Novice driver crashes: The relation between putative causal factors, countermeasures, real world implementations, and policy - A case study in simple, scalable solutions.

Novice drivers are at a greatly inflated risk of crashing. This led in the 20th century to numerous attempts to develop training programs that could reduce their crash risk. Yet, none proved effective. Novice drivers were largely considered careless, not clueless. This article is a case study in the United States of how a better understanding of the causes of novice driver crashes led to training countermeasures targeting teen driving behaviors with known associations with crashes. These effects on behaviors were large enough and long-lasting enough to convince insurance companies to develop training programs that they offered around the country to teen drivers. The success of the training programs at reducing the frequency of behaviors linked to crashes also led to several large-scale evaluations of the effect of the training programs on actual crashes. A reduction in crashes was observed. The cumulative effect has now led to state driver licensing agencies considering as a matter of policy both to include items testing the behaviors linked to crashes on licensing exams and to require training on safety critical behaviors. The effort has been ongoing for over a quarter century and is continuing. The case study highlights the critical elements that made it possible to move from a paradigm shift in the understanding of crash causes to the development and evaluation of crash countermeasures, to the implementation of those crash countermeasures, and to subsequent policy changes at the state and federal level. Key among these elements is the development of simple, scalable solutions.

[Safety measures in traffic; how risk compensation affects our behaviour]. / Veiligheidsmaatregelen in het verkeer.

In 2020, more than 600 people died as a result of a traffic crash in the Netherlands and 6,500 were hospitalized after they had sustained a serious injury (MAIS 3+). These numbers are much lower than those in the beginning of the seventies of the last century, when there were more than 3,000 road fatalities. To reduce the number of fatalities, many measures have been taken to avoid road crashes and reduce injury severity. By road design that makes it impossible for road users to collide, by improving the safety of vehicles, and by educating road users. Traffic psychologists often warn for behavioural adaptations that nullify the expected effect of road safety measures (risk compensation). Numerous studies have shown examples of risk compensation in traffic. What is the psychological mechanism behind risk compensation? Which factors enhance risk compensation? And are there any advantages of risk compensation?

Influencing factors of observed speed and rule compliance of speed-pedelec riders in high volume cycling areas: Implications for safety and legislation.

Speed pedelecs (s-pedelecs) are electric bicycles offering pedal assistance up to 45 km/h. S-pedelecs may contribute to a more efficient and green traffic system. However, their potential to reach high speeds has raised road safety concerns. In the Netherlands a new legislation bans s-pedelecs from bicycle paths in urban areas. On the roads with a maximum speed limit of 50 km/h with adjacent bicycle paths, s-pedelec riders must use the roadways instead of the bicycle path. The impact of this legislation on the behaviour of s-pedelec riders and other road users as well as the possible consequences for road safety are yet unknown. Therefore, this naturalistic riding study investigated the safety-relevant behaviours of s-pedelec riders, i.e. speed characteristics while riding on the roadway, the extent of non-compliance with the ban on using bicycle paths, and speed and speed adaptation while using bicycle paths. Furthermore the study explored factors possibly influencing rider behaviour (the s-pedelec's motor-power, riders' beliefs and perceptions) as well as negative reactions of other road users encountering s-pedelec riders. 28 participants used a s-pedelec (a 350 W type or a 500 W type) for everyday trips for at least a fortnight. The s-pedelecs were equipped with two action cameras with integrated sensors and GPS. The results showed that mean speed on 50 km/h roadways was 31.8 km/h, which is far below the road's speed limit. The mean speed did not differ between s-pedelec types, but the speed distribution did. The '500 W riders' travelled 31.7% of the total distance in the 41-50 km/h speed band, as compared to 6.9% of the '350 W riders'. Furthermore the 500 W riders evaluated riding on the roadway more positively than the 350 W riders. On the roadway s-pedelec riders experienced signals of hinderance of the traffic flow (on average every 2 km) and negative reactions from drivers (on average every 27.5 km). As for non-compliance riders covered on average 22.5% of the distance on bicycle paths. The more the riders disagreed with the new legislation, the more distance they covered on the bicycle path. Mean speed on bicycle paths was 28.5 km/h, and it was significantly higher for 500 W riders than for 350 W riders. Speeds between 41 and 50 km/h were also far more common for 500 W riders (14.9% of the distance) than for 350 W riders (0.5%). Compared to the roadway 350 W riders reduced their speed on the bicycle paths to a higher extent (from 31.4 to 25.7 km/h) than 500 W riders did (from 31.9 to 30.5 km/h). The frequency of harsh braking of s-pedelec riders was low and did not differ between the roadway and the bicycle paths. In conclusion, s-pedelec riders in the Netherlands frequently ride on the bicycle paths although it is illegal. On the bicycle paths their speeds are much higher than those of conventional cyclists. On the 50 km/h-roadways, however, s-pedelec riders are apparently too slow for the traffic conditions. Overall, the speed profiles of 350 W types were better suited to the bicycle paths, whereas those of 500 W types to the roadways.

Traffic conflicts involving speed-pedelecs (fast electric bicycles): A naturalistic riding study.

Speed-pedelecs -fast electric bicycles offering pedal support up to a speed of 45 km/h- are a recent, environmentally friendly, and mobility efficient innovation. However, their high travel speed may increase crash and injury risk. Due to their recent introduction accurate crash data are not available yet. Since near-crashes may serve as a proxy for crashes this study analyzed traffic conflicts (i.e., near-crashes and minor crashes) in the Netherlands with the aim to proactively identify potential crash partners, crash patterns, and crash risk increasing factors. To this end, twenty-eight participants used a speed-pedelec in daily traffic, equipped with a forward and a backward facing camera, for two to three consecutive weeks. In a total of 227 h of video footage in which a distance of 6584 km was travelled, 115 conflicts were identified of which 114 were near-crashes in which evasive actions were performed to avert a crash, and one was a minor crash. The most frequent conflict partner were bicycles (51 %), followed successively by cars and vans (28 %), pedestrians (12 %), powered two-wheelers (5 %) and animals (3 %). One conflict was with a truck. With conventional bicycles, most conflicts occurred in crossing maneuvers (36 %) and when the speed-pedelec and bicycle were travelling in the same direction (36 %). Also, with cars and vans, most conflicts occurred in crossing maneuvers (63 %). The case-cohort analyses in which characteristics in conflicts and characteristics in randomly selected moments of the same participant were identified, showed conflict risks to be high if: (1) bicycles or cars were in the proximity of the speed-pedelec but was substantially higher for bicycles than for cars (OR = 43.28, 95 % CI = [16.85-111.17] and OR = 22.43, 95 % CI = [7.59-66.28] respectively), (2) speed-pedelecs overtook other road users which were mostly bicycles (OR = 17.25, 95 % CI = [7.58-39.24]), (3) the speed-pedelecs travelled on bicycle facilities (both legally or illegally) (OR = 1.81, 95 % CI = [1.08-3.03]), and (4) speed-pedelecs rode near or at an intersection, OR = 3.94, 95 % CI = [2.42-6.43]. These findings suggest that conflict risks are higher when speed-pedelec riders make use of bicycle facilities than when they ride on the roadway for cars. However, the consequences of crashes with motorized vehicles on the roadway will probably be more severe for speed-pedelec riders than with bicycles on the cycle path. This study further illustrates the value of naturalistic conflict observations for assessing the safety implications of innovations proactively.

Speed characteristics of speed pedelecs, pedelecs and conventional bicycles in naturalistic urban and rural traffic conditions.

To assess the potential impact of the higher speeds of pedal-assisted bicycles on safety, this study compared conventional bicycles, pedelecs and speed pedelecs (hereafter called s-pedelecs) on mean speeds, speed variability, harsh braking events (decelerations > 2 m/s2), and mean speeds above the speed limit (MSAL) in rural and urban areas in the Netherlands Data were collected in daily traffic, while the legal maximum speed for speed-pedelecs was 25 km/h, and pedelecs and s-pedelecs shared the infrastructure with conventional bicycles. Data were collected, using two-wheelers equipped with accelerometers and GPS. Personality factors - sensation seeking and risk taking - were measured with surveys. Regular commuters used one of the three bicycle types for two weeks. Participant bias was intentionally included by allowing participants to select a bicycle type of their preference, resulting in 12 conventional bicycle riders (71 % women), 14 pedelec riders (67 % women) and 20 s-pedelec riders (25 % women). S-pedelecs were much faster than conventional bicycles, amounting to a speed difference with conventional bicycles of 10.4 km/h in urban areas (M =28.2 km/h vs. 17.8 km/h) and of 13.2 km/h in rural areas (M = 31.4 km/h vs. 18.2 km/h). The speed differences between pedelecs and conventional bicycles were much smaller: 2.3 km/h in urban areas (20.1 km/h vs 17.8 km/h) and 4 km/h in rural areas (22.2 km/h vs. 18.2 km/h). Compared to conventional bicycles, s-pedelecs varied their speed to a greater extent and also braked harshly more frequently, showing a greater need for speed adjustment. These adjustments were larger at higher speeds. In contrast, pedelecs did not differ from conventional bicycles on speed variation. MSAL for s-pedelec riders differed by gender. For men the MSAL was 87 % on urban sections and 91 % on rural sections. For women, the MSAL was lower, respectively 23 and 69 %. None of the personality factors were associated with speed variability, harsh braking or MSAL. However, sensation seeking was associated with higher mean speeds on all three bicycle types. To conclude, pedelecs and conventional bicycles are similar in speed patterns, whereas the speed patterns of s-pedelecs differ significantly from the former two. The safety implications are discussed.

Higher-order cycling skills among 11- to 13-year-old cyclists and relationships with cycling experience, risky behavior, crashes and self-assessed skill.

INTRODUCTION: In the Netherlands, young cyclists are extremely vulnerable in traffic, which may partly be due to their still underdeveloped higher-order cycling skill. So far, knowledge on their actual level of skill is lacking. Using a computerized test battery mimicking real-life risky traffic conditions, this study assessed the level of higher-order cycling skill in children 11 and 12 years of age and tested the hypothesis that these skills show caveats. Furthermore, factors potentially influencing the development and impact of these skills were studied, such as cycling experience, risky road behavior, crash involvement, and self-assessed skill. METHOD: A total of 335 students (49% female) completed computerized tests on hazard perception, gap acceptance, blind spot strategies, and priority decisions in traffic, and completed questionnaires on cycling experience, risky cycling behavior, crashes, and self-assessment of cycling skill. RESULTS: On the hazard perception test, one-third of the participants missed at least half of the number of hazards. They made errors in about 50% of the priority decisions, accepted critical gaps when crossing the road, and conversely rejected safe gaps; only 1% of the participants identified all blind spots of a truck correctly, while 69% made unsafe decisions when interacting with trucks in traffic scenarios. Overall, in complex traffic situations performance was worse than in simple ones. The hypothesis of lack of skills was therefore accepted. However, the study failed to demonstrate consistent relationships between subtest performance and cycling experience, risky behavior, crashes, and self-assessed skill, which weakens the theoretical assumptions concerning the subtests. CONCLUSIONS: The results suggest that children at the end of primary school are still lacking elementary skills for safe cycling, calling for measures to accelerate skill development. PRACTICAL APPLICATIONS: Test batteries are essential tools for systematically monitoring skill development in cyclists, evaluating education programs, and for guiding the development of effective road safety education. The next step is the validation of such batteries.

Speed choice and mental workload of elderly cyclists on e-bikes in simple and complex traffic situations: a field experiment.

To study the speed choice and mental workload of elderly cyclists on electrical assisted bicycles (e-bikes) in simple and complex traffic situations compared to these on conventional bicycles, a field experiment was conducted using two instrumented bicycles. These bicycles were identical except for the electric pedal support system. Two groups were compared: elderly cyclists (65 years of age and older) and a reference group of cyclists in middle adulthood (between 30 and 45 years of age). Participants rode a fixed route with a length of approximately 3.5 km on both bicycles in counterbalanced order. The route consisted of secluded bicycle paths and roads in a residential area where cyclist have to share the road with motorized traffic. The straight sections on secluded bicycle paths were classified as simple traffic situations and the intersections in the residential area where participants had to turn left, as complex traffic situations. Speed and mental workload were measured. For the assessment of mental workload the peripheral detection task (PDT) was applied. In simple traffic situations the elderly cyclists rode an average 3.6 km/h faster on the e-bike than on the conventional bicycle. However, in complex traffic situations they rode an average only 1.7 km/h faster on the e-bike than on the conventional bicycle. Except for the fact that the cyclists in middle adulthood rode an average approximately 2.6 km/h faster on both bicycle types and in both traffic conditions, their speed patterns were very similar. The speed of the elderly cyclists on an e-bike was approximately the speed of the cyclists in middle adulthood on a conventional bicycle. For the elderly cyclist and the cyclists in middle adulthood, mental workload did not differ between bicycle type. For both groups, the mental workload was higher in complex traffic situations than in simple traffic situations. Mental workload of the elderly cyclists was somewhat higher than the mental workload of the cyclists in middle adulthood. The relatively high speed of the elderly cyclists on e-bikes in complex traffic situations and their relatively high mental workload in these situations may increase the accident risk of elderly cyclist when they ride on an e-bike.

Five road safety education programmes for young adolescent pedestrians and cyclists: a multi-programme evaluation in a field setting.

A practical approach was developed to assess and compare the effects of five short road safety education (RSE) programmes for young adolescents that does not rely on injury or crash data but uses self reported behaviour. Questionnaires were administered just before and about one month after participation in the RSE programmes, both to youngsters who had participated in a RSE programme, the intervention group, and to a comparable reference group of youngsters who had not, the reference group. For each RSE programme, the answers to the questionnaires in the pre- and post-test were checked for internal consistency and then condensed into a single safety score using categorical principal components analysis. Next, an analysis of covariance was performed on the obtained safety scores in order to compare the post-test scores of the intervention and reference groups, corrected for their corresponding pre-test scores. It was found that three out of five RSE programmes resulted in significantly improved self-reported safety behaviour. However, the proportions of participants that changed their behaviour relative to the reference group were small, ranging from 3% to 20%. Comparisons among programme types showed cognitive approaches not to differ in effect from programmes that used fear-appeal approaches. The method used provides a useful tool to assess and compare the effects of different education programmes on self-reported behaviour.

Young drivers who obtained their licence after an intensive driving course report more incidents than drivers with a traditional driver education.

This paper studies the effectiveness of intensive driving courses; both in driving test success and safe driving after passing the driving test. The so-called intensive driving course (IDC) consists of a limited number of consecutive days in which the learner driver takes driving lessons all day long; and is different from traditional training in which lessons are spread out over several months and in which learners take one or two driving lessons of approximately 1 h each per week. Our study indicates that--in the first two years of their driving career--IDC drivers (n=35) reported an incident significantly more often (43%) than 351 drivers who obtained their driving licence after traditional training (26%). Our study also indicates that the IDC drivers underwent almost the same number of training hours as the drivers who had traditional training, although spacing of these hours was different. There was no difference in the number of attempts to pass the driving test. We did not find any evidence that a self-selection bias was responsible for the difference in reported number of incidents.

Inexperience and risky decisions of young adolescents, as pedestrians and cyclists, in interactions with lorries, and the effects of competency versus awareness education.

BACKGROUND: Road injuries are a prime cause of death in early adolescence. Often road safety education (RSE) is used to target risky road behaviour in this age group. These RSE programmes are frequently based on the assumption that deliberate risk taking rather than lack of competency underlies risk behaviour. This study tested the competency of 10-13 year olds, by examining their decisions - as pedestrians and cyclists - in dealing with blind spot areas around lorries. Also, the effects of an awareness programme and a competency programme on these decisions were evaluated. METHOD: Table-top models were used, representing seven scenarios that differed in complexity: one basic scenario to test the identification of blind spot areas, and 6 traffic scenarios to test behaviour in traffic situations of low or high task complexity. Using a quasi-experimental design (pre-test and post-test reference group design without randomization), the programme effects were assessed by requiring participants (n=62) to show, for each table-top traffic scenario, how they would act if they were in that traffic situation. RESULTS: On the basic scenario, at pre-test 42% of the youngsters identified all blind spots correctly, but only 27% showed safe behaviour in simple scenarios and 5% in complex scenarios. The competency programme yielded improved performance on the basic scenario but not on the traffic scenarios, whereas the awareness programme did not result in any improvements. The correlation between improvements on the basic scenarios and the traffic scenarios was not significant. CONCLUSIONS: Young adolescents have not yet mastered the necessary skills for safe performance in simple and complex traffic situations, thus underlining the need for effective prevention programmes. RSE may improve the understanding of blind spot areas but this does not 'automatically' transfer to performance in traffic situations. Implications for the design of RSE are discussed.

Do Crashes and Near Crashes in Simulator-Based Training Enhance Novice Drivers' Visual Search for Latent Hazards?

Young drivers (younger than 25 years of age) are overrepresented in crashes. Research suggests that a relevant cause is inadequate visual search for possible hazards that are hidden from view. The objective of this study was to develop and evaluate a low-cost, fixed-base simulator training program that would address this failure. It was hypothesized that elicited crashes in the simulator training would result in better scanning for latent hazards in scenarios that were similar to the training scenarios but situated in a different environment (near transfer), and, to a lesser degree, would result in better scanning in scenarios that had altogether different latent hazards than those contained in the training scenarios (far transfer). To test the hypotheses, 18 trained and 18 untrained young novice drivers were evaluated on an advanced driving simulator (different from the training simulator). The eye movements of both groups were measured. In near transfer scenarios, trained drivers fixated the hazardous region 84% of the time, compared with only 57% of untrained drivers. In far transfer scenarios, trained drivers fixated the hazardous region 71 % of the time, compared with only 53% of untrained drivers. The differences between trained and untrained drivers in both the near transfer scenarios and the far transfer scenarios were significant, with a large effect size in the near transfer scenarios and a medium effect size in the far transfer scenarios [respectively: U = 63.00, p(2-tailed) < .01, r = -.53, and U = 88.00, p(2-tailed)<.05,r = -.39].