Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies

Connected vehicles (CVs) will enable new applications to improve traffic flow. This study’s focus is to investigate how potential implementation of variable speed limit (VSL) through different types of communication and sensing technologies on CVs may improve traffic flow at a sag curve. At sag curves, the gradient changes from negative to positive values which causes a reduction in the roadway capacity and congestion. A VSL algorithm is developed and implemented in a simulation environment for controlling the inflow of vehicles to a sag curve on a freeway to minimize delays and increase throughput. Both vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) options for CVs are investigated while implementing the VSL control strategy in a simulation environment. Through a feedback control algorithm, the speed of CVs are manipulated in the upstream of the sag curve to avoid the formation of bottlenecks caused by the change in longitudinal driver behavior. A modified version of the intelligent driver model (IDM) is used to simulate driving behavior on the sag curve. Depending on the traffic density at a sag curve, the feedback control algorithm adjusts the approach speeds of CVs so that the throughput of the sag curve is maximized. A meta-heuristic algorithm is employed to determine the critical control parameters. Various market penetration rates for CVs are considered in the simulations for three alternative communications and sensing technologies. It is demonstrated that for higher Market Penetration Rates (MPR) the performance is the same for all three scenarios which means there is no need for infrastructure-based sensing when the MPR is high enough. The results demonstrate that not only the MPR of CVs but also how CVs are distributed in the traffic stream is critical for system performance. While MPR could be high, uneven distribution of CVs and lack of CVs at the critical time periods as congestion is building up may cause a deterioration in system performance

Deep Reinforcement Learning Approach for Lagrangian Control: Improving Freeway Bottleneck Throughput Via Variable Speed Limit

Connected vehicles (CVs) will enable new applications to improve traffic flow. The focus of this dissertation is to investigate how reinforcement learning (RL) control for the variable speed limit (VSL) through CVs can be generalized to improve traffic flow at different freeway bottlenecks. Three different bottlenecks are investigated: A sag curve, where the gradient changes from negative to positive values causes a reduction in the roadway capacity and congestion; a lane reduction, where three lanes merge to two lanes and cause congestion, and finally, an on-ramp, where increase in demand on a multilane freeway causes capacity drop. An RL algorithm is developed and implemented in a simulation environment for controlling a VSL in the upstream to manipulate the inflow of vehicles to the bottleneck on a freeway to minimize delays and increase the throughput. CVs are assumed to receive VSL messages through Infrastructure-to-Vehicle (I2V) communications technologies. Asynchronous Advantage Actor-Critic (A3C) algorithms are developed for each bottleneck to determine optimal VSL policies. Through these RL control algorithms, the speed of CVs are manipulated in the upstream of the bottleneck to avoid or minimize congestion. Various market penetration rates for CVs are considered in the simulations. It is demonstrated that the RL algorithm is able to adapt to stochastic arrivals of CVs and achieve significant improvements even at low market penetration rates of CVs, and the RL algorithm is able to find solution for all three bottlenecks. The results also show that the RL-based solutions outperform feedback-control-based solutions

Developing accident-speed relationships using a new modelling approach

Changing speed limit leads to proportional changes in average speeds which may affect the number of traffic accident occurrences. It is however critical and challenging to evaluate the impact of a speed limit alteration on the number and severity of accidents due primarily to the unavailability of adequate data and the inherent limitations of existing approaches. Although speed is regarded as one of the main contributory factors in traffic accident occurrences, research findings are inconsistent. Independent of the robustness of their statistical approaches, accident frequency models typically use accident grouping concepts based on spatial criteria (e.g. accident counts by link termed as a link-based approach). In the link-based approach, the variability of accidents is explained by highly aggregated average measures of explanatory variables that may be inappropriate, especially for time-varying variables such as speed and volume. This thesis re-examines accident-speed relationships by developing a new accident data aggregation method that enables improved representation of the road conditions just before accident occurrences in order to evaluate the impact of a potential speed limit increase on the UK motorways (e.g. from 70 mph to 80 mph). In this work, accidents are aggregated according to the similarity of their pre-accident traffic and geometric conditions, forming an alternative accident count dataset termed as the condition-based approach. Accident-speed relationships are separately developed and compared for both approaches (i.e. link-based and condition-based) by employing the reported annual accidents that occurred on the Strategic Road Network of England in 2012 along with traffic and geometric variables. Accident locations were refined using a fuzzy-logic-based algorithm designed for the study area with 98.9% estimated accuracy. The datasets were modelled by injury severity (i.e. fatal and serious or slight) and by number of vehicles involved (i.e. single-vehicle and multiple-vehicle) using the multivariate Poisson lognormal regression, with spatial effects for the link-based model under a full Bayesian inference method. The results of the condition-based models imply that single-vehicle accidents of all severities and multiple-vehicle accidents with fatal or serious injuries increase at higher speed conditions, particularly when these are combined with lower volumes. Multiple-vehicle slight injury accidents were not found to be related with higher speeds, but instead with congested traffic. The outcomes of the link-based model were almost the opposite; suggesting that the speed-accident relationship is negative. The differences between the results reveal that data aggregation may be crucial, yet so far overlooked in the methodological aspect of accident data analyses. By employing the speed elasticity of motorway accidents that was derived from the calibrated condition-based models it has been found that a 10 mph increase in UK motorway speed limit (i.e. from 70 mph to 80 mph) would result in a 6-12% increase in fatal and serious injury accidents and 1-3% increase in slight injury accidents

Analysing traffic crashes in Riyadh City using statistical models and geographic information systems

Road safety is a serious societal concern in Riyadh city, Kingdom of Saudi Arabia. Because of the negative impact of traffic crashes which cause losses in the form of deaths, injuries and property damage, in addition to the pain and social tragedy affecting families of the victims, it is important for transport policy makers to reduce their impact and increase safety standards by reducing the severity and frequency of crashes in the city of Riyadh. It is therefore important to fully understand the relationship between traffic crash severity and frequency and their contributing factors so to establish effective safety policies which can be implemented to enhance road safety in Riyadh city. Data used in previous research have only consisted of basic information as there was unavailability of suitable and accurate data in Riyadh and there are very few studies that have undertaken as small area-wide crash analysis in Riyadh using appropriate statistical models. Therefore safety policies are not based on rigorous analyses to identify factors affecting both the severity and the frequency of traffic crashes. This research aims to explore the relationship between traffic crash severity and frequency and their contributing factors by using statistical models and a GIS approach. The analysis is based on the data obtained over a period of five years, namely AH 1425, 1426, 1427, 1428, and 1429 (roughly equivalent to 2004, 2005, 2006, 2007, and 2008). Injury crash severity data were classified into three categories: fatal, serious injury and slight injury. A series of statistical models were employed to investigate the factors that affect both crash severity (i.e. ordered logit and mixed logit models) and area-wide crash frequency (i.e. classical Poisson and negative binomial models). Because of a severe underreporting problem on the slight injury crashes, binary and mixed binary logistic regression models were also estimated for two categories of severity: fatal and serious crashes. The mixed binary logit model and the negative binomial model are found to be the best models for crash severity and crash frequency analyses respectively. The model estimation results suggest that the statistically significant factors in crash severity are the age and nationality of the driver who is at fault, the time period from 16.00 to 19.59, excessive speed, road surface and lighting conditions, number of vehicles involved and number of casualties. Older drivers are associated with a higher probability of having a fatal crash, and, as expected, excessive speeds were consistently associated with fatal crashes in all models. In the area-level crash frequency models, population, percentage of illiterate people, income per capita and income per adult were found to be positively associated with the frequency of both fatal and serious injury crashes whereas all types of land use such as percentages of residential use, transport utilities, and educational use in all models were found to be negatively associated with the frequency of occurrence of crashes. Results suggest that safety strategies aimed at reducing the severity and frequency of traffic crashes in Riyadh city should take into account the structure of the resident population and greater emphasis should be put on native residents and older age groups. Tougher enforcement should be introduced to tackle the issue of excessive speed. This thesis contributes to knowledge in terms of examining and identifying a range of factors affecting traffic crash severity and frequency in Riyadh city

Development and test of dynamic congestion pricing model

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2009.Includes bibliographical references (p. 129-137).Dynamic congestion pricing is an approach to control the traffic flow on the network by setting variable tolls that are adjusted with time based on the traffic condition. Different models have been developed and tested in the past. However, most of these models are based on deterministic network equilibrium rather than stochastic choices of travelers, and case studies on complex networks are rare. These disadvantages limit the use of existing models. In this research, a new dynamic congestion pricing model is developed based on a discrete choice framework to capture users' personal choices. Several solution algorithms are examined and tested in a synthetic network for solving this model. Among these algorithms, SPSA is found to be the best, and is applied successfully to a real case study in Lower Westchester County in New York State. The usefulness and effectiveness of dynamic congestion pricing is also examined and discussed. The results show that dynamic congestion pricing has the potential to improve network performance.by Shunan Xu.S.M

Book of abstracts of the 2nd International Conference of TEMA: mobilizing projects

Based on its Human Capital and Capacities, the Centre for Mechanical Technology and Automation (TEMA) embraces a mission aiming to contribute to a sustainable industry, with specially focus on the surrounding SMEs, and to the wellbeing of society. Sustainable manufacturing aims to contribute to the development of a sustainable industry by developments and innovations on manufacturing engineering and technologies, to increase productivity, improve products quality and reduce waste in production processes. Technologies for the Wellbeing wishes to contribute to the wellbeing of society by the development of supportive engineering systems focusing on people and their needs and intending to improve their quality of life. TEMA intends to maximize its national and international impact in terms of scientific productivity and its transfer to society by tackling the relevant challenges of our time. TEMA is aware of the major challenges of our days, not only confined to scientific issues but also the societal ones, (a strategic pillar of the Horizon 2020 program), at the same time placing an effort to have its research disseminated, in high impact journals to the international scientific community. (...)publishe

Golden Gate National Recreation Area, Muir Woods National Monument: Final General Management Plan/Environmental Impact Statement, Volume II

We are pleased to present this final General Management Plan for Golden Gate National Recreation Area and Muir Woods National Monument. The plan is the culmination of several years of effort involving the thoughtful input and participation of thousands of individuals, dozens of public agencies, and numerous outside organizations and stakeholder groups. This plan replaces the 1980 General Management Plan. That plan for a National Park in an Urban Area effectively guided the park for over three decades, and most of its major concepts have been fulfilled. A general management plan is a key document for any unit of the National Park System, because within the plan can be found the aspirations of those who care about the park, expressed as a framework that will direct and sustain more detailed implementation planning and guide management decisions over the next 20 years. The new plan for Golden Gate National Recreation Area and Muir Woods reflects the intent of Congress in establishing the parks, as well as the vast amount of knowledge about the parks\u27 exceptional natural and cultural resources that has been gained since 1980. The plan offers a vision of the park that accommodates its changing cultural and social landscape. It was developed in the context of the evolution in attitudes toward conservation and preservation that has occurred over the past three decades - as well as changing preferences in modes of transportation, recreation choices, and ways of experiencing parklands. The vision in this plan is predicated on partnership as an effective management approach, and will rely on the continued support of our partners, especially the Golden Gate National Parks Conservancy. This park has become central to the life of the San Francisco Bay Area, and a destination for millions of people from elsewhere in the United States and around the world. Because of the way the park engages the community as visitors, stewards and advocates, it has become a model of success for park managers around the world

Energy-Efficient and Semi-automated Truck Platooning

This open access book presents research and evaluation results of the Austrian flagship project “Connecting Austria,” illustrating the wide range of research needs and questions that arise when semi-automated truck platooning is deployed in Austria. The work presented is introduced in the context of work in similar research areas around the world. This interdisciplinary research effort considers aspects of engineering, road-vehicle and infrastructure technologies, traffic management and optimization, traffic safety, and psychology, as well as potential economic effects. The book’s broad perspective means that readers interested in current and state-of-the-art methods and techniques for the realization of semi-automated driving and with either an engineering background or with a less technical background gain a comprehensive picture of this important subject. The contributors address many questions such as: Which maneuvers does a platoon typically have to carry out, and how? How can platoons be integrated seamlessly in the traffic flow without becoming an obstacle to individual road users? What trade-offs between system information (sensors, communication effort, etc.) and efficiency are realistic? How can intersections be passed by a platoon in an intelligent fashion? Consideration of diverse disciplines and highlighting their meaning for semi-automated truck platooning, together with the highlighting of necessary research and evaluation patterns to address such a broad task scientifically, makes Energy-Efficient and Semi-automated Truck Platooning a unique contribution with methods that can be extended and adapted beyond the geographical area of the research reported