Estimating and exploiting the capacity of urban street networks

The paper deals with the problem of estimating and exploiting traffic capacity of different road elements (link, nodes, network) and presents the results obtained by performing a systematic investigation of the role that the parameters of a microscopic simulation model play on the macroscopic representation of different road elements. An analysis of traffic parameters has been performed using a microsimulation software package to identify the most important parameters affecting the arterial capacity and to calibrate driver's behavior models through macroscopic traffic observations

Exploring the Effects of Cooperative Adaptive Cruise Control in Mitigating Traffic Congestion

The aim of this research is to examine the impact of CACC (Cooperative Adaptive Cruise Control) equipped vehicles on traffic-flow characteristics of a multilane highway system. The research identifies how CACC vehicles affect the dynamics of traffic flow on a road network and demonstrates the potential benefits of reducing traffic congestion due to stop-and-go traffic conditions. An agent-based traffic simulation model is developed specifically to examine the effect of these intelligent vehicles on the traffic flow dynamics. Traffic performance metrics characterizing the evolution of traffic congestion throughout the road network, are analyzed. Different CACC penetration levels are studied. The positive impact of the CACC technology is demonstrated and shown that it has an impact of increasing the highway capacity and mitigating traffic congestions. This effect is sensitive to the market penetration and the traffic arrival rate. In addition, a progressive deployment strategy for CACC is proposed and validated

Driving Information in a Transition to a Connected and Autonomous Vehicle Environment: Impacts on Pollutants, Noise and Safety

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A Sigmoid-based car-following model to improve acceleration stability in traffic oscillation and following failure in free flow

This paper proposes an improved Intelligent driving model (Sigmoid-IDM) to address the problems of excessive acceleration in traffic oscillation and following failure in free flow. The Sigmoid-IDM uses a Sigmoid function to enhance the start-following characteristics, improve the output strategy of the spacing term, and stabilize the steady-state velocity in free flow. Moreover, the model asymmetry is improved by means of introducing cautious following distance, driving caution factor, and segmentation function. The anti-interference ability of the Sigmoid-IDM is demonstrated by local stability and string stability analyses.Comment: 15 pages, 51 figures

SURVEY STUDY FOR VEHICULAR AD HOC NETWORKS PERFORMANCE IN CITY AND URBAN RESIDENTIAL AREAS

This thesis it survey study for VANET (Vehicular Ad-Hoc Networks) and it performance in city and urban residential areas, when the the number of vehicles on roads is increasing annually, due to the higher amount of traffic, there are more accidents associated with road traffic complexity. VANET can be used to detect dangerous situations which are forwarded to the driver assistant system by monitoring the traffic status.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Safety of a multi-vehicle system in mixed communication environments

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007.Includes bibliographical references (leaves 131-138).Recent news events and statistics demonstrate the frequent occurrence of pile-up crashes on highways. A predominant reason for the occurrence of such crashes is that current vehicles (including those equipped with an Automatic Cruise Control system) do not provide the driver with advance information of events occurring far ahead of him/her. The use of inter-vehicular communication to provide advance warnings to enhance automotive safety is therefore being actively discussed in the research community. In this thesis, we investigate scenarios wherein only a subset of the vehicles in a multi-vehicle stream, are equipped with such advance warning capabilities. These vehicles (equipped with the capability to receive far-ahead information) are arbitrarily distributed among other unequipped vehicles that are capable of receiving only local, near-neighbor information. It is seen that there are conditions wherein even a partial equipment of the system can be beneficial (to both the equipped and the unequipped vehicles in a mixed vehicle stream). We demonstrate this through both simulations and a theoretical analysis. Towards this end, two distinct modeling approaches are adopted: microscopic and macroscopic.(cont.) The microscopic modeling approach uses ordinary differential equations to model each driver-vehicle unit and its interactions with its neighbors. A single-lane model is employed; and the problem is formulated as a collision avoidance problem. Sufficient conditions on the number of equipped vehicles, as well as their distributions in a mixed vehicle string are obtained; under these conditions, it is guaranteed that collisions do not occur. The macroscopic modeling approach, on the other hand, uses partial differential equations that govern the average behavior of groups of vehicles. In this approach, a multi-lane formulation is employed. This thesis examines the influence of partial equipment of the advance warning system on some of the wave effects that are known to exist in traffic flows, in particular, shocks and large negative velocity gradient waves that travel unattenuated or get amplified as they pass through the traffic. We examine the influence of the equipped vehicles in attenuating such waves. The resulting velocity gradients are parametrized as a function of the percentage of equipped vehicles. A prototype of an advance warning system was also developed and road tests were conducted to test the concept. These road tests have demonstrated the system's performance to be satisfactory, subject to good communication links, for the class of scenarios tested.by Animesh Chakravarthy.Ph.D

Analytical and simulation models of weaving area operations under non-freeway conditions

The Highway Capacity Manual covers adequately the operation of weaving areas on freeways. Weaving on non-freeway facilities, however, has not been addressed as yet. This research effort presents a state-of-the-art procedural analytical approach and simulation models for the analysis of the level of service and operation of non-freeway weaving areas. Weaving under non-freeway conditions is classified into two broad categories; basic weave and ramp weave. The analytical models for these two weaving categories are calibrated and validated based on data obtained from several sites selected in the states of New Jersey and New York. New level of service criteria are developed for these two weaving categories. A FORTRAN program was developed to compute average weaving and nonweaving speeds and determine the level of service. In addition, simulation is used to develop a model for basic weave only. The simulation model is microscopic, enabling the user to study the dynamics of individual vehicles and the overall traffic flow

Driving Information in a Transition to a Connected and Autonomous Vehicle Environment: Impacts on Pollutants, Noise and Safety

The main objective of this vision paper is to present the project “DICA-VE: Driving Information in a Connected and Autonomous Vehicle Environment: Impacts on Safety and Emissions”, which aims to develop an integrated methodology to assess driving behavior volatility and develop warnings to reduce road conflicts and pollutants/noise emissions in a vehicle environment. A particular attention will be given to the interaction of motor vehicles with vulnerable road users (pedestrians and cyclists). The essence of assessing driving volatility aims the capture of the existence of strong accelerations and aggressive maneuvers. A fundamental understanding of instantaneous driving decisions (through a deep characterization of individual driver decision mechanisms, distinguishing normal from anomalous) is needed to develop a framework for optimizing these impacts. Thus, the research questions are: 1) Which strategies are adopted by each driver when he/she performs short-term driving decisions and how can these intentions be mapped, in a certain road network?; 2) How is driver’s volatility affected by the proximity of other road users, namely pedestrians or cyclists?; 3) How can driving volatility information be integrated into a platform to alert road users about potential dangers in the road infrastructure and prevent the occurrence of crash situations?; 4) How can anomalous driving variability be reduced in autonomous cars, in order to prevent road crashes and have a performance with a minimum degree of emissions? This paper brings a literature review on this topic and an evaluation of methods that can be used to assess driving behavior patterns and their influence on road safety, pollutant and noise emissions.publishe