Inter-vehicle Spacing Research Articles

Compensation control of commercial vehicle platoon considering communication delay and response lag

The real-time accurate control of vehicle is of great significance for the stability of platoon driving. To address the impact of random time-varying communication delays, communication packet loss, data disorder, and significant response lag of commercial vehicle on platoon control performance in non-ideal communication environment, a novel compensation control method for commercial vehicle platoon is proposed to overcome the abovementioned issues. The proposed method significantly improves the impact of communication issues and vehicle response lag on platoon control, ensuring platoon safety while reducing inter-vehicle spacing and spacing error, and maintaining platoon stability. In addition, this method combines the comprehensive compensation mechanism with the Distributed Model Predictive Controller (DMPC), avoiding the establishment of additional compensation control modules and effectively reducing the computational burden. The results under emergency braking condition show that, compared with the method without compensation, the proposed method significantly reduces inter-vehicle spacing and spacing error, reducing the average maximum spacing error from 29.25 m to 1.44 m, shortening the error convergence time of the platoon by 28 %, and ensuring platoon stability. Additionally, compared to the compensation method based on Kalman Filtering (KF) and Smith predictor, the proposed method can reduce the average maximum spacing error by 60 % while maintaining similar convergence time and platoon stability.

Constraint-following adaptive robust control for multi-vehicle system formation with collision avoidance

For the formation on unstructured road with complex road conditions, the rationality of constraint design and uncertainty compensation seriously affect the connected and autonomous vehicle (CAV) system performance. The system constraints are studied for safe and efficient formation driving, and an adaptive robust formation control scheme is proposed. First, for the desired configuration and global collision avoidance, a series of equality and unilateral inequality constraints are designed for inter-vehicle spacing. Second, a constraint handling scheme is proposed based on the diffeomorphism method, adjustable transformation function, and bounded constraint. Third, (possibly fast) time-varying but bounded multi-source uncertainty is considered, and then a self-adjusting leakage-type adaptive law is proposed to estimate the integrated uncertainty bound online. Fourth, the performance measure β is defined to evaluate the constraint-following error, and an adaptive robust control is proposed. The effectiveness of the proposed control scheme is verified by simulation. The results show that the proposed control renders the error to be uniformly bounded and uniformly ultimately bounded. The CAV system approximately follows the constraints, regardless of the uncertainty.

Distributed event-triggered constrained control for linear homogeneous vehicle platoons

In this paper, an event-triggered distributed safety-critical control scheme for cooperative adaptive cruise control (CACC) is presented. The approach merges two control actions. In the first block, a nominal controller that guarantees practical consensus of a platoon characterized by linear dynamics, while excluding the Zeno behavior which refers to the occurrence of an infinite number of events within finite time. It exploits a novel communication triggering condition (CTC) where the minimum inter-event times for all vehicles are lower bounded. The second block considers the physical limitations of the vehicles, i. e. it avoids unreasonable accelerations/decelerations, and it integrates safety measures in terms of collision avoidance by exploiting the concept of tunable input-to-state safe control barrier functions (TISSf-CBFs). To enhance the platoon cohesiveness, and to maintain a desired inter-vehicle spacing between the vehicles, a bidirectional communication strategy is utilized. Under this control strategy, acceleration transmissions occur intermittently at specific time instants rather than continuously. In conclusion, the proposed controller’s effectiveness is validated through simulation, where we show a significant reduction in communication under various scenarios.

Distributed adaptive sliding-mode control for 2-D plane vehicle platoon with prescribed performance and angle constraint

This paper focuses on the distributed adaptive sliding-mode control problem for two-dimensional (2-D) plane vehicle platoon with prescribed performance, angle constraints, and actuator faults. The quadratic spacing policy (QSP) is first adopted for the 2-D plane vehicle platoon to adjust the inter-vehicle spacing. The spacing error can converge within a finite time to the small region predetermined by a new finite-time performance function (FTPF). Meanwhile, a new transformed error function is introduced to convert the FTPF-constrained spacing errors into equivalent unconstrained ones. Besides, the property of the invertible nonlinear mapping function is used for the original system with the angle constraint to get a new unconstrained system. Moreover, a new controller based on hyperbolic tangent function is designed to handle actuator faults occurring multiple times over a period. Furthermore, the stability and string stability of the 2-D plane vehicle platoon are achieved through sliding-mode control. Finally, the simulation results validate the effectiveness of the proposed techniques.

Asynchronous Platoon Control for Connected Vehicles With Intermittent and Delayed Information Transmission

This technical note investigates the asynchronous platoon control problem for connected vehicles with intermittent and delayed information transmission under dynamically changing communication topologies. An asynchronous consensus based protocol is proposed for each vehicle based on the state information of its neighbors at discrete times with communication delays, in which the asynchrony means that each agent updates its dynamics at discrete time instants determined by its own clock. The update intervals and the communication delays are allowed to be arbitrary bounded. We employ nonnegative matrix theory and graph theory to prove that the vehicle platoon asymptotically reaches a desired inter-vehicle spacing and a common velocity, if the effective communication topology jointly contains a directed spanning tree. Furthermore, we show that the string stability of the platoon control system is attained under the predecessor-following topology. Finally, we present numerical examples to validate the theoretical results.

Should Autonomous Vehicles Collaborate in a Complex Urban Environment or Not?

A specialized version of collaborative driving is convoy driving. It is referred to as the practice of driving more than one vehicle consecutively in the same lane with a small inter-vehicle distance, maintaining the same speed. Extensive research has been conducted on convoys of heavy-duty trucks on the highway; however, limited research has studied convoy driving in an urban environment. The complex dynamics of an urban environment require short-lived collaboration with varying numbers of vehicles rather than collaborating over hours. The motivation of this research is to investigate how convoy driving can be realized to address the challenges of an urban environment and achieve the benefits of autonomous driving such as reduced fuel consumption, travel time, improved safety, and ride comfort. In this work, the best-fitted coalitional game framework is utilized to formulate the convoy driving problem as a coalition formation game in an urban environment. A hypothesis is formulated that traveling in a coalition is more beneficial for a vehicle than traveling alone. In connection with this, a coalitional game and an all-comprehensive utility function are designed, modeled, and implemented to facilitate the formation of autonomous vehicle coalitions for convoy driving. Multiple solution concepts, such as the Shapley allocation, the Nucleolus, and the Core, are implemented to solve and analyze the proposed convoy driving game. Furthermore, several coalition formation strategies such as traveling mode selection, selecting optimal coalitions, and making decisions about coalition merging are developed to analyze the behavior of the vehicles. In addition to this, extensive numerical experiments with different settings are conducted to evaluate and validate the performance of the proposed study. The experimental results proved the hypothesis that traveling in a convoy is significantly more beneficial than traveling alone. We conclude that traveling in a convoy is beneficial for coalition sizes of two to four vehicles with an inter-vehicle spacing of less than 4 m considering the limitations of an urban environment. Traveling in a coalition allows vehicles to save on fuel, minimize travel time and enhance safety and comfort. Furthermore, the findings of this research state that achieving the enormous benefits of traveling in a coalition requires finding the right balance between inter-vehicle distance and coalition size. In the future, we plan to extend this work by studying the evolving dynamics of the coalitions and the environment.

Communication delay-aware cooperative adaptive cruise control with dynamic network topologies-a convergence of communication and control

Wireless communication-enabled Cooperative Adaptive Cruise Control (CACC) is expected to improve the safety and traffic capacity of vehicle platoons. Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network (VCN) topologies. However, when the network is under attack, the communication delay may be much higher, and the stability of the system may not be guaranteed. This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies (DADNT). The main idea is that for various communication delays, in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error, the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing. To this end, a multi-objective optimization problem is formulated, and a 3-step Divide-And-Conquer sub-optimal solution (3DAC) is proposed. Simulation results show that with 3DAC, the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%, 10%, and 14%, respectively, compared with the traditional CACC with fixed one-vehicle, two-vehicle, and three-vehicle look-ahead network topologies, thereby improving the traffic efficiency.

Numerical Investigation of The Aerodynamics of Lorry Platooning Travelling through Road Tunnels

With potential benefits in drag reduction and fuel saving, the aerodynamics of vehicle platoons have been investigated for a wide range of cases in open space. When vehicle platoons travel in road tunnels, the platooning strategy could be affected by the tunnel size, the traffic lane, and the inter-vehicle spacing. This paper presents a detailed investigation of these effects by numerically simulating the aerodynamics of an eight-lorry platoon travelling through road tunnels. The slipstream velocity and pressure fields, flow structures, and drag forces are examined as the inter-vehicle spacing are varied from 0.1L to 1.5L, where L is the length of a single lorry. It is found that the airflow induced by the moving platoon in the large tunnel (two-lane tunnel) is weaker than that in the small tunnel (single-lane tunnel), but similar to the case in the open air. As a result, the drag reduction due to platooning is most significant in the small tunnel, while the results in the large tunnel and the open air are largely identical. It is further found that, owing to the efficient shielding, the drag reduction in the open air increases monotonically as the inter-vehicle spacing decreases. However, the flow fields in both small and large tunnels change pronouncedly when the inter-vehicle spacing is 0.25L, resulting in relatively larger drag coefficients at this spacing. These findings are less sensitive to the traffic lane. This study provides useful insight into the platooning strategy of a long lorry platoon.

Distributed Antittack Fault-Tolerant Tracking Control for Vehicle Platoon Systems Under Cyber-Physical Threats

Vehicle platoon systems are considered as automatous vehicles in a platoon-based driving pattern in which a following vehicle follows the preceding vehicle and maintains the desired vehicle spacing. This study investigates the leader-following tracking issue of vehicle platoon systems under cyber-physical threats with the distributed anti-attack fault-tolerant tracking control strategy. Vehicle platoon systems, complicated actuator faults in physical layer, and connectivity-mixed attacks in cyber layer are modeled, respectively. Decentralized fault-estimation unknown input observer and distributed anti-attack fault-tolerant tracking control designs are developed in an integrated control framework to guarantee the robust and resilient tracking property of estimation errors and platoon tracking errors as well as the reliable inter-vehicle spacing by virtue of attack activation rate and attack frequency metrics. Simulations validate the proposed distributed anti-attack fault-tolerant tracking control algorithm in pernicious cyber-physical threatened scenarios.

Distributed Robust Platooning Control for Heterogeneous Vehicle Group under Parametric Uncertainty and Hybrid Attacks

This study addresses the problem of distributed robust control resistance to vehicle parametric uncertainty and hybrid attacks in heterogeneous vehicular platoon systems. First, an invaded heterogeneous vehicular platoon system is modeled accompanied by the technique of inverse model compensation to deal with the problem of non-linearities in longitudinal dynamics, a nominal vehicle mass is introduced to tackle the problem of heterogeneity and variability of vehicle masses. Besides, we quantize the effects of false-data injection (FDI) and message-delay (MD) attacks and integrate them into the proposed heterogeneous platoon system. Additionally, to obtain the desired inner-vehicle stability of a heterogeneous platoon, an inner-vehicle <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_\infty $</tex-math></inline-formula> distributed robust stable controller is presented based on Lyapunov-Krasovskii functional. Finally, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathcal{L}}_2$</tex-math></inline-formula> -based string stability criterion is put forward to weaken the attacks' effects when they propagate along with the platoon. To explain the superiority of the derived theory more directly, simulations with two different control methods about the heterogeneous platoon under hybrid attacks are provided. The results show that, compared to regular platoon control method, the proposed robust controller performs better in achieving the desired inter-vehicle spacing tracking and can maintain string stability of the platoon.

Simulating Traffic-wake Effects in a Wind Tunnel

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Road-vehicle platooning is known to reduced aerodynamic drag. Recent aerodynamic-platooning investigations have suggested that follower-vehicle drag-reduction benefits persist to large, safe inter-vehicle driving distances experienced in everyday traffic. To investigate these traffic-wake effects, a wind-tunnel wake-generator system was designed and used for aerodynamic-performance testing with light-duty-vehicle (LDV) and heavy-duty-vehicle (HDV) models. This paper summarizes the development of this Road Traffic and Turbulence System (RT&lt;sup&gt;2&lt;/sup&gt;S), including the identification of typical traffic-spacing conditions, and documents initial results from its use with road-vehicle models.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;Analysis of highway-traffic-volume data revealed that, in an uncongested urban-highway environment, the most-likely condition is a speed of 105 km/h with an inter-vehicle spacing of about 50 m. Probability distributions for spacing and road speed were used to identify a range of suitable inter-vehicle spacings to target for wake conditions. Combining these data with previous research activities that examined the characteristics of road-vehicle wakes, three phases of development for the RT&lt;sup&gt;2&lt;/sup&gt;S were undertaken in multiple wind tunnels leading to a system using porous grids and sets of vertically-oriented vanes. Specific grid and vane combinations generate wake shapes, wind-speed deficits, flow-angularities, and turbulence representative of every-day traffic wakes. Lateral positioning of the system and rotation of the vanes provide wake positioning and flow characteristics representing a variety of wake-in-crosswind conditions, while being able to effectively change the lane of the wake-source vehicles.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;The results of two experiments are presented to document the influence of traffic wakes, via application of the RT&lt;sup&gt;2&lt;/sup&gt;S, on the aerodynamic performance of road vehicles. First, measurements are presented based on the use of a prototype version of the system with a 15%-scale DrivAer fastback model. Drag reductions from 10% to 31% and side-force-coefficient reductions in excess of 50% were observed for the DrivAer model, relative to uniform-flow conditions, for the 13 specific wake-like conditions replicated. The second set of experiments applied the final RT&lt;sup&gt;2&lt;/sup&gt;S design to testing of a 30%-scale tractor-trailer HDV model, which showed drag reductions as high as 15% for an HDV-wake configuration, with drag reductions of 2% measured for a compact-sedan-wake at 50 m effective forward distance, relative to uniform winds. For both sets of experiments, examining wake effects on LDV and HDV models, changes in aerodynamic performance are attributed in large part to reductions in effective dynamic pressure, but surface-pressure measurements indicate that flow-angularity variations also play a role in crosswind conditions.&lt;/div&gt;&lt;/div&gt;

Eco-driving policy for connected and automated fuel cell hybrid vehicles platoon in dynamic traffic scenarios

Cooperation of platooning vehicles enabled by eco-driving and connected and automated technology has shown considerable potential in energy saving and traffic efficiency improvement. However, affected by the impacts of the randomly changed states of traffic vehicles and the uncertainty of future road conditions, the adoption of eco-driving for the connected and automated fuel cell vehicle (CAFCHV) platoon in a dynamic traffic environment will encounter significant challenges. Additionally, improper inter-vehicle spacing can significantly affect operating safety and energy efficiency. To address this problem, a centralized variable spacing control strategy that adaptively adjusts with velocity and slope for the CAFCHV platoon is designed to calculate the optimal speed and promote energy allocation efficiency. In the upper control layer, gradient-based model prediction control (GRAMPC) is leveraged to calculate the optimal speed of the platoon, where the velocity of each vehicle can be regulated via its own and the surrounding vehicle's state and relative position. In the bottom layer, each vehicle in the platoon solves an MPC-based energy management strategy (EMS) to achieve power allocation in various power sources. Compared with the adaptive cruise control (ACC) driving manner, the simulation results regulated by the Planning manner display a considerable improvement in terms of the global cost, hydrogen consumption, battery degradation, and SOC by 1.36%, 1.48%, 2.47%, and 1.56%, respectively.

A MAS-Based Hierarchical Architecture for the Cooperation Control of Connected and Automated Vehicles

Complex traffic scenarios pose a challenge to the cooperation control of connected and automated vehicles (CAVs). Conventional platoon control or advanced driver-assistance systems only provide an isolated solution due to their inadequacies in systematic perspective. To this end, a multi-agent system (MAS) based distributed control architecture together with a hierarchical controller is proposed for the CAVs cooperation control system. The upper layer considers the potential states of a CAV in the platoon evolution (i.e., vehicle-cruising maneuver and vehicle-following maneuver) and elaborates the transition rules for discrete maneuvering behaviors. The lower layer includes the corresponding motion controller for each CAV. Artificial potential field (APF) combined with the distributed model predictive control algorithm is adopted to realize the integrated longitudinal, lateral and yaw motion control of CAVs. Next, inspired by the Pareto-optimal method for tackling the MAS-cooperation system, an optimal solution strategy is introduced to solve the CAVs cooperation problem from the viewpoint of the control theory. Furthermore, multi-constraints are designed to ensure a safety inter-vehicle spacing between CAVs, while the vehicle stability can also be guaranteed. The simulation results demonstrate that the MAS-based hierarchical control architecture can effectively handle the cooperation control of CAVs in the typical traffic scenarios. The real-time implementation of the proposed controller also proves the feasibility.

Distributed integrated sliding mode control via neural network and disturbance observer for heterogeneous vehicle systems with uncertainties

A distributed sliding mode control based on neural network and disturbance observer is investigated for heterogeneous vehicle systems in this paper. The vehicle systems in this paper consider both parameter uncertainty and disturbance. First, the radial basis function neural network is applied to estimate the parameter uncertainty owing to its universal approximation ability, and the disturbance observer is designed to compensate for the external disturbance. Compared with the existing adaptive methods, the disturbance observer can estimate the external disturbance directly and effectively. Then, constant time headway policy is employed to regulate the inter-vehicle distance and improve the string stability. Unlike most existing sliding mode control strategy for vehicle platoons, the string stability is achieved via employing sufficient conditions on the control parameters rather than employing coupled sliding mode control. Afterward, modified constant time headway policy is designed to reduce the effect of nonzero initial inter-vehicle spacing and improve the traffic density. Finally, the simulation results with constant time headway policy and modified constant time headway policy are provided to demonstrate the effectiveness and advantages of the proposed approaches.

Explicitly incorporating surrogate safety measures into connected and automated vehicle longitudinal control objectives for enhancing platoon safety

The concepts of Connected and Automated Vehicles (CAV) and vehicle platooning have generated high expectations regarding the safety performance of future transportation systems. Existing CAV longitudinal control research primarily focuses on efficiency and control stability, by considering different inter-vehicle spacing policies. In very few cases, safety was also considered as a constraint, but not in the main control objectives. Theoretically, stability can only guarantee that CAV platoons eventually achieve an equilibrium state but is unable to promise safety along the process of achieving equilibrium. It is important to note that CAV does not mean absolutely safe, and its longitudinal or platoon control safety performance depends on how the control algorithms are designed, how accurately it can detect and predict its lead vehicle’s (could be a human-driven vehicle) next move, and other practical factors such as control and communication delays. To optimize CAV platoon safety, this study integrates surrogate safety measures (SSM) and model predictive control (MPC) into CAV longitudinal control for trajectory optimization. SSM has been widely adopted for modeling the safety consequences of various vehicle control strategies and identifying near-crash events from either simulated or field-captured traffic data. This study directly incorporates three typical SSM into the longitudinal control objectives of CAV and constructs a state-space MPC algorithm to model how these SSM vary as a result of CAV dynamics. Numerical examples are provided to show the performance of these SSM-based optimal CAV longitudinal control methods under traffic flow perturbations. To further confirm the necessity of explicitly considering SSM in CAV longitudinal control and its effectiveness in reducing rear-end collision risk, the proposed methods are compared with three classical longitudinal control models that do not consider SSM based on microscopic traffic simulation. It is noted that all SSM-based optimal control methods perform better than others as manifested by some key risk indicators, demonstrating the importance of explicitly considering SSM and safety in CAV longitudinal control.

Collision Avoidance in Longitudinal Platooning: Graceful Degradation and Adaptive Designs

An externally positive system has the property of giving a nonnegative output for any nonnegative input. By making the inter-vehicle spacing a nonnegative output, this system property is significant for collision avoidance in platooning. Yet, existing platooning results based on external positivity just apply to adaptive cruise control (ACC): as ACC uses on-board sensing only, these results do not apply when on-board sensing is integrated with inter-vehicle communication, as in cooperative adaptive cruise control (CACC). This work provides an integrated external positivity design for CACC. When unreliable communication requires transitions between CACC and ACC, the design still guarantees graceful degradation in terms of collision avoidance and disturbance rejection. Such graceful transitions can be attained also in the presence of vehicle parameter uncertainty, via a suitable adaptive control design.

Vehicle Trajectory-Based Calibration Procedure for Microsimulation

In practice, traffic engineers and researchers calibrate microscopic driver behavior in microsimulation models using macroscopic inputs (e.g., aggregated traffic throughput) instead of microscopic inputs (e.g., inter-vehicle spacing and acceleration). This mismatch has naturally led to concerns that these models have not accurately captured the microscopic driver behaviors, despite the apparent goodness-of-fit in the macroscopic performance measures. There is renewed interest in trajectory-based calibration for microsimulation models given the recent improvements in data collection and data processing technologies. Toward this end, this project collected aerial vehicle trajectories using cameras attached to drones at three real-world sites (producing 800 ft trajectories) and a helicopter at one site (producing 1.2 mi trajectories). This study used these datasets to develop a new microsimulation model trajectory-based calibration method and calibrated four urban freeway models: I-270, I-15, I-75, and I-95. Next, this study calibrated models of the same four sites using macroscopic data (e.g., average segment speed and throughout). Finally, this study compared the two methods’ calibration accuracy to understand the benefits of the trajectory-based calibration method. The experimental results provided evidence that analysts should not trust traditional calibration methods to produce models with realistic vehicle trajectories. However, explicit integration of trajectories into the calibration process (i.e., hybrid calibration methods) can significantly improve the modeled trajectories’ realism. Calibrated model results were most impressive at I-75, which is the only site that collected data via helicopter, yielding significantly longer trajectories.

Platoon Tracking Control With Road-Friction Based Spacing Policy for Nonlinear Vehicles

This paper investigates the platoon control problems for a group of nonlinear vehicles, in which the road-friction coefficient between the vehicle and road is taken into consideration. When the road-friction coefficient is small, the platoon safety may be affected with small inter-vehicle spacing headway. Hence, to improve the vehicle platoon safety with various road frictions, a novel spacing policy is developed for the vehicle platoon. This spacing policy is obtained by optimizing a certain safety cost function, which contains both the vehicle positions and the road-friction coefficients. Accordingly, the vehicle platoon would automatically adjust the inter-vehicle spaces to match the road friction. On this basis, a nonlinear vehicle platoon control scheme is proposed such that the vehicles can asymptotically converge to the proposed spacing policy. Particularly, a state observer is developed to approximate the vehicle states, such that only the position measurements can be applied to the control scheme. Moreover, the stability of proposed platoon tracking system is strictly analyzed. In final, numerical simulations are provided to verify the effectiveness and feasibility of proposed approaches.

Cooperative Constrained Control of Autonomous Vehicles With Nonuniform Input Quantization

Responsive and highly controlled autonomous vehicles (AVs) on the road easily form platoons with small inter-vehicle gaps to increase traffic throughput and reduce energy consumption. Unlike human drivers, AVs typically employ discrete quantization signals and only generate finite discrete acceleration. Finite discrete acceleration easily causes unstable inter-vehicle gaps and inter-vehicle collisions, especially when there are inaccurate quantization parameters due to quantizer aging. Based on the backstepping technique, this paper proposes the cooperative constrained control algorithm under unknown quantization parameters for AVs with nonuniform input quantization and motion uncertainties. The control laws of each AV in the platoon only depend on the state information of its consecutive AVs. The position trajectories of consecutive AVs are constructed as inter-vehicle collision-free constraints to avoid emergency braking and inter-vehicle collisions. In addition, the consistent characteristic of two types of nonuniform quantizers (i.e., logarithmic quantizers and hysteresis quantizers) is proposed, and unknown disturbances in vehicle motion are compensated. The Lyapunov based local stability and string stability are proved. Numerical simulation shows that the control algorithm is applicable to AVs with either logarithmic quantizers or hysteresis quantizers. Compared with the previous control algorithms without considering input quantization and inter-vehicle collision avoidance, the control algorithm proposed reduces inter-vehicle spacing errors, avoids high acceleration, and avoids inter-vehicle collisions.

A reliability-based approach to evaluate the lateral safety of truck platoon under extreme weather conditions

The truck platoon is one of the most promising connected and autonomous vehicle (CAV) technologies that can reduce fuel consumption and emission, enhance traffic safety, and increase roadway capacity. It is predicted to become mainstream in the next decade. Therefore, it is imperative to fully investigate the safety issues of the truck platoon before its large-scale deployment. However, studies on the lateral safety of the truck platoon under extreme weather, especially crosswinds are still lacking. To fill such a research gap, the current study contributes to the literature by proposing a reliability-based framework to evaluate the safety of the truck platoon regarding incursion into neighboring lanes due to extreme weather, especially crosswinds. The proposed approach involved three main steps: (1) the computational fluid dynamics (CFD) simulation of the aerodynamics of the truck platoon; (2) the truck platoon driving simulation under crosswind; and (3) the advanced response surface model development and the reliability analysis. Four main factors regarding lateral safety of the platoon were considered: wind speed, road friction coefficients, driving speed, and inter-vehicle spacing. The maximum lateral displacement (MLD) was chosen as a measure of lateral safety. The results showed that there was a significant difference between the aerodynamics of a single truck and that of the truck platoon vehicles and the inter-vehicle spacing between trucks within the truck platoon barely influenced the MLD. The MLD was largest for the leading truck as compared to those of the following trucks. The inter-vehicle spacing didn’t have a significant influence on MLD when the inter-vehicle spacing is shorter than 1.5 times of the truck length, while the other factors impacted the MLD significantly. In addition, the support vector regression with the radial basis function outperformed the other response surface functions. Based on reliability analysis, the risk level of the truck platoon was quantified using the safety index, and the impact of contributing factors towards the safety index of the truck platoon was also evaluated. This study confirmed that the proposed framework could be applied to evaluate the lateral safety of the truck platoon. The findings provide important practical implications for the decision-making of transportation management agencies and tailored countermeasures in the CAV) environment.