on the t-bike, increasing his/her average speed by 2.9–5.0 km/h. Riding an e-bike also increased the probability to unexpectedly have to brake hard (odds ratio = 1.72). In addition, the risk of confronting abrupt braking and sharp deceleration were higher when riding an e-bike than when riding a t-bike.Our findings provide evidence that cyclists’ behavior and the way cyclists interact with other road users change when cyclists switch from t-bikes to e-bikes. Because of the higher velocity, when on e-bikes, cyclists appear to have harder time predicting movements within the traffic environment and, as a result, they need to brake abruptly more often to avoid collisions, compared with cycling on t-bikes. This study provides new insights into the potential impact on safety that a cycling society moving to e-bikes may have, indicating that e-cycling requires more reactive maneuvers than does cycling traditional bicycles and suggesting that any distractive activity may be more critical when riding e-bikes compared to traditional bikes.     

Validation of the Cycling Behavior Questionnaire: A tool for measuring cyclists' road behaviors

IntroductionEven though cycling is an activity whose benefits in terms of urban mobility and health are globally recognized, its disproportional growth during the past few decades has led to some unexpected dynamics. In fact, the increasing number of traffic injuries and deaths involving cyclists has a high cost for public health systems. Considering the available empirical evidence, aberrant and positive behaviors on the road constitute relevant predictors for the injuries suffered by road users. Nevertheless, the scarcity of tools that measure and evaluate the behavior of road users, especially in the case of cyclists, constitutes a serious lack in terms of explaining, intervening and preventing traffic crashes through behavioral approaches.ObjectiveThis study had two essential purposes: first, to describe in detail the validation of measurement of risky and positive road user behaviors of cyclists using the Cycling Behavior Questionnaire. Second, to compare the mean scores of the validated version of the CBQ according to demographic and cycling-related factors.MethodAs a part of a larger collaborative research project, our data was collected from 1064 Spanish-speaking cyclists (between 17 and 80 years old) from 20 countries, who filled out an anonymous electronic survey on their riding behaviors. The data was analyzed using competitive Confirmatory Factor Analyses (CFA), thus obtaining basic psychometric values and an optimized structure for the scale.ResultsThe obtained results suggest that the CBQ has a clear factorial structure, items with high factorial weight, and good internal consistency. In particular, the results of the latent variable model with three factors, which were labeled errors, violations and positive behaviors, show that the CBQ is satisfactorily adjusted.ConclusionThe findings of this research support the idea that the CBQ may have important applications in the improvement of road safety through the study of cyclists' behavioral factors and their relationship to demographic and cycling-related factors.     

Cyclist efficiency and its dependence on infrastructure and usual speed

Bicyclists are a heterogeneous group, with varying abilities, traffic education and experience. While efficiency was identified as an important factor on utility bicycle trips, it might be traded for experienced safety, for example by choosing different pathways in a given situation, or by relinquishing one’s right of way. In a semi-controlled study with 41 participants, a grouping was made according to self-reported riding speed in relation to other cyclists. The participants cycled twice along a 3 km inner-city route, passing four intersections with different priority rules. The cyclists were free to choose how to negotiate the intersections. Speed and the traffic surroundings were recorded via gps and cameras on the bike of the participant and of a following experimenter. For each cyclist, the ‘base’ speed on undisturbed segments was determined as reference. Based on this, the efficiency in different types of intersections was computed per cyclist group. It turned out that infrastructural aspects, cyclist group and the presence and behaviour of interacting traffic influenced cyclist efficiency. Faster cyclists were delayed more when the infrastructure required a stop regardless of the traffic situation, like at a red traffic light or a stop sign. The members of the so-called ‘comfort cyclists’ group were delayed the most in a roundabout with mixed traffic, where many chose to get off their bike and walk. In a society working for equality of access to the transport system, it is recommended to develop solutions that consider and accommodate the behaviours of different cyclist groups when planning bicycling infrastructure.     

Who,where, when: the demographic and geographic distribution of bicycle crashes in West Yorkshire

Factors associated with cycle safety, including international differences in injury and mortality rates, protective equipment and bicycle training, have been subject to increasing academic interest. Environmental variables associated with cycle safety have also been scrutinised, but few studies have focussed on geographical factors at the local level. This paper addresses this research gap by analysing a geo-referenced dataset of road traffic incidents, taken from the UK’s STATS19 dataset (2005–2012). We investigate incidents involving cyclists within West Yorkshire. This is an interesting case study area as it has an historically low cycling rate but very ambitions cycling plans following investment from the Department of Transport. West Yorkshire is found to be an unusually risky area for cyclists, with an estimated 53 deaths and 1372 serious injuries per billion kilometres cycled, based on census commuting statistics. This is roughly double the national average. This riskiness varies spatially and temporally, broadly in line with expectations from the previous literature. An unexpected result was that cycling seems to be disproportionately risky for young people in West Yorkshire compared with young people nationally. The case study raises the issue of potential negative health impacts of promoting cycling amongst vulnerable groups in dangerous areas. We conclude by highlighting opportunities for increasing cycling uptake via measures designed primarily to improve safety. The analysis underlying this research is reproducible, based on code stored at github.com/Robinlovelace/bikeR.     

Risk comparative judgments while driving a car among competitive road cyclists and non-cyclists

This study examines risk comparative judgments and risky behaviors while driving a car among competitive road cyclists (n = 119) and among controls (i.e., drivers who have almost no cycling experience, n = 142). A questionnaire-based cross-sectional survey was conducted. Results showed that competitive road cyclists assess their own vulnerability to be involved in an accident while riding (VAR) as being lower than that of the average cyclists, and their abilities to manage risks while riding (AMRR) as being higher. They assessed their own vulnerability to be involved in an accident while driving a car (VAD) as being lower than that of the average drivers, and their own quality of reflexes while driving a car (QRD) as being higher. Their tendency to express comparative optimism while assessing their comparative VAD and QRD was higher than that of controls. They also reported more prudent behaviors while driving a car than did controls. Results are discussed, as well as implications in terms of prevention.     

Unsafety on two wheels,or social prejudice? Proxying behavioral reports on bicycle and e-scooter riding safety – A mixed-methods study

The use of non-motorized transportation and micro-mobility is increasing in many cities. Bicycle riding and e-scooter use are now more common and affordable than ever. However, users of these devices face certain key issues. These include their own risky behaviors as well as involvement in conflicts with other road users. Self-report data may not adequately capture these behaviors and interactions. Despite this, more objective data (i.e., how third parties perceive these users’ road behaviors) is scarce. Aims: This study aimed to understand whether e-scooter riders have comparable or different riding behaviors than cyclists. This was investigated using a mixed-method study. Methods: This paper is divided into two sub-studies. In Study 1, 950 Spanish non-cyclists and non-e-scooter riders (mean age 31.98 ± 13.27 years; 55.3% female) provided external ratings (proxies) regarding the perceived behaviors of bicycle and e-scooter riders. In Study 2, collective Rapid Assessment Processes (RAPs; n = 23) were used to develop qualitative configurations of some of the key risky behaviors highlighted in Study 1. Results: There were significant differences in the perceived errors and violations rated by proxies for both types of riders (with e-scooter riders perceived as having higher rates of risky behaviors). However, there were also structural differences in the effects of external raters’ risk perceptions, traffic rule knowledge, and traffic incidents with two-wheeled riders on how they rated the behaviors. Conclusion: The results of both studies suggest that external raters’ perceptions provide further understanding of the causes, dynamics, and conflicts related to road behaviors performed by certain groups of road users. This is particularly apparent when there is no clear legislation and information on safe riding in urban areas. In this sense, improving infrastructure could promote safer interactions. Finally, road safety education could focus on promoting safer practices and interactions in order to improve how others perceive riders’ behavior.     

Cars overtaking cyclists on different urban road types – Expectations about passing safety are not aligned with observed passing distances

Cars overtaking cyclists have been identified as a source of crashes and subjective risk. Several studies investigated the passing distance for different road types. There has been less research concerning cyclists’ expectations concerning the passing distance at different road types. Thus, we aim at contrasting cyclists’ expectations about the passing safety for different speed limits and cycling infrastructures with the passing distances observed at corresponding urban road types. For this purpose, we show participants images of a predefined set of survey zones in a web-based survey, and ask them about the expected passing safety of cars overtaking them when imagining riding their bikes at these locations. We measure the observed passing distances at the same survey zones with a bike-mounted sensor. We find that cars meet the German legal minimum passing distance of 1.5 m in towns in only 30% of all observed events. In 30 km/h speed zones, passing distances at roads featuring dedicated cycling infrastructure (e.g. bike lanes, cycling boulevards) are decreased as compared to those featuring no cycling infrastructure. In contrast, people estimate that the passing safety on roads with dedicated cycling infrastructure is safer than without cycling infrastructure. This effect is even more pronounced on living streets. Situations where oncoming cars (e.g. living streets, ‘opposite’ roads) must be passed in close distance are apparently not perceived as particularly dangerous. Cycling tracks in 50 km/h speed zones increase both the observed passing distance and the corresponding expectations about passing safety. Taken together, the qualitative comparison of the two datasets implies that cyclists’ expectations about cars passing them in a more adequate and safe distance in streets with reduced speed limits and dedicated cycling infrastructure are not justified in light of the actually observed passing distances. Possible explanations for the contradicting patterns could be that cyclists prefer situations where space is explicitly dedicated for bikes, that they account for the anticipated car traffic volume, and that they assume oncoming cars as less dangerous to pass.     

Understanding cyclist identity and related interaction strategies. A novel approach to traffic research

It is an established fact that interaction of road users is crucial for road safety. However, the knowledge about what governs people’s behaviour in interaction with others and what these interactions mean is not well documented. The present study introduces a novel approach for traffic safety research and puts the cyclist identity at the centre of attention, in order to answer the questions how the heterogeneity of cyclists in terms of applied interaction strategies, opinions towards infrastructure and traffic safety can be explained. For this purpose, a qualitative study following the Grounded Theory methodology has been carried out. Fifteen in-depth-interviews with cyclists in Vienna were analysed in order to obtain data about these questions. As a result, we present a model sketch about constructing a cyclist identity, which serves as a framework that links different power relations in traffic, the switching perspectives of being a cyclist/car user and the changing conditions of cycling traffic policy through interaction strategies of self-portrayal, power demonstration and coping with fear. Finally, we argue that applying the often overlooked concept of ‘identity’ can bring new concepts into the debate on traffic safety for cyclists and support efficient traffic policy making.     

Self-reported anger among ordinary and delivery electric bike riders in China: A comparison based on the cycling anger scale

As vulnerable traffic participants, electric bike (EB) riders have suffered from high collision casualties in recent years. Road user anger has been shown to affect riding behavior and lead to traffic accidents. Besides, studies have highlighted that there may be differences in road user anger in driving different vehicles due to varying perceptions of the relative vulnerability of vehicle type characteristics (control performance and cognitive processes). However, current road user anger investigations for two-wheelers have focused mainly on conventional cyclists, and little attention has been paid to e-bike riders, especially with the emerging group of delivery e-bike (DEB) riders. This study aims to develop a Cycling Anger Scale (CAS) for EB riders based on the Cycling Anger Scale and explore the road user anger experienced by EB riders and the differences between ordinary and delivery EB riders. The survey was conducted in Nanjing, China, and collected from 281 Ordinary EB (OEB) riders and 268 DEB riders. Exploratory factor analysis and confirmatory factor analysis are conducted to determine the revised four-factor structure of the 14-item CAS for EB. The results show that the scores of police interaction and cyclist interaction on the CAS subscales are significantly different between the OEB and DEB groups. The police interaction is the largest source of anger for both groups. Besides, the aggressive riding behaviors are significantly correlated with riding anger, which can be predicted by different aspects of riding anger for the two types of EB riders. This study provides a theoretical basis for designing intervention measures and safety education programs to enhance EB riders’ road safety.     

Estimating the safety benefit of separated cycling infrastructure adjusted for behavioral adaptation among drivers; an application of agent-based modelling

Separated cycling infrastructure is a key strategy employed by urban and transport planners to reduce car vs cyclist crashes.We constructed an agent-based model (ABM) to explore the potential effects of introducing progressively greater levels of saturation (e.g., more kms) of separated cycling infrastructure into a transport network in which drivers also demonstrated behavioral adaptation in response to increased exposure to cyclists as suggested by the safety in numbers (SiN) theory.The findings highlight that if behavioral adaptation among drivers is assumed to be a strong mechanism underpinning cyclist safety, the introduction of low levels of separated cycling infrastructure across a network (e.g., few kms) may provide little or no reduction in car vs cyclist crashes. This is due to the countervailing effects that separated infrastructure may have on drivers’ exposure to cyclists; a fundamental contributor to the concept of behavioral adaptation.This study demonstrates the utility of ABMs to explicitly define and model candidate behavioral mechanisms associated with cyclist and vehicle interaction when estimating the interaction of infrastructure and behavioral mechanisms proposed to underlie cyclist safety. Practically, it suggests that greater saturation of separated cycling infrastructure across transport networks may be required to reduce overall car vs cyclist crashes in circumstances where behavioral adaptation is also a strong mechanism contributing to cyclist safety.     

The effects of safety knowledge and psychological factors on self-reported risky driving behaviors including group violations for e-bike riders in China

ObjectivesIt is unknown that how safety knowledge and psychological factors affect e-bike rider safety. Also, group violation behaviors, which are commonly observed in the field, have been rarely examined for e-bike riders in China. In this paper, the effects of safety knowledge and psychological factors on self-reported risky driving behaviors including group violations were examined.MethodsA questionnaire was developed to acquire information of e-bike riders in Guilin, Guangxi Province. Explanatory factor analysis was used to examine the reliability of the questionnaire and exclude redundant measurement items. Then, a Structure Equation Model was developed to examine the relationships among safety knowledge, safety attitude, risk perception and risky driving behaviors. After that, multiple regression models were fitted to examine the effect of safety knowledge on each type of risky driving behavior, as well as factors associated with group violations. At last, ANOVA tests were conducted to identify significant differences among e-bike rider groups in safety knowledge, safety attitude, and risk perception.ResultsSafety knowledge was found significantly associated with risky driving behaviors for e-bike riders in China, including aggressive driving, erroneous driving, and group violations. E-bike riders severely lack safety knowledge, especially that of traffic rules, including unmarried riders, under-educated riders, riders without driver’s license, younger riders, and riders with little riding experience. Group violations were largely found among e-bike riders, and to be associated with safety knowledge of traffic rules, risk-taking attitude, and riding experience of e-bike riders.ConclusionsThe findings could add some new safety implication and be beneficial for developing safety policies and interventions for e-bikes.     

Modeling pedestrian-cyclist interactions in shared space using inverse reinforcement learning

The objective of this study is to model the microscopic behaviour of mixed traffic (cyclist-pedestrian) interactions in non-motorized shared spaces. Video data were collected at two locations of Robson Square non-motorized shared space in downtown Vancouver, British Columbia. Trajectories of cyclists and pedestrians involved in interactions were extracted using computer vision algorithms. The extracted trajectories were used to obtain several variables that describe elements of road users’ behaviour including longitudinal and lateral distances, speed and speed differences, interaction angle, and cyclist acceleration and yaw rate. The road users behaviour was modeled as utility-based intelligent rational agents using the finite-state Markov Decision Process (MDP) framework with unknown reward functions. The study implemented Inverse Reinforcement Learning (IRL) using two algorithms: the Maximum Entropy (ME) algorithm, and the Feature Matching (FM) algorithm to recover/estimate the reward function weights of cyclists in two types of interactions with pedestrians: following and overtaking interactions. Reward function weights infer cyclist preferences during their interactions with pedestrians in non-motorized shared spaces, and can form the key component in developing agent based microsimulation model for road users. Furthermore, the estimated reward functions were used to estimate cyclists’ optimal policy for such interactions. A simulation platform was developed using the estimated reward functions and the cyclist optimal policies to simulate cyclist trajectories for the validation dataset. Results show that the Maximum Entropy (ME) IRL algorithm outperformed the Feature Matching (FM) IRL algorithm, and generally provided reasonable results for modeling such interactions in non-motorized shared spaces, considering the high degrees of freedom in movement and the more-complex road users interactions in such facilities. This research is considered an important step toward developing a full Agent-Based Model (ABM) for road users in shared space facilities to evaluate the safety and efficiency of such facilities.     

Risky riding behaviours among motorcyclists in Malaysia: A roadside survey

Motorcyclists are over-represented in fatal crashes in Low- and Middle-Income Countries (LMICs). In Malaysia, motorcyclists comprise about 60% of all fatalities in road crashes. However, the prevalence and determinants of risky riding behaviours have been rarely studied in the country. This study aims to investigate motorcycle-related risky riding behaviours at signalised intersections. A total of 72,377 observations were made during six days at six different signalised intersections in Terengganu, Malaysia. Four risky riding behaviours were observed together (i.e. helmet non-use, red-light running, mobile phone use, turn signal neglect) along with additional demographic and contextual factors. The most prevalent risky riding behaviour was turn signal neglect (29.7% of all observations), and the least prevalent was mobile phone while riding (0.2% of all observations). Four logistic regressions were fitted to predict the four risky riding behaviours using the demographic and contextual explanatory factors. The results suggest that helmet non-use increases among female riders, riders wearing industrial uniforms, carrying passengers, riding during the weekend, during off-peak hours, during clear weather, at T-junctions, on multi-lane roads, and on minor road approaches. Red light running increases among female riders, riders wearing industrial uniforms, carrying passengers, during clear weather, at T-junctions, on multi-lane roads, and on major road approaches. Mobile phone use increases among female riders, riders wearing industrial uniforms, carrying passengers, and at cross-junctions. Turn signal neglect increases among male riders, riders not wearing industrial uniforms, solo riders, on weekends, during off-peak hours, during clear weather, on single-lane roads, and on minor road approaches. The findings of this study have significant implications for the development of targeted countermeasures such as education programs and road policing.     

“Put the blame on…others!”: The battle of cyclists against pedestrians and car drivers at the urban environment. A cyclists’ perception study

The main hypothesis of the paper is that cyclists tend to blame primarily car drivers, for the conflict events they have experienced with cars, but they do not have the same intention for the conflict events with pedestrians. For this purpose, 306 cyclists were interviewed through a revealed questionnaire survey and 64% revealed that they had experienced a conflict with a pedestrian whereas 55% revealed that they had experienced a conflict with a car. From the responses, two linear regression models were developed, with the perceived responsibility considered as the dependent variable.The cycling–pedestrian model indicated that cyclists who also have car accessibility, tend to blame primarily the pedestrians for the incidents, compared to cyclists who do not possess a car. Further, cyclists tend to give less responsibility to pedestrians for incidents occurred at sidewalks, crosswalks, etc. compare to incidents occurred at shared use paths. In addition, cyclists do not blame pedestrians for conflicts occurred primarily at sidewalks and crosswalks; places were pedestrians are considered to have the priority. Finally, cyclists aged between 55 and 64 years old, are giving less responsibility to pedestrians for the incident, compare to cyclists aged between 25 and 39 years old.On the other hand, the cycling–car model showed that an illegal cyclist’s movement at a road segment can reduce by half the responsibility the cyclists give to the car drivers, compare to the responsibility they give when the latter have an aggressive driving behavior. It was also found that cyclists, who tend to cycle less than 1 h, do not blame so much the car drivers for the incident, compared to cyclists that cycle for longer. Finally, cyclists who prefer the bicycle lane to be located along the road instead at the sidewalk, tend to accuse less the drivers for the incident.     

An investigation of expertise in cycling: Eye tracking,Think Aloud and the influence of a competitor

ObjectivesTwo studies investigated expert-novice differences in information-seeking behaviour, cognitions and performance during cycling time trials (TT). Study 1 examined trained and novice cyclist’s cognitions whilst performing a TT, using a Think Aloud (TA) protocol and eye-tracking techniques. Study 2 investigated expertise differences during alone and competitive TTs.Methodsin Study 1, six trained and seven novice cyclists performed a 16.1 km TT. In Study 2, eight trained and ten novice cyclists performed three 16.1 km TT; a baseline TT, an alone TT and a trial against a virtual competitor. In both studies, participants were asked to TA and in Study 1 they also wore mobile gaze-tracking glasses. Performance feedback and a simulated TT course were visually displayed during all trials, as was a virtual avatar during the competitor trial. Verbalisations were coded into primary and secondary themes. Cognitions and pacing strategies were compared between groups and across the duration of the TTs. In Study 1, eye-tracking data for total dwell time and gaze frequency were calculated for each area of interest (Time Elapsed, Power, Heart Rate, Cadence, Distance Covered, Speed and Course Scenery).ResultsIn Study 1, no significant differences were found in information-seeking behaviour between groups, however there were expertise differences in the cognitive strategies used. Trained cyclists’ verbalisations were more performance-relevant (i.e., power output), whereas the untrained group were more focused on task completion (i.e., distance and time) and irrelevant information. Both groups talked more about distance and motivational thoughts in the later stages of the trial, and dwell time on distance feedback also increased in this final 4 km. In Study 2, the trained group performed faster than the untrained group but there were no significant differences in pace or performance between alone and competitive TTs for either group. Differences in cognitions were found between groups and across the TT duration.ConclusionBoth studies demonstrate that cognitive processes differ as a function of expertise during self-paced cycling time trials. There were no differences in information-seeking behaviour between trained and untrained cyclists and there was no effect of an opponent on pace or performance.