357,133 research outputs found

    Longitudinal Dynamic versus Kinematic Models for Car-Following Control Using Deep Reinforcement Learning

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    The majority of current studies on autonomous vehicle control via deep reinforcement learning (DRL) utilize point-mass kinematic models, neglecting vehicle dynamics which includes acceleration delay and acceleration command dynamics. The acceleration delay, which results from sensing and actuation delays, results in delayed execution of the control inputs. The acceleration command dynamics dictates that the actual vehicle acceleration does not rise up to the desired command acceleration instantaneously due to dynamics. In this work, we investigate the feasibility of applying DRL controllers trained using vehicle kinematic models to more realistic driving control with vehicle dynamics. We consider a particular longitudinal car-following control, i.e., Adaptive Cruise Control (ACC), problem solved via DRL using a point-mass kinematic model. When such a controller is applied to car following with vehicle dynamics, we observe significantly degraded car-following performance. Therefore, we redesign the DRL framework to accommodate the acceleration delay and acceleration command dynamics by adding the delayed control inputs and the actual vehicle acceleration to the reinforcement learning environment state, respectively. The training results show that the redesigned DRL controller results in near-optimal control performance of car following with vehicle dynamics considered when compared with dynamic programming solutions.Comment: Accepted to 2019 IEEE Intelligent Transportation Systems Conferenc

    Effects of a Secretin Receptor Antagonist on Cerebellar Learning

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    Eyeblink conditioning (EBC) is an important procedure used to understand the neuronal plasticity that occurs with learning and memory. Delay EBC requires a brainstem-cerebellar circuit while the role of the cerebellum in trace EBC is not as well understood because it requires a more complex neural circuitry involving regions of the medial prefrontal cortex and hippocampus. Secretin is a neuropeptide that is found in high concentrations within the cerebellum. Previous work has shown that blocking secretin’s effects in the cerebellum with intra-cerebellar infusion of relatively large volume of a secretin receptor antagonist impairs delay EBC (Fuchs et al. 2014). Here we study the effect that intra-cerebellar infusion of 0.5 μL secretin receptor antagonist (5-27 secretin) or vehicle prior to training sessions 1 and 2 has on delay and trace EBC in rats. A 600-ms tone CS was used for the delay EBC paradigm and a 300-ms tone CS followed by a 300-ms trace interval was used for the trace EBC paradigm. For delay EBC, the delay vehicle and antagonist groups displayed similar acquisition of conditioned responses (CRs). There was a trend for the trace antagonist group to underperform compared to the trace vehicle group though not quite at a significant level. One explanation for why the results for the delay EBC do not support previous work is that slow learning occurred in the delay vehicle group that may have prevented the effects of secretin receptor antagonist from reaching significance. The trend for the trace antagonist group to display decreased acquisition of CRs suggests that the cerebellum does play an important role in trace EBC. However, in order to better understand the neural circuitry involved in trace EBC, future work should analyze the role that cerebellar secretin itself has on trace EBC

    Inefficient emergent oscillations in intersecting driven many-particle flows

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    Oscillatory flow patterns have been observed in many different driven many-particle systems. The conventional assumption is that the reason for emergent oscillations in opposing flows is an increased efficiency (throughput). In this contribution, however, we will study intersecting pedestrian and vehicle flows as an example for inefficient emergent oscillations. In the coupled vehicle-pedestrian delay problem, oscillating pedestrian and vehicle flows form when pedestrians cross the street with a small time gap to approaching cars, while both pedestrians and vehicles benefit, when they keep some overcritical time gap. That is, when the safety time gap of pedestrians is increased, the average delay time of pedestrians decreases and the vehicle flow goes up. This may be interpreted as a slower-is-faster effect. The underlying mechanism of this effect is explained in detail.Comment: For related publications see http://www.helbing.or

    17-11 Evaluation of Transit Priority Treatments in Tennessee

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    Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition

    Analytical Studies on a Modified Nagel-Schreckenberg Model with the Fukui-Ishibashi Acceleration Rule

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    We propose and study a one-dimensional traffic flow cellular automaton model of high-speed vehicles with the Fukui-Ishibashi-type (FI) acceleration rule for all cars, and the Nagel-Schreckenberg-type (NS) stochastic delay mechanism. By using the car-oriented mean field theory, we obtain analytically the fundamental diagrams of the average speed and vehicle flux depending on the vehicle density and stochastic delay probability. Our theoretical results, which may contribute to the exact analytical theory of the NS model, are in excellent agreement with numerical simulations.Comment: 3 pages previous; now 4 pages 2 eps figure

    Short-range laser obstacle detector

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    Detector, designed for slow-moving vehicle to explore surface of Mars, will automatically divert vehicle from obstacles as small as 0.5 m in its path. Detector comprises injection laser operating in pulse time-delay measurement, or radar, mode. It is capable of scanning area extending from few meters to approximately 30 m

    Decomposing the dynamics of heterogeneous delayed networks with applications to connected vehicle systems

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    Delay-coupled networks are investigated with nonidentical delay times and the effects of such heterogeneity on the emergent dynamics of complex systems are characterized. A simple decomposition method is presented that decouples the dynamics of the network into node-size modal equations in the vicinity of equilibria. The resulting independent components contain distributed delays that map the spatiotemporal complexity of the system to the time domain. We demonstrate that this new approach can be used to reveal new physical phenomena in heterogenous vehicular traffic when vehicles are linked via vehicle-to-vehicle (V2V) communication.Comment: The paper has been updated in response to referee comments. 5 pages, 2 figure
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