Effect of design factors on drivers’ understanding of variable message signs locating traffic events

BackgroundThis article addresses how to combine three elements (a pictogram, an arrow, a city) in a variable message sign (VMS) to locate temporary events (e.g., “congestion before Milan”). We adopted the G1c stack model as a design template, an Advanced Directional Sign (ADS) recommended by the 1968 Convention to locate cities, which can be easily adapted to modern VMS. However, as most of the VMS in operation are not full-matrix, we have also adapted this design to more restrictive display conditions. This adaptation critically concerned the arrow function on the message that either points up broadly (generically, as in G1c) or connects with the city more specifically (explicit). Although G1c reads top-down like a verbal text, previous studies indicated drivers’ preference for bottom-up landmark order in VMS, so both ordering criteria were compared in the present study.MethodsThe experiment involved 99 people (70 drivers and 29 drivers in training). Participants were informed that they would see various VMS reporting certain events (e.g., congestion) related to one of four cities along the road. Their task was to identify the event location (before, after the city) after seeing blocks of two consecutive messages (first a complementary message, then the target message), limiting their response to the content of the second message. Three design-focused factors were tested: typographical alignment (left or centre), landmark order (bottom-up or top-down), and arrow function (explicit or generic). The rate of correct location answers was the dependent variable.ResultsResults revealed that comprehension varied greatly depending on the arrow’s function and the placing of elements. In the explicit-arrow messages, comprehension was good both in the Top-down and Bottom-up conditions, but in the generic-arrow messages, only in the Bottom-up condition was comprehension good. Likewise, understanding was better in the Before condition than in the After condition in all combinations of Landmark order and Arrow function conditions. In general, left alignment of the central column elements of the VMS improved comprehension respective to centred alignment. Finally, the complementary message factor had an effect under certain circumstances.Practical implicationsThe messages displaying a generic arrow (following the G1c model) were better understood when the landmarks were ordered bottom-up, not top-down. In addition, explicit-arrow messages were better understood per se (in the absence of a complementary message) than generic-arrow messages. Overall, this work suggests that improving our understanding of how thought processes and design features relate to each other can contribute to safer driving nationally and internationally.     

The effect of context and drivers’ age on highway traffic signs comprehension

Background: Comprehension of traffic signs is crucial to safety. Objectives: To test the effects of the presentation condition (with or without driving context) on symbolic based road signs comprehension and comprehension time for young and older drivers. Method: 50 young drivers and 50 older drivers were presented with images of 28 Israeli road signs, both without context (with a white background) and in context (with the driving surrounding). Data were collected on the accuracy of signs meaning and on the time it took the participants to provide the meaning. Results: Younger drivers performed significantly better than older drivers on both accuracy and response time (RT). Older drivers’ average RT was approximately twice as long as younger drivers’ RT. However, the presentation mode (with or without context) did not affect sign comprehension of either group, but the presence of the context did increase the time it took the drivers to comprehend the sign’s meaning. In addition, correct response time was similar to opposite to sign’s meaning response time. Implications: Older drivers, can benefit from retraining in sign comprehension of current signage. The training should involve signs in their natural road environment to reduce comprehension time while actually driving. Moreover, signs that were understood as having an opposite meaning should be redesigned or be accompanied by text.     

Me have a traffic accident? The effects of core self-evaluations on the perceived likelihood and perceived undesirability of traffic accidents

Problem: The aim of this article was to demonstrate the influence of “Core Self-Evaluations” (CSEs) on the perception which drivers have of the occurrence of a “traffic accident”, in particular the evaluation of its likelihood, of the personal control exercised and its undesirability (attitude). More generally, this article introduces the concept of CSE in the field of driver psychology and discusses its relevance. Method: 201 French drivers replied to a questionnaire measuring CSEs, the perceived likelihood of having an accident, attitude and perceived personal control. Results and discussion: The more positively drivers evaluated themselves, the more they judged that they were in control and that accidents were unlikely. Drivers with a negative self-evaluation had an attitude more negative than drivers with positive CSEs solely when they judged the accident as unlikely. This positive correlation between attitude and perceived likelihood for drivers with negative CSEs could be viewed as the result of “wishful thinking” or “rationalisation” modes of reasoning. For these drivers a positive relationship was also observed between driving experience and perceived personal control, the latter thus cancelling out the effect of CSEs. This result suggest that with experience self-evaluation as a driver becomes positive and compensates for the effect of a negative general self-evaluation on perceived personal control and perceived likelihood. Practical implications: Using and adapting the Experience-Based Analysis technique for each group of drivers (positive or negative CSEs) is recommended, as well as implementing interventions that triggers drivers’ awareness of CSEs influence and that promote their self-regulating skills.     

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.     

Adversarial attacks against profile HMM website fingerprinting detection model

People are accustomed to using an anonymous network to protect their private information. The Profile HMM (Hidden Markov Model) Website Fingerprinting Detection algorithm can detect the website that the data stream accesses by pattern matching the captured data traffic. This makes the anonymous network lose its effect. In order to bypass the detection of this model, we propose a method based on genetic algorithm to generate adversarial samples. By migrating the problem of adversarial samples in deep learning, our approach is used for the broader machine learning detection model to do traffic confusion, and then achieves the purpose of bypassing the Profile HMM model detection. The key challenge is how to construct a suitable fitness function to generate an effective adversarial sample at minimal cost. The experimental results show that the success rate of our traffic confusion method is as high as 97%. At the same time, we only need to add less perturbation traffic than the traditional traffic confusion method.     

Can prosocial attitude reduce the risk behavior in simulated driving?

High traffic density may lead to more traffic accidents because of more frequent lane change and overtaking behaviors, but drivers with different characteristics may exhibit different driving behaviors. The present study explored the difference in driving behaviors between drivers with a high/low prosocial attitude under high/low traffic density. In this study, a 2 (high/low prosocial attitude) *2 (high/low traffic density) mixed design was used to investigate the interaction between prosocial attitude and traffic density on lane change and overtaking behavior. The implicit association test paradigm was used to measure prosocial attitude, and drivers were divided into two groups. Forty subjects were asked to complete simulated driving tasks under the two conditions of high and low traffic density, and driving behaviors were recorded by driving simulators. The results show that high traffic density leads to more lane change and overtaking behavior. Drivers with a high prosocial attitude have better driving performance under both high and low traffic density, but drivers with a low prosocial attitude maintain a smaller transverse distance from adjacent vehicles in high traffic density, which may increase risk. This study provides support for the selection, training and intervention of professional drivers.     

Driver's avoidance characteristics to hazardous situations: A driving simulator study

When analyzing the causes of an accident, it is critical to determine whether the driver could have prevented the accident. In previous studies on the reaction times of drivers, the definition and values of reaction times vary, so applying reaction time is difficult. In such analysis, the driver’s reaction time from perception is required to determine whether the driver could have prevented the accident, but past studies are difficult to utilize in accident analysis as reaction time measurements were taken after the occurrence of hazardous situations. In this study, 93 subjects from age groups ranging from 20 s to 40 s participated in an experiment inside a full-scale driving simulator, to determine reaction time values that can be practically applied to accident analysis. A total of 4 hazardous accident situations were reproduced, including driving over the centerline, pedestrian jaywalking, a vehicle cutting in, and intersection traffic signal violation. The Time-To-Collision (TTC) was 2.5 s and the driving speed was set to the common city road speed limits of 60 and 80 km/h. An eye tracker was used to determine the driver’s Saccade Latency (SL) during hazardous situations. Brake Reaction Time from Perception (BRT_P), Steer Reaction Time from Perception (SRT_P), and Driver Reaction Time from Perception (DRT_P) were derived, and the measurements were statistically analyzed to investigate differences by age group, gender, speed, and type of hazardous situation. Most participants were found to avoid collisions by braking first rather than steering for the presented hazardous situations, except for the cutting in situation. Also, to determine a reaction time that would cover most drivers, the 85th percentile of DRT_P was calculated. The 85th percentile of DRT_P was in the range of 0.550 – 0.800 s. Specifically for each hazardous situation, it was 0.650 s for driving over the centerline, 0.800 s for the pedestrian jaywalking, 0.660 s for cutting in, and 0.550 s for the intersection traffic signal violation. For all 4 hazardous situations combined, the 85th percentile of DRT_P was 0.646 s. The findings can be utilized to determine the driver’s likelihood of avoiding accidents when faced with similar hazardous situations.     

Psychometric adaptation of the driving cost and benefit scale in Chinese drivers

The present study aimed to adapt the Driving Cost and Benefit Scale (DCBS, Taubman-Ben- Ari, 2008) to Chinese drivers and examine its relationships with driving style and traffic violations. Nine hundred drivers aged 18 to 60 years were asked to complete the DCBS and the Multidimensional Driving Style Inventory. The results of exploratory factor analysis (n = 429) and confirmatory factor analysis (n = 429) yielded a 36-item scale with satisfactory reliability. The Chinese version of the DCBS contains seven factors, including three driving cost factors (damage to self-esteem, life endangerment and distress) and four driving benefit factors (impression management, sense of control, thrill and pleasure). Significant associations between the DCBS-C factors and driving styles and traffic violations show that the discriminant validity of the scale is acceptable. Moreover, the driving cost factor of damage to self-esteem and the driving benefit factor of thrill both contributed to drivers’ traffic violations and crashes. The findings show that the reliability and validity of the Chinese version of the DCBS are acceptable, and it can be used as a tool to measure driving motivation in China.     

Red light running by young motorcyclists: Factors and beliefs influencing intentions and behavior

Traffic violations by young riders are major safety problems in motorcycle dominated countries. This study investigates young motorcyclist’s red light running (RLR) intentions and behavior based on the Theory of Planned Behavior (TPB) framework. Behavioral, normative, and control beliefs underlying rider’s RLR are identified. Young riders (N = 246) complete a TPB questionnaire measuring direct and beliefs-based measurement items. The exploratory factor analysis technique reveals factors according to TPB. Structural Equation Modeling (SEM) results show moderate to good fits to the observed data and provide qualified support for the utility of TPB in explaining traffic violation behavior. The findings reveal that perceived norm and attitude dominate violation intentions. Beliefs about normative referents and negative outcomes affect RLR intentions. Intentions affect behavior, especially when riders lack of perceived autonomy. Rider’s degree of control is affected by the beliefs about facilitating circumstances and weather conditions. Besides, perceived autonomy and perceived capacity each influence violation intention and behavior independently. Implications for young motorcyclist safety interventions based on current findings are discussed.     

The failure to respond to changes in the road environment: Does road familiarity play a role?

Road signs do not necessarily lead to the right response. Especially when signs are changed, drivers may not always detect new signs and may therefore fail to respond correctly to the situation indicated. The present driving simulator study investigated whether road familiarity (increased exposure to the same road) influenced failure to respond to a change in road signs. In order to study the failure to respond, participants were presented with a change in the road lay-out (as indicated by a road sign) in the last of a series of simulated drives. The change introduced was the conversion of a normal road into a No-Entry road. Results show that several participants failed to respond to this change. However, the failure to respond was not simply the result of familiarity with the road or prior exposure to precisely the same road, but seemed to be influenced by expectations induced by the road design. Additional safety measures such as the placement of additional road signs reduced the failure to respond. An auditory in-vehicle message gave the best results. Interestingly, both in the case of additional signs and of the in-vehicle message, a general warning was sufficient, without the need to specify the precise traffic situation.