Understanding interactions between autonomous vehicles and other road users: A literature review

This review draws on literature relating to the interactions of vehicles with other vehicles, interactions between vehicles and infrastructure, and interactions between autonomous vehicles and cyclists and autonomous vehicles and pedestrians. The available literature relating to autonomous vehicles interactions is currently limited and hence the review has considered issues which will be relevant to autonomous vehicles from reading and evaluating a broader but still relevant literature.The project is concerned primarily with autonomous vehicles within the urban environment and hence the greatest consideration has been given to interactions on typical urban roads, with specific consideration also being given to shared space. The central questions in relation to autonomous vehicles and other road users revolve around gap acceptance, overtaking behaviour, behaviour at road narrowings, the ability to detect and avoid cyclists taking paths through a junction which conflict with the autonomous vehicle’s path, and the ability of autonomous vehicles to sense and respond to human gestures. A long list of potential research questions has been developed, many of which are not realistically answerable by the Venturer project. However, the important research questions which might potentially be answered by the current project are offered as the basis for the more detailed consideration of the conduct of the interaction trial

Simulating the Impact of Traffic Calming Strategies

This study assessed the impact of traffic calming measures to the speed, travel times and capacity of residential roadways. The study focused on two types of speed tables, speed humps and a raised crosswalk. A moving test vehicle equipped with GPS receivers that allowed calculation of speeds and determination of speed profiles at 1s intervals were used. Multi-regime model was used to provide the best fit using steady state equations; hence the corresponding speed-flow relationships were established for different calming scenarios. It was found that capacities of residential roadway segments due to presence of calming features ranged from 640 to 730 vph. However, the capacity varied with the spacing of the calming features in which spacing speed tables at 1050 ft apart caused a 23% reduction in capacity while 350-ft spacing reduced capacity by 32%. Analysis showed a linear decrease of capacity of approximately 20 vphpl, 37 vphpl and 34 vphpl when 17 ft wide speed tables were spaced at 350 ft, 700 ft, and 1050 ft apart respectively. For speed hump calming features, spacing humps at 350 ft reduced capacity by about 33% while a 700 ft spacing reduced capacity by 30%. The study concludes that speed tables are slightly better than speed humps in terms of preserving the roadway capacity. Also, traffic calming measures significantly reduce the speeds of vehicles, and it is best to keep spacing of 630 ft or less to achieve desirable crossing speeds of less or equal to 15 mph especially in a street with schools nearby. A microscopic simulation model was developed to replicate the driving behavior of traffic on urban road diets roads to analyze the influence of bus stops on traffic flow and safety. The impacts of safety were assessed using surrogate measures of safety (SSAM). The study found that presence of a bus stops for 10, 20 and 30 s dwell times have almost 9.5%, 12%, and 20% effect on traffic speed reductions when 300 veh/hr flow is considered. A comparison of reduction in speed of traffic on an 11 ft wide road lane of a road diet due to curbside stops and bus bays for a mean of 30s with a standard deviation of 5s dwell time case was conducted. Results showed that a bus stop bay with the stated bus dwell time causes an approximate 8% speed reduction to traffic at a flow level of about 1400 vph. Analysis of the trajectories from bust stop locations showed that at 0, 25, 50, 75, 100, 125, 150, and 175 feet from the intersection the number of conflicts is affected by the presence and location of a curbside stop on a segment with a road diet

An Accident Waiting to Happen: Cognitive Drivers of Unsafe Cycling Behavior

Bicycling is a popular method of transportation and recreational activity utilized ubiquitously around the world. In the United States alone thousands of active cycling clubs exist, in addition to the millions of riders who ride independently, and cycling has shown a continual steady increase for decades. As cycling becomes more and more popular, a commensurate increase in cycling accidents and fatalities has also occurred. Regardless of current safety interventions employed hundreds of cyclist fatalities and tens of thousands of cyclist injuries are recorded/reported annually. Cycling accidents are estimated to cost billions of dollars in damages, medical expenses, lost wages, and insurance. The current body of literature may not comprehensively take into account important factors associated with unsafe cycling behaviors and resulting cycling safety efforts may be predicated on this incomplete information. Thus, my doctoral research focuses on investigating cognitive drivers of unsafe cycling behaviors through multiple studies. Study 1 was a systematic review of the current unsafe cycling behavior literature utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. Emergent themes from this review were incomplete representations of actual behaviors, shortcomings associated with the various methodological approaches employed, and scant understanding of why cyclists choose to ride unsafely. Study 2 utilized an observational approach to identify actual rates of unsafe cycling behaviors across different infrastructure design characteristics. Accident data in conjunction with laws governing cyclists drove the selection of behaviors observed (e.g., failing to stop at a stop light or making an illegal turn), and infrastructure design characteristics (e.g., enhanced pedestrian walkway or staggered t-intersection) were identified via established parameters according to the Department of Transportation. High rates of unsafe behaviors were consistently seen across locations including, for example, failing to stop at a stop light and failing to yield to traffic. Significant differences across locations were, for instance, making an illegal turn and riding in an unauthorized area. Study 3 employed questionnaires to quantitatively examine several cognitive drivers of unsafe cycling behaviors. Factors that impact cyclists’ decisions to ride unsafely, as well as unsafe behavioral outcomes, were analyzed using Analytic Hierarchy Process and Policy Capturing methodologies. Results indicated which factors were significant (e.g., if the cyclist is running late or has ample time to reach their destination) and which were not (e.g., the presence or lack of a dedicated bicycle path) within the decision making process to ride unsafely. Finally, the overall results of the studies were synthesized into a policy statement outlining major findings and recommendations to inform future legal, civil, and academic endeavors associated with cycling safety interventions

The interrelationships between speed limits, geometry, and driver behavior: a proof-of-concept study utilizing naturalistic driving data

Speed management has been an extensive focus of traffic safety research dating back to the 1960\u27s. Research has generally shown crash risk to increase as the average speed of traffic increases and as the standard deviation of travel speeds increases within a traffic stream. However, research as to the effects of speed limits has been somewhat inconclusive. This study investigates how speed limits affect driver speed selection, as well as the resultant crash risk, while controlling for various confounding factors such as traffic volumes and roadway geometry. Data are obtained at very high resolution from a Naturalistic Driving Study (NDS) conducted as a part of the second Strategic Highway Research Program (SHRP 2). These data are integrated with a Roadway Information Database (RID), which provides extensive details as to roadway characteristics in the six-state study area (Florida, Indiana, New York, North Carolina, Pennsylvania, and Washington.) These sources are used to examine how driver speed selection varies among freeways with different posted speed limits, and how the likelihood of crash/near-crash events change with respect to various speed metrics. Regression models are estimated to assess three measures of interest: the average speed of vehicles during the time preceding crash, near-crash, and baseline (i.e., normal) driving events; the variation in travel speeds leading up to each event as quantified by the standard deviation in speeds over this period (i.e. the average acceleration/deceleration rate); and the probability of a specific event resulting in a crash or near-crash based on speed selection and other salient factors. Significant correlation was observed with respect to speed selection behavior among the same individuals and particularly within a single driving event. Mean speeds are shown to increase with speed limits. However, these increases are less pronounced at higher speed limits. Drivers tend to reduce their travel speeds along horizontal or vertical curves, under adverse weather conditions, and particularly under heavy congestion. Increases in average travel speed and the variability in travel speeds are both found to increase crash risk. Crash risk also increases on vertical curves and ramp junctions, as well as among the youngest and oldest age groups of drivers. Ultimately, this research provides an important demonstration of how naturalistic driving data may be leveraged to examine driver behavior and research questions of interest that are difficult or impractical through other empirical settings. The results also provide important insights that provide greater understanding of how drivers adapt their speed selection behavior in response to posted speed limits and other roadway characteristics

Advancing the Age of Cycling

In the Netherlands, the number of older cyclists is increasing. This is desirable because cycling supports healthy ageing and personal independence. Older cyclists, however, run relatively large risks on (single) bicycle crashes. The goal of this thesis is to explore which parts of the infrastructure and (on-road) interactions lead to problems for older cyclists and, thereafter, to test the effectiveness of infrastructural and on-bicycle interventions to increase safety. ‘Everyday cycling’ observations of older cyclists revealed that obstacles, irregular surfaces, sharp corners, slopes, and narrow paths may cause difficulties. Some cyclists were also observed to (unintentionally) ride into the verge. Predicting the behaviour of other cyclists was also found to be difficult. At different locations, the effects of virtual 3D-objects, edge lines, slanted kerbstones, shoulder strips, and edge strips on cycling behaviour of older cyclists were measured. With small GPS action-cameras mounted on older participant’s bicycles, on-site experiments revealed that shoulder strips and edge strips were the most beneficial interventions for safety: at cycle paths with these modifications, participants rode further away from the soft verge compared to other (control) paths. They also cycled slower on the cycle paths with shoulder strips. Lastly, effects of using bicycle lights to communicate speed, braking, and turning intentions to other road users were investigated. The results showed that the tested speed signal was not effective. The turning indicator and brake light, however, seem useful for older cyclists

Right-Hook Crash Scenario: Effects of Environmental Factors on Driver\u27s Visual Attention and Crash Risk

A right-hook (RH) crash is a common type of bicycle–motor vehicle crash that occurs between a right-turning vehicle and through-moving bicycle at an intersection in right-hand driving countries. Despite the frequency and severity of this crash type, no significant driver-performance based evidence of the causes of RH crashes at signalized intersections was found in the literature. This study examined the driver’s visual attention in a right-turning scenario at signalized intersections with bicycle lanes but no exclusive right-turning lanes while interacting with a bicyclist to develop an understanding of RH crash causality. Fifty-one participants in 21 simulated road scenarios performed a right-turning maneuver at a signalized intersection while conflicting with traffic, pedestrians, and bicyclists. Overall, a total of 820 (41 × 20) observable right-turn maneuvers with visual attention data were analyzed. The results show that in the presence of conflicting oncoming left-turning vehicular traffic, drivers spent less visual attention on the approaching bicyclist, thus, making them less likely to be detected by the driver. The presence of oncoming left-turning traffic and the bicyclist’s speed and relative position, and conflicting pedestrians were found likely to increase the risk of RH crashes. The results of the current study will help identify effective crash mitigation strategies that may include improving the vehicle–human interface or the implementation of design treatments in the road environment to improve driver and bicyclist performance

Cycling with low vision

In the Netherlands, cycling is important for independent mobility and social participation: many people cycle on a daily basis, for example to go to school, work or to do shopping. But what if you have impaired vision, can you still cycle independently and safely?It is known that there are people with severe (permanent) limitations of visual acuity or visual field who cycle independently. But there are also people with less severe visual function limitations who ceased cycling. The severity of the vision limitation is not always decisive for one’s bicycle use: additional circumstances also play a role. This project aimed to provide insight into these circumstances, the difficulties experienced by visually impaired cyclists, and how they adjust their behaviour to enable themselves to cycle. Better knowledge on this topic could support other visually impaired people who wish to cycle, which could further optimise their mobility.This project shows that not only environmental circumstances (including infrastructure and traffic situation) but also self-confidence are important for the bicycle use. Difficulties experienced by many visually impaired cyclists are related to: light-dark transitions, crossing intersections without traffic lights, and the bad visibility of others. Visually impaired cyclists maintain a lower speed more frequently than their normally sighted peers, possibly to process visual information. There are no indications that visually impaired take different, safer routes. A more general finding is that guidelines for independent cycling should not be based solely on the nature or severity of the visual function limitation as this would unnecessarily exclude too many visually impaired people from cycling