Truck Platooning Research Articles

Opportunities and Barriers for Truck Platooning on Norwegian Rural Freight Routes

Truck platooning can potentially make road freight transportation safer and greener. Technological readiness, business opportunities, and acceptance of truck platooning have mainly been studied for multilane highways with ample truck volumes. Less is known about truck platooning in areas with low traffic volumes and challenging roads and weather conditions. This paper investigates the opportunities and barriers for truck platooning on Norwegian rural freight routes, through stakeholder interviews and realistic case examples. Given modest freight volumes, dispersed industry clusters, and challenging road conditions, this study identified several prerequisites to deploying platooning and achieving economic savings. The paper discusses the future steps required to organize platooning across carriers, ensure appropriate infrastructure, and gain acceptance among truck drivers, motorists, and other road users.

Analyzing Freight Truck Platoon Accessibility with Route Deviations

Truck platooning is emerging as a sustainable means of transporting goods and commodities to destinations. Platooning optimizes road space and contributes to reducing freight truck emissions. However, there has been limited research on freight truck platoon accessibility to the destination that is often necessary to understand the impact of routes on which platoon is deployed. This study develops an analytical formulation for platoon accessibility by considering the possibility of the detour of trucks forming a platoon. Analyses with four prominent interstates in California, CA, USA, show that accessibility with truck platooning on select lengths of the I-5 continues to increase for about an initial 165 miles, attains a maximum there, and starts to drop after. The other three freeways, I-10, I-405, and I-710, show a continuous increase in accessibility for their lengths and the number of ramps considered. The findings can have significant implications in determining the selection of freeway routes that could be regarded as facilitators for a truck platoon.

Vehicle Platooning Impact on Drag Coefficients and Energy/Fuel Saving Implications

In this paper, empirical data from the literature are used to develop general power models that capture the impact of a vehicle position, in a platoon of homogeneous vehicles, and the distance gap to its lead (and following) vehicle on its drag coefficient. These models are developed for light duty vehicles, buses, and heavy duty trucks. The models were fit using a constrained optimization framework to fit a general power function using either direct drag force or fuel measurements. The model is then used to extrapolate the empirical measurements to a wide range of vehicle distance gaps within a platoon. Using these models we estimate the potential fuel reduction associated with homogeneous platoons of light duty vehicles, buses, and heavy duty trucks. The results show a significant reduction in the vehicle fuel consumption when compared with those based on a constant drag coefficient assumption. Specifically, considering a minimum time gap between vehicles of $0.5 \; secs$ (which is typical considering state-of-practice communication and mechanical system latencies) running at a speed of $100 \; km/hr$, the optimum fuel reduction that is achieved is $4.5 \%$, $15.5 \%$, and $7.0 \%$ for light duty vehicle, bus, and heavy duty truck platoons, respectively. For longer time gaps, the bus and heavy duty truck platoons still produce fuel reductions in the order of $9.0 \%$ and $4.5 \%$, whereas light duty vehicles produce negligible fuel savings.

Comparison of the response of an instrumented pavement section under individual and platoon truck loading

ABSTRACT Truck platooning is a recent solution proposed to optimise road transportation. Platooning can help improve transport efficiency and road safety, reduce traffic congestion, fuel consumption and greenhouse gases emissions. Considering that truck platoon configurations are new, studying their impact on pavement response and damage is crucial. In this context, this study presents the results obtained in a full-scale experiment designed to evaluate the structural responses of a test track subjected to the pass of trucks under two configurations: individual and platoon. The pavement was instrumented to measure the transverse and longitudinal strains at the bottom of the asphalt layers of the pavement structure. Strains were measured under two test configurations, individual trucks and platoons, for four vehicle speeds: 40 , 60 , 70 , and 80 km/h. In order to consider the weather influence, two test campaigns were performed, one during the winter and the other during the summer. The study's main conclusion is that by managing inter-truck distances, truck speeds, lateral deviation (wandering), time, and periods of circulation, it is possible to minimise the impact of platooning trucks on the pavement's structure responses.

Fatigue Life Predictions for a European Pavement Test Section Subjected to Individual and Platoon Truck Configurations

Truck platooning for the transportation of loads is a strategy recently proposed by the automotive sector to cope with traffic congestion, fuel consumption, and operational costs. This new way of configuring trucks changes the typical pressures pavements structures experience. For this reason, the research efforts of the pavement sector should be aligned with the automotive sector to propose road-friendly platoon configurations. This is one of the objectives of the European project ENSEMBLE. ENSEMBLE, as indicated by its acronym, works on ENabling SafE Multi-Brand pLatooning for Europe. In this context, the present study presents a real scale test done in the Applus IDIADA facilities to evaluate the fatigue behavior of a pavement structure subjected to individual and platoon truck configurations. The effects of parameters such as traffic distribution through the year and by time of day, percentage of platoons, truck loads, number of trucks in platoon configuration, lateral wandering, and inter-truck distances were evaluated. The study’s findings revealed that the reduced rest times between trucks in the platoon configuration reduce the recovery time of the asphalt layers, increasing the fatigue damage to the pavement at high temperature conditions. This underlines the need for further research to allow the proper implementation of truck platoons. For example, research is needed to define strategies to make truck platoon configurations more pavement-friendly and analyze the costs associated with the changes in the required road maintenance/rehabilitation treatments, among others.

Fuel Efficient High-Density Platooning Using Future Conditions Prediction

A promising application of cooperative driving is high-density platooning, which main goal is to reduce fuel consumption by driving with inter-vehicle distances below ten meters. The prediction of factors influencing the platoon capability to drive with such inter-vehicle distances the derived safe inter-vehicle distances, drives the potential fuel saving. Our aim is to study the influence of the prediction, especially the prediction horizon, on the achieved fuel saving as a function of different maneuver parameters. The contributions of this paper are: introducing the concept of maneuver reference to distribute the effort of maneuvering in truck platooning; linking the fuel consumption to a compensation time, that is the time during which the platoon will counterbalance the fuel consumption by benefiting from the reduced air drag; presenting an optimization method for maximizing the fuel saving depending on some predictive quality of service parameters. To model the fuel consumption and the duration of the maneuvers, we use a lasso regressions on data obtained from simulation. We then use these regression models in our optimization framework, which is based on particle swarm optimization. We show that to benefit from high-density platooning, the magnitude order of the prediction horizon required by a five-truck platoon is minimum hundred seconds.

An Exact Algorithm for the Multi-Trip Container Drayage Problem with Truck Platooning

An Exact Algorithm for the Multi-Trip Container Drayage Problem with Truck Platooning

Crosswind Effects on Truck Platoon and Cooperative Strategy to Counteract Crosswind

Crosswind Effects on Truck Platoon and Cooperative Strategy to Counteract Crosswind

Improving Lateral Driving Stability of Truck Platoon Under Crosswinds of Long-Span Bridge Through Vehicle Bridge Cooperative System

Improving Lateral Driving Stability of Truck Platoon Under Crosswinds of Long-Span Bridge Through Vehicle Bridge Cooperative System

Stable and Sustainable Vehicle Integrated Control for Truck Platooning

Stable and Sustainable Vehicle Integrated Control for Truck Platooning

Effects of Traffic-related Environmental Factors on Acceptability and Safety of Truck Platooning for Peripheral Drivers: A Simulator Study

Effects of Traffic-related Environmental Factors on Acceptability and Safety of Truck Platooning for Peripheral Drivers: A Simulator Study

Examining Truck Platoon Configurations to Maximize Operational, Safety, and Environmental Performance

Examining Truck Platoon Configurations to Maximize Operational, Safety, and Environmental Performance

Numerical Analysis of Aeroacoustic Phenomena Generated by Truck Platoons

In recent years there has been dynamic progress in the development of fully autonomous trucks and their combination and coordination into sets of vehicles moving behind each other within short distances, i.e., platooning. Numerous reports from around the world present significant benefits of platooning for the environment due to reduced emissions, reduced fuel costs, and improved logistics in the transport industry. This paper presents original aerodynamic and aeroacoustic studies of identical truck column models. They are divided into four main stages. In the first, a truck model and three columns of identical trucks with different distances between the vehicles was made and tested using computational fluid dynamics (CFD). Two turbulence models were used in the study: k−ω shear stress transport (SST) and large eddy simulation (LES). The aim of the work was to determine the drag coefficients for each set of vehicles. The second stage of work included determination of sound field distributions generated by moving vehicles. Using the Ffowcs Williams–Hawkings (FW-H) analogy, the sound pressure levels were determined, followed by the sound pressure levels A. In order to verify the correctness of the work carried out, field tests were also performed and additional acoustic calculations were carried out using the NMPB-Routes-2008 and ISO 9613-2 models. Calculations were performed using SoundPlan software. The performed tests showed good quality of the built aerodynamic and aeroacoustic models. The results presented in this paper have a universal character and can be used to build intelligent transport systems (ITSs) and intelligent environmental management systems (IEMSs) for municipalities, counties, cities, and urban agglomerations by taking into account the platooning process.

A two-stage trajectory planning model for cooperative truck platooning on freeways

Truck platooning is considered as a promising approach to improve traffic stability and to reduce fuel consumption and emissions on freeways. This article develops a two-stage trajectory planning model for cooperative and automated trucks (CATs) traveling on freeways to minimize overall fuel consumption considering platooning time and velocity change. In the first stage, five different strategies are proposed to determine the permutation of the platoon given the initial states and travel information of CATs. Once the feasibility is confirmed, the model is formulated as a mixed-integer programming to optimize the trajectories of all CATs on the entire freeway section. The results from the numerical experiments show that the platooning time optimization (PTO) strategy has superior performance in optimizing overall platooning time. Moreover, the velocity change under the condition of maximum platooning time is generally lower for the PTO and the passing time minimum strategies. These characteristics make the PTO strategy combined with the trajectory optimization program a suitable application for cooperative truck platooning management.

Efficient Position Change Algorithms for Prolonging Driving Range of a Truck Platoon

Cooperative automated driving technology has emerged as a potential way to increase the efficiency of transportation systems and enhance traffic safety by allowing vehicles to exchange relevant information via wireless communication. Truck platooning utilizes this technology and achieves synchronized braking and acceleration, controlling two or more trucks simultaneously. This synchronized control makes driving with a very short inter-vehicle distance among trucks possible and reduces aerodynamic drag. This provides significant fuel consumption reduction, both in leading and trailing trucks, and achieves fuel-saving improvement. However, the static positioning sacrifices trucks in the front since they consume more fuel energy because of more air resistance than the rears. To solve this in-equivalent fuel consumption reduction benefit, this paper presents several heuristic algorithms to balance fuel consumption reduction and prolong the driving ranges by exploiting position changes among trucks in a platoon. Furthermore, the proposed algorithms try to reduce the number of position changes as much as possible to prevent any fuel waste caused by the unnecessary position change operations. In this manner, each truck in the platoon is likely to share a similar fuel consumption reduction with fewer position change counts, thus addressing the challenge of in-equivalent fuel savings distribution and obtaining optimal fuel efficiency. Our extensive simulation results show that the proposed algorithms can prolong the total distance by approximately 3% increased in two-truck platooning and even higher in six-trucks platooning of approximately 8%. Moreover, our proposed algorithms can decrease the position change count and ensure that trucks only switch to position arrangement once with no duplicate. Therefore, truck platooning obtains the maximum driving range with fewer position change counts, thus achieving efficient fuel saving.

A Bayesian regression analysis of truck drivers’ use of cooperative adaptive cruise control (CACC) for platooning on California highways

Cooperative Adaptive Cruise Control (CACC), as an advanced version of adaptive cruise control (ACC), automates brake and engine controls based on the information received from wireless V2V communications and remote sensors, enabling smaller vehicle-following time gaps. It can improve the safety of vehicle platooning and increase fuel savings. As an extension of our previous investigation of truck drivers’ acceptance of CACC, this case study investigates factors affecting the use of CACC for truck platooning. Nine commercial fleet drivers were recruited to operate two following trucks in a CACC-enabled string on freeways in Northern California. We analyzed the usage of CACC time gaps and its correlation with truck drivers’ stated preferences for these time gaps, and we found that the highest preferred Gap 3 (1.2 s) was used the most. Moreover, a Bayesian regression model was built to show that truck drivers are more likely to disengage CACC when driving in low-speed traffic or on downgrades where this CACC could not provide sufficient braking. In high-speed traffic or on upgrades, truck drivers are more likely to engage CACC, particularly at Gap 3. Truck position, however, does not affect truck drivers’ time gap selection. The findings encourage the adoption of CACC in the trucking industry through implementing driver-preferred time gaps and responsive braking systems, and operating on routes with minimal interference to truck speeds.

Determining Road Networks’ Platoonability

Truck platooning has several benefits over traditional truck mobility. Platooning improves safety and reduces fuel consumption up to 15%, depending on platoon configuration. Although platooning benefits are quantifiable, platooning routes are not identified. Many factors are relevant to identifying these routes. For efficient platooning, a truck platoon needs to travel at a constant high speed for an extended distance. In addition, platoon integrity should be preserved from interfering vehicles and frequent ramps that may compromise the robustness and safety of the operation. This study presents an easy to implement approach to determine platoonable routes based on platoon configuration, speed, roadway volume/capacity, and number of highway exit and entry conflicts. Based on this approach, each roadway section is assigned a level of platoonability from one to five, where one is the most platoonable. This approach was used to analyze the highway network in Illinois. According to this approach, 89% of the interstates and freeways in Illinois are platoonable under average traffic conditions.

Edge-based platoon control

Platooning of cars or trucks is one of the most relevant applications of autonomous driving, since it has the potential to greatly improve efficiency in road utilization and fuel consumption. Traditional proposals of vehicle platooning were based on distributed architectures with computation on board platoon vehicles and direct vehicle-to-vehicle (V2V) communications (or Dedicated Short Range Communication—DSRC), possibly with the support of roadside units. However, with the introduction of the 5G technology and of computing elements at the edge of the network, according to the multi-access edge computing (MEC) paradigm, the possibility emerges of placing control of platoons on MEC, with several significant advantages with respect to the V2V approach. For this reason, in this article we investigate the feasibility of vehicle platooning in an edge-based scenario where the control of vehicle speed and acceleration is managed by the network through its MEC facilities, possibly with a platooning-as-a-service (PaaS) paradigm. Using a detailed simulator, we show that, with realistic values of latency and packet loss probability, as well as of engines and inertia of vehicles, large platoons can be effectively controlled by MEC hosts. On the one hand, we unveil that platooning on the edge is a viable and robust solution. On the other hand, we also shed light on the necessity to consider realistic characteristics of vehicles and speed profiles, since they can yield severe, yet not critical, performance degradation with respect to simple models.

Describing I2V Communication in Scenarios for Simulation-Based Safety Assessment of Truck Platooning

V2X communication plays an important role in the transition towards connected, cooperative, automated driving. Wireless communication enables instant information exchange between vehicles (V2V) to support, e.g., platooning, and between the infrastructure and vehicles (I2V) to inform vehicles on, e.g., the local speed limit information or the approach of an accident location. In the Horizon 2020 HEADSTART project, we have shown how to test V2V communication in a scenario-based safety assessment framework. Safety assessment aims to determine the impact on safety in the case of potentially critical scenarios, e.g., due to, or in parallel to deterioration of communication. In this study, we extend this methodology with the incorporation of I2V communication. The developed method allows us to treat V2V and I2V communication independently. We demonstrate the method in the use case of an Intelligent Speed Adaptation I2V-functionality for platooning trucks. The practical implementation of test descriptions that consider the potential deterioration of communication signals in the standardized OpenSCENARIO format is shown. The study illustrates how tests are performed in a hardware-in-the-loop setup specifically developed for testing platooning functions. The availability of a test method that is capable of dealing with V2X communication is an important step towards the implementation of type approval methods for Cooperative, Connected and Automated Mobility (CCAM) systems.

Itinerary planning for cooperative truck platooning

A cooperative truck platoon is a set of virtually linked trucks driving with a small intra-vehicle headway enabled by connected and automated vehicle technologies. One of the primary benefits of truck platooning is energy savings due to the reduction of aerodynamic drag on the platooned vehicles. The focus of this paper is on scheduling travel itineraries of a given set of trucks to facilitate the formation of platoons to maximize energy savings. By constructing a time-expanded network, we formulate the problem as a minimum concave-cost network flow problem, and devise a few solution methods to find the optimal or high-quality solutions. The solution methods include an outer approximation algorithm for solving a mixed-integer convex minimization reformulation of the problem, a dynamic-programming-based heuristic scalable to large-scale instances, and a fast approximation algorithm with guaranteed performance for a restrictive version of the problem. All the proposed algorithms are examined and benchmarked on medium to large networks under various test scenarios. The numerical results demonstrate the efficiency of the proposed methods and their applicability in real-world settings.