National Highway Traffic Safety Administration

To mitigate the "black-and-white tunnel" phenomenon and associated traffic safety hazards at highway tunnel entrances, this study proposes an intelligent control system integrating PLC and anti-halo technology. The research begins with illumination data collection and analysis at tunnel entrances, confirming the existence of the "black-and-white tunnel" effect. Specifically, daytime tunnel entrances exhibit a sharp increase in illumination (black hole effect), while nighttime entrances show a dramatic decrease (white hole effect). Both conditions significantly impair driver visibility and pose substantial safety risks. The implementation of the PLC and anti-halo intelligent control system effectively mitigates these illumination variations during both day and night, thereby reducing visual strain on drivers. This validation demonstrates the effectiveness of the proposed solution, which holds significant practical implications for road safety.

Disruptions in urban rail transit (URT) systems can significantly impact operational efficiency, while well-designed bus bridging service (BBS) can effectively mitigate such effects. To address the surge in travel demand caused by disruptions, this study comprehensively considers alternative transportation modes that affected passengers may adopt (including taxis, shared bicycles, bridging buses, and walking), aiming to minimize both the operational costs of bridging buses and the total travel time of passengers. A travel choice model based on the random regret minimization (RRM) theory is developed to characterize passengers’ decision-making behavior following station disruptions. Demand uncertainty is represented using trapezoidal fuzzy variables, and a distributionally robust credibility optimization model is established. An innovative reinforcement learning-based parallel genetic algorithm (RPGA) is proposed for solving the model. A case study of a bidirectional disruption during the 08:00–10:00 on the section of Xi’an Metro Line 2 demonstrates that: (1) The proposed model exhibits stronger robustness under demand uncertainty, achieving a reduction of 3 dispatched vehicles and a cost saving of 9,439 RMB by moderately increasing passenger costs by 850 RMB and extending bridging time; (2) The RPGA algorithm outperforms Non-dominated Sorting Genetic Algorithm II (NSGA-II), Reinforcement Learning-based NSGA-II (RLNSGA-II), and Multi-objective Particle Swarm Optimization Algorithm (MOPSO) in hypervolume (HV), generational distance (GD), and non-dominated ratio (NDR); (3) Increasing the rated passenger capacity within a certain range can reduce average passenger delays but correspondingly raises transportation costs. This method effectively enhances the system’s ability to cope with demand fluctuations and provides decision-making support for emergency scheduling in urban rail transit.

Regional disparities in road infrastructure access in Kenya hinder socioeconomic development and challenge progress toward the Vision 2030 goals. This study addresses spatial inequality in transport provision by developing a transport network need index (TNNI) based on socioeconomic indicators and comparing it with existing road network density, termed transport network provision (TNP). The difference between TNNI and TNP yields the index of disparity between needs and provision (IDNP), identifying counties that are over- or under-served relative to their development needs. Machine learning models are employed to predict road density based on socioeconomic features, with the best-performing model selected through accuracy metrics. Shapley additive explanations (SHAP) are used to interpret the model and determine the empirical importance of each input feature. These SHAP-based weights are compared with literature-based weights used in TNNI to assess disparities in factor prioritization. Results highlight critical spatial disparities, with counties such as Turkana, Wajir, and Mandera falling into the most under-served category (IDNP >0.8). SHAP analysis reveals that population density is the dominant driver of current road provision (56.8% weight), while poverty and unemployment, despite their policy relevance, are underrepresented in actual infrastructure allocation. This twofold analysis—identifying both regional service gaps through IDNP and mismatches in factor prioritization—provides critical insights for policymakers. By pinpointing under-served regions and highlighting which socioeconomic drivers are being overlooked, the study offers a robust, data-driven framework for guiding equitable infrastructure investments, advancing transport justice, and supporting diversity and inclusion in Kenya’s road transport planning.

The vibratory roller’s compaction in the initial and middle stages is crucial for transforming loose subgrade filler particles into a dense state. The subgrade shows nonlinear characteristics of large and small plastic deformation. To describe these nonlinear characteristics, a new nonlinear model of vibratory roller-soil coupling is proposed. Initially, a two-degree-of-freedom model of the vibrating roller-subgrade system is established, considering the subgrade’s vibration. A small parameter is introduced to improve the elastic element of the frame shock absorber and the subgrade’s nonlinear hysteresis model. The analytical solution of the proposed nonlinear dynamic equation is solved and verified by the numerical solution. Subsequently, the vibrating wheel’s nonlinear dynamic responses are studied, including time-frequency domain, Poincare section, and bifurcation diagrams. It is found that during the initial stage, increasing excitation frequency or decreasing excitation force causes the vibrating wheel’s response to shift from “double period” to “single period.” In the middle stage, the vibrating wheel’s motion exhibits three states: “chaos,” “double period,” and “single period.” These nonlinear vibration response characteristics provide a theoretical foundation for selecting intelligent compaction parameters.

<div class="section abstract"><div class="htmlview paragraph">The Large Omnidirectional Child (LODC) developed by the National Highway Traffic Safety Administration (NHTSA) has an improved biofidelity over the currently available Hybrid III 10-year-old (HIII-10C) Anthropomorphic Test Device (ATD). The LODC design incorporates enhancements to many body region subassemblies, including a redesigned HIII-10C head with pediatric mass properties, and the neck, which produces head lag with Z-axis rotation at the atlanto-occipital joint, replicating the observations made from human specimens. The LODC also features a flexible thoracic spine, a multi-point thoracic deflection measurement system, skeletal anthropometry that simulates a child's sitting posture, and an abdomen that can measure belt loading directly. This study presents the development and validation of a dynamic nonlinear finite element model of the complete LODC dummy. Based on the three-dimensional CAD model, Hypermesh was used to generate a mesh of the finite element (FE) LODC model. LS-PrePost was used to specify the material parameters, contact definitions, and initial conditions and then converted to LS-DYNA solver input format. A detailed description of the assemblies of the LODC dummy and their finite element representation is given. Component-level qualification test procedures were simulated using the LODC FE model, replicating the experimental test setups and boundary conditions for the head, neck, thorax, abdomen, and spine. Each component test provides a physical response that is used to calibrate the model's strain-rate-dependent viscoelastic material properties and other characteristics using an inverse method that minimizes the divergence between measured and predicted data. CORrelation and Analysis (CORA) ratings are provided between the simulation and experimental curves. Finally, a system-level sled test was modeled with the dummy upright on a sled bench for validation.</div></div>

Objective The history of airbags for occupant protection in frontal crashes is reviewed from the perspective of a former Senior Executive at NHTSA from the early 1970’s to the late 1980’s. This paper summarizes the factors that led to regulatory delays as well as those that led to voluntary adoption of airbags by several manufacturers. Methods The regulatory history and interactions with airbag suppliers and vehicle manufactures is recounted citing key steps in the evolution of frontal airbags. Results When the Advanced Notice of Proposed Rulemaking for Standard 208, “Occupant Protection” was issued on July 2, 1969 the Safety Agency anticipated that the industry response would provide automatic frontal crash protection from airbags that deployed to protect all front seat occupants from injury in severe frontal crashes. It was not until, September 1, 1998 that airbags were required in all cars and light trucks. The interim 29 years involved a series of stops and starts during which most of the original airbag suppliers lost interest and abandoned the airbag market. The issues associated with airbags and their place in Standard 208 were directly influenced by interventions from the President, the Congress, the Supreme Court, Secretaries of Transportation, NHTSA Administrators, the Presidents of US Auto Companies and Senior Executives of Insurance Companies. Conclusion In 1966, there was support from the US auto industry for a single source of safety regulations that apply to new vehicles sold in the US. This is evidenced by the unanimous passage by the House of Representatives and Senate of the Law that created the Federal auto safety regulatory framework. The Law also required seatbelts in new cars and prohibited States from making separate safety rules. However, the large safety benefits offered by seatbelts were negated because they were rarely used. Consequently, finding ways of providing high levels of protection without requiring action by occupants became a goal of the new Safety Agency. The airbag offered the possibility of achieving that goal. From the initial airbag notice of proposed rulemaking on July 2, 1969, Safety Agency required 2 years to resolve objections before a final Standard 208 could be issued (on July 8,1971). The subsequent industry opposition to the Standard 208 employed Presidential influence and Court suits to cause a 5½ year delay until the Coleman Decision on December 6, 1976. Changes in regulatory approach of the Ford, Carter, and Reagan Administrations and associated Court suits caused another 7½ year delay until the Dole Decision on July 17, 1984. It required another 7 ½, until December 18, 1991, for market forces to reduce industry opposition to airbags and permit Congress to pass a law that mandated them. Another 6½ years of lead time was required before all cars and light trucks were required to meet the airbag standard. During the mid and late 1980’s vehicle safety ratings, seatbelt use laws, and Vince and Larry PSA’s had all acted to increase safety awareness and safety belt use. Consequently, added public demand for vehicle safety features slowly developed. Changes in economic incentives encouraged a number of vehicle lines to install driver airbags as standard equipment and the feature was being widely advertised by Chrysler. This combination of events made it possible for Congress to pass and President Bush 41 to sign legislation requiring airbags in cars and light trucks by September 1, 1998 – more than 29 years after the initial rulemaking notice in 1969.