Article

Traffic Flow Impacts of Converting an HOV Lane Into a Dedicated CACC Lane on a Freeway Corridor

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Abstract

Cooperative Adaptive Cruise Control (CACC) systems can increase roadway capacity, but the benefits are marginal at low market penetration rates (MPRs). Thus, a CACC dedicated lane is considered to group CACC vehicles for efficient traffic stream. Concepts of converting existing High Occupancy Vehicle (HOV) lanes into CACC lanes emerge, which leverages the infrastructural facilities and experience with HOV lanes. However, it is unclear to which extent changing HOV lanes to CACC lanes can influence freeway operations. This study examines the traffic flow impacts of converting HOV lanes into CACC lanes regarding CACC MPRs on a complex freeway corridor with multiple interacting bottlenecks in California. A simulation model capable of reproducing flow characteristics with HOV lane and CACC systems is employed for the assessment. Special attention is paid to macroscopic congestion patterns, CACC lane utilization, travel time reliability and CACC operation characteristics. The results show that converting to CACC lanes at low MPRs (130%) can exacerbate congestion in general purpose lanes, whereas at mediate CACC MPRs (40%-50%) the congestion is drastically alleviated due to a large share of traffic carried by CACC lanes.

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... Some model the impact of lane changes realistically, however do not analyze the traffic capacity under platoon organization [17,18]. Zhong et al [17] use a CACC model (E-IDM) and a lane change model (MOBIL) that describe the flow disruption of lane changes. ...
... Zhong et al [17] use a CACC model (E-IDM) and a lane change model (MOBIL) that describe the flow disruption of lane changes. Xiao et al [18] implement an extensive model of lane change behavior [19,20] and simulate a mixed traffic of CAVs and non-CAVs on a freeway network. However, the analysis on traffic capacity is missing. ...
... The dedicated lanes will be more saturated at higher CAV penetration, however both studies only use the same demand for all CAV penetration levels and do not analyze the traffic flowing at capacity at high CAV pen-etration. Note that Xiao et al [18] observed speed reduction in the dedicated lanes for CAVs due to the lane changes to enter and exit the dedicated lanes. ...
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Connected Automated Vehicles (CAVs) bring promise of increasing traffic capacity and energy efficiency by forming platoons with short headways on the road. However at low CAV penetration, the capacity gain will be small because the CAVs that randomly enter the road will be sparsely distributed, diminishing the probability of forming long platoons. Many researchers propose to solve this issue by platoon organization strategies, where the CAVs search for other CAVs on the road and change lanes if necessary to form longer platoons. However, the current literature does not analyze a potential risk of platoon organization in disrupting the flow and reducing the capacity by inducing more lane changes. In this research, we use driving model of Cooperative Adaptive Cruise Control (CACC) vehicles and human-driven vehicles that are validated with field experiments and find that platoon organization can indeed drop the capacity with more lane changes. But when the traffic demand is well below capacity, platoon organization forms longer CAV platoons without reducing the flow. Based on this finding, we develop the Flow-Aware platoon organization strategy, where the CAVs perform platoon organization conditionally on the local traffic state, i.e., a low flow and a high speed. We simulate the Flow-Aware platoon organization on a realistic freeway network and show that the CAVs successfully form longer platoons, while ensuring a maximal traffic flow.
... Therefore, researchers recently consider converting other existing dedicated lanes such as high-occupancy vehicle lanes to dedicated lanes for autonomous vehicles. For example, in [15], [16], simulations and experiments are conducted to investigate the benefit of converting an existing highoccupancy vehicle lane to a dedicated lane for autonomous vehicles. ...
... To complete the proof, we have to also show that f + ∈ S exists. To show this, we prove that there exists * that both satisfies condition (15) and (3) ...
... and f = f + . Due to f ∈ S and f + ∈ S, we have that f and f + both satisfy Equation(15). Thus we haveJ (f ) − J f + ...
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We consider the scenario where human-driven/autonomous vehicles with low/high occupancy are sharing a segment of highway and autonomous vehicles are capable of increasing the traffic throughput by preserving a shorter headway than human-driven vehicles. We propose a toll lane framework where a lane on the highway is reserved freely for autonomous vehicles with high occupancy, which have the greatest capability to increase social mobility, and the other three classes of vehicles can choose to use the toll lane with a toll or use the other regular lanes freely. All vehicles are assumed to be only interested in minimizing their own travel costs. We explore the resulting lane choice equilibria under the framework and establish desirable properties of the equilibria, which implicitly compare high-occupancy vehicles with autonomous vehicles in terms of their capabilities to increase social mobility. We further use numerical examples in the optimal toll design, the occupancy threshold design, and the policy design problems to clarify the various potential applications of this toll lane framework that unites high-occupancy vehicles and autonomous vehicles. To our best knowledge, this is the first work that systematically studies a toll lane framework that unites autonomous vehicles and high-occupancy vehicles on the roads.
... Assigning a lane to C/AVs could not only improve the probability of platooning with increased concentration of these vehicles in one lane, but it could also decrease the interactions between C/AVs and MVs (Talebpour et al., 2017). However, dedicating a lane to C/AVs can increase the congestion in the remaining lanes for regular traffic and cause shockwaves near entry/exit areas of these lanes (Talebpour et al., 2017;Xiao et al., 2019;Zhong, 2018). ...
... DLs not only improves the traffic efficiency (Van Arem et al., 2006;Fakharian Qom et al., 2016;Ivanchev et al., 2017;Xiao et al., 2019;Amirgholy et al., 2018;Vander Laan and Sadabadi, 2017;Ye and Yamamoto, 2018;Melson et al. 2018;Amirgholy et al., 2020), but also improves the traffic safety evaluated by surrogate safety indicators and their standard deviations (Rahman and Abdel-Aty, 2018) as well as shockwaves reduction (Van Arem et al., 2006). A recent study by Liu et al. (2020) shows that implementing DLs can also improve fuel efficiency and that this is more evident at low MPRs. ...
... A level of penetration rate could be considered as a "turning point" for changing the traffic performance, where below it, implementing DLs can degrade the traffic performance and above it could enhance it. Depending on the number of lanes, the configurations of DLs, and traffic flow conditions, the "turning point" has been reported at different rates in the literature: ranging from 15% (Yang et al., 2019) to 50% (Ivanchev et al., 2017;Vander Laan & Sadabadi, 2017;Xiao et al., 2019;Arnaout and Bowling, 2014). Another reason behind these differences is because simulation studies were conducted under different assumptions and C/AVs were programmed to behave differently as further detailed in Table 3. ...
Article
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Dedicated Lanes (DLs) have been proposed as a potential scenario for the deployment of Automated and/or Connected Vehicles (C/AVs) on the road network. However, evidence-based knowledge regarding the impacts of different design configurations, utilization policies, and the design of their access/egress on traffic safety and efficiency is limited. In order to develop an adequate design for DLs, first, a conceptual framework describing the relations and interrelations between these factors and traffic safety and efficiency is needed. Therefore, the main aim of this paper is to develop a conceptual framework accounting for the factors that could affect the safety and efficiency of DLs. This conceptual framework is underpinned based on relevant literature on how the deployment of C/AVs, driver behaviour, and DL design and operation affect traffic safety and efficiency. Based on the conceptual framework, the knowledge gaps on DL design for C/AVs were identified and a research agenda, including prioritization of the research needs, is proposed. Following the developed conceptual framework, the necessary building blocks for investigating the impacts of different design configurations, utilization policies, and the design of their access/egress on traffic safety and efficiency are: (1) to specify the types of vehicles with certain capabilities allowed to drive on DLs; (2) to incorporate existing algorithms of C/AVs, which reflect more realistically their behaviour, in both driving simulator experiments and microscopic simulation; (3) to translate the empirical data regarding human behavioural adaptation collected from field tests and driving simulator studies to mathematical models and implement them in traffic flow simulation platform. It is also recommended to develop automated lane change algorithms, taking into account connectivity between C/AVs which can be also implemented in driving simulators and traffic flow simulation platforms. Finally, it is recommended that future research investigate the combined effects of traffic safety and efficiency in designing DLs while considering driver behaviour adaptation and control transitions between manual and automated operation.
... Based on the above analysis, the car-following model calibrated by the PATH laboratory in a field test, known as the CACC [33,34] model, has been selected as the adopted model for certain CAVs and CVs. Additionally, the adaptive cruise control (ACC) [34,35] model is adopted as the carfollowing model for AVs and some CAVs and CVs. ...
... Based on the above analysis, the car-following model calibrated by the PATH laboratory in a field test, known as the CACC [33,34] model, has been selected as the adopted model for certain CAVs and CVs. Additionally, the adaptive cruise control (ACC) [34,35] model is adopted as the carfollowing model for AVs and some CAVs and CVs. At the same time, the IDM [36] has been widely used and can well describe the status of traffic flow and drivers' habits, which is selected as the following model for HVs. ...
... Based on the above analysis, the car-following model calibrated by the PATH laboratory in a field test, known as the CACC [33,34] model, has been selected as the adopted model for certain CAVs and CVs. Additionally, the adaptive cruise control (ACC) [34,35] model is adopted as the carfollowing model for AVs and some CAVs and CVs. ...
... Based on the above analysis, the car-following model calibrated by the PATH laboratory in a field test, known as the CACC [33,34] model, has been selected as the adopted model for certain CAVs and CVs. Additionally, the adaptive cruise control (ACC) [34,35] model is adopted as the carfollowing model for AVs and some CAVs and CVs. At the same time, the IDM [36] has been widely used and can well describe the status of traffic flow and drivers' habits, which is selected as the following model for HVs. ...
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This paper proposes a capacity analysis model for a mixed traffic flow environment that considers the heterogeneity and maximum platoon size of connected vehicles. Firstly, we explore how the organization mode of platoon affects car-following characteristics in mixed traffic flow with connected and automated vehicles, connected human-driven vehicles, automated vehicles, and human-driven vehicles. Different car-following models are used to describe the car-following characteristics of different types of vehicles. Secondly, the probability distribution model is developed for the size of platoons considering the penetration rate and the maximum platoon size of connected and automated vehicles, connected human-driven vehicles. Thirdly, the fundamental diagram of mixed traffic flow is further derived based on the probability distribution of platoon size and car-following models. Then, the capacity model of mixed traffic flow is proposed. Finally, a numerical experiment is designed to evaluate the impact of different penetration rates and maximum platoon sizes of connected and automated vehicles, connected human-driven vehicles on the capacity of the mixed traffic flow. The results show that (1) with a low penetration rate of connected and automated vehicles, connected human-driven vehicles, the change in the maximum platoon size has no noticeable effect on the distribution of platoon size of connected and automated vehicles, connected human-driven vehicles. (2) Road capacity increases with the maximum platoon size and the penetration rate of connected vehicles. (3) Compared with connected human-driven vehicles, the penetration rate of connected and automated vehicles has a more significant impact on road capacity.
... In addition, since heavy vehicles like trucks have different specifications and speed compared to general vehicles, their result occurred from more interaction or conflict with AVs [14]. For this reason, there was a bottleneck at the exit, and the bottleneck spread upstream [31], resulting in increased queues; however, the main and entrance sections have been shown to alleviate these issues. These are different results from the expected effect that the multifaceted situation of the road will change positively with the introduction of AVs, and a way to solve this problem is required. ...
... In particular, according to [25], when introducing a dedicated lane for new mobility, they affirmed that a comprehensive strategy considering MPR, operational perspective, traffic per-formance, environment, and driver characteristics are needed. Accordingly, various studies have been conducted on AVs lanes, but most of them have only presented the positive effects of the DLs introduction [12,[31][32][33][34][35], and research on the presentation of utilization policy for DLs has been understudied. Therefore, we intend to present a judgment methodology for establishing an operation strategy for self-driving cars based on the situation in which negative delay/conflict occurs. ...
Article
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As new mobility called automated vehicles (AVs) appears on the road, positive effects are expected, but in fact, unexpected adverse effects may arise due to the mixed traffic situation with human-driven vehicles (HVs). Prior to the commercialization of AVs, a preliminary review and preventive measures are required, and among them, the interaction between the existing vehicle and the new mobility and the interaction with the infrastructure must be considered. Therefore, we propose (i) the positive–negative effect of introducing AVs in a mixed traffic situation and (ii) the optimal operation plan for the dedicated lane for AVs. First, the effect of introducing AVs considering the interaction between vehicles in the mixed traffic situation showed mostly positive such as speed increase, delay time reduction, and capacity increase. However, in a 75% Market Penetration Rate (MPR) environment of all levels of Service (LOS), the effect was diminished compared to the previous MPR. This is contemplated to be the result of a conflict caused by the operation of some HVs (including heavy vehicles) behavior as obstacles in the situation where most of the vehicles on the road are AVs. Based on the previous result, we deployed the dedicated lane to resolve the negative effect in the 75% MPR environment and proposed an optimal operation strategy for the AVs dedicated lane from the perspective of operational efficiency for a more feasible operation. Given the 75% MPR, the Mixed-Use operation strategy of High-Occupancy Vehicles (HOV) and AVs is ascertained as the most suitable operation strategy. This implies that even in the era of AVs, the influence of other vehicles (e.g., heavy vehicles, other mobility) must be considered. This study is significant by considering the negative effects of the introduction of AVs and presenting an optimal operation strategy for dedicated lanes, and it can expect to be used as a new strategy as part of the Free/Expressway Traffic Management System (FTMS) applicable in the era of autonomous driving.
... However, under the present legal system, trucks are allowed to run on designated lanes, and there have been no studies on the new operational strategy view of the situation in which there is no platoon dedicated lane. e mobility performance and merging characteristics were evaluated in the previous studies for identifying the effectiveness of truck platooning [20,21]. However, it is necessary to evaluate the traffic safety of mixed traffic flow by identifying the interactions between truck platoons and general vehicles. ...
... e other consideration is that, according to the Korean Road Traffic Act, the trucks must travel in the rightmost lane on a three-lane freeway segment, which is the designated lane for trucks in Korea. Existing studies evaluated the effectiveness when the leftmost lane was used for the high-occupancy lane (HOV) or dedicated lane [21,23]. On the other hand, this study conducted simulation experiments based on the current Korean traffic regulation that trucks should travel in the designated rightmost lane on freeways. ...
Article
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Vehicle platooning service through wireless communication and automated driving technology has become a reality. Vehicle platooning means that several vehicles travel like a train on the road with a minimum safety distance, which leads to the enhancement of safety, mobility, and energy savings. This study proposed a framework for exploring traffic mobility and safety performance due to the market penetration rate (MPR) of truck platoons based on microscopic traffic simulations. A platoon formation algorithm was developed and run on the VISSIM platform to simulate automated truck maneuvering. As a result of the mobility analysis, it was found that the difference in network mobility performance was not significant up to MPR 80%. Regarding the mobility performance of the truck-designated lane, it was found that the average speed was lower than in other lanes. In the truck-designated lane of the on-ramp section, the average speed was identified to be approximately 33% lower. From the viewpoint of network safety, increasing the MPR of the truck platoon has a positive effect on longitudinal safety but has a negative effect on lateral safety. The safety analysis of the truck-designated lane indicated that the speed difference by lane of MPR 100% is 2.5 times higher than that of MPR 0%. This study is meaningful in that it explores traffic flow performance on mobility and safety in the process of platoon formation. The outcomes of this study are expected to be utilized as fundamentals to support the novel traffic operation strategy in platooning environments.
... Li et al. [47] systematically conducted a detailed survey to review the investigations on the utilization of AVs to improve urban traffic control in mixed traffic environments, ranging from the intersections to the network. According to the simulation results conducted by Xiao et al. [48], it is observed that the capacity of mixed traffic tends to decrease when the penetration rate of AVs falls below 30%. ...
Article
With the evolution of technologies related to automated vehicles (AVs), vehicles with automation are increasingly approaching large-scale deployment nowadays. This research concentrates on mixed traffic scenarios in the near future, which capitalize on the implications of AVs on the transportation system and environment. How to co-exist with AVs in a complex environment is quite an unfamiliar challenge for human drivers of conventional vehicles. To conquer the difficulty, we investigate the behavioral response of human-driven vehicles (HVs) to AVs in multiple mixed traffic situations based on the real-world trajectory dataset and propose the driving characteristic indicator based on machine learning to conduct the quantitative comparison of different car-following (CF) behaviors. Additionally, to precisely replicate the driving features of HVs and longitudinal control of AVs in mixed traffic, a microscopic behavior modeling framework consisting of model-based and data-driven CF strategies is designed, which accurately reproduces the sophisticated microscopic behavior and maintains the interpretability of the intrinsic controller mechanism. Furthermore, simulation experiments on a real-world urban scale network in Suzhou, China are performed to thoroughly evaluate the implications of widespread implementation of AVs under different market penetration rates (MPRs). The result indicates that the low penetration rate may exert adverse effects on the mixed traffic environment.
... Considering operations of CAV platoons in mixed traffic, Liu et al. (2018) also simulated positive impacts of both CAV dedicated lanes and CAV platooning operations on mixed traffic capacity improvement. Further, HOV (High Occupancy Vehicle) lane is considered as variable CAV dedicated lane in simulations (Xiao et al. 2019). It is indicted that CAVs would cause interferences to traditional traffic flow if CAV penetration rate is below 30 %, which made reductions of mixed traffic capacity. ...
Article
Recently, the market has witnessed the emergence of intelligent vehicles equipped with diverse functionalities. Among these are connected automated vehicles (CAVs) boasting a comprehensive platooning capability, and connected vehicles (CVs), which essentially refer to human-driven vehicles (HVs) equipped with connectivity features. As a result, CAVs, CVs, and regular human-driven vehicles (RVs) will form a mixed CAV-CV-RV flow to affect stability of existing traffic flow, which is an important characteristic of traffic flow operations. This paper investigates stability of this new mixed CAV-CV-RV flow, explores effect of CVs on stability, and proposes CV management strategy aimed at achieving a stable traffic flow. We firstly establish definition of the novel mixed flow comprising CAVs, CVs, and RVs. Subsequently, we present a general analytical approach for evaluating stability of this mixed flow. Then we undertake an empirical study that incorporates car-following models, validated using real experiments involving the aforemen-tioned vehicle types. Based on findings from our stability analysis, we proceed to propose a CV management strategy designed to guarantee stable conditions within this mixed traffic flow. Results indicate the effectiveness of the proposed general analytical method in assessing influences of various system factors on stability of this new mixed flow. Subsequent to an application of the analytical method, empirical study uncovers a noteworthy finding that CVs prove to be more effective than CAVs in ensuring stable conditions within the mixed flow. Then we can manage market proportion of CVs in order to achieve stable mixed flow, according to varying CAV penetration rates. Specifically, some interesting lessons are learned based on the empirical study: (i) to guarantee stable operations of mixed traffic flow, about one third of CVs are needed to be among HVs, before CAVs running on road (CV-RV mixed flow); (ii) management strategy for stable flow requires an increase of minimum CV proportion among HVs from 33% to 55%, as CAV penetration rates increase up to 50%; (iii) when CAV penetration rates are greater than 50%, the required minimum CV proportion for ensuring traffic flow stability decreases with the increase of CAV penetration rates.
... Ma et al., 2022), which may result in higher valence of perception of AV platoons than if they shared multiple lanes with normal vehicles. However, dedicated lanes for AVs and AVs that form "lines" in a single lane may cause speed reductions due to increased lane changes to enter and exit the dedicated lane or line in a shared lane; they also exhibit poor performance under low AV penetration conditions (Xiao et al., 2020). Limitations of dedicated and single-line lanes have led researchers to propose partially-dedicated lanes in which normal vehicles may follow a group of collocated AVs across multiple lanes (cf. ...
... Analogously, Li and Wang [11] struck a trade-off among driving comfort, fuel efficiency, and traffic throughput with CACC. Moreover, it is shown that CACC can dramatically mitigate the congestions on freeways if the market penetration rate of CACC exceeds 40% [12]. ...
Article
Cooperative Adaptive Cruise Control (CACC) is a promising technology for improving the capacity and energy efficiency of the ground transportation system. In this paper, a novel CACC control scheme is proposed to deal with the adverse impacts of both inter- and intra-vehicle network delays. First, a hetero-integration poly-net (PN) loop delay analysis method is presented to clarify the system delays in CACC considering both inter- and intra-vehicle network influences. A mathematic equation is put forward to calculate the upper bound of the PN loop delays. Then a collaborative software-defined network scheme is presented to deal with the PN loop delays, which consists of the application/strategy, network-control and network-data planes. In the network-control plane, a fraction-type basic period scheduling method is adopted. In the application/strategy plane, a delay-tolerant model predictive controller is designed for decision-making while a combination of an H<sub>∞</sub> controller and a linear quadratic regulator is adopted for acceleration tracking control against local intra-vehicle network delays. Finally, the proposed scheme is verified under a variety of scenarios based on comprehensive Hardware-in-the-Loop tests.
... This work is the first to propose a deep learning approach for DAS feature extraction that can be leveraged in ITS for detecting the size and occupancy of vehicles. Advances in intelligent traffic flow such as Cooperative Adaptive Cruise Control (CACC) have raised the question of re-purposing existing road networks, and HOV lanes in particular, to reduce congestion [28]. In this context, it is necessary to distinguish the sizes and occupancy of vehicles moving within the road network. ...
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Intelligent transport systems (ITS) are pivotal in the development of sustainable and green urban living. ITS is data-driven and enabled by the profusion of sensors ranging from pneumatic tubes to smart cameras. This work explores a novel data source based on optical fibre-based distributed acoustic sensors (DAS) for traffic analysis. Detecting the type of vehicle and estimating the occupancy of vehicles are prime concerns in ITS. The first is motivated by the need for tracking, controlling, and forecasting traffic flow. The second targets the regulation of high occupancy vehicle lanes in an attempt to reduce emissions and congestion. These tasks are often conducted by individuals inspecting vehicles or through the use of emerging computer vision technologies. The former is not scale-able nor efficient whereas the latter is intrusive to passengers' privacy. To this end, we propose a deep learning technique to analyse DAS signals to address this challenge through continuous sensing and without exposing personal information. We propose a deep learning method for processing DAS signals and achieve 92% vehicle classification accuracy and 92-97% in occupancy detection based on DAS data collected under controlled conditions.
... Many scholars have been committed to the study of methods to improve the efficiency of highway traffic and alleviate highway congestion [1][2][3].Therefore, many methods to solve highway congestion have been put forward, and making vehicles run in a platoon is one of the effective methods [4][5][6]. During the driving process, the driving behavior of all following vehicles follow the leading vehicle. ...
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The mixed platoon including human driving vehicles (HVs) and connected automated vehicles (CAVs) are becoming more common. In order to alleviate the traffic congestion of highway, we present a control strategy of mixed platoon based on vehicle grouping with abnormal communication for two-lane. First, we grouped the vehicles on the road into many small platoons according to the spatial location of the CAVs, and then proposed the CAVs control algorithm under the mixed platoon. Based on this, combined with the vehicle dynamics characteristics, we analyzed the string stability of the mixed platoon. In addition, by considering the abnormal communication of CAVs during driving, we propose a control strategy for vehicle split and vehicle formation in the two-lane situation. Through VISSIM verification, it can be seen that the method proposed in this paper has a significant effect on the improvement of mixed traffic efficiency.
... Dedicating an existing highway lane to CAVs implies restricting MVs from using one lane of the motorway which could significantly increase their travel time if the actual share of CAVs in traffic or penetration rate (PR) of CAVs is lower than the lane saturation level (Ivanchev et al., 2017;Van Arem, Van Driel, Visser, 2006). So, exploiting the beneficial implications of a DL would only be possible when we reach to moderate PRs around 30-50% (Ivanchev et al., 2017;Van Arem, Van Driel, Visser, 2006;Vander Laan & Sadabadi, 2017;Xiao, Wang, & Van Arem, 2020;Madadi, Van Nes, Snelder, & Van Arem, 2021). This raises the question as to how would be the behavioural adaptation of MV drivers at moderate PRs of CAVs just before we can implement a DL. ...
Article
Connected and automated vehicles (CAVs) are expected to enhance traffic efficiency by driving at shorter time headways, and traffic safety by shorter reaction times. However, one of the main concerns regarding their deployment is the mixed traffic situation, in which CAVs and manually driven vehicles (MVs) share the same road. This study investigates the behavioural adaptation of MV drivers in car-following and lane changing behaviour when they drive next to a dedicated lane (DL) for CAVs and compares that to a mixed traffic situation. The expectation is that in a mixed traffic situation, the behavioural adaptation of MV drivers is negligible due to lower exposure time and scarce platoons, while concentrating the CAVs on one dedicated lane may cause significant behavioural adaptation of MV drivers due to a higher exposure time and conspicuity of CAV platoons. Fifty-one participants were asked to drive an MV on a 3-lane motorway in three different traffic scenarios, in a fixed-base driving simulator: (1) Base, only MVs were present in traffic, (2) Mixed, platoons of 2–3 CAVs driving on any lane and mixed with MVs, (3) DL, platoons of 2–3 CAVs driving only on a DL. The DL was recognizable by road signs and a buffer demarcation which separated the DL from the other lanes. A moderate penetration rate of 43% was assumed for CAVs. During the drives, the car following headways and the accepted merging gaps by participants were collected and used for comparisons of driving behaviour in different scenarios. Based on the results, we conclude that there is no significant difference in the driving behaviour between Base and Mixed scenarios at tested penetration rate, confirming our research expectation. However, in DL scenario, MV drivers drove closer to their leaders specially when driving on the middle lane next to the platoons and accepted shorter gaps (up to 12.7% shorter at on-ramps) in lane changing manoeuvres. Dedicating a lane to CAVs increases the density of CAV platoons on one lane and consequently their conspicuity becomes higher. As a result, MV drivers are influenced by CAV platoons on a DL and imitate their behaviour. The literature suggests that dedicating a lane to CAVs improves the traffic efficiency by providing more possibilities for platooning. This study shows that implementing such a solution will affect the driving behaviour of human drivers. This should be taken into consideration when evaluating the impacts of dedicated lanes on traffic efficiency and traffic safety.
... There is rich literature about the influence of CACC vehicles on traffic flow properties, such as travel cost, safety, fuel efficiency, and emissions, among others. Some recent studies Makridis et al. 2020;Milakis et al. 2017;Qin et al. 2019;Shladover 2018;Xiao et al. 2019) were reviewed for a basic understanding on this topic. ...
Article
String stability analysis is one of key factors to understanding traffic flow dynamics. Cooperative adaptive cruise control (CACC) vehicles are desired to enhance stability of vehicular flow by monitoring multiple vehicles. From the perspective of mixed traffic, this study proposes a generalized analysis method for CACC feedback gains to achieve stable mixed flow. To deal with this, a random mixed flow is divided into general small platoons, in which one tail CACC monitors multiple vehicles ahead. These general platoons with different lengths are defined as connected vehicular systems. Based on the generalized car-following models, transfer function theory is employed to derive string stability criteria that can keep these connected vehicular systems stable for all possible vehicle speeds. A case study is also carried out to validate usability of the proposed generalized work. The proposed generalized method is applicable to various car-following models and large connected vehicular systems, thereby helping achieving the string stability enhancement of mixed traffic flow.
... ree cases of CAV lanes, as shown in Table 4, are implemented in the network: As revealed in previous studies [31,32,66,67], a managed lane may have a detrimental effect on traffic performance if implemented prematurely, that is, usually with an MPR less than 30%. erefore, in this study, we set CAV MPRs for "CAV-1" to start from 30%. ...
Article
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Managed lanes, such as a dedicated lane for connected and automated vehicles (CAVs), can provide not only technological accommodation but also desired market incentives for road users to adopt CAVs in the near future. In this paper, we investigate traffic flow characteristics with two configurations of the managed lane across different market penetration rates and quantify the benefits from the perspectives of lane-level headway distribution, fuel consumption, communication density, and overall network performance. The results highlight the benefits of implementing managed lane strategies for CAVs: (1) A dedicated CAV lane significantly extends the stable region of the speed-flow diagram and yields a greater road capacity. As the result shows, the highest flow rate is 3400 vehicles per hour per lane at 90% market penetration rate with one CAV lane. (2) The concentration of CAVs in one lane results in a narrower headway distribution (with smaller standard deviation) even with partial market penetration. (3) A dedicated CAV lane is also able to eliminate duel-bell-shape distribution that is caused by the heterogeneous traffic flow. (4) A dedicated CAV lane creates a more consistent CAV density, which facilitates communication activity and decreases the probability of packet dropping.
... A macroscopic evaluation of a dedicated AV lane policy on all highways for the city of Singapore has been presented in [9]. Additionally, a microscopic analysis of replacing High Occupancy Vehicle lanes with dedicated AV lanes has been performed in [10]. Those studies, however, model expected AV behaviour rather than trying to design its logic so that it benefits traffic conditions, which is the focus of our work. ...
Chapter
This paper explores the interaction between autonomous and human-driven cars on a microscopic level using an agent-based traffic simulator. More specifically, it deals with the design of driving logic models of “socially-aware” autonomous vehicles that can improve the performance of surrounding vehicles on the road. Congestion waves, which are created as a result of an abrupt stopping or a car joining a highway, are a known phenomenon in current traffic systems. Experiments performed, demonstrate how the presence of intelligent social vehicles on the road can reduce such effects by acting as a flexible medium between human-driven cars. Metrics to evaluate benefits ot our AV behaviour models under various states of traffic conditions/congestion are also proposed. Finally, results showing the effectiveness of these models are presented.
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The emergence of connected autonomous vehicles (CAVs) provides a possibility to develop an efficient and sustainable mobility option. To foster the adoption of CAVs, the dedicated CAV lanes have been widely discussed in terms of optimal planning and allocating infrastructures for CAVs. Meanwhile, a sensible operation manner of dedicated lanes is also crucial to reap the maximum benefits. In this paper, we propose a novel idea, i.e., the intermittent dedicated CAV lanes (IDCLs), which dynamically provide a separate right-of-way for human-driven vehicles (HVs) to maximize traffic efficiency and minimize environmental costs. To this end, we first tailor two multi-class queuing models as fundamental tools to evaluate the traffic state. A traffic emission model is proposed based on the proposed queuing models. Then, a queuing-based bi-objective optimization model, which aims to maximize the traffic throughput and minimize the green tax simultaneously, is developed for the optimal operation of IDCL. Subsequently, the non-dominated sorting genetic algorithm-II (NSGA-II) is employed to find the Pareto optimal solutions. Finally, numerical experiments are conducted under different market penetration rates (MPRs) of CAVs and various traffic intensities. The results reported in this paper help policymakers and authorities draw insights into the IDCL policy.
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Congestions and rear-end crashes are two undesirable phenomena of freeway traffic flows, which are interrelated and highly affected by human psychological factors. Congestions on freeways increase rear-end crash risk, and rear-end crashes can initiate or aggravate congestions. Since congestion are everyday problems, and crashes are rare events, congestion management and crash risk prevention strategies are often implemented through separate research directions. As a result, traffic control studies focusing on increasing efficiency may increase the risk of rear-end crashes, whereas those focusing on improving traffic safety may not necessarily be desirable from efficiency perspective. Both freeway traffic flow and safety management will be more challenging in the era of connected driving. In connected environments, the role of human psychological factors on the traffic flow dynamics and traffic safety will be much more pronounced. The motivation behind this Ph.D. research is to pave the way for traffic management scenarios that result in more efficient and safer freeway traffic in the era of connected driving. As such, the research aim is to develop a robust understanding of freeway traffic flow dynamics and their safety implications with respect to human psychological factors. This research selects the continuum framework to understand traffic flow dynamics and proactive safety assessment framework to understand the safety implications of traffic flow dynamics. A comprehensive and critical literature review is conducted to understand the state-of-the-art of continuum traffic flow models. The review effort aims to obtain a robust knowledge about existing discussions and debates over continuum models’ analytical properties and real-world performances. A major part of the review explores the research gaps in continuum models for the era of connected and automated vehicles (CAVs). It is found that none of the existing continuum models can describe the role of complex human psychological factors (e.g., risk perception) on traffic flow dynamics. As well, the critical review revisits the properties and issues with continuum models for both conventional and CAV traffic flows. The review aims to take a close look on a wide range of theoretical, practical, and behavioral issues that must be kept in mind when developing new continuum models. Next, this research conducts a comprehensive benchmarking study on single-pipe continuum models by using traffic data from the German A5 autobahn. Model families are examined based on the review effort, and suitable representative models are selected within the families. A set of benchmarking criteria is designed, ranging from the operational measures (e.g., delay and travel time) as well as the complex traffic phenomena (e.g., scattering, oscillations, capacity drop, and hysteresis phenomena). Suitable real-world traffic scenarios are carefully selected concerning the benchmarking criteria, and the selected models are comprehensively assessed for real-world scenarios. Based on the understanding obtained from the review and benchmarking efforts, a novel behavioural continuum model (Non-Equilibrium Traffic model based on Risk Allostasis Theory, i.e., NET-RAT) is developed. NET-RAT fills a huge gap in the literature, that is, lack of behavioural continuum models with respect to a well-established human factor theory. Perceived risk and preferred response time are selected as the major human psychological factors of the conventional and connected environment. Perceived risk is defined in terms of the proportion of stopping distance which is a car-following safety measure. The selected human psychological factors are incorporated into the full velocity difference car-following model (FVDM). A novel continuum model is derived from the extended FVDM, and the interplay between preferred response time and perceived risk is formulated within the well-established risk allostasis theory. The analytical properties of NET-RAT are explored in detail, and its relationship with the notable existing continuum models are discussed. NET-RAT’s performance against real-world traffic is investigated comprehensively and compared with the models studied in the benchmarking effort. The results demonstrates that NET-RAT outperforms the existing continuum models in the benchmarking effort regarding some aspects of real-world traffic, e.g., travel time estimation and qualitative propagation of jam front. It is shown that drivers that have higher perception of risk can aggravate congestions by increasing shockwave speeds. Such drivers, however, can stabilize traffic flow regardless of traffic conditions due to responding quickly to initial perturbations. On the other hand, those with lower perceptions of risk can reduce congestions, but can initiate traffic instabilities in the intermediately congested states due to increased response time. This research also explores the implications of NET-RAT for the environments, where drivers are provided with information about traffic and their risk perception may be affected. Next, this dissertation proposes a hybrid methodological framework combining probabilistic and machine learning models to develop the relationships between safety and macroscopic state variables within a flexible conflict-based safety assessment framework. Time spent in conflict is introduced as the total time spent by all vehicles in rear-end conflicts, where the conflict instances are defined based on the proportion of stopping distance and a flexible threshold. The proposed hybrid framework can assess the time spent in conflict for all underlying car-following interactions using only macroscopic state variables, and thus, overcoming the need for trajectory data. Besides, it provides an endogenous safety dimension to the fundamental relations of freeway traffic flows that can be utilized to balance freeway traffic flow efficiency and safety. For instance, control studies can utilize the proposed framework to minimize total travel time while also minimizing total time spent in conflict for crash-prone situations such as shockwaves and traffic oscillations. Finally, the proposed safety assessment model is utilized in conjunction with NET-RAT to investigate the safety implications of various driving behaviours in relation to risk perception. It is shown that drivers with low perception of risk spend more time in conflict rear-end conflicts during critical situations from safety perspective, e.g., when entering shockwaves and when undergoing stop-and-go waves. The proposed methodology in this Ph.D. is a pathway for unifying freeway traffic flow modelling and rear-end crash prevention in the era of mixed traffic, when human factors play significant role on both congestion and rear-end crashes.
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This paper shows the results of ex-ante impact assessment of automated vehicles on capacity of freeways using microscopic traffic flow simulation. The simulation was conducted for different penetration rates of automated vehicles in Germany´s national vehicle fleet, which were predicted using a newly developed vehicle cohort stock model. For this aim, the standard segments of German freeway infrastructure including basic, merge, diverge, and weaving segments were simulated. The resulting capacity increments were assigned to a country-wide traffic flow model of Germany. In the next step, an economic appraisal was conducted based on the methodology for the cost-benefit analysis used in the current German Federal Transport Infrastructure Plan (BVWP). The results reveal that the conservative driving behavior of automated vehicles, as foreseen by the current legislation, has a negative impact on the capacity of freeways. On the contrary, automated technologies that allow shorter headways between the vehicles, have the potential to increase the capacity of the freeway network by 30 % and reduce traffic delays significantly. However, small market penetration rates of automated vehicles do not lead to discernible capacity benefits and the potential benefits are likely to be realized at higher penetration into the traffic mix.
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Adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) are important technologies for the achievement of vehicle automation, and their effect on traffic systems generally is evaluated with microscopic traffic simulations. A successful simulation requires realistic vehicle behavior and minimal vehicle collisions. However, most existing ACC-CACC simulation studies used simplified models that were not based on real vehicle response. The studies rarely addressed collision avoidance in the simulation. The study presented in this paper developed a realistic and collision-free car-following model for ACC-CACC vehicles. A multiregime model combining a realistic ACC-CACC system with driver intervention for vehicle longitudinal motions is proposed. This model assumes that a human driver resumes vehicle control either according to his or her assessment or after a collision warning asks the driver to take over. The proposed model was tested in a wide range of scenarios to explore model performance and collision possibilities. The testing scenarios included three regular scenarios of stop-and-go, approaching, and cut-out maneuvers, as well as two extreme safetyconcerned maneuvers of hard brake and cut-in. The simulation results show that the proposed model is collision free in the full-speed-range operation with leader accelerations within -1 to 1 m/s² and in approaching and cut-out scenarios. Those results indicate that the proposed ACC-CACC car-following model can produce realistic vehicle response without causing vehicle collisions in regular scenarios for vehicle string operations.
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Autonomous vehicles are expected to significantly influence our daily travel. Despite the autonomous vehicles' potential to enhance safety and reduce congestion, energy consumption, and emissions, many studies suggest that the system level effects will be minimal at low market penetration rates. Introducing reserved lanes for autonomous vehicles is one potential approach to address this limitation as it increases autonomous vehicles' density within those lanes. However, preventing regular vehicles from using specific lanes can significantly increase congestion in other lanes. Accordingly, this study explores the potential effects of reserving one lane for autonomous vehicles on traffic flow dynamics and travel time reliability. A two-lane hypothetical segment with an on-ramp and a four-lane highway segment in Chicago, IL are simulated under different market penetration rates of autonomous vehicles. Three different strategies are evaluated: (1) mandatory use of the reserved lane by autonomous vehicles, (2) optional use of the reserved lane by autonomous vehicles, and (3) limiting the autonomous vehicles to operate autonomously in the reserved lane. Different policies based on different combinations of these strategies are simulated. It is found that optional use of the reserved lane without any limitation on the type of operation can improve congestion and reduce the scatter in fundamental diagram. Throughput analysis showed the potential benefit of reserving a lane for autonomous vehicles at market penetration rates above 50% for the two-lane highway and 30% for the four-lane highway. Travel time reliability analysis also revealed that optional use of the reserved lane is significantly beneficial.
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Cooperative Adaptive Cruise Control (CACC) systems are a candidate to improve highway capacity by shortening headways and attenuating traffic disturbances. Although encouraging results have been obtained until now, a wide range of traffic circumstances has to be investigated in order to get reliable CACC systems driving on real roads. Among them, handling both vehicle-to-vehicle (V2V) communications equipped and unequipped vehicles merging into the string of CACC vehicles is a commonly-mentioned challenge. In this paper, an algorithm for managing the transitions in response to cut-ins from V2V or non-V2V equipped vehicles is developed and tested using a string of four CACC vehicles. A CACC controller is implemented in four production Infiniti M56s vehicles and tested in real traffic, where non-V2V equipped vehicles can cut in. The effects of a vehicle performing a cut-out, are also investigated. Then, responses to cut-ins by equipped and non-equipped vehicles are simulated for longer strings of vehicles using car-following models for both the production Adaptive Cruise Control (ACC) system and the newly developed CACC controller. Results demonstrate that the CACC system is able to handle cut-in vehicles without causing major perturbations and also reducing significantly the impact of this maneuver on the following vehicles, improving traffic flow.
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Cooperative Adaptive Cruise Control (CACC) includes multiple concepts of communicationenabled vehicle following and speed control. This paper presents definitions and classifications to help clarify the distinctions among different types of automatic vehicle following control that are often conflated with each other. A distinction is made between V2V CACC, based on vehicle-vehicle cooperation, and I2V CACC, in which the infrastructure provides information or guidance to the CACC system (such as the target set speed value). In V2V CACC, communication provides enhanced information so that vehicles can follow their predecessors with higher accuracy, faster response, and shorter gaps, resulting in enhanced traffic flow stability and possibly improved safety. A further distinction is made between CACC, which uses constant-time-gap vehicle following (forming CACC strings), and automated platooning, which uses tightly-coupled, constant-clearance, vehicle-following strategies. Although ACC and CACC are examples of Level 1 automation, as defined by both SAE and NHTSA, the vehicle following performance that can be achieved under each scenario is representative of the performance that should be expected at higher levels of automation. Implementation of CACC in practice will also require consideration of more than the lowest level vehicle-following and speed regulation performance. Because CACC requires interactions between adjacent equipped vehicles, strategies are needed such as ad-hoc, local, or global coordination to cluster CACC vehicles. This paper discusses some of the challenges that must be overcome to implement the clustering strategies, and strategies for separating CACC clusters as they approach their destinations, since potential traffic improvements from CACC will be negated if the vehicles cannot disperse effectively.
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This paper studies the traffic assistance system consisting of different kinds of vehicles (manual, Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) vehicle). By using the application programming interface in microscopic-traffic simulation, the aim that constructing simulation framework of CACC platoon is achieved. Maneuvers like forming, adjusting, splitting, dismissing and joining in a platoon are implemented under the simulation platform. Then a platoon with 6 CACC vehicles is simulated to examine the interactions in a platoon and how they react to shockwaves microscopically, which in turn verify the driver model partly. Finally different market penetration and platoon size of CACC are tested. Results illustrate the lane capacity increased significantly when market penetration of CACC vehicles added, however platoon size have little impact on traffic capacity. These preliminary working will be a foundation for our future work in this area. (C) 2013 The Authors. Published by Elsevier Ltd.
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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.
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This paper describes the use of microscopic simulation to estimate the effect of varying market penetrations of adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) on highway capacity. The distribution of time gap settings that drivers from the general public used in a real field experiment were used in the simulation, making this the first study of the effects of ACC and CACC on traffic to be based on real data on driver usage of ACC and CACC. The results show that the use of ACC is unlikely to change lane capacity significantly. However, CACC is able to greatly increase capacity after its market penetration reaches moderate to high percentages. The capacity increase can be accelerated by equipping non-ACC vehicles with Vehicle Awareness Devices so that they can serve as the lead vehicles for CACC vehicles.
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This paper investigates two different longitudinal control policies for automatically controlled vehicles. One is based on maintaining a constant spacing between the vehicles while the other is based upon maintaining a constant headway (or time) between successive vehicles. To avoid collisions in the platoon, controllers have to be designed to ensure string stability, i.e the spacing errors should not get amplified as they propagate upstream from vehicle to vehicle. A measure of string stability is introduced and a systematic method of designing constant spacing controllers which guarantee string stability is presented. The constant headway policy does not require inter-vehicle communication to assure string stablity. Also, since inter-vehicle communication is not required it can be used in systems with mixed automated-nonautomated vehicles, e.g for AICC (Autonomous Intelligent Cruise Control). It is shown in this paper that for all the autonomous headway control laws, the desired control torques are inversely proportional to the headway time.
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The effects of Cooperative Adaptive Cruise Control (CACC) on traffic flow is an important issue as traffic flow stability, capacity and safety are concerned. In contrast to most research we focus on traffic flow stability. We use the Intelligent Driver Model and CACC algorithms to assess the effects. A recently field-tested and CACC-based advisory system is also evaluated as an intermediate solution. It is found that CACC can quickly damp shockwaves at lower penetration rates (50%) and that shockwaves move faster.
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We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. 82, 4360 (1999)]. We simulate these situations with a continuous microscopic single-lane model, the "intelligent driver model," using empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.
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Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles
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We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. {\bf 82}, 4360 (1999)]. We simulate these situations with a novel continuous microscopic single-lane model, the ``intelligent driver model'' (IDM), using the empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has practically the same effect as an on-ramp. Comment: Now published in Phys. Rev. E. Minor changes suggested by a referee are incorporated; full bibliographic info added. For related work see http://www.mtreiber.de/ and http://www.helbing.org/
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Modeling impacts of Cooperative Adaptive Cruise Control (CACC) on multi-lane freeway traffic can be challenging. It requires an accurate description of the formation and disengagement of CACC vehicle strings when CACC vehicles are mixed with manually driven vehicles in the traffic stream. It also needs to depict the behaviors of CACC vehicles under the influence of CACC operation strategies such as the CACC vehicle managed lane (ML) and implementing the Vehicle Awareness Devices (VAD), which are intended to enhance the CACC string operations. To address these challenges, we extended a state of the art CACC modeling framework to incorporate new algorithms that are essential to describe the interactions among the CACC vehicles and manually driven vehicles in mixed traffic. The updated modeling framework adopts a new vehicle dispatching model to generate the high-volume traffic flow expected to exist due to the CACC string operation. The framework also includes new lane changing rules and automated speed control algorithms that ensure realistic CACC vehicle behaviors at freeway on/off-ramp areas where traffic disturbances might frequently interrupt the CACC string operations. With the model updates, we can further reproduce traffic flow dynamics under the influence of the CACC operation strategies. The modeling capability of the presented framework has been verified via case studies on a simple 4-lane freeway segment with an on-ramp and an off-ramp and a complex 18-kilometer freeway corridor. The case study results indicate that the presented modeling framework not only quantifies the mobility improvements for the study sites under different CACC market penetrations and CACC operation strategies, but also discloses the mechanism that governs the improvement. This study creates a methodology that can estimate detailed kinematics of connected automated vehicles under realistic traffic environments. Findings produced by the methodology are helpful for the future development, implementation and management of the advanced transportation technologies.
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Cooperative Adaptive Cruise Control (CACC) allows vehicles to exchange real-time operational information wirelessly, enabling vehicles to travel in strings with shorter than normal time gaps between adjacent vehicles and ultimately increasing the freeway capacity. This study is intended to investigate the impact of CACC vehicle string operation on the capacity of multilane freeway merge bottlenecks, commonly found at on-ramp merging areas on urban freeways. Simulation experiments were conducted using CACC car-following models derived from field test data, together with lane-changing models of CACC vehicles and manually driven vehicles, as well as a maximum CACC string length and inter-string time gap constraint. Simulation results reveal that the freeway capacity increases quadratically as the CACC market penetration increases, with a maximum value of 3080 veh/hr/lane at 100% market penetration. The disturbance from the on-ramp traffic causes the merge bottleneck and can reduce the freeway capacity by up to 13% but the bottleneck capacity still increases in a quadratic pattern as CACC market penetration becomes larger. The findings suggest that there is a need to implement advanced merging assistance systems with CACC at merge bottlenecks for achieving the capacity improvement comparable with the observations at homogeneous freeway segments.
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This study presents a thorough microscopic simulation investigation of a recently developed model-based approach for per-lane density estimation, as well as on-ramp and off-ramp flow estimation, for highways in the presence of connected vehicles. The estimation methodology is mainly based on the assumption that a certain percentage of vehicles is equipped with Vehicle Automation and Communication Systems (VACS), which provide the necessary measurements used by the estimator, namely vehicle speed and position measurements. In addition, a minimum number of conventional flow detectors is needed. In the investigation, a calibrated and validated, with real data, microscopic multi-lane model is employed, which concerns a stretch of motorway A20 from Rotterdam to Gouda in the Netherlands. It is demonstrated that the proposed methodology provides satisfactory estimation performance even for low penetration rates of connected vehicles, while it is also shown that the method is little sensitive to the parameters (two in total) of the model utilized by the estimator.
Chapter
In the next decades, road transport will undergo a deep transformation with the advent of connected and automated vehicles (CAVs), which promise to drastically change the way we commute. CAVs hold significant potential to positively affect traffic flows, air pollution, energy use, productivity, comfort, and mobility. On the other hand, there is an increasing number of sources and reports highlighting potential problems that may arise with CAVs, such as, conservative driving (relaxed thresholds), problematic interaction with human-driven vehicles (inability to take decisions based on eye contact or body language) and increased traffic demand. Therefore, it is of high importance to assess vehicle automated functionalities in a case-study simulation. The scope of this paper is to present some preliminary results regarding the impact assessment of cooperative adaptive cruise control (CACC) on the case-study of the ring road of Antwerp, which is responsible for almost 50% of the traffic and pollution of the city. Scenarios with various penetration rates and traffic demands were simulated showing that coordination of vehicles may be needed to significantly reduce traffic congestion and energy use.
Article
This paper presents a thorough microscopic simulation investigation of a recently proposed methodology for highway traffic estimation with mixed traffic, i.e., traffic comprising both connected and conventional vehicles, which employs only speed measurements stemming from connected vehicles and a limited number (sufficient to guarantee observability) of flow measurements from spot sensors. The estimation scheme is tested using the commercial traffic simulator Aimsun under various penetration rates of connected vehicles, employing a traffic scenario that features congested as well as free-flow conditions. The case of mixed traffic comprising conventional and connected vehicles equipped with adaptive cruise control, which feature a systematically different car-following behavior than regular vehicles, is also considered. In both cases, it is demonstrated that the estimation results are satisfactory, even for low penetration rates.
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This paper provides formulations of traffic operational capacity in mixed traffic, consisting of automated vehicles (AVs) and regular vehicles, when traffic is in equilibrium. The capacity formulations take into account (1) AV penetration rate, (2) micro/mesoscopic characteristics of regular and automated vehicles (e.g., platoon size, spacing characteristics), and (3) different lane policies to accommodate AVs such as exclusive AV and/or RV lanes and mixed-use lanes. A general formulation is developed to determine the valid domains of different lane policies and more generally, AV distributions across lanes with respect to demand, as well as optimal solutions to accommodate AVs.
Conference Paper
A macroscopic approach modeling the penetration rate of Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) vehicles and its effect on traffic dynamics is investigated. Modeling is based on the introduction of a relaxation term in a gas-kinetic traffic flow (GKT) model that satisfies the time-gap principle of ACC or CACC systems and allows for consideration of mixed traffic of manual and ACC/CACC vehicles. The relaxation time is assigned to multiple leading vehicles in the CACC case; whereas in the ACC case only relates to the direct leading vehicle. Numerical simulations investigate the effect of the penetration rates of ACC and CACC equipped vehicles to traffic flow macroscopic stability, with respect to perturbations introduced in a ring road, and to flow characteristics in an open freeway with merging flow at an on-ramp.
Article
Cooperative adaptive cruise control (CACC) includes multiple concepts of communication-enabled vehicle following and speed control. Definitions and classifications are presented to help clarify the distinctions between types of automated vehicle-following control that are often conflated with each other. A distinction is made between vehicle-to-vehicle (V2V) CACC, based on vehicle–vehicle cooperation, and infrastructure-to-vehicle CACC, in which the infrastructure provides information or guidance to the CACC system (such as the target set speed value). In V2V CACC, communication provides enhanced information so that vehicles can follow their predecessors with higher accuracy, faster response, and shorter gaps; the result would be enhanced traffic flow stability and possibly improved safety. A further distinction is made between CACC, which uses constant-time-gap vehicle following (forming CACC strings), and automated platooning, which uses tightly coupled, constant-clearance, vehicle-following strategies....
Conference Paper
The incorporation of a macroscopic approach reflecting Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) traffic dynamics in a gas-kinetic (GKT) traffic flow model is presented. The approach is a novel one and is based on the introduction of a relaxation term that satisfies the time/space-gap principle of ACC or CACC systems. The relaxation time is assigned on multiple leading vehicles in the CACC case, whereas in the ACC case this relaxation time is only assigned to the direct leading vehicle. Numerical simulations investigate the effect of ACC and CACC to traffic flow macroscopic stability with respect to perturbations introduced in a ring road and to flow characteristics in open freeways with merging flows at an on-ramp. Following from the results, it can be deduced that CACC vehicles increase the stabilization of traffic flow, compared to ACC ones. Further, the proposed CACC approach can further improve the dynamic equilibrium capacity and traffic dynamics, especially at on-ramp bottlenecks.
Article
Automation may be assumed to have a beneficial impact on traffic flow efficiency. However, the relationship between automation and traffic flow efficiency is complex because behavior of road users influences this efficiency as well. This paper reviews what is known about the influence of automation on traffic flow efficiency and behavior of road users, formulates a theoretical framework, and identifies future research needs. It is concluded that automation can be assumed to have an influence on traffic flow efficiency and on the behavior of road users. The research has shortcomings, and in this context directions are formulated for future scientific research on automation in relation to traffic flow efficiency and human behavior.
Article
This paper examines the impact of having cooperative adaptive cruise control (CACC) embedded vehicles on traffic flow characteristics of a multilane highway system. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce traffic congestion resulting from the acceleration/deceleration of the operating vehicles. An agent-based microscopic traffic simulation model (Flexible Agent-based Simulator of Traffic) is designed specifically to examine the impact of these intelligent vehicles on traffic flow. The flow rate of cars, the travel time spent, and other metrics indicating the evolution of traffic congestion throughout the lifecycle of the model are analyzed. Different CACC penetration levels are studied. The results indicate a better traffic flow performance and higher capacity in the case of CACC penetration compared to the scenario without CACC-embedded vehicles.
Article
A proposed lane change model can be integrated with a car-following model to form a complete microscopic driver model. The model resembles traffic better at a macroscopic level, especially regarding the amount of traffic volume per lane, the traffic speeds in different lanes, and the onset of congestion. In a new approach, lane change incentives are combined for determining a lane change desire. Included incentives are to follow a route, to gain speed, and to keep right. Classification of lane changes is based on behavior that depends on the level of lane change desire. Integration with a car-following model is achieved by influencing car-following behavior for relaxation and synchronization, that is, following vehicles in adjacent lanes. Other improvements of the model are trade-offs between lane change incentives and the use of anticipation speed for the speed gain incentive. Although all these effects are captured, the lane change model has only seven parameters. Loop detector data were used to validate and calibrate the model, and an accurate representation of lane distribution and the onset of congestion was shown.
Article
Vehicle longitudinal control systems such as (commercially available) autonomous Adaptive Cruise Control (ACC) and its more sophisticated variant Cooperative ACC (CACC) could potentially have significant impacts on traffic flow. Accurate models of the dynamic responses of both of these systems are needed to produce realistic predictions of their effects on highway capacity and traffic flow dynamics. This paper describes the development of models of both ACC and CACC control systems that are based on real experimental data. To this end, four production vehicles were equipped with a commercial ACC system and a newly developed CACC controller. The Intelligent Driver Model (IDM) that has been widely used for ACC car-following modeling was also implemented on the production vehicles. These controllers were tested in different traffic situations in order to measure the actual responses of the vehicles. Test results indicate that: (1) the IDM controller when implemented in our experimental test vehicles does not perceptibly follow the speed changes of the preceding vehicle; (2) strings of consecutive ACC vehicles are unstable, amplifying the speed variations of preceding vehicles; and (3) strings of consecutive CACC vehicles overcome these limitations, providing smooth and stable car following responses. Simple but accurate models of the ACC and CACC vehicle following dynamics were derived from the actual measured responses of the vehicles and applied to simulations of some simple multi-vehicle car following scenarios.
Article
Cooperative adaptive cruise control (CACC) vehicles are intelligent vehicles that use vehicular ad hoc networks (VANETs) to share traffic information in real time. Previous studies have shown that CACC could have an impact on increasing highway capacities at high market penetration. Since reaching a high CACC market penetration level is not occurring in the near future, this study presents a progressive deployment approach that demonstrates to have a great potential of reducing traffic congestions at low CACC penetration levels. Using a previously developed microscopic traffic simulation model of a freeway with an on-ramp -- created to induce perturbations and trigger stop-and-go traffic, the CACC system's effect on the traffic performance is studied. The results show significance and indicate the potential of CACC systems to improve traffic characteristics which can be used to reduce traffic congestion. The study shows that the impact of CACC is positive and not only limited to a high market penetration. By giving CACC vehicles priority access to high-occupancy vehicle (HOV) lanes, the highway capacity could be significantly improved with a CACC penetration as low as 20%.
Article
This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.
Article
Previous research efforts have quantified the capacity of non-barrier-separated. high-occupancy vehicle (HOV) lanes. However, the majority of these efforts have focused on HOV lanes that usually operate well below capacity. In contrast, the 1-85 HOV lanes in Atlanta, Georgia, usually operate under constrained flow conditions during morning and afternoon peak periods. This provides an opportunity to assess the relative performance of the HOV lane to the adjacent general-purpose (GP) lanes, which also undergo constrained How conditions. This paper considers the relationship between the performance of the HOV and GP lanes by, examining speed differential effects as a function of congestion on GP lanes. The research provides evidence of a sympathetic reduction in vehicle speeds in the HOV lane. This is likely explained by the safety concerns of the HOV drivers associated with the potential for vehicles using the congested GP lanes to enter the HOV lane, as well as the safety concerns of HOV drivers looking for an acceptable gap to merge into the GP lanes to access a downstream exit ramp.
Article
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.
Article
This paper develops models to calculate an upper limit on per-lane throughput for an automated highway system with mixed vehicle classes and platooned operation. The models arc analytical and based on independent arrivals among the classes. The results indicate that a mixture of vehicle classes or categories can have u significant detrimental effect on vehicle capacity. With a single entrance lane, capacity drops by more than 40% when the traffic stream moves from 100% light vehicles to a 90%/10% split between light and heavy vehicles. The capacity drop is substantially less when different classes are allowed to queue in separate lanes, but still significant (a 20% drop). It also does not appear that sorting vehicles into destination groups at the point of entry is an effective strategy to enhance exit capacity. A separate model was developed to evaluate capacity losses at the point of exit, where exiting vehicles must be separated by a minimum distance that exceeds normal intra-platoon requirements. Our results show that capacity losses are moderate (10% or less) when less than 20% of vehicles exit at any particular off-ramp.
Conference Paper
The inter-vehicle separation during vehicle following is one of the most critical parameters of the automated highway system (AHS), as it affects both safety and highway capacity. The trade-off between capacity and safety gives rise to a variety of different AHS concepts and architectures. In this study we consider a family of AHS operational concepts. For each concept we calculate the minimum inter-vehicle spacing that could be used for collision-free vehicle following, under different road conditions. For architectures involving platoons we also use the alternative constraint of bounded energy collisions to calculate the minimum spacing that can be applied if we allowed collisions at a limited relative velocity in case of emergency stopping. The minimum spacing is used to calculate the maximum possible capacity that could be achieved for each operational concept
Article
Drivers were asked to execute last-second braking and steering maneuvers while approaching a surrogate target lead vehicle. This surrogate target was designed to allow safely placing naive drivers in controlled, realistic rear-end crash scenarios under test track conditions. Maneuver intensity instructions were varied so that drivers' perceptions of normal and non-normal braking envelopes could be properly identified and modeled for forward collision warning timing purposes. The database modeled includes 3536 last-second braking judgment trials. A promising inverse time-to-collision model was developed, which assumes that the driver deceleration response in response to a crash alert is based on an inverse time-to-collision threshold that decreases linearly with driver speed.
Article
We calculate bounds on per-lane Automated Highway System (AHS) capacity as a function of vehicle capabilities and control system information structure. We assume that the AHS lane is dedicated for use by fully automated vehicles. Capacity is constrained by the minimum inter-vehicle separation necessary for safe operation. A methodology for deriving the safe minimum inter-vehicle separation for a particular safety criterion is presented. The inter-vehicle separation, which depends on the vehicle braking capability, control loop delays and operating speed, is then used to compute site-independent upper bounds on AHS capacity for a given mix of vehicle classes. The sensitivity of the capacity with respect to the degree of inter-vehicle cooperation, check-in policies (governing minimum acceptable vehicle-braking capability), highway speed limits, and lane-use policies (governing the sharing of a lane by multiple vehicle classes) is also investigated. 1. INTRODUCTION The goal of an Automa...
Cooperative adaptive cruise control: Definitions and operating concepts
  • S E Shladover
  • C Nowakowski
  • X Y Lu
  • R Ferlis
S. E. Shladover, C. Nowakowski, X. Y. Lu, and R. Ferlis, "Cooperative adaptive cruise control: Definitions and operating concepts," Transp. Res. Record, J. Transport. Res. Board, vol. 2489, pp. 145-152, 2015. doi: 10.3141/2489-17.
Evaluation of cooperative adaptive cruise control (CACC) vehicles on managed lanes utilizing macroscopic and mesoscopic simulation
  • qom