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With the steadily increasing pedestrian fatalities, pedestrian safety is a growing concern, especially in urban environments. Advanced Driver Assistance Systems (ADAS) have been developed to mitigate road user risks by predicting potential pedestrian crossings and issuing timely driver alerts. However, there is limited understanding of how drivers respond to different modalities of alerts, particularly in the presence of false alarms. In this study, we utilized a full-scale driving simulator to compare the effectiveness of different alert modalities, audio-visual (AV), visual-tactile (VT), and audio-visual-tactile (AVT), in alerting drivers to various pedestrian jaywalking events. Our findings reveal that, compared to no alerts, multimodal alerts significantly increased the number of vehicles stopped for pedestrians and the distance to pedestrians when stopped. However, the false alarms negatively impacted driver trust, with some drivers exhibiting excessive caution, alert fatigue and anxiety, even including one instance where a driver fully stopped when no pedestrian was present., Comment: 15 pages

Transportation Cyber-Physical Systems (T-CPS) are critical in improving traffic safety, reliability, and sustainability by integrating computing, communication, and control in transportation systems. The connected vehicle corridor is at the forefront of this transformation, where Cellular Vehicle-to-Everything (C-V2X) technology facilitates real-time data exchange between infrastructure, vehicles, and road users. However, challenges remain in processing and synchronizing the vast V2X data from vehicles and roadside units, particularly when ensuring scalability, data integrity, and operational resilience. This paper presents a digital twin framework for T-CPS, developed from a real-world connected vehicle corridor to address these challenges. By leveraging C-V2X technology and real-time data from infrastructure, vehicles, and road users, the digital twin accurately replicates vehicle behaviors, signal phases, and traffic patterns within the CARLA simulation environment. This framework demonstrates high fidelity between physical and digital systems and ensures robust synchronization of vehicle trajectories and signal phases through extensive experiments. Moreover, the digital twin's scalable and redundant architecture enhances data integrity, making it capable of supporting future large-scale C-V2X deployments. The digital twin is a vital tool in T-CPS, enabling real-time traffic monitoring, prediction, and optimization to enhance the reliability and safety of transportation systems.

Tribal lands in the United States have consistently exhibited higher crash rates and injury severities compared to other regions. To address this issue, effective data-driven safety analysis methods are essential for resource allocation and tribal safety program development. This study outlines the minimum data requirements and presents a generic tribal crash dashboard prototype to enable feasible and reproducible tribal crash analysis. The dashboard offers statistical performance measurement techniques, tracks tribal safety trends using various indicators, and updates in with incoming data, making it adaptable for any state. Specifically, the dashboard's capabilities are showcased using Wisconsin tribal crash data, locating high-risk tribal land areas while analyzing and comparing statewide crashes and tribal crashes based on severity. The results reveal that tribal land roads, particularly rural ones, are more dangerous than those in other Wisconsin areas. The dashboard also examines crash types to uncover the causes and insights behind Wisconsin tribal crashes. Demonstrating this dashboard concept reveals its potential to facilitate a more intuitive understanding of tribal crashes from a statistical standpoint, thereby enabling more effective applications of available data sources and the development of targeted safety countermeasures.

An accurate and robust localization system is crucial for autonomous vehicles (AVs) to enable safe driving in urban scenes. While existing global navigation satellite system (GNSS)-based methods are effective at locating vehicles in open-sky regions, achieving high-accuracy positioning in urban canyons such as lower layers of multi-layer bridges, streets beside tall buildings, tunnels, etc., remains a challenge. In this paper, we investigate the potential of cellular-vehicle-to-everything (C-V2X) wireless communications in improving the localization performance of AVs under GNSS-denied environments. Specifically, we propose the first roadside unit (RSU)-enabled cooperative localization framework, namely CV2X-LOCA, that only uses C-V2X channel state information to achieve lane-level positioning accuracy. CV2X-LOCA consists of four key parts: data processing module, coarse positioning module, environment parameter correcting module, and vehicle trajectory filtering module. These modules jointly handle challenges present in dynamic C-V2X networks. Extensive simulation and field experiments show that CV2X-LOCA achieves state-of-the-art performance for vehicle localization even under noisy conditions with high-speed movement and sparse RSUs coverage environments. The study results also provide insights into future investment decisions for transportation agencies regarding deploying RSUs cost-effectively.

Crash sequence analysis has been shown in prior studies to be useful for characterizing crashes and identifying safety countermeasures. Sequence analysis is highly domain-specific, but its various techniques have not been evaluated for adaptation to crash sequences. This paper evaluates the impact of encoding and dissimilarity measures on crash sequence analysis and clustering. Sequence data of interstate highway, single-vehicle crashes in the United States, from 2016-2018, were studied. Two encoding schemes and five optimal matching based dissimilarity measures were compared by evaluating the sequence clustering results. The five dissimilarity measures were categorized into two groups based on correlations between dissimilarity matrices. The optimal dissimilarity measure and encoding scheme were identified based on the agreements with a benchmark crash categorization. The transition-rate-based, localized optimal matching dissimilarity and consolidated encoding scheme had the highest agreement with the benchmark. Evaluation results indicate that the selection of dissimilarity measure and encoding scheme determines the results of sequence clustering and crash characterization. A dissimilarity measure that considers the relationships between events and domain context tends to perform well in crash sequence clustering. An encoding scheme that consolidates similar events naturally takes domain context into consideration.

Previous studies have found correlations between the implementation of transit signal priority (TSP) and the reduction in number of crashes. To further understand how TSP affects traffic safety, a more in-depth evaluation was carried out using detailed bus automatic vehicle location (AVL) data. The data was from Minneapolis-Saint Paul Metro Transit Bus Route 5, where TSP was implemented at 30 signalized intersections in early 2019. A surrogate safety measure, bus speed volatility (BSV), was used to estimate the safety effects of TSP, with a higher BSV indicating more safety risks. A regression analysis was carried out on 23,123 event-level observations, with event defined as a bus traversal of a TSP-equipped intersection. Results indicate that with a TSP request, BSV was significantly lower than without a TSP request, confirming the effectiveness of TSP in smoothing bus trips through intersections, thus reducing risks of bus collisions and passenger fall-overs.

This paper develops a test scenario specification procedure using crash sequence analysis and Bayesian network modeling. Intersection two-vehicle crash data was obtained from the 2016 to 2018 National Highway Traffic Safety Administration Crash Report Sampling System database. Vehicles involved in the crashes are specifically renumbered based on their initial positions and trajectories. Crash sequences are encoded to include detailed pre-crash events and concise collision events. Based on sequence patterns, the crashes are characterized as 55 types. A Bayesian network model is developed to depict the interrelationships among crash sequence types, crash outcomes, human factors, and environmental conditions. Scenarios are specified by querying the Bayesian network conditional probability tables. Distributions of operational design domain attributes - such as driver behavior, weather, lighting condition, intersection geometry, traffic control device - are specified based on conditions of sequence types. Also, distribution of sequence types is specified on specific crash outcomes or combinations of operational design domain attributes.

Previous surveys of public attitudes toward automated vehicle (AV) and transit integration primarily took place in large urban areas. AV-transit integration also has a great potential in small urban areas. A survey of public attitudes towards AV-transit integration was carried out in two small urban areas in Wisconsin, United States. A total of 266 finished responses were analyzed using text mining, factor analysis, and regression analysis. Results showed that respondents knew about AVs and driving assistance technologies. Respondents welcome AV-transit integration but were unsure about its potential impacts. Technology-savvy respondents were more positive but had more concerns about AV-transit integration than others. Respondents who enjoyed driving were not necessarily against transit, as they were more positive about AV-transit integration and were more willing to use automated buses than those who did not enjoy driving as much. Transit users were more positive toward AV-transit integration than non-transit users.

With safety being one of the primary motivations for developing automated vehicles (AVs), extensive field and simulation tests are being carried out to ensure AVs can operate safely on roadways. Since 2014, the California DMV has been collecting AV collision and disengagement reports, which are valuable data sources for studying AV crash patterns. In this study, crash sequence data extracted from California AV collision reports were used to investigate patterns and how they may be used to develop AV test scenarios. Employing sequence analysis, this study evaluated 168 AV crashes (with AV in automatic driving mode before disengagement or collision) from 2015 to 2019. Analysis of subsequences showed that the most representative pattern in AV crashes was (collision following AV stop) type. Analysis of event transition showed that disengagement, as an event in 24 percent of all studied AV crash sequences, had a transition probability of 68 percent to an immediate collision. Cluster analysis characterized AV crash sequences into seven groups with distinctive crash dynamic features. Cross-tabulation analysis showed that sequence groups were significantly associated with variables measuring crash outcomes and describing environmental conditions. Crash sequences are useful for developing AV test scenarios. Based on the findings, a scenario-based AV safety testing framework was proposed with sequence of events embedded as a core component.

Transit signal priority (TSP) has been implemented to transit systems in many cities of the United States. In evaluating TSP systems, more attention has been given to its operational effects than to its safety effects. Existing studies assessing safety effects of TSP reported mixed results, indicating that the safety effects of TSP vary in different contexts. In this study, TSP implementations in Portland, Oregon, were assessed using interrupted time series analysis (ITSA) on month-to-month changes in number of crashes from January 1995 to December 2010. Single-group and controlled ITSA were conducted for all crashes, property-damage-only crashes, fatal and injury crashes, pedestrian-involved crashes, and bike-involved crashes. Evaluation of the post-intervention period (2003 to 2010) showed a reduction in all crashes on street sections with TSP (-4.5 percent), comparing with the counterfactual estimations based on the control group data. The reduction in property-damage-only crashes (-10.0 percent) contributed the most to the overall reduction. Fatal and injury crashes leveled out after TSP implementation but did not change significantly comparing with the control group. Pedestrian and bike-involved crashes were found to increase in the post-intervention period with TSP, comparing with the control group. Potential reasons to these TSP effects on traffic safety were discussed., Comment: Published in Accident Analysis & Prevention

Atomically thin two-dimensional (2D) materials are promising candidates for sub-10 nm transistor channels due to their ultrathin body thickness, which results in strong electrostatic gate control. Properly scaling a transistor technology requires reducing both the channel length (distance from source to drain) and the contact length (distance that source and drain interface with semiconducting channel). Contact length scaling remains an unresolved epidemic for transistor scaling, affecting devices from all semiconductors, from silicon to 2D materials. Here, we show that clean edge contacts to 2D MoS2 provide immunity to the contact-scaling problem, with performance that is independent of contact length down to the 20 nm regime. Using a directional ion beam, in situ edge contacts of various metal-MoS2 interfaces are studied. Characterization of the intricate edge interface using cross-sectional electron microscopy reveals distinct morphological effects on the MoS2 depending on its thickness, from monolayer to few-layer films. Chromium is found to outperform other metals in the edge contact scheme, which is attributed to the shorter Cr-MoS2 bond length. Compared to scaled top contacts with 20 nm contact length, in situ edge contacts yield better performance with an effective contact length of ~ 1 nm and 18 times higher carrier injection efficiency. The in situ edge contacts also exhibit ~8 times higher performance compared to the best-reported edge contacts. Our work provides experimental evidence for a solution to contact scaling in transistors, using 2D materials with clean edge contact interfaces, opening a new way of designing devices with 2D materials.

After the school bell rings, young people are learning, exploring, making and questioning. Afterschool programs have long influenced students' personal development and supported their social and emotional growth. Today, the afterschool field has enthusiastically embraced STEM as an integral part of their educational offerings. This handout presents highlights from the research paper "Examining the Impact of Afterschool STEM Programs". It is a useful tool in advocacy efforts to communicate the impact of afterschool STEM programs on youth. [For the full research paper, see ED546628.]

Video Job Shadows encourages students to develop questions about a job and offers them the chance to videotape a business person answering those questions about his or her job. The program can be an effective method of teaching high school students about the world of work and the specific requirements and responsibilities of some jobs in their community. This can also be an opportunity for students to learn the basics of videotaping and editing. The goals of this program are for students to develop and complete a Video Job Shadow of a business in their community, for students to become familiar with specific jobs, and for community business people to make a positive connection to the school and also to see the school valuing them and what they do. Specific instructions on how to set up the program and the resources that will be needed are given. The project is a practical way to connect school to the work environment. Connecting students to real-world jobs and these jobs requirements can affect students in ways that guest speakers and job fairs cannot. (RJM)

A study of 657 reviews of children's fiction, published in 1975 and 1976, revealed information to show that writers and publishers of children's fiction are moving close to equality in treatment of the sexes. It was concluded from the survey of books reviewed in "Bulletin of the Center for Children's Books" that female and male protagonists are appearing in nearly equal numbers, that they are displaying similar personality traits--with the exception of a larger representation of females with physical impairments than males, and that the number of female authors of fiction is increasing. (Author)

If students are to be responsible in significant ways for their own learning, teachers must develop the ability to move from directive teaching behaviors to supportive ones. This paper examines a teacher-behavior model, presented in a book by Muska Mosston, that includes a spectrum of seven teaching styles, ranging from total teacher direction through total student direction. It then reports on a pilot study that attempted to program a teacher through these variations in teaching style by improvising on Mosston's model, and it comments on findings that indicate which steps are crucial in the transition from teacher direction to student direction. The paper shows how a teacher may structure a series of lessons based on the American folklore collections of Alvin Schwartz in such a way that students may move toward independence in learning. Guidelines for structuring the lessons are provided, along with lists of folklore resources that may be used. (GW)

The Enrichment Triad Model, developed by Joseph Renzulli, interrelates three kinds of learning activities to match student interests and preferred learning styles to experiences outside the regular curriculum. Two of the learning activities are appropriate for all learners, while the third is especially suitable for students capable of superior performance in a particular area. General exploratory activities provide students with experiences extending from the regular curriculum to stimulate involvement at higher levels. Activities of this type might include field trips, exposure to resource people, and library browsing. Activities in the second prong of the triad model are group training activities that expand the thinking and feeling processes of children, equipping them with skills for dealing with new problems. Examples of these activities are training exercises in the techniques of critical and creative thinking, inquiry training, and values clarification. Type three enrichment activities are individual investigations of real problems that involve the learners in areas of their own choice. (RL)

Working with a sample of third-grade students, researchers compared two sentence-modeling curricula: one focusing exclusively on writing and the other, the Integrated Sentence-Modeling Curriculum (ISMC), combining language arts areas. Designed for elementary school students, the ISMC introduces children to complex syntactic structures by involving them in listening, speaking, writing, and reading activities. (RH)