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Effects of Adaptive Cruise Control Systems on Highway Traffic Flow Capacity
Abstract
The effects on traffic flow of increasing proportions of both autonomous and cooperative adaptive cruise control (ACC) vehicles relative to manually driven vehicles were studied. Such effects are difficult to estimate from field tests on highways because of the low market penetration of ACC systems. The research approach used Monte Carlo simulations based on detailed models presented in the literature to estimate the quantitative effects of varying the proportions of vehicle control types on lane capacity. The results of this study can help to provide realistic estimates of the effects of the introduction of ACC to the vehicle fleet. Transportation system managers can recognize that the autonomous ACC systems now entering the market are unlikely to have significant positive or negative effects on traffic flow. An additional value of studying ACC systems in this way is that these scenarios can represent the first steps in a deployment sequence that will lead to an automated highway system. Benefits gained at the early stages in this sequence, particularly through the introduction of cooperative ACC with priority access to designated (although not necessarily dedicated) lanes, can help support further investment in and development of automated highway systems.
... Extensive research on CAV platooning control has been conducted, and many approaches have been proposed, e.g., adaptive cruise control (ACC) [13,16,18,31,38], cooperative adaptive cruise control (CACC) [26,27,30,35], and platoon centered vehicle platooning control [4,5,32,33]. The ACC and CACC approaches aim to improve an individual vehicle's safety and mobility as well as string stability instead of system performance of the entire platoon, although simulations and field experiments demonstrate that they do enhance system performance to some extent. ...
... where the constant matrix K and the constant vector d are given by (31), and A c is the closed loop dynamics matrix for the linear vehicle dynamics given by (32). This leads to the closed loop dynamics for p > 1: ...
... It follows from Theorem 6.3 that there exist two positive constants ν z and ν d such that for any ξ with ∥ξ∥ ≤ ν z and d = (d(k)) k∈Z + ∈ ℓ m ∞ with ∥d∥ ∞ ≤ ν d , z(k, ξ, d) ∈ U z for all k ∈ Z + . In view of the right-hand side of the closed loop dynamics given by (43), we see that d(k) = u 0 (k) · d + ∆ h(z(k), v 0 (k), u 0 (k), φ) for all k ∈ Z + , where d is the constant vector given by (31), and ∥∆ h(z, v 0 , u 0 , φ) ...
CAV platooning technology has received considerable attention, driven by the next generation smart transportation systems. This paper considers nonlinear vehicle dynamics and develops fully distributed optimization based CAV platooning control schemes via the platoon centered MPC approach for a possibly heterogeneous CAV platoon. The nonlinear vehicle dynamics leads to major difficulties in distributed algorithm development and control analysis. Specifically, the underlying MPC optimization problem is nonconvex and densely coupled. Further, the closed loop dynamics becomes a time-varying nonlinear system with non-vanishing external perturbations, making stability analysis rather complicated. To overcome these difficulties, we formulate the underlying MPC optimization problem as a locally coupled, albeit nonconvex, optimization problem and develop a sequential convex programming based fully distributed scheme for a general MPC horizon. Such a scheme can be effectively implemented for real-time computing using operator splitting methods. To analyze the closed loop stability, we apply various tools from global implicit function theorems, stability of linear time-varying systems, and Lyapunov theory for input-to-state stability to show that the closed loop system is locally input-to-state stable uniformly in all small coefficients pertaining to the nonlinear dynamic effects. Numerical tests on a heterogeneous CAV platoon in a real traffic condition illustrate the effectiveness of the proposed method.
... This section presents the car-following and lane-changing models applied to simulate vehicles' behavior in this study. One conventional model and two typical ACC/CACC models are chosen to respectively imitate the longitudinal control systems for MVs and AVs [26]- [28]. For lateral control, two typical ML algorithms, RF and BPNN, are chosen to imitate lane-changing behaviors. ...
... The speed and position of a certain vehicle can be calculated by (3)-(4). The settings of TACC = 2.2 s, k1 = 0.23 s −2 and k2 = 0.07 s −1 are employed according to the same tests conducted in [28]. ...
... 3) CACC: The PATH model was developed and calibrated using production cars equipped with a PATH-Nissan High-Level Controller, which is one of few realistic models based on experimental data [28]. It can capture the features of cooperative communications in microscopic traffic flow. ...
This paper proposes a lateral control strategy for autonomous vehicles (AVs) and develops an evolutionary learning framework for off-ramps. Random forest (RF) and back-propagation neural network (BPNN) integrated with model predictive control (MPC) algorithm are respectively used to capture the decision-making and trajectory characteristics during the lane-changing maneuver based on the Next Generation Simulation (NGSIM) dataset. Then, a running cost function is calculated to optimize the trajectory dataset. Finally, the numerical simulation is conducted to investigate the characteristics of the proposed framework. Simulation results indicate that the performance of our method is much better than some other methods in lane-changing gap choice and trajectory execution. Moreover, the traffic system controlled by the evolutionary algorithms reaches the highest capacity and safest level when all vehicles are equipped with cooperative adaptive cruise control (CACC) systems. On the contrary, the scenario with 50% CACC vehicles shows the lowest travel efficiency and the worst safety because of the CACC vehicles' degradation. Furthermore, three iterations and 500 vehicle trajectories at each optimization cycle are recommended for the application in the off-ramp traffic control.
... Last decade witnessed a growing interest in automated vehicles (AVs) due to its potential in enhancing passenger safety, improving travel mobility, reducing fuel consumption, and maximizing traffic throughput [1]- [3]. Early development starts with research projects in academia, such as DARPA challenges [4], PATH program [5], Grand Cooperative Driving Challenges [6], etc. ...
... and derive its derivative to transform the state variable from actuator torque T to acceleration a H . Differentiating model (1) and utilizing (1)(2)(3)(4) in the substitution, we obtaiṅ v H = a H , ...
... and derive its derivative to transform the state variable from actuator torque T to acceleration a H . Differentiating model (1) and utilizing (1)(2)(3)(4) in the substitution, we obtaiṅ v H = a H , ...
This paper investigates the longitudinal control problem in a dynamic traffic environment where driving scenarios change between free-driving scenarios and car-following scenarios. A comprehensive longitudinal controller is proposed to ensure reasonable transient response and steady-state response in scenarios changes, which is independent of planning algorithms. This design takes into account passenger comfort, safety concerns and disturbance rejections, and attempts to meet the requirement of lower cost, faster response, increased comfort, enhanced safety and elevated extendability from the automated vehicle industry. Design insights and intuitions are provided in detail. Comprehensive simulations are conducted to demonstrate the efficacy of the proposed controller in different driving scenarios.
... in the literature [2], [33]- [40], wherē ...
... which is calculated based on the follower speed v F instead of the predecessor speed v P . We remark that simulation results look similar for this linear controller with both range policies (2,59). When initial conditions are far from the uniform flow equilibrium, they always generate unexpected behaviors exhibited in these figures. ...
... This desired distance h des acts as ultimate desired value when the predecessor speed is not changing, because the ultimate desired speed of the follower is v P . Changing range policy (2) to (59) is equivalent to changing the ultimate desired distance to current desired distance that relies on current speed v F . Variations on current speed v F in closed-loop control will in turn lead to variations in desired distance that deteriorate performance. ...
This paper investigates the car-following problem and proposes a nonlinear controller that considers driving comfort, safety concerns, steady-state response and transient response. This controller is designed based on the demands of lower cost, faster response, increased comfort, enhanced safety and elevated extendability from the automotive industry. Design insights and intuitions are provided in detail. Also, theoretical analysis are performed on plant stability, string stability and tracking performance of the closed-loop system. Conditions and guidelines are provided on the selection of control parameters. Comprehensive simulations are conducted to demonstrate the efficacy of the proposed controller in different driving scenarios.
... Extensive research on CAV platooning control has been conducted, and many approaches have been proposed, e.g., adaptive cruise control (ACC) [13,16,18,31,38], cooperative adaptive cruise control (CACC) [26,27,30,35], and platoon centered vehicle platooning control [4,5,32,33]. The ACC and CACC approaches aim to improve an individual vehicle's safety and mobility as well as string stability instead of system performance of the entire platoon, although simulations and field experiments demonstrate that they do enhance system performance to some extent. ...
... where d = W Q w e 1 that agrees with what is given in (31) for p = 1, and w e (k) depends on v 0 (k) and ϕ. Further, there exists a positive constant κ such that w e (k) ≤ κ · ϕ for any v 0 (k) ∈ [v min , v max ]. ...
... where the constant matrix K and the constant vector d are given by (31), and A c is the closed loop dynamics matrix for the linear vehicle dynamics given by (32). This leads to the closed loop dynamics for p > 1: ...
CAV platooning technology has received considerable attention in the past few years, driven by the next generation smart transportation systems. Unlike most of the existing platooning methods that focus on linear vehicle dynamics of CAVs, this paper considers nonlinear vehicle dynamics and develops fully distributed optimization based CAV platooning control schemes via the model predictive control (MPC) approach for a possibly heterogeneous CAV platoon. The nonlinear vehicle dynamics leads to several major difficulties in distributed algorithm development and control analysis and design. Specifically, the underlying MPC optimization problem is nonconvex and densely coupled. Further, the closed loop dynamics becomes a time-varying nonlinear system subject to external perturbations, making closed loop stability analysis rather complicated. To overcome these difficulties, we formulate the underlying MPC optimization problem as a locally coupled, albeit nonconvex, optimization problem and develop a sequential convex programming based fully distributed scheme for a general MPC horizon. Such a scheme can be effectively implemented for real-time computing using operator splitting methods. To analyze the closed loop stability, we apply various tools from global implicit function theorems, stability of linear time-varying systems, and Lyapunov theory for input-to-state stability to show that the closed loop system is locally input-to-state stable uniformly in all small coefficients pertaining to the nonlinear dynamics. Numerical tests on homogeneous and heterogeneous CAV platoons demonstrate the effectiveness of the proposed fully distributed schemes and CAV platooning control.
... The study considered a range of MPR of connected adaptive cruise control (CACC) technology (0%-100%) and set up a number of scenarios with changes in VOTT (up to 75% reduction), roadway capacity (up to 77% increase), willingness to pay (WTP) for CACC technology ($0, $5,000, and $1,500), and autonomous intersections (only for 100% MPR of CACC). Auld et al. (2017) utilized the empirical function from Shladover et al. (2014) andVander Werf et al. (2002) to update the roadway link capacity at different MPR of CACC. The link capacity was expressed as a linear function of the percentage of vehicles equipped with CACC traversing through that link Vander Werf et al. 2002). ...
... Auld et al. (2017) utilized the empirical function from Shladover et al. (2014) andVander Werf et al. (2002) to update the roadway link capacity at different MPR of CACC. The link capacity was expressed as a linear function of the percentage of vehicles equipped with CACC traversing through that link Vander Werf et al. 2002). The model incorporated an extreme case with 75% reduction in VOTT and 77% increase in capacity to simulate 100% MPR of CAVs. ...
... The impact of AVs and CAVs on capacity has been studied both from a theoretical perspective (using fundamental equations of motion to derive acceleration/deceleration, speed, and spacing for the vehicles of interest) and through simulation analysis. Capacity findings related to the introduction of AVs into the traffic stream are mixed, with many studies reporting improvement (Chang and Lai 1997;Minderhoud and Bovy 1999;Tientrakool et al. 2011;Vander Werf et al. 2002) while others reporting degradation (Bierstedt et al. 2014;Adebisi et al. 2020). The literature that showed promising gains in capacity due to the introduction of AVs reported inconsistent levels of improvements for the same MPR across studies. ...
... Previous numerical simulations studies have indicated that use of ACC-equipped vehicles at various penetration rates can help improve traffic stability, increase capacity and reduce travel times [15] [16]. Similar numerical simulation studies for CACC-equipped vehicles, which can communicate with neighboring vehicles and infrastructure, have also indicated an increase in roadway capacity at medium-to-high penetration rates [17][18] [19]. ...
... Building on the analysis in Section VI, the steady-state analysis for mixed traffic flows requires the knowledge of transition probability rates of joining and leaving a vehicular cluster, for both human-driven and congestion-aware CACCequipped vehicles. The effective transition probability rate of joining a cluster (w) in a mixed traffic flow can be expressed using (17) as: ...
... which can be further analyzed by substituting the appropriate expressions from (28), (17), and (23) to obtain: ...
Previous work has shown that Adaptive Cruise Control (ACC) can improve traffic flow by raising the critical vehicular density at which congestion first appears. However, these works also indicate that traffic with medium-to-high penetration of ACC-equipped vehicles is more susceptible to the formation of self-organized phantom traffic jams induced by perturbations in vehicular demographics. In this work, we propose a congestion-aware Cooperative Adaptive Cruise Control (CACC) algorithm as an alternative to address the trade-off between competing goals of raising the critical density, and reducing susceptibility to congestion observed at higher penetration rates of ACC-equipped vehicles. The congestion-aware CACC algorithm is modeled after the General Motor's car-following models, wherein the driver sensitivity is altered based on the prevailing congestion state (or traffic jam size) downstream of the connected vehicle. The dynamics of the self-organized traffic jam are modeled using a master equation. Results indicate that the congestion-aware CACC algorithm can increase the effective critical density leading to higher traffic flows, while also reducing the susceptibility to perturbations in vehicle demographics in the density range that adversely affects ACC-equipped vehicles.
... According to previous studies, AVs can improve traffic flow [10][11][12], consequently, allowing increased road capacity [13,14] of up to 50% in uninterrupted flow [5,6,8]. However, another study reports that the improvement will not be significant (or could even worsen) until a penetration rate of 40% is achieved [15]. Most of the previous studies report the impact of AVs on highways, but the impact on urban roads is rarely reported. ...
... However, there is still a debatable point. Some studies report that traffic flow will become worse with a low or medium AV penetration rate, between around 20% and 70% [5,7,8,15,28]. e studies considering vehicles on highways with ACC emphasized that AVs would make it possible to reduce headway between vehicles and that this will lead to an improvement in traffic flow and even road capacity. Conversely, few studies were performed for urban roads. ...
Automated vehicles (AVs) are believed to have great potential to improve the traffic capacity and efficiency of the current transport systems. Despite positive findings of the impact of AVs on traffic flow and potential road capacity increase for highways, few studies have been performed regarding the impact of AVs on urban roads. Moreover, studies considering traffic volume increase with a mixture of AVs and human-driven vehicles (HDVs) have rarely been conducted. Therefore, this study investigated the impact of gradual increments of AV penetration and traffic volume on urban roads. The study adopted a microsimulation approach using VISSIM with a Wiedmann 74 model for car-following behavior. Parameters for AVs were set at the SAE level 4 of automation. A real road network was chosen for the simulation having 13 intersections in a total distance of 4.5 km. The road network had various numbers of lanes from a single lane to five lanes in one direction. The network consists of a main arterial road and a parallel road serving nearby commercial and residential blocks. In total, 36 scenarios were investigated by a combination of AV penetrations and an increase in traffic volumes. The study found that, as AV penetration increased, traffic flow also improved, with a reduction of the average delay time of up to 31%. Also, as expected, links with three or four lanes had a more significant impact on the delay. In terms of road capacity increase, when the penetration of AVs was saturated at 100%, the road network could accommodate 40% more traffic.
... These benefits include increasing highway capacity and improving safety, reducing negative impacts on the surrounding environment and enhancing driver comfort [102], [103]. All these advantages are achieved by working on platoons parameters [104] that affect the road capacity as we can see in Figure 3.2: ...
... Most of the study cases done are based on simulation models. One of these projects, carried out by VanderWerf, studied the ability to grow demand for adaptive cruise control and cooperative adaptive cruise control vehicles to penetrate the market more effectively compared to manual driving [104]. They simulated a single-lane of 16-kilometre highway with entry and exit ramps every 1.6 kilometres. ...
The thesis topic is a part of the global interest in wireless vehicular networks. Over the past decade, the number of road accidents has increased quickly with the growth of the automotive sector. Statistics have demonstrated that the high number of accidents on the road is primarily due to the high traffic density and the lack of information about other drivers' decisions. Recent studies have shown the importance of vehicular communications, which allow the exchange of real-time traffic safety information between vehicles and thus contribute to accidents avoidance.Through vehicular communication, known as vehicle-to-everything (V2X), which includes vehicle-to-vehicle (V2V) and vehicle-to-infrastructure, vehicles can exchange road safety and traffic management messages with low latency. Platoon formation is considered an interactive option that can improve V2X communication and ensure more safety. The vehicle platoon is defined as a group of vehicles following each other, moving in a straight line with a very short inter-vehicle space. Several vehicle platoon formation strategies have been defined in order to manage the platoon's lifetime and stability. However, none of these strategies has taken into account traffic congestion and speed constraints.The first objective of our work is to propose a new platoon formation algorithm called speed platoon splitting (SPS) where vehicles are grouped according to their destination (the leading vehicle has the farthest destination and the latest vehicle has the nearest destination). The main purpose of SPS is to target alleviating congestion by using a ticket pool and classify platoons according to their velocity in two different lanes. Performance analysis shows that SPS provides platoon stability and reduces highway congestion.V2X communications can be achieved via radio frequency (RF) technologies, especially the 802.11p standard. However, due to the accelerated growth in the number of devices, this technology suffers from several problems such as high latency and channel congestion. An alternative communication solution is provided by visible light communication (VLC). VLC is the usage of visible light as a wireless data transmission technique. VLC reduces complexity and cost, enables high precision positioning and increases network scalability and security.The second objective of this thesis tackles the performance of VLC in V2V among the platoon members. For this purpose, we considered two mathematical models validated by simulations for two different scenarios (we have taken an M/M/1 and an M/GI/1 queues for the first and the second scenarios respectively). The performance evaluations present a detailed study of the VLC in the presence of disruptive vehicles and they are used to derive computations of the Quality of Service parameters. The main conclusion drawn is that VLC technology is considered an efficient technique but it is affected by disruptive vehicles.The third objective of the thesis focuses on proposing a mechanism for vertical handover (VHO) between VLC and RF technologies. This objective is composed of two parts, the first one is based on the threshold value to make a vertical handover decision or by using machine learning techniques. The second part is to choose the appropriate technology after VHO using the utility function or the cooperative game.Throughout the thesis, the performance evaluation of the VLC is based on mathematical modelling. Moreover, the simulation is performed to validate this mathematical modelling.
... While looking into the CAV environment, many researchers considered road capacity (throughput) as a basic measure of performance (Vander Werf et al., 2002;Davis, 2004;Kestin et al., 2007;Ni et al., 2012;Talebpour and Mahmassani, 2016;Chen et al., 2017). Some researchers considered traffic stability (Van Arem et al., 2006;Talebpour and Mahmassani, 2016), travel time and travel time reliability (Rios-Torres et al., 2015;Rios-Torres and Malikopoulos, 2016;Abdulsattar et al., 2020), average speed (Makridis et al., 2018;Shelton et al., 2019), delay (Ding et al., 2019;Mathew et al., 2020), number of stops (Guler et al., 2014;Mathew et al., 2020), fuel consumption and emission (Rios-Torres et al., 2015;Rios-Torres and Malikopoulos, 2016) as the measures of operational performance in a CAV environment. ...
... Vander Werf et al. (2002) used Monte Carlo simulation technique to assess the effect of varying the proportions of autonomous adaptive cruise control (AACC) equipped vehicles on lane capacity. The findings from their research indicated a 7% growth in lane capacity when market penetration of AACC is in the 20% to 60% range. ...
... Improvements in capacity and stability from automated driving largely result from lower reaction times admitting shorter following headways (Kesting and Treiber, 2008;Chen et al., 2017;Makridis et al., 2019). Until vehicle manufacturers and drivers are comfortable with short headways, capacity increases may be limited (Vander Werf et al., 2002;Shladover et al., 2012;Makridis et al., 2019), or capacity may even decrease (Calvert et al., 2017;James et al., 2019). Nevertheless, most studies suggest significant (positive or negative) changes in traffic flow resulting from AVs. ...
... The masses and lengths of each vehicle were randomly determined. The safe time gap was assumed to be T g ≥ T S , T S = 1 s for all vehicles [27][28][29]. All vehicles entered the road at the same initial speed v s = 100 km/h. ...
Autonomous vehicle merging schemes require a central control or a complex communication system between the vehicles. We suggest an alternative local traffic control method based on distance sensors and roadside units which provides the vehicles with the desired gap profile without the need for vehicle-to-vehicle communication. The gap profile aims to open gaps between the vehicles before an upcoming junction. To explore the profiles’ governing parameters, 140,000 simulation cases with varying conditions were run. Results show that, for a speed limit of 100 km/h and high inlet density (of 1–1.5 s between vehicles), the best strategy with respect to flow and merging percentage (of ~90%) is to use early gapping and platoon merging using linear profiles with long stabilization sections (>0.6 km). Moreover, the gapping process should start when the vehicle ahead attains a velocity of 75 km/h. In this way, fluent traffic can be sustained without perpetuating upstream traffic jams.
... The platoon time-headway can drop to as low as 0.5seconds according to field tests, much smaller compared to the 1-2seconds smallest time headway of Human-driven Vehicles (HVs) Shladover et al., 2010;Shladover et al., 2012). This time headway reduction leads to an increase in traffic capacity to over 4,200veh/hr/ln, which nearly doubles conventional road capacity (Vander Werf et al., 2002). Cooperation among vehicles is also expected to reduce 12% fuel consumption and 14% carbon dioxide emission (Park et al., 2011). ...
A cooperative adaptive cruise control (CACC) system may be impeded by slow-moving traffic in the application. To improve the mobility of CACC, this research proposes a CACC controller with successive platoon lane-change capability. The goal is to help a platoon cut through traffic successively like a snake via smaller windows. The proposed controller has the following features: i) with successive platoon lane-change capability; ii) with string stability and lateral stability; iii) with consideration of vehicle dynamics. The proposed controller is evaluated on a simulation platform with the context of traffic and a joint simulation platform consisting of PreScan and Matlab/Simulink. the Results demonstrate that compared to the conventional controller: i) platoon lane-change competence is enhanced by 71.36% on arterials and 120.49% on freeways; ii) platoon lane-change efficiency is enhanced by 25.05% on arterials and 41.36% on freeways; iii) the proposed controller is more robust against congestion. Moreover, the computation time of the proposed controller is approximately 15 milliseconds when running on a laptop equipped with an Intel i7-8750H CPU. This indicates that the proposed controller is ready for real-time implementation.
... The penetration of vehicles with advanced features like ACC and CACC can aid in better traffic flow performance, improve traffic stability, and influence road capacity [7]- [14]. However, the effectiveness depends on the percent of vehicles with such advanced features in the traffic stream [8] [13]. ...
... Vander et al. [67] used Monte Carlo simulation to estimate the impact of the proportion of ACC and CACC vehicles on freeway capacity and analyzed the sensitivity of headway parameters of ACC and CACC vehicles. ...
Intelligent transportation has become a hot research field in recent years The development direction of road traffic construction in the future, the relevant technologies and methods in the process of gradual promotion and application of intelligent connected vehicles continue to attract the attention of scholars and engineers. There are more and more relevant theories, methods and systems. This paper summarizes the current state of microscopic and macroscopic traffic models, characteristic analysis methods of mixed traffic flow, and lane management methods in connected vehicle environments. At the end of this paper, the conclusions of this work are presented, and possible future directions for safety warning research under connected vehicle environments are discussed. This paper represents the current research status of traffic flow characteristics under connected vehicle environments to some extent, which can provide references for future traffic flow characteristic research in terms of framework, methods and technologies, etc.
... Last decade witnessed an increased effort in the deployment of automated vehicle (AV) technology because it can enhance passenger safety, improve travel mobility, reduce fuel consumption, and maximize traffic throughput [1]- [3]. Early deployment dates back to research projects, such as DARPA challenges [4], PATH program [5], Grand Cooperative Driving Challenges [6]. ...
This paper revisits the fundamental mathematics of Taylor series to approximate curves with function representation and arc-length-based parametric representation. Parametric representation is shown to preserve its form in coordinate transformation and parameter shifting. These preservations can significantly facilitate lane estimation in vehicle control since lanes perceived by cameras are typically represented in vehicle body-fixed frames which are translating and rotating. Then we derived the transformation from function representation to arc-length-based parametric representation and its inverse. We applied the transformation to lane estimation in vehicle control problem, and derived the evolution of coefficients for parametric representation that can be used for prediction. We come up with a procedure to simulate the whole process with perception, lane estimation and control for the path-following problem. Simulations are performed to demonstrate the efficacy of the proposed lane estimation algorithm using parametric representation. The results indicate that the proposed technique ensures that vehicle control can achieve reasonably good performance at very low perception updating rate.
... Many researchers have dealt with the modelling of ACC equipped vehicles behaviour (Rajamani et al., 2001, Deng, 2016, its microscopic parametrization and the string stability of the system (Caudill and Garrard, 1977, Swaroop et al., 2001, VanderWerf et al. 2001, Shladover et al., 2012, Rajamani, 2012. Vanderwerf et al (2001Vanderwerf et al ( , 2002 used a set of mathematical models for developing an ACC model and assessed the impact of automation on traffic flow and road capacity. This model was also used by Deng et al (2016) for modelling the platooning formulation of Cooperative automated heavy duty vehicles (HDV). ...
The advent of autonomous vehicles brings major changes in the transportation systems influencing the infrastructure design, the network performance, as well as driving functions and habits. The penetration rate of this new technology highly depends on the acceptance of the automated driving services and functions, as well as on their impacts on various traffic, user oriented and environmental aspects. This research aims to present a methodological framework aiming to facilitate the modelling of the behaviour of new AV driving systems and their impacts on traffic, safety and environment. This framework introduces a stepwise approach, which will be leveraged by stakeholders in order to evaluate the new technology and its components at the design or implementation phase in order to increase acceptance and favor the adoption of the new technology. The proposed framework consists of four sequential steps: i. conceptual design, ii. data collection, processing and mining, iii. modelling and iv. autonomous vehicles impact assessment. The connection between these steps is illustrated and various Key Performance Indicators are specified for each impact area. The paper ends with highlighting some conceptual and modeling challenges that may critically affect the study of acceptance of autonomous vehicles in future mobility scenarios.
... In contrast to the positive effect of AVs, some studies suggested that in the mixed traffic flow, the impact of AV technologies is not significant and may be negative in some certain scenarios. For instance, VanderWerf et al. (2001VanderWerf et al. ( , 2002 defined a set of mathematical models and carried out the simulations to predict the effect of ACC vehicles on traffic dynamics and capacity. It was shown that ACC vehicles only have a small impact on highway capacity even under the most favorable conditions. ...
This paper reports an experimental study on oscillation growth in mixed traffic flow of automated vehicles (AVs) and human driven vehicles (HVs). The leading vehicle moves with constant speed in the experiment. The following vehicles consist of six developable AVs and different number of HVs. Thus, the market penetration rate (MPR) of AVs decreases with the increase of platoon size. The AVs are homogeneously distributed in the platoon. The constant time gap car-following policy is adopted for the AVs and the gap is set to 1.5 s. The experiment shows that in the 7-vehicle-platoon, the oscillations grow only slightly. In the 10-vehicle-platoon, the AVs could still significantly suppress the growth of oscillations. With the further decrease of MPR of AVs in the 13- and 20-vehicle-platoon, the AVs become having no significant impact on oscillation growth. On the other hand, with the decrease of MPR of AVs, average density of the vehicles and flow rate of the platoon increase, which demonstrates a trade-off between traffic stability and throughput under the given setup of AVs. The simulation study is also carried out, which exhibits good agreement with the experiment. Finally, sensitivity analysis of the parameters in the AV upper-level control algorithm has been performed, which is expected to guide future experiment design.
... Common simulation models used in traffic flow include CORSIM, MITSIM, and VISSIM, but most of these models are based on homogeneous traffic conditions and are not suitable for studying the characteristics of heterogeneous traffic flow. erefore, Vander Werf et al. [53] used Monte Carlo simulation to estimate the impact of vehicle types on lane capacity based on models in the literature and conducted a sensitivity analysis of ACC and CACC vehicle timeinterval parameters in simulation tests. Van Arem et al. [54] applied the intelligent vehicle test simulation platform to simulate and analyze the influence of different CACC vehicle ratios on traffic capacity because of the bottleneck section of the expressway with fewer lanes. ...
Mapping knowledge domain (MKD) is an important application in bibliometrics, which is a method of visually presenting and explaining newly developed interdisciplinary scientific fields using data mining, information analysis, scientific measurement, and graphic rendering. This study combines applied mathematics, visual analysis technology, information science, and scientometrics to systematically analyze the development status, research distribution, and future trend of the heterogeneous traffic flow by using the MKD software tools VOSviewer and CiteSpace. Based on the MKD and Bibliometrics approaches, 4709 articles have been studied, which were published by Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) from 2004 to 2021 in the field of heterogeneous traffic flows. Firstly, this paper presents the annual numbers of articles, origin countries, main research organizations, and groups as well as the source journals on heterogeneous traffic flow studies. Then, cocitation analysis is used to divide heterogeneous traffic flow into three main research directions, which include “heterogeneous traffic flow model,” “traffic flow capacity analysis,” and “traffic flow stability analysis.” The keyword cooccurrence analysis is applied to identify five dominant clusters: “modeling and optimization methods,” “traffic flow characteristics analysis,” “driving behavior analysis,” “simulation experiment,” and “policies and barriers.” Finally, burst keywords were studied according to the publication date to present more clearly the change of research focus and direction over time.
... Vander Werf et.al. considered adopting ACC vehicles headway of 1.4 sec, and cooperative adaptive cruise control (CACC) vehicles headway of 0.5 sec [21]. ...
Despite the fact that significant research efforts have been made to the traffic flow theory of autonomous vehicles and manual vehicles, few existing studies have incorporated different modes of both vehicles in their analysis. In this study, we develop a cellular automata simulation model to investigate the impact of different modes of autonomous vehicles (autonomous car, autonomous bus, and autonomous micro car) and conventional vehicles (manual car, manual bus, and manual micro car) on the characteristics of traffic flow. A new type of autonomous mode, i.e., autonomous micro car, is investigated in the model to study the effects of this vehicle mode on the overall capacity of the network. Furthermore, two types of lane-changing behavior, i.e., aggressive lane changing and polite lane changing, are incorporated into the model. The results reveal that micro cars (manual and autonomous) have the potential to reduce traffic congestions and increase the capacity or flow rate (vehicles/hour) of the road. Where the average vehicle occupancy is less than 2, if autonomous micro cars are deployed alongside autonomous cars, the flow rate (vehicles/hour) can be increased significantly. The results highlight the significance of the autonomous micro cars to traffic flow, passenger occupancy, and road capacity.
... There is extensive literature on CAV platooning control. The widely studied approaches include adaptive cruise control (ACC) [8,10,11,18,24], cooperative adaptive cruise control (CACC) [14,15,17,22], and platoon centered vehicle platooning control [4,5,19,20]. The first two approaches intend to improve an individual vehicle's safety, mobility, and string stability rather than systematical performance of the entire platoon, even though enhanced system performance is validated by analysis, simulations, or field experiments. ...
This paper develops distributed optimization-based, platoon-centered connected and autonomous vehicle (CAV) car-following schemes, motivated by the recent interest in CAV platooning technologies. Various distributed optimization or control schemes have been developed for CAV platooning. However, most existing distributed schemes for platoon centered CAV control require either centralized data processing or centralized computation in at least one step of their schemes, referred to as partially distributed schemes. In this paper, we develop fully distributed optimization based, platoon centered CAV platooning control under the linear vehicle dynamics via the model predictive control approach with a general prediction horizon. These fully distributed schemes do not require centralized data processing or centralized computation through the entire schemes. To develop these schemes, we propose a new formulation of an objective function and a decomposition method that decomposes a densely coupled central objective function into the sum of multiple locally coupled functions whose coupling satisfies the network topology constraint. We then exploit locally coupled optimization and operator splitting methods to develop fully distributed schemes. Control design and stability analysis is carried out to achieve desired traffic transient performance and asymptotic stability. Numerical tests demonstrate the effectiveness of the proposed fully distributed schemes and CAV platooning control.
... Research has shown that in situations where drivers suddenly have to take control of the vehicle, they have an increased reaction time [41]. As a result, many of these models [16,42,43] maintain an increased distance to the vehicle in front, in the range of 1.1-1.6 s, to allow the driver to react in time [43]. In comparison, AVs can operate with the technically possible minimum vehicle following time. ...
A new set of lane changing rules is introduced with that the model introduced in (Physica A 570 (1) (2021) 125792) is able to simulate multi lane heterogeneous traffic where human driven vehicles mix with automated or communicating automated vehicles. The model predicts that (communicating) automated vehicles will increase road capacity and traffic flow in all traffic situations more strongly than on one lane traffic even though they behave more passive while lane changing and following human driven vehicles. The main reason for this improvement was found to be the creation of automated vehicle platoons naturally organized by the system.
... Adaptive cruise control (ACC) is a radar-based system, which is designed to enhance driving comfort and safety by adjusting a vehicle's speed to match the speed of the preceding vehicle. However, ACC only has a small impact on the highway capacity [1]. The objective of cooperation in a highway scenario is to ensure that all vehicles in a lane move at the same speed while maintaining a desired formation geometry, which is specified by a desired inter-vehicle gap policy. ...
Cooperative driving relies on communication among vehicles to create situational awareness. One application of cooperative driving is Cooperative Adaptive Cruise Control (CACC) that aims at enhancing highway transportation safety and capacity. Model-based communication (MBC) is a new paradigm with a flexible content structure for broadcasting joint vehicle-driver predictive behavioral models. The vehicle's complex dynamics and diverse driving behaviors add complexity to the modeling process. Gaussian process (GP) is a fully data-driven and non-parametric Bayesian modeling approach which can be used as a modeling component of MBC. The knowledge about the uncertainty is propagated through predictions by generating local GPs for vehicles and broadcasting their hyper-parameters as a model to the neighboring vehicles. In this research study, GP is used to model each vehicle's speed trajectory, which allows vehicles to access the future behavior of their preceding vehicle during communication loss and/or low-rate communication. Besides, to overcome the safety issues in a vehicle platoon, two operating modes for each vehicle are considered; free following and emergency braking. This paper presents a discrete hybrid stochastic model predictive control, which incorporates system modes as well as uncertainties captured by GP models. The proposed control design approach finds the optimal vehicle speed trajectory with the goal of achieving a safe and efficient platoon of vehicles with small inter-vehicle gap while reducing the reliance of the vehicles on a frequent communication. Simulation studies demonstrate the efficacy of the proposed controller considering the aforementioned communication paradigm with low-rate intermittent communication.
... The fundamental idea is to use range sensors (radar, lidar, camera) to measure the inter-vehicle distance and the velocity difference to the vehicle ahead, and then adjust the speed accordingly by controlling the "throttle" and the brake. If all vehicles were equipped with ACC, one might expect increased safety, fuel economy, driving comfort and traffic efficiency [72][73][74][75][76][77][78] due to the faster and more accurate sensing and actuation abilities. However, due to the relatively high cost of range sensors and the perception limitation by the line of sight, this technology still has a low penetration in current traffic systems. ...
Vehicle-to-everything (V2X) communication allows vehicles to monitor the nearby traffic environment, including participants that are beyond the line of sight. Equipping conventional vehicles with V2X devices results in connected vehicles (CVs) while incorporating the information provided by V2X devices into the controllers of automated vehicles (AVs) leads to connected automated vehicles (CAVs). CAVs have great potential for improving driving comfort, reducing fuel consumption and advancing active safety for individual vehicles, as well as enhancing traffic efficiency and mobility for human-dominated traffic systems. In this dissertation, we study a class of connected cruise control (CCC) algorithms for longitudinal control of CAVs, where they respond to the motion information of one or multiple connected vehicles ahead. For validation and demonstration purposes, we utilize a scaled connected vehicle testbed consisting of a group of ground robots, which can provide us with insights about the controller design of full-size vehicles. On the one hand, intermittencies in V2X communication combined with the digital implementation of controllers introduce information delays. To ensure the performance of individual CAVs and the overall traffic, a set of methods is proposed for design and analysis of such communication-based controllers. We validate them with the scaled testbed by conducting a series of experiments on two-car predecessor-follower systems, cascaded predecessor-follower systems, and more complex connected vehicle systems. It is demonstrated that CAVs utilizing information about multiple preceding vehicles in the CCC algorithm can improve the system performance even for low penetration levels. This can be beneficial at the early stage of vehicle automation when human-driven vehicles still dominate the traffic system. On the other hand, we study the delay variations caused by stochastic packet drops in V2X communication and derive the stochastic processes describing the dynamics for the predecessor-follower systems. The dynamics of the mean, second moment and covariance are utilized to obtain stability conditions. Then the results of the two-car predecessor-follower system with stochastic delay variations are extended to an open chain as well as to a closed ring of cascaded predecessor-followers where stochastic packet drops lead to heterogeneity among different V2X devices. It is shown that the proposed analytical methods allow CCC design for CAVs that can achieve stability and stochastic disturbance attenuation in the presence of stochastic packet drops in complex connected vehicle systems.
... Several simulation-based studies conducted mobility analysis for mixed traffic through capacity shifts [9,[18][19][20][21][22][23][24][25][26][27]. ...
Weaving sections are components of highway networks that introduce a heightened likelihood for bottlenecks and collisions. Automated vehicle technology could address this as it holds considerable promise for transportation mobility and safety improvements. However, the implications of combining automated vehicles (AuVs) with traditional human-driven vehicles (HuVs) in weaving freeway sections have not been quantitatively measured. To address this gap, this paper objectively experimented with bidirectional (i.e., longitudinal and lateral) motion dynamics in a microscopic modeling framework to measure the mobility and safety implications for mixed traffic movement in a freeway weaving section. Our research begins by establishing a multilane microscopic model for studied vehicle types (i.e., AuV and HuV) from model predictive control with the provision to form a CACC platoon of AuV vehicles. The proposed modeling framework was tested first with HuV only on a two-lane weaving section and validated using standardized macroscopic parameters from the Highway Capacity Manual. This model was then applied to incrementally expand the AuV share for varying inflow rates of traffic. Simulation results showed that the maximum flow rate through the weaving section was attained at a 65% AuV share. At the same time, steadiness in the average speed of traffic was experienced with increasing AuV share. The results also revealed that a 95% AuV share could reduce potential conflicts by 94.28%. Finally, the results of simulated scenarios were consolidated and scaled to report expected mobility and safety outcomes from the prevailing traffic state and the optimal AuV share for the current inflow rate in weaving sections.
... Partners for Advanced Transit and Highways (PATH) project demonstrated a platoon of eight automated vehicles in 1997, following each other in close formation, with one of them changing lanes and shifting its position in the platoon formation [2]. Joel et al. shows that ACC can have only a small impact on highway capacity [3]. On the other hand, Steven et al. expresses that CACC has the potential to substantially increase highway capacity when it reaches a moderate to high market penetration [4]. ...
Cooperative driving, enabled by communication between automated vehicle systems, is expected to significantly contribute to transportation safety and efficiency. Cooperative Adaptive Cruise Control (CACC) and platooning are two of the main cooperative driving applications that are currently under study. These applications offer significant improvements over current advanced driver assistant systems such as adaptive cruise control (ACC). The primary motivation of CACC and Platooning is to reduce traffic congestion and improve traffic flow, traffic throughput, and highway capacity. These applications need an efficient controller to consider the computational cost and ensure driving comfort and high responsiveness. The advantage of Model Predictive Control is that we can realize high control performance since all constrain for these applications can be explicitly dealt with through solving an optimization problem. These applications highly depend on information update and Communication reliability for their safety and stability purposes. In this paper, we propose a Model Predictive Control (MPC) based approach for CACC and platooning, and examine the impact of communication loss on the performance and robustness of the control scheme. The results show an improvement in response time and string stability, demonstrating the potential of cooperation to attenuate disturbances and improve traffic flow.
... The class of CACC systems utilizing V2V communication could allow the mean following time gap to decrease from about 1.4 s when driving manually to approximately 0.6 s when using CACC, resulting in increased highway lane capacity (Nowakowski et al. 2010). Several highway traffic simulations conducted by the California Partners for Advanced Transportation Technology showed that autonomous ACC alone, even at high CAV market penetration rates, had little effect on lane capacity (Vander et al. 2002;Shladover et al. 2012). Additionally, recent on-the-road experiments have shown that a stream of autonomous ACC vehicles is string unstable, resulting in a negative impact on lane capacity and safety Eilbert et al. 2019;Knoop et al. 2019). ...
The purpose of this report is to document a simulation-based case study completed by the project team to investigate the effectiveness of SAE J3016 Level 1 automation technology for mitigating or solving existing transportation problems related to congestion, fuel consumption, and emissions (SAE International 2016). The case study conducted simulations on a real-world corridor, I—66 in Northern Virginia. This report discusses simulated infrastructure and connected and automated vehicle (CAV) technological strategies. The study evaluated the effectiveness of three CAV applications: cooperative adaptive cruise control, speed harmonization, and cooperative merge. The case study also evaluated the potential benefits of changes to the physical infrastructure, including dedicated ramps and a realistic managed-lane concept—a connected vehicle (CV)— and CAV—eligible high-occupancy vehicle (HOV) lane—where CVs, CAVs, and HOVs (human-driven or CV and CAV) can access a left-side managed lane. The report identifies the most critical simulation parameters related to CAV algorithms, CV and CAV market penetration, traffic demand, and infrastructure enhancement alternatives and used various combinations of these factors to generate different simulation scenarios. The simulation results provide operational insights that State and local departments of transportation may use in future strategic planning for CAV programs.
... In contrast, low penetrations did not yield noticeable capacity benefits. Hartmann et al. found that traffic consisting of 20% conventional vehicles, 60% Cooperative Adaptive Cruise Control (CACC) and 20% Adaptive Cruise Control (ACC) increased lane capacity from 2100 vehicles/hour for 100% conventional vehicles to 2900 vehicles/h [9]. Chen et al. studied highway traffic capacity for mixed traffic of conventional vehicles and AVs considering different AV penetration rates, microscopic characteristics of conventional vehicles and AVs and other lane policies (conventional vehicles exclusive and/or AV lanes or mixed lanes) [10]. ...
The increasing worldwide demand on urban road transportation systems requires more restrictive measures and policies to reduce congestion, time delay and pollution. Autonomous vehicle mobility services, both shared and private, are possibly a good step towards a better road transportation future. This article aims to study the expected impact of private autonomous vehicles on road traffic parameters from a macroscopic level. The proposed methodology focuses on finding the different effects of different combinations of autonomous vehicle penetration and Passenger Car Units (PCU) on the chosen road traffic model. Four parameters are studied: traveled daily kilometers, daily hours, total daily delay and average network speed. The analysis improves the four parameters differently by implementing autonomous vehicles. The parameter total delay has the most significant reduction. Finally, several mathematical models are developed for the percentage of improvement for each chosen parameter.
... There is extensive literature on CAV platooning control. The widely studied approaches include adaptive cruise control (ACC) [8,10,11,18,24], cooperative adaptive cruise control (CACC) [14,15,17,22], and platoon centered vehicle platooning control [4,5,19,20]. The first two approaches intend to improve an individual vehicle's safety, mobility, and string stability rather than systematical performance of the entire platoon, even though enhanced system performance is validated by analysis, simulations, or field experiments. ...
This paper develops distributed optimization based, platoon centered CAV car following schemes, motivated by the recent interest in CAV platooning technologies. Various distributed optimization or control schemes have been developed for CAV platooning. However, most existing distributed schemes for platoon centered CAV control require either centralized data processing or centralized computation in at least one step of their schemes, referred to as partially distributed schemes. In this paper, we develop fully distributed optimization based, platoon centered CAV platooning control under the linear vehicle dynamics via the model predictive control approach with a general prediction horizon. These fully distributed schemes do not require centralized data processing or centralized computation through the entire schemes. To develop these schemes, we propose a new formulation of the objective function and a decomposition method that decomposes a densely coupled central objective function into the sum of several locally coupled functions whose coupling satisfies the network topology constraint. We then exploit the formulation of locally coupled optimization and operator splitting methods to develop fully distributed schemes. Control design and stability analysis is carried out to achieve desired traffic transient performance and asymptotic stability. Numerical tests demonstrate the effectiveness of the proposed fully distributed schemes and CAV platooning control.
... 0.5 s is often noted as the minimal acceptable car following time for drivers [43,45] as well as the technical possible reaction time [46]. Most ACC models rather work with car following times between 1-1.6 s [16,42,43]. This is due to two reasons. ...
This paper introduces a cellular automaton design for single lane highway sections with a reduced time step length of 0.1 s. It is able to model automated and human vehicle agents in heterogeneous as well as homogeneous traffic. Furthermore, it allows agents to adopt different behaviour patterns depending on whether they follow automated or human vehicle agents. A distinction between communicating and non-communicating automated vehicles is also possible. Simulations showed that autonomous vehicles are expected to increase road capacity, reduce the frequency and lifetime of traffic jams, and improve traffic synchronization. Homogeneous communicating automated vehicles traffic can increase the capacity up to about 480% compared to conventional traffic. Furthermore, potential problems with the human–robot interaction that could result in accidents were identified and removed.
Utilizing Vehicle-to-everything (V2X) communication technologies, vehicle platooning systems are expected to realize a new paradigm of cooperative driving with higher levels of traffic safety and efficiency. Connected and Autonomous Vehicles (CAVs) need to have proper awareness of the traffic context. The cooperative platoon’s performance will be influenced by the communication strategy. In particular, time-triggered or event-triggered are of interest here. The expenses related to communication will increase significantly as the number of connected entities increases. Periodic communication can be relaxed to more flexible aperiodic or event-triggered implementations while maintaining desired levels of performance. This paper proposes a predictive model-based and control-aware communication solution for vehicle platoons. The method uses a fully distributed Event-Triggered Communication (ETC) strategy combined with Model-Based Communication (MBC) and aims to minimize communication resource usage while preserving desired closed-loop performance characteristics. In our method, each vehicle runs a remote vehicle state estimator based on the most recently communicated model and the event-driven communication scheme only updates the model when the performance metric error exceeds a certain threshold. Our approach achieves a significant reduction in the average communication rate (82%) while only slightly reducing control performance (e.g., less than 1% speed deviation).
p>This manuscript has been accepted with no further changes for an upcoming issue of the IEEE Open Journal of Intelligent Transportation Systems.</p
p>This manuscript has been accepted with no further changes for an upcoming issue of the IEEE Open Journal of Intelligent Transportation Systems.</p
Evaluation of Innovative Modes of Transport in the Framework of Sustainable Urban MobilityAlong with the developing technology, innovative modes of transportation, such as autonomous vehicles and urban air mobility (UAM), on which many research, patent and investment studies are carried out, are expected to be widely used in our cities in the medium term. Infrastructure development-oriented transportation planning approaches can increase the mobility supply more than necessary while solving the bottlenecks in the transportation system. In recent years, a sustainable urban mobility planning approach has been developed to prevent this. In this study, the sustainability criteria that should be observed by researchers and practitioners were examined, and in this framework, the measures that may be necessary for the integrated application of innovative types with the existing transportation infrastructure were discussed.
A recent empirical study (Shi and Li, 2021) showed that commercial automated vehicles (AVs) became more unstable as the headway was set to a smaller value, implying possible intrinsic tradeoffs between safety, mobility, and stability aspects in AV following control design. This study aims to analytically explain the underlying vehicle control mechanism that dictates these tradeoffs. To this end, a robust optimization model is formulated based upon a parsimonious linear AV following model to capture the first-order tradeoffs between safety, mobility, and stability. The robust optimization model aims to maintain a sufficient safety buffer to avoid collisions against all possible realistic preceding vehicle trajectories. As opposed to a numerical solution, we managed to solve this model to an analytical solution that captures relationships between the key parameters determining safety, mobility, and stability. The analytical solution reveals that improving AV mobility (or reducing AV following headway) would require overcoming more safety challenges (e.g., enhancing vehicle control to maintain a short safety buffer) while causing more string-instability. The theoretical findings are consistent with the empirical observations in previous studies. Further, they provide a possible explanation for the observed string instability of commercial AV following control (e.g., adaptive cruise control) as a tradeoff for a smaller headway. Overall, this study lays a new methodology foundation for incorporating safety in traffic flow analysis that traditionally focused on only mobility and stability. Further, the findings yield a set of managerial insights into reasonable AV following design and its implications to emerging AV traffic management.
Autonomous vehicles (AVs) have been introduced into the traffic stream alongside traditional vehicles (TVs) with the expectation of improved transportation safety, efficiency, and reliability. The majority of AV safety research has been done through simulation. The results of such research on the safety performances of AVs are heavily influenced by the methodological framework, algorithms, and assumptions about AV driving characteristics in a simulated environment. There is a need for AV safety research based on real-world settings before any wide-scale deployment of this technology.
This paper investigates the impact of the presence of SAE level 2 AVs in the traffic stream in reducing longitudinal traffic conflicts using Surrogate Safety Measures on a real-world open-source database of mixed traffic trajectories. The analysis is conducted for both AV-exclusive and mixed AV-TV platoons. Furthermore, we explore whether the presence of AVs decreases longitudinal traffic conflicts in two-vehicle platoons comprising AV and TV mixed leaders and followers.
We find that an exclusive AV platoon behaves similarly to an exclusive TV platoon and produces similar longitudinal conflicts. However, mixed platoons with both AVs and TVs result in a higher number of longitudinal conflicts. Maintaining near-identical leader–follower conditions, we find that the number of conflicts in mixed platoons when an AV follows a TV is higher than when a TV follows an AV. The increase in conflict numbers in a TV-AV mixed platoon can be attributed to AV’s longer response time lag. In summary, analyses conducted in this paper indicate that exclusive platoons and pairs of vehicles exhibit fewer longitudinal conflicts than mixed platoons and pairs.
This study presents a methodology for optimal control of connected automated vehicles (CAVs) in freeway segments with a lane drop. Lane drops can create bottlenecks with a considerable number of mandatory and discretionary lane-changing maneuvers when traffic volume is high, which can eventually lead to stop-and-go conditions. Proper motion planning aligned with optimal lane changing upstream of a lane drop can increase capacity and reduce the number of stops and the risk of collision. This paper introduces a vehicle-level mixed-integer program to control longitudinal and lateral movement of CAVs, provide a smooth flow of traffic, and avoid congestion in freeway segments with lane drops. To ensure the feasibility of vehicle-level decisions and promote system-level optimality, a cooperative distributed algorithm is established, where CAVs coordinate their decisions to find the optimal longitudinal and lateral maneuvers that avoid collisions among all vehicles. The proposed coordination scheme lets CAVs find their optimal trajectories based on predictive information from surrounding vehicles (i.e., future locations and speeds) and coordinate their lane-changing decisions to avoid collisions. The results show that optimal lane changing of CAVs smoothens the traffic flow and increases freeway capacity in congested traffic conditions. Compared with all-knowing CAVs simulated in Vissim, the proposed methodology reduced the average travel time by up to 86.4%. It increased the number of completed trips by up to 134.3% based on various traffic demands and lane drop layout combinations.
This paper proposes a novel driving strategy for Connected and Automated Vehicles (CAVs) in a lane-free traffic environment. To this end, a combination of artificial forces and a reinforcement learning approach are used. To ensure the safe driving behavior of vehicles, an artificial ellipsoid border is assumed around each vehicle by which the lateral and longitudinal forces are obtained and applied. Furthermore, a longitudinal repulsive force based on a Deep Deterministic Policy Gradient (DDPG) network is exerted on the vehicles to avoid longitudinal collisions. Using this approach, the reaction of vehicles is improved, and vehicles may experience closer longitudinal space gaps allowing higher network throughput. The proposed lane-free driving methodology is implemented in the SUMO traffic simulator to showcase its benefits. Additionally, by implementing typical lane-based scenarios in SUMO with the same road condition and traffic demand as lane-free scenarios, a comparison in terms of average speed and time delay has been drawn between the proposed innovative approach and its conventional counterpart, proving the developed approach's functionality.
Despite high expectations of driving automation improving road traffic, its practical implications on traffic flow and emissions are not yet definite. This study systematically reviewed literature on practical impacts of non‐connected automation of passenger cars on motorway traffic efficiency. A conceptual framework showed the importance of understanding interactions between vehicles, both human‐driven and automated, but they are not yet sufficiently known and reproduced by traffic models. Field studies have focused on equipped vehicles. Simulation studies have used different models and assumptions, narrow fleet compositions and road layouts, and covered the theoretical potential in ideal conditions rather than likely impacts in practice. Simulations with automated vehicle time gaps below 1.2 s have found throughput increases, but recent field experiments and simulations using commercial ACC vehicles indicate decreased traffic flow efficiency with increasing traffic volumes and penetration rates. Concluding implications for real traffic from available data is challenging. While benefits are possible for equipped vehicles in low traffic, results suggest negative implications for throughput and emissions at higher traffic volumes. Importantly, more differentiated discussion on the impacts of automated vehicles on traffic flow is needed, considering also the practical implications, such as tradeoffs with safety goals, if benefits are to be achieved.
This paper investigates the car-following problem and proposes a nonlinear controller that considers driving comfort, safety concerns, steady-state response and transient response. This controller is designed based on the demands of lower cost, faster response, increased comfort, enhanced safety and elevated extendability from the automotive industry. Design insights and intuitions are provided in detail. Also, theoretical analysis are performed on plant stability, string stability and tracking performance of the closed-loop system. Conditions and guidelines are provided on the selection of control parameters. Comprehensive simulations are conducted to demonstrate the efficacy of the proposed controller in different driving scenarios.
https://arxiv.org/abs/2205.01879
Recent technological developments allow to connect vehicles via digital data transmission, so that a queue of trucks can safely be driven in close proximity. The lower air resistance of these truck platoons decreases fuel consumption and, thus, contributes to reducing the carbon footprint of road-based freight transportation. The efficiency of platooning depends not only on the aerodynamic drag, which considerably reduces with decreasing inter-vehicle distance. Whether a suitable platooning partner can be found also depends on the trucks’ willingness-to-wait and on a successful platoon formation process. Electric vehicles have to wait while loading their batteries anyway. Therefore, it might be possible to successfully coordinate charging with waiting for partner trucks. Furthermore, driving in a platoon reduces energy consumption, so that electric trucks can increase their driving ranges, which gives them an additional motive for platooning. This paper provides optimization approaches to schedule the platoon formation process of electric commercial vehicles via a central platform. Given a set of trucks with predetermined routes and time windows for their on-time arrivals at their destinations, we derive driving, charging and platoon formation schedules, such that total energy costs are minimized. We formulate the problem, analyze its computational complexity, and provide a novel matheuristic. Its suitable performance is documented by extensive computational experiments. Furthermore, we apply our algorithm to quantify the performance gains when platooning electric trucks and benchmark these outcomes with individual driving schedules of electric trucks and with platoons of traditional trucks powered by a combustion engine.
The scientific advancements in the vehicle and infrastructure automation industry are progressively improving nowadays to provide benefits for the end-users in terms of traffic congestion reduction, safety enhancements, stress-free travels, fuel cost savings, and smart parking, etc. The advances in connected, autonomous, and connected autonomous vehicles (CV, AV, and CAV) depend on the continuous technology developments in the advanced driving assistance systems (ADAS). A clear view of the technology developments related to the AVs will give the users insights on the evolution of the technology and predict future research needs. In this paper, firstly, a review is performed on the available ADAS technologies, their functions, and the expected benefits in the context of CVs, AVs, and CAVs such as the sensors deployed on the partial or fully automated vehicles (Radar, LiDAR, etc.), the communication systems for vehicle-to-vehicle and vehicle-to-infrastructure networking, and the adaptive and cooperative adaptive cruise control technology (ACC/CACC). Secondly, for any technologies to be applied in practical AVs related applications, this study also includes a detailed review in the state/federal guidance, legislation, and regulations toward AVs related applications. Last but not least, the impacts of CVs, AVs, and CAVs on traffic are also reviewed to evaluate the potential benefits as the AV related technologies penetrating in the market. Based on the extensive reviews in this paper, the future related research gaps in technology development and impact analysis are also discussed.
The current non-connected autonomous vehicle scheme for speed changing along the road has limitations. Other alternatives require a central control or a complex communication system between the vehicles. We suggest a low cost and simple method for controlling the traffic of a line of autonomous vehicles using predetermined speed profiles imposed upon the vehicles along the road. We introduce a novel method to control autonomous vehicles traffic. Particularly, we investigate cases where specific velocities are required at some points along the road. This is done by comparing different velocity profiles for acceleration, deceleration or a combination of both. As traffic flow and speed limit may change due to upcoming road conditions, it is imperative to control vehicle line traffic, such that phantom jams will be prevented while preserving maximal traffic flow at minimum energy. We provide a comparison of these profiles for acceleration, deceleration, and for the combined case in terms of traffic flow, energy consumption, travel duration and the resulting jam characteristics. Following the comparison, we conclude that the best strategy would be to use linear speed profiles both to accelerate and to decelerate. Lastly, we suggest a tool to compare speed profiles for deceleration cases where the formation of an upstream propagated traffic congestion is inevitable.
Smart roads, AV and CAV are emerging technologies that represent the new paradigm of mobility. To support the public and private road operators better prepare themselves to implement these technologies in their respective existing or planned infrastructures, there is an urgent need to develop an integrated analysis framework to evaluate the impact of these novel systems on road capacity and safety in function of different market penetration levels of AVs and CAVs. The research focuses on novel smart road geometric design and review criteria based on the performance of AVs and CAVs. The case study of one of the first planned smart roads in Italy has been analysed.
This study assesses the impact of the introduction of connected and automated vehicles on Virginia freeway corridors. Three vehicle types: legacy vehicles (LV), automated vehicles (AV), and connected automated vehicles (CAV), were considered in mixed traffic scenarios. Previous relevant studies were reviewed and the proper operating parameters for LV, AV, and CAV identified. AV and CAV driving behavior models were developed in the VISSIM environment. According to the basic freeway test network results, AV and CAV increase road capacity by 29% and 91%. In the merging freeway test network, AV and CAV increase road capacity by 48% and 60% compared with LV, respectively. A model with diverse LV, AV, and CAV market penetration and diverse traffic demand was tested on I-95 in Virginia, where the research team tested the speed and throughput. Under the current traffic demand, the average speed was higher when there were more AV and no CAV in the traffic flow. However, the average speed of CAV in a congested segment is higher than LV. In the case of throughput, CAV shows poor performance under current traffic demand. With increased traffic demand, high penetrations of AV and CAV present better performance because of their short headway and homogeneity. Therefore, the study predicts that in the future, as the traffic demand grows, AV and CAV can reduce traffic congestion.
Recognizing the need for responsible highway agencies to effectively manage emerging autonomous vehicles (AV) flows in contending with daily recurrent congestion, this study presents a systematic procedure for understanding the impacts of AV flows on traffic conditions under different AV behavioral mechanisms (i.e., car-following and lane-changing), and different penetration rates. Research results show that the presence of AV flows, depending on their adopted behavioral mechanisms, may have significant (either positive or negative) impacts on the overall traffic conditions. Hence, it is essential for responsible highway agencies to have proper operational guidelines to manage and coordinate AV flows. To demonstrate the proposed methodology, this study has carried out extensive simulation experiments using a congested segment of the MD-100 network (a multilane highway segment located in Maryland) under various AV penetration rates and observable behavioral patterns. The collected Measures of Effectiveness highlight that at each AV penetration level there exists a set of optimal behavioral patterns for the AV flows to coordinate with non-AV flows via the Vehicle to Infrastructure or Vehicle to Vehicle infrastructure so as to maximize the roadway capacity and minimize the resulting highway congestion.
A set of mathematical models is defined to predict the effects of emerging driver control assistance systems such as adaptive cruise control (ACC) on traffic flow dynamics and capacity. It is important to understand these effects in order to ensure that ACC systems are implemented in ways that improve, rather than degrade, traffic conditions. Existing traffic models were not designed for, and are not suitable for, this purpose, so it has been necessary to develop a new family of simulation models incorporating the key elements of driver behavior and control system design that will affect traffic flow dynamics and capacity. Example outputs from simulation validation test cases are Illustrated and explained to show that the models are producing reasonable results.
The most serious challenge to the credibility of highway automation as a potential solution to transportation problems has been the lack of a convincing deployment strategy. Such a strategy is needed to show how to advance, step by step, from today's transportation system to a future system that includes automated highway systems (AHSs). The existing literature on AHS deployment is reviewed, and a set of principles that can be used to govern the design of AHS deployment strategies is suggested. A deployment sequence for AHSs is proposed, beginning with adaptive cruise control and then adding elements of vehicle-vehicle cooperation and lane protection to build toward AHS capabilities within the constraints of technological and human factors and economic feasibility. Finally, some example deployment "road maps" are shown for transit buses, heavy trucks, and light-duty passenger vehicles.
The introduction of driver support systems such as (autonomous) intelligent cruise control (ICC) is foreseen within a few years. However, it is still uncertain how these systems will affect traffic-flow characteristics on motorways. A simulation study has been conducted to assess the impacts on roadway capacity more precisely. Ten different ICC designs are investigated and compared with a reference situation without such support systems. The equipment penetration rates of the systems studied varied and were 10, 20, 50, to 100 percent. A capacity analysis was performed for a common bottleneck situation: an on-ramp to a two-lane motorway. On the basis of the simulation results, some unexpected findings emerged. Support systems that support the driver at all speeds and that do not restrict the deceleration level give rise to capacity gains of about 12 percent. However, the first-generation ICC systems will hardly increase traffic-flow performance. A special stop-and-go ICC design did not improve the traffic-flow quality. It was found that, regardless of the ICC type, a headway setting of 1.2 s did not change roadway capacity near an on-ramp bottleneck significantly.
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1999. Includes bibliographical references (p. 185-189).
The sample of drivers, representing a random sample of the
population of licensed drivers in southeastern Michigan, was selected
according to a design that stratified the population by age and prior
use of conventional cruise control. An essential element of the design
was that each driver's operation with adaptive cruise control (ACC) is
compared with the same individual's driving in the “manual”
mode of vehicle operation. The experimental design was based, in part,
on findings from previous research projects. Specifically, the
independent variables of participant age and conventional cruise control
usage were previously found to influence both objective and subjective
dependent measures. The paper delineates the experimental design and
outlines its execution
Human Driver Model for SmartAHS Based on Cognitive and Control Approaches
- B Song
- D Delorme
Song, B., and D. Delorme. Human Driver Model for SmartAHS Based on Cognitive and Control Approaches. Proc., 10th Annual Meeting of the Intelligent Transportation Society of America, Boston, Mass., 2000.
Investigating the Impact of AICC Concepts on Traffic Flow Quality
- M Cremer
- C Demir
- S Demir
- S Donikian
- S Espie
- M Mcdonald
Cremer, M., C. Demir, S. Demir, S. Donikian, S. Espie, and M. McDonald. Investigating the Impact of AICC Concepts on Traffic Flow Quality. Presented at 5th World Congress on Intelligent Trans-port Systems, Seoul, Korea, 1998.
An Assessment of the Impact of Autonomous Intelligent Cruise Control
- Van Aremb
- H Hogemaj
- Verheulc J W A H Vanderschurenm