Shared road is double happiness: Evaluation of a “Share the road” sign

A road sign with the text «Share the road» and a picture of a smiling cyclist and a passing car was evaluated in a before–after study with surveys among cyclists and car drivers. The sign was set up at two sites on a test road near Oslo in summer 2014. A similar road was used as a comparison. About two thirds of the participants on the test road had noticed the sign. The majority liked it and agreed with its message. Cyclists have more often noticed the sign than car drivers have and they were somewhat more positive towards the sign. Effects on self-reported behavior and the perceived behavior of others were evaluated by comparing changes from the before- to the after-period between test and comparison road. Self-reported behavior of both cyclists and car drivers has improved on the test road after the sign was set up, especially in overtaking situations, and these results are in accordance with how cyclists and car drivers perceived each other’s behavior. The general perception of other road users has improved as well. The results are most likely representative of similar roads with a large proportion of car traffic that is related to recreation and a relatively low level of conflict.     

Drivers’ and cyclists’ safety perceptions in overtaking maneuvers

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.     

Investigating the motivational factors influencing drivers intentions to unsafe driving behaviours: Speeding and overtaking violations

Achieving road safety depends on driver attitudes and behaviours in handling the vehicle on roads. The availability of good road, improvement of vehicle designs and drivers experience lead to reduction in crashes but not prevention of crashes. The study aims to predict the drivers’ intentions towards speeding and overtaking violations when under the influence of motivational factors using belief measure of TPB and DBQ variables. To achieve this, questionnaires were randomly administered to a sample of Ghanaian drivers (N = 354) who held valid driving licenses. This study applied regression techniques. The result shows that the components of TPB and DBQ variables were able to predict drivers’ intentions towards speeding and overtaking violations. The study further shows that components of TPB made larger contributions to the prediction of divers’ intentions to speeding and overtaking than the DBQ. Further analysis revealed that, in the prediction of drivers’ intentions, speeding attitude was the most frequent violations compared to overtaking. The drivers tend to involved in overtaking violations when they perceived the driving motivations would enhance the performance of the behaviour. Additionally, control belief has been the strongest predictor of drivers’ intentions under the influence of motivations to speeding and overtaking violations. It appeared that the drivers who intended to involve in speeding and overtaking violations had strong beliefs in the factors and are more likely to violate based on their beliefs. The practical implications of the findings for the development of interventions to promote road safety and positive changes are also discussed.     

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.     

A comparison of computational driver models using naturalistic and test-track data from cyclist-overtaking manoeuvres

The improvement of advanced driver assistance systems (ADAS) and their safety assessment rely on the understanding of scenario-dependent driving behaviours, such as steering to avoid collisions.This study compares driver models that predict when a driver starts steering away to overtake a cyclist on rural roads. The comparison is among four models: a threshold model, an accumulator model, and two models inspired by a proportional-integral and proportional-integral-derivative controller. These models were tested and cross-applied using two different datasets: one from a naturalistic driving (ND) study and one from a test-track (TT) experiment. Two perceptual variables, expansion rate (the horizontal angular expansion rate of the image of the lead road user on the driver’s retina) and inverse tau (the ratio between the image’s expansion rate and its horizontal optical size), were tested as input to the models. A linear cost function is proposed that can obtain the optimal parameters of the models by computationally efficient linear programming.The results show that the models based on inverse tau fitted the data better than the models that included expansion rate. In general, the models fitted the ND data reasonably well, but not as well the TT data. For the ND data, the models including an accumulative component outperformed the threshold model. For the TT data, due to the poorer fit of the models, more analysis is required to determine the merit of the models. The models fitted to TT data captured the overall pattern of steering onsets in the ND data rather well, but with a persistent bias, probably due to the drivers employing a more cautious strategy in TT.The models compared in this paper may support the virtual safety assessment of ADAS so that driver behaviour may be considered in the design and evaluation of new safety systems.     

Improved driver behaviour at bus stops on local roads: Comparison of different treatments

Every day, millions of students use school bus as a mean of transportation to and from schools. Nevertheless, most of the school bus related crashes occur at or near bus stops. The overtaking of stopped school buses during boarding and alighting of students imposes safety risks on students and drivers. This study aims to investigate the impact of three different treatments on driving behavior at bus stops. In total, this study compared four different conditions. Three of them were treatment conditions namely (Red Pavement, Road Narrowing, and smart LED), which were compared with a control condition (i.e., the default bus stop layout without any additional treatments as implemented in the State of Qatar). Each condition was tested for three situations. Situation 1 and Situation 2 were designed with the presence of a stopped school bus on the same and on the opposite travel directions, respectively, while, Situation 3 was designed without any school bus at the bus stop location. A total of 72 subjects participated in the experiment. Generalized Linear Mixed Model (GLMM) was employed to study the impact of several factors on the overtaking/crossing probability of the stopped school bus. In Situation 1, Road_narrowing condition outperformed the other conditions by making 94.3 % of drivers to stop for the bus, while in Situation 2, LED condition performed best by making 48.6 % of drivers stop for the bus that is stopped at the opposite travel direction. Moreover, the LED and Road_narrowing treatments were effective in moderating drivers’ speed behavior, lowering their traveling speed by 5.16 km/h and 5.11 km/h, respectively even in the absence of any bus at the bus stop. Physical road narrowing condition outperformed the other tested conditions, and therefore, can be recommended as a low-cost treatment to improve safety at bus stops. In locations where the implementation of physical road narrowing is not feasible, LED treatment can be used to moderate driver traveling speed and stopping behavior.     

The effects of adaptive cruise control (ACC) headway time on young-experienced drivers' overtaking tendency in a driving simulator

The preference to maintain a certain desired speed is perhaps the most prevalent explanation for why a driver of a manually driven car decides to overtake a lead vehicle. Still, the motivation for overtaking is also affected by other factors such as aggressiveness, competitiveness, or sensation-seeking caused by following another vehicle. Whether such motivational factors for overtaking play a role in partially automated driving is yet to be determined. This study had three goals: (i) to investigate whether and how a driver's tendency to overtake a lead vehicle changes when driving a vehicle equipped with an adaptive cruise control (ACC) system. (ii) To study how such tendencies change when the headway time configuration of the ACC system varies. (iii) To examine how the manipulation of the speed and speed variance of the lead vehicle affect drivers' tendencies to overtake a lead vehicle. We conducted two different experiments, where the second experiment followed the first experiment's results. In each experiment, participants drove three 10–12 min simulated drives under light traffic conditions in a driving simulator under manual and level one (L1) automation driving conditions. The automation condition included an ACC with two headway time configurations. In the first experiment, it was 1 sec and 3 secs, and in the second, it was 1 sec and 2 secs. Each drive included six passing opportunities representing three different speeds of the lead vehicle (−3 km/h, +3 km/h, +6 km/h relative to the participant), with or without speed variance. Results show that drivers tended to overtake a lead vehicle more often in manual mode than in automated driving modes. In the first experiment, ACC with a headway time of 1 sec led to more overtaking events than ACC with 3 secs headway time. In addition, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies. In the second experiment, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies only when interacting with each other and with driving configuration. When the speed of the lead vehicle was +3 km/h and included variability, more overtaking events occurred in manual mode than both automation modes. This work has shown that driving with ACC might help reduce overtaking frequencies and more considerable when the headway time is set to 3 secs.     

Objective and perceived risk in overtaking: The impact of driving context

The assistance and autonomous performance of overtaking manoeuvres can offer significant safety benefits. The impact of driving context on perceived risk emphasises the benefits of using contextual information to adjust the manoeuvring behaviour. This paper follows a mixed approach, addressing two main objectives: identifying factor combinations related to overtaking crashes (objective risk) and exploring their relationship to perceived risk. Factor combinations were extracted from a multi-year dataset, acquired from the UK in-depth study RAIDS (Road Accident In-depth Studies). Selected factors were used to create motorway overtaking scenarios with different manoeuvring behaviour (pull-out distance, manoeuvre duration, speed) and driving context (day/night, overtaking car/truck), while 237 participants assessed their impact on perceived risk through an online survey. The findings highlight the strong impact of manoeuvre characteristics on perceived risk, mediated or intensified by the driving context. Long pull-out distance and short manoeuvre duration time were preferred; under night conditions, short pull-out distances were perceived as riskier compared to daytime, while the opposite effect appeared for high speed, which was considered safer. The results can inform future research on motorway overtaking safety perception and acceptability, as well as the design of systems that assist or autonomously perform overtaking. Specifically, they can be used as guidelines for incorporating context related information to adjust overtaking behaviour according to user preferences and create a positive passenger experience.     

Sharing is (s)caring? Interactions between buses and bicyclists on bus lanes shared with bicyclists

This paper presents the results of an observation study of interactions between bicyclists and buses on shared bus lanes. The aim of the paper is to analyse bicyclists’ safety on bus lanes shared with bicyclists. Straight sections of two bus lanes shared with bicyclists in Belgium are observed. All interactions between bicyclists and buses over two full weeks are recorded and analysed. Additionally, the lateral position and riding speed of bicyclists that are in interaction with buses are compared with the behaviour of bicyclists that are not in interaction with buses. One of the observed bus lanes is in line with road design guidelines in a number of countries that state that a sufficiently narrow bus lane (<3.5 m) is hypothesised to be safer than a somewhat wider bus lane; the other observed bus lane is deemed too wide according to these guidelines and is hypothesised to lead to close overtaking manoeuvres.The results show that close interactions between bicyclists and buses are relatively frequent on both types of analysed bus lanes. Close overtaking manoeuvres (a bus overtakes a bicyclist with a lateral distance less than 1 m) as well as close bicycle-following situations (a bus drives behind a bicyclist with a time gap less than 2 s) are quite common on both analysed bus lanes. The analyses could not confirm the hypothesis that a sufficiently narrow bus lane is safer than a wider bus lane. On the contrary, close interactions seem even slightly more common on the narrower bus lane. Slightly more close overtaking manoeuvres take place on the narrower bus lane, but the difference is not statistically significant. Additionally, more bicycle-following situations take place on the narrower bus lane because overtaking is more difficult. The results show that buses often maintain a close time gap in these situations. The overtaking speed of the buses is, however, significantly higher on the wider bus lane compared to the narrower one.Moreover, the presence of a bus has an influence on the behaviour of bicyclists. Bicyclists who get overtaken by a bus ride more closely to the edge of the road than bicyclists who are not in interaction with a bus. While the road design guidelines assume that bicyclists take up a width of one meter from the edge on bus lanes shared with bicyclists, the observations show that bicyclists take up much less space while being overtaken. The presence of a bus does not have a significant influence on the standard deviation of the lateral position of the bicyclist. On the narrower bus lane, some findings suggest that bicyclists who are involved in an interaction with a bus ride faster than bicyclists who are not involved in an interaction with a bus.     

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.