A Situation-Aware Collision Avoidance Strategy for Car-Following

In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy

Assessing the Impact of Game Day Schedule and Opponents on Travel Patterns and Route Choice using Big Data Analytics

The transportation system is crucial for transferring people and goods from point A to point B. However, its reliability can be decreased by unanticipated congestion resulting from planned special events. For example, sporting events collect large crowds of people at specific venues on game days and disrupt normal traffic patterns. The goal of this study was to understand issues related to road traffic management during major sporting events by using widely available INRIX data to compare travel patterns and behaviors on game days against those on normal days. A comprehensive analysis was conducted on the impact of all Nebraska Cornhuskers football games over five years on traffic congestion on five major routes in Nebraska. We attempted to identify hotspots, the unusually high-risk zones in a spatiotemporal space containing traffic congestion that occur on almost all game days. For hotspot detection, we utilized a method called Multi-EigenSpot, which is able to detect multiple hotspots in a spatiotemporal space. With this algorithm, we were able to detect traffic hotspot clusters on the five chosen routes in Nebraska. After detecting the hotspots, we identified the factors affecting the sizes of hotspots and other parameters. The start time of the game and the Cornhuskers’ opponent for a given game are two important factors affecting the number of people coming to Lincoln, Nebraska, on game days. Finally, the Dynamic Bayesian Networks (DBN) approach was applied to forecast the start times and locations of hotspot clusters in 2018 with a weighted mean absolute percentage error (WMAPE) of 13.8%

Road network equilibrium approaches to environmental sustainability

Environmental sustainability is closely related to transportation, especially to the road network, because vehicle emissions and noise damage the environment and have adverse effects on human health. It is, therefore, important to take their effect into account when designing and managing road networks. Road network equilibrium approaches have been used to estimate this impact and to design and manage road networks accordingly. However, no comprehensive review has summarized the applications of these approaches to the design and management of road networks that explicitly address environmental concerns. More importantly, it is necessary to identify this gap in the literature so that future research can improve the existing methodologies. Hence, this paper summarizes these applications and identifies potential future research directions in terms of theories, modelling approaches, algorithms, analyses, and applications.postprin

The second-phase development of the China JinPing underground Laboratory

During 2013-2015 an expansion of the China JinPing underground Laboratory (CJPL) will be undertaken along a main branch of a bypass tunnel in the JinPing tunnel complex. This second phase of CJPL will increase laboratory space to approximately 96,000 m^3, which can be compared to the existing CJPL-I volume of 4,000 m^3. One design configuration has eight additional hall spaces, each over 60 m long and approximately 12 m in width, with overburdens of about 2.4 km of rock, oriented parallel to and away from the main water transport and auto traffic tunnels. Concurrent with the excavation activities, planning is underway for dark matter and other rare-event detectors, as well as for geophysics/engineering and other coupled multi-disciplinary sensors. In the town meeting on 8 September, 2013 at Asilomar, CA, associated with the 13th International Conference on Topics in Astroparticle and Underground Physics (TAUP), presentations and panel discussions addressed plans for one-ton expansions of the current CJPL germanium detector array of the China Darkmatter EXperiment (CDEX) collaboration and of the duel-phase xenon detector of the Panda-X collaboration, as well as possible new detector initiatives for dark matter studies, low-energy solar neutrino detection, neutrinoless double beta searches, and geoneutrinos. JinPing was also discussed as a site for a low-energy nuclear astrophysics accelerator. Geophysics/engineering opportunities include acoustic and micro-seismic monitoring of rock bursts during and after excavation, coupled-process in situ measurements, local, regional, and global monitoring of seismically induced radon emission, and electromagnetic signals.Comment: 9 pages, 3 figures. 13th International Conference on Topics in Astroparticle and Underground Physics, TAUP 201

Uncertainty propagation from the cell transmission traffic flow model to emission predictions: a data-driven approach

Road traffic exhaust emission predictions are used to inform transport policy and investment decisions aimed at reducing emissions and achieving sustainable mobility. Emission predictions are also used as inputs when modeling air quality and human exposure to traffic-related air pollutants. To be effective, such policies and/or integration must be based on robust models that not only provide point-based predictions but also inform these with an interval of confidence that properly accounts for the propagation of uncertainties through the complex chain of models involved. This paper develops a data-driven methodological framework that enables calculating the uncertainty in average speed–based emission predictions induced by uncertainty in its traffic data inputs, which are most often predictions (or outputs) of traffic flow models. An ensemble-based optimisation approach is used to estimate both calibration and validation errors arising from uncertainty in the structure and parameterisation of the cell transmission model, a discretised first-order macroscopic traffic flow model that is often integrated with average speed–based emission models. A Monte Carlo sampling approach is proposed to propagate the uncertainty in traffic flow inputs to emission predictions. To ensure transferability of findings, this methodology has been tested using multiple real data sets on three motorway road networks, one of which operates under variable speed limits

Intelligent flight control systems

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms