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Contribution to the Assessment Methodology for Connected and Automated Vehicles on Traffic
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Cooperative Intelligent Transportation Systems (C-ITS) are currently being widely deployed on the road network. However, the impact of such systems on traffic flow is still to be addressed, especially for advanced deployment phases (high number of connected and automated vehicles). In this context, the paper investigates the impacts assessment of Connected and Automated Vehicles (CAVs) on traffic efficiency, safety and environmental sustainability. The main contribution of the work is a multivariate assessment of the impacts CAVs subject to varying fractions of CAVs (representing successive C-ITS deployment phases). To illustrate the expected results of the proposed evaluation methodology, the authors design realistic scenarios in an agent-based simulation framework that integrate CAVs models. The wide range of indicators presented in this paper are calculated to assess the benefits of CAVs. The results highlight how the introduction of CAVs into traffic stream impacts the indicators’ distributions. Multi-dimensional statistical analyses (Principal Component Analysis, Hierarchical Cluster Analysis) provide a synthetic insight on how these indicators are correlated to each other. The paper also investigates the quality of the selected indicators and derive some guidelines for the design of an assessment methodology of the potential benefits of CAVs from traffic efficiency, safety and environmental sustainability perspective.
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April 2019
... As CAV deployment is still at an early stage, research studies utilize microscopic traffic simulation and indicators [9], [10] to evaluate the impact of CAV technologies. A recent extensive survey of CAV simulation [11] highlights that effects of CAVs on traffic flow characteristics and traffic safety have both been investigated in multiple studies, but separately. ...
... To observe vehicle speeds, we use the Travel Rate (TR) [20] that gives the rate of motion in minutes per kilometre (min/km), showing an estimation of travel time based on the observed average speed for the studied section. We evaluate the efficiency of traffic through recording the Total Time Spent (TTS) [9] that consists of adding up of all of the individual vehicle travel times on the studied section. ...
... Thus, for both national and motorway scenario, we have selected the widely-used Time-tocollision (TTC) [10] indicator, that is suited for capturing carfollowing types of conflicts (i.e., potential rear-end collision). For the urban network, we selected the Post-Encroachment Time (PET) [9], that is more appropriate for intersecting conflicts [10] (e.g., potential transversal collision), which is motivated by the high number of (signalised or not) intersections in Dublin. A conflict is detected when the value of an indicator is below a pre-defined threshold [7], and this methodology has been shown to result in similar locations on simulated and real networks [22]. ...
Connected and Autonomous Vehicles (CAVs) are expected to bring major transformations to transport efficiency and safety. Studies show a range of possible impacts, from worse efficiency of CAVs at low penetration rates, to significant improvements in both efficiency and safety at high penetration rates and loads. However, these studies tend to explore efficiency and safety separately, focus on one type of a road network, and include only cars rather than other vehicle types. This paper presents a comprehensive study on impact of CAVs on both efficiency and safety, in three types of networks (urban, national, motorway), simulating different penetration rates of vehicles with multiple levels of automation, using historical traffic data captured on Irish roads. Our study confirms existing results that near-maximum efficiency improvements are observed at relatively low penetration rates, but reveals further insights that the exact penetration ranges between 20% and 40% depending on the network type and traffic conditions. Safety results show a 30% increase of conflicts at lower penetration rates, but 50-80% reduction at higher ones, with consistent improvement for increased penetration. We further show that congestion has a higher impact on conflicts than penetration rates, highlighting the importance of unified evaluation of efficiency and safety.
... At the operational level, CAV technologies are expected to improve fuel economy [27] and reduce emissions per unit of distance thanks to fewer stop-and-go movements [28] and due to more gradual acceleration and deceleration patterns [29]. Due to its lower reaction time compared to CVs, an increase in road capacity is expected due to short following distances [30], [31]. It has been shown that for freeway corridors with dedicated lanes for CAVs, benefits can be obtained in terms of the overall corridor performance metrics with increasing penetration rates up to 50%. ...
The environmental impact of connected and autonomous vehicles (CAVs) is still uncertain. Little is known about how CAVs operational behavior influences the environmental performance of network traffic, including conventional vehicles (CVs). In this paper, a microscopic traffic and emission modeling platform was applied to simulate CAVs operation in Motorway, Rural, and Urban road sections of a medium-sized European city, assuming different configurations of the car-following model parameters associated with a pre-determined or cooperative adaptative behavior of the CAVs. The main contribution is to evaluate the impact of the CAVs operation on the distribution of accelerations, Vehicle Specific Power (VSP) modal distribution, carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for different road types and Market Penetration Rates (MPR). Results suggest CAVs operational behavior can affect CVs environmental performance either positively or negatively, depending on the driving settings and road type. It was found network-wide CO2 varies between savings of 18% and an increase of 4%, depending on the road type and MPR. CAVs adjusted driving settings allowed minimization of system NOx up to 13-23% for MPR ranging between 10 and 90%. These findings may support policymakers and traffic planners in developing strategies to better accommodate CAVs in a sustainable way.
The continued evolutions in automated driving technologies and their rapid testing on common roads make it necessary to evaluate their impacts on land use and transportation models. It is crucial to quantify the number of advanced driving system-equipped vehicles that are going to be part of transportation networks. On the other hand, the intuitive property of these vehicles to create an induced demand can bring both positive and negative effects on the travel equilibrium costs that create inequity. To cater for the gap of realistic quantification of penetration rate and inequity evaluation on the inclusion of such vehicles; this research crafts a detailed and effective methodology. This research formulates a convex minimization problem as a lower-level part of the bi-level optimization model intending to minimize the travel equilibrium cost for all OD pairs. Also, acts as an assignment of demand to the network following the stochastic user equilibrium approach by using the Frank–Wolfe algorithm. Whereas, the upper level of the model maximizes the production of newly generated demand incorporating inequity constraints. A genetic algorithm is used to solve the multi-objective fitness function yielded from the bi-level optimization model by application of the model on a real transportation network of the city of Genoa, Italy.
Advances in Information and Communication Technologies (ICT) allow the transportation community to foresee dramatic improvements for the incoming years in terms of a more efficient, environmental friendly and safe traffic management. In that context, new ITS paradigms like Cooperative Systems (C-ITS) enable an efficient traffic state estimation and traffic control. C-ITS refers to three levels of cooperation between vehicles and infrastructure: (i) equipped vehicles with Advanced Driver Assistance Systems (ADAS) adjusting their motion to surrounding traffic conditions; (ii) information exchange with the infrastructure; (iii) vehicle-to-vehicle communication. Therefore, C-ITS makes it possible to go a step further in providing real time information and tailored control strategies to specific drivers. As a response to an expected increasing penetration rate of these systems, traffic managers and researchers have to come up with new methodologies that override the classic methods of traffic modeling and control. In this paper, we discuss some potentialities of C-ITS for traffic management with the methodological issues following the expansion of such systems. Cooperative traffic models are introduced into an open-source traffic simulator. The resulting simulation framework is robust and able to assess potential benefits of cooperative traffic control strategies in different traffic configurations.
This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the microscopic level and the resulting traffic flow characteristics at the macroscopic level. The results give new insights into impacts of ADAS on traffic flow characteristics.
This study used microscopic simulation to estimate the effect on highway capacity of varying market penetrations of vehicles with adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC). Because the simulation used the distribution of time gap settings that drivers from the general public used in a real field experiment, this study was the first on the effects of ACC and CACC on traffic to be based on real data on driver usage of these types of controls. The results showed that the use of ACC was unlikely to change lane capacity significantly. However, CACC was able to increase capacity greatly after its market penetration reached moderate to high percentages. The capacity increase could be accelerated by equipping non-ACC vehicles with vehicle awareness devices so that they could serve as the lead vehicles for CACC vehicles.
This paper presents results from measurements on Vehicle to Vehicle (V2V) communication between participants in a cooperative application: vehicle platooning. The platoon being studied consists of four vehicles; one truck in the lead and three passenger cars following. The V2V-communication node in each vehicle contains an 802.11p radio tuned to 5.9 GHz. It is used to send messages between vehicles to coordinate movements and maintain safety in the platoon. In cooperative applications, V2V-communication is an enabling technology. The V2V-communication quality is studied according to packet error rate. This is measured in tests with different speeds, antenna position and on two tracks. The paper draws general conclusions on the performance of V2Vcommunication and presents a comparison of the tested antenna placements on the truck.
Safety is emerging as an area of increased attention and awareness within transportation engineering. Historically, the safety of new and innovative traffic treatments has been difficult to assess, primarily because of a lack of good predictive models of crash potential and a lack of consensus on what constitutes a safe or unsafe facility. An FHWA-sponsored research project investigated the potential to derive surrogate measures of safety from existing traffic simulation models. These surrogate measures could then be used to support evaluations of various traffic engineering alternatives, including facilities that have not yet been built and strategies that have not yet been used. Each surrogate measure is collected on the basis of the occurrence of a conflict event, which is an interaction between two vehicles in which one vehicle must take evasive action to avoid a collision. The surrogate measures that are proposed as the best are time to collision, postencroachment time, deceleration rate, maximum speed, and speed differential. Time to collision, postencroachment time, and deceleration rate can be used to measure the severity of the conflict. Maximum speed and the speed differential can be used to measure the severity of the potential collision (by use of additional information about the mass of the vehicles involved to assess momentum). After the simulation model is executed for a number of iterations, a postprocessing tool would be used to compute the statistics for the various measures and perform comparisons between design alternatives.
In this paper, we propose a heterogeneous car following model in terms of an extension to the original optimal velocity model characterizing two classes of different self-stabilizing control vehicles. Linear stability analysis method is utilized to the extended model, for purpose to explore how the varying percentages of the vehicles with short-duration self-stabilizing control influence the stability of the heterogeneous traffic flow. We obtain the neutral stability lines for different percentages of two classes of vehicles, with finding that the traffic flow trends to stable with the decrease of the percentage for short-duration self-stabilizing control vehicles. Moreover, we explore a special case that the same numbers of two different classes of vehicles with self-stabilizing control. We theoretically derive the stability condition of the special case, and conclude the effect of the average value and the standard deviation of two time gaps, on the heterogeneous traffic stability. At last, direct simulations are conducted to verify the conclusion of theoretical analysis.
Variable speed limit systems where variable message signs are used to show speed limits adjusted to the prevailing road or traffic conditions are installed on motorways in many countries. The objectives of variable speed limit system installations are often to decrease the number of accidents and to increase traffic efficiency. Currently, there is an interest in exploring the potential of cooperative intelligent transport systems including communication between vehicles and/or vehicles and the infrastructure. In this paper, we study the potential benefits of introducing infrastructure to vehicle communication, autonomous vehicle control and individualized speed limits in variable speed limit systems. We do this by proposing a cooperative variable speed limit system as an extension of an existing variable speed limit system. In the proposed system, communication between the infrastructure and the vehicles is used to transmit variable speed limits to upstream vehicles before the variable message signs become visible to the drivers. The system is evaluated by the means of microscopic traffic simulation. Traffic efficiency and environmental effects are considered in the analysis. The results of the study show benefits of the infrastructure to vehicle communication, autonomous vehicle control and individualized speed limits for variable speed limit systems in the form of lower acceleration rates and thereby harmonized traffic flow and reduced exhaust emissions.
Advances in Information and Communication Technologies (ICT) allow the transportation community to foresee relevant improvements for the incoming years in terms of a more efficient, environmental friendly and safe traffic management and operations. In that context, new ITS paradigms like Cooperative Systems (C-ITS) enable an efficient traffic state estimation and traffic control. C-ITS refers to three levels of cooperation between vehicles and infrastructure: (i) equipped vehicles with Advanced Driver Assistance Systems (ADAS) adjusting their motion to surrounding traffic conditions; (ii) information exchange with the infrastructure; (iii) vehicle-to-vehicle communication. Therefore, C-ITS make it possible to go a step further in providing real time information and tailored control strategies to specific drivers. As a response to an expected increasing penetration rate of these systems, traffic managers and researchers have to come up with new methodologies that override the classical methods of traffic modelling and traffic control. We focus in this paper on the potentialities of C-ITS for traffic management with the methodological issues following the expansion of such systems. The methods for introducing a cooperative modelling framework within existing traffic models are discussed. The paper also provides a building block for Cooperative Traffic Management (CTM). Finally, the potential applications of such blocks are presented from a technical as well as an operational standpoint.
