Background. Over the years, between 2013 and 2017, accidents between HeavyGoods Vehicles and Pedestrians have come to increase. Leading causes stem frominattentiveness and lack of communication between driver and pedestrians. Withthe advent of Autonomous vehicles, set to be able to reduce accidents, uncertainties in how communication and trust between humans and machines will be formed re-mains. Objectives. The research aim has been to understand the difficulties and problemssurrounding heavy vehicles, and the problems that today’s heavy vehicle operators faces, from which a technical solution that addressees the uncovered needs, is devel-oped. Methods. Design Research Methodology and MSPI Innovation Process has beenused in combination for acquiring and validating information around the problem.Shadowing sessions, unstructured interviews has been used for acquiring information.Literature reviews have been done to find academic validation in hypotheses statedthroughout the research. From the information gathered, iterative prototypes havebeen built. Results. From the needfinding that was conducted, safety around trucks was thefield on which the scope of the research was focused around. Due the larger size oftruck, decision-making through eye contact and intention determining is set to beharder when dealing with heavy vehicles, leading to an uncertainty around heavyvehicles residing with pedestrians in how to act around these. With the operatorsof these vehicles finding the unpredictable nature of pedestrians and cyclist in trafficto be troublesome and safety imposing, the research aim was set around addressing these needs. A communication console was developed, that is able to communi-cate safety-critical information between heavy vehicle operators and vulnerable road users, as means of reducing front collisions between said parts. Conclusions. The console has been developed through iterative prototyping andtesting, with design requirements being acquired through learnings and feedbackgathered from each iteration. The resulting communication console being presentedis able to share critical information being sought by pedestrians for decision-making,primarily that of eye contact and intentions of oncoming vehicles. The system servesas a proof of concept, that could through extensive traffic safety testing, help reducefront collisions between Heavy Goods Vehicles and Vulnerable Road Users, as well as, through further development, become the central communication console for au-tonomous vehicles to ensure partnership and intuitive communication between these and the surroundings.

<p>  </p> <p>Historically, agencies have been reliant on physical infrastructure, crash data, manual data collection, and modeling to evaluate their road networks. Over the past several years, enhanced probe data has become commercially available and has shown itself to be a relatively inexpensive and scalable way to evaluate the performance of road networks. In January 2022 alone, 11.3 billion passenger vehicle trajectory waypoints and 279 million passenger vehicle event records were logged in the state of Indiana. This data, typically segmented into vehicle trajectory waypoints and vehicle event records, contains a variety of information including, but not limited to, location, speed, heading, and timestamp. </p> <p>One use for this enhanced probe data is the evaluation of traffic signals for safety improvements. Typically, agencies require 3 – 5 years of crash data to be able to statistically identify intersections in need of safety improvements. This study compared crash data over a 4.5-year period at 8 signalized intersections to one month of weekday hard-braking and hard-acceleration data from July 2019. A Spearman’s rank-order correlation test was used, and a strong to very strong correlation between event data and crashes could be found indicating that just one month of event data could be an adequate substitute for 3 – 5 years of crash data. </p> <p>The representativeness of this data is often a major concern for many agencies as the usefulness of the data is only as good as the data itself. This paper describes and demonstrates a methodology for measuring connected vehicle penetration using data provided by state highway performance monitoring stations. This study looked at 1.7 billion count station vehicle counts and 70 million connected vehicle records across 381 count stations in 11 different states (California, Connecticut, Georgia, Indiana, Minnesota, North Carolina, Ohio, Pennsylvania, Texas, Utah, and Wisconsin). Across the 11 states and 381 stations, the average percent penetration was 3.8% in August 2020 and 3.9% in August 2021. Drilling down to August 2021, the percent penetration observed among the 187 interstate stations varied from 1.6% in Indiana to 10.0% in Wisconsin. A similar comparison of 162 non-interstate count stations showed a variation of 2.1% in MN and 18.0% in WI on non-interstates. </p>

Aggressive driving is a phenomenon that has taken on tremendous significance in society. While the issue has been studied from perspectives of several disciplines, relatively few comprehensive empirical investigations have been conducted. This may be due, at least in part, to a scarcity of comprehensive theoretical works in the field, from which methodical research hypotheses could be derived. This paper reviews major extant theories of general aggression to offer a rationale for choosing a particular framework to apply to the topic of aggressive driving. The social-cognitive model of aggressive driving is recommended, as it takes into account wide-ranging cognitive, situational, and dispositional factors. Implications for future research are also considered.

Street layout and design, once established, are then not easily changed. Urban form affects community development, livability, sustainability, and traffic safety. There has been an assumed relationship between urban form and traffic safety that favors designs with less through streets to improve safety. An empirical study to test this assumed relationship was carried out for crash data for Portland, Oregon. This thesis presents an empirical methodology for analyzing the relationship between urban form and traffic safety utilizing a uniform grid for the spatial unit. Crashes in the Portland, Oregon city limits from 2005-2007 were analyzed and modeled using negative binomial regression to study the effect of urban form and street layout through factors on exposure, connectivity, transit accessibility, demographic factors, and origins and destinations. These relationships were modeled separately by mode: vehicle crashes, pedestrian and bicycle crashes. Models were also developed separately by crash type and by crash injury severity. The models found that urban form factors of street connectivity and intersection density were not significant at 95% confidence for vehicle and pedestrian crash rates, nor for different crash severity levels, indicating that high connectivity grid street layout may have comparable safety to loops and lollipops, in contrast to results in earlier studies. Elasticity for all models was dominated by VMT increases. Business density, population and transit stops were also significant factors in many models, underlining the importance not only of street layout design, but also planning to direct development to influence where businesses, employment, and housing will grow and handle traffic volumes safely.

Indiana University-Purdue University Indianapolis (IUPUI) / With the increasing number of vehicles on the road and the amount of time people spend driving their vehicles, traffic control and management has become an important part within logistics. Effective traffic control would involve traffic signal control and control over vehicle movement. Since Petri nets are versatile enough to represent traffic signals and traffic flow, it has become an important tool in urban traffic control. Many traffic systems are modeled using hybrid Petri nets. Chapter 1 briefly talks about traffic management systems and previous related work in the area of traffic control. Chapter 2 is a basic background on various Petri nets used in the study. The section also uses examples to demonstrate the working of Petri nets. Chapter 3 introduces the need for optimization in various industry. And then, it discusses different steps involved in optimizing a process. Chapter 4 discusses the existing model of two one-way intersection. In an effort to understand the model better, simulations are also carried out. Then, drawbacks of the existing model are discussed. This paves way for a new, improved, and realistic version of two one-way intersection. Various optimization steps discussed in Chapter 3 is used to optimize traffic light of the improved model. And then, a comparison between existing model and improved model is carried out. Chapter 5 expands the study of traffic models by connecting two different one-way intersection through a road (thus making it a network). Optimization and simulation of the connected-intersection model is also carried out. Chapter 6 is the summary which will provide a brief overview about each chapter.

This diplom thesis deals with the analysis of existing state and prorosal to improve bicycle parking in the part of town Bohumín. Thesis also deals with evalution of critical section of cycling traffic in the Bohumín. It propose the optimalization of the existing state, or a complete change of it. The aim of the proposal is to improve the traffic situation in place e.g. to increase safety and driving comfort.

No description available.

Given that “driver error” is cited as a contributing factor in 93 percent of all crashes, understanding driver behavior is an essential element in mitigating the crash problem. Among the more dangerous roadway elements are unsignalized intersections where drivers’ gap acceptance behavior is strongly correlated to the operational and safety performance of the intersection. While a basic understanding of drivers’ gap acceptance behavior exists, several unanswered questions remain. Previous work has attempted to address some of these questions, however to date the research has been somewhat limited in scope and scale due to the challenges of collecting high fidelity gap acceptance data in the field. This research initiative utilized software newly developed for this project to collect gap acceptance data on 2,767 drivers at 60 sites, totaling 10,419 driver decisions and 22,639 gaps in traffic. This large-scale data collection effort allowed many of these remaining questions to be answered with an improved degree of certainty. This research initiative showed that naturalistic driver gap acceptance behavior can realistically be observed and accurately recorded in the field in real time using a newly developed software tool. This software tool and study methodology was validation using high fidelity video reduction techniques. This research compared different methods of analyzing gap acceptance data, in particular determining critical gap, seeing that the method used significantly affects the results. Conclusions were draw about the merits of each of the ten analysis methods considered. Through the analysis of the large data set collected, the research determined that there exist appreciable and identifiable differences in gap acceptance behavior across drivers under varied conditions. The greatest differences were seen in relationship to wait time and queue presence. If a driver has queued vehicles waiting behind them and/or has been waiting to turn for a long period of time, they will be more likely to accept a smaller gap in traffic. Additionally, an analysis of gap acceptance as it relates to crash experience identified critical situations where a driver's gap acceptance behavior contributes to the occurrence of a crash. Characteristics of the driver such as gender and approximate age associated with specific crashes were examined. Teen drivers were identified as exhibiting aggressive gap acceptance behavior and were found to be overrepresented in gap acceptance related crashes. Ultimately, a better understanding of the driver and environmental factors that significantly contribute to increased crash risk will help guide the way to targeted design solutions.

Arguably the greatest issue facing the transportation profession is the ability to provide social equity with regards to both safety and mobility given the aging population. Given the overall dominance of the automobile within the transportation system, the ability to provide feasible alternatives is daunting. This fact, when coupled with the well-documented challenges of older drivers, underscores the need for improved safety features and system-wide safety approaches with a focus on the older driver. This paper describes an application of spatial crash analysis and road safety investigations that were employed in Massachusetts with a direct focus on the older driver. Specifically, the paper outlines an approach for identifying high crash locations for older drivers and presents the results of older driver focused road safety investigations for selected locations. The research approach targets both intersections and roadway segments identifying locations where older drivers are overrepresented in crashes. The road safety investigations resulted in recommended countermeasures aimed at mitigating the older driver crash problem at the identified locations. Although the resulting countermeasures, which were based upon established literature such as the Older Driver Design Handbook, included a full spectrum of recommendations, a specific emphasis was placed upon short-term and low cost measures that could be readily employed. Techniques to identify relationships between high crash location identification methods and the recommended countermeasures for the identified locations are considered. Ultimately the application of these techniques may provide transportation professionals with a means to associate specific older driver focused countermeasures with the results of particular methods of high crash location identification.

Jährlich sterben weltweit 1,35 Millionen Menschen durch Verkehrsunfälle. Ob Cloud-Computing zu einer Reduzierung dieser Zahl beitragen wird, wird in der vorliegenden Arbeit untersucht. Zunächst werden Cloud-Anwendungen ermittelt, welche im Straßenverkehr verwendet werden und Einfluss auf die Straßenverkehrssicherheit haben. Anschließend wird deren genauer Einfluss auf die Straßenverkehrssicherheit durch die Betrachtung von Stu-dienergebnissen, Herstellerangaben sowie eigenen Kalkulationen untersucht. Zudem werden die Gefahren von Cyberangriffen und Netzausfällen für die ermittelten Anwendungen analysiert. Es folgt eine kritische Diskussion sowie die Zusammenfassung des Erarbeiteten: Cloud-Computing ermöglicht durch den einfachen, risikoarmen Zugang zu unlimitierten Rechenressourcen die Entwicklung und den Betrieb von Anwendungen, die Einfluss auf die Verkehrssicherheit nehmen. Es ist davon auszugehen, dass die Anwendungen bei einer weiter voranschreitenden Felddurchdringungsrate positiven Einfluss auf die Straßenverkehrssicherheit in Deutschland und anderen Industriestaaten nehmen und damit aktiv zur Reduzierung der Anzahl Verkehrstoter und -verletzter beitragen werden. Cloud-Computing wird somit ein indirekt positiver Einfluss auf die Straßenverkehrssicherheit zugeschrieben. / 1.35 million people die in traffic accidents worldwide every year. Whether cloud computing contributes to a reduction of this number is examined in the present work. First, cloud com-puting applications are identified, which are used in road traffic and have an impact on traffic safety. The exact influence on traffic safety is then examined by considering study results, manufacturer information and through own calculations. In addition, the dangers of cyber-attacks and network failures are examined in the context of the identified applications. This is followed by a critical discussion and a summary of what has been worked out: Cloud computing enables the development and operation of applications that affect traffic safety through simple, low-risk access to unlimited computing resources. It can be assumed that the applica-tions will have a positive influence on traffic safety in Germany and other industrialized countries and will thus actively contribute to reducing the number of deaths and injuries, given that the penetration rate is further increasing. Cloud computing is thus attributed an indirect positive influence on road safety.