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Cham : Springer International Publishing AG, 2022

1 online resource (245 pages)

ISBN 9783030886820 (electronic bk.)

ISBN 9783030886813

Lecture Notes in Intelligent Transportation and Infrastructure Ser.

Print version: Schirrer, Alexander Energy-Efficient and Semi-Automated Truck Platooning Cham : Springer International Publishing AG,c2022 ISBN 9783030886813

Intro -- Foreword by Richard Bishop -- Foreword by Michael Nikowitz -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- Part I Contextualising Truck Platooning -- 1 Connecting Austria Project Outline -- 1.1 Connecting Austria in a Nutshell -- 1.2 Connecting Austria’s Objectives -- 1.3 Technology Domains of Connecting Austria and the Planned Testing Procedure -- 1.4 Connecting Austria Use Cases -- 1.4.1 Use Case 1: Trucks Entering the Motorway -- 1.4.2 Use Case 2: Truck Platoon Approaching a Hazardous Location -- 1.4.3 Use Case 3: Truck Platoon Leaving the Motorway -- 1.4.4 Use Case 4: Truck Platoon Crossing an Intersection -- 1.5 Challenges, International Uniqueness and Discussion -- 2 Truck Platooning Worldwide -- 2.1 Introduction -- 2.2 Opportunities and Challenges of Truck Platooning -- 2.2.1 Interoperability -- 2.2.2 Road Safety and Traffic Efficiency -- 2.2.3 Operation Costs and Fuel Consumption -- 2.2.4 Reduction of CO2 Emissions -- 2.2.5 Shortage of Professional Drivers -- 2.2.6 New Requirements for Vehicles and the Infrastructure -- 2.3 Conclusion -- References -- 3 Towards Truck Platooning Deployment Requirements -- 3.1 Requirements Related to Energy Efficient Truck Platooning -- 3.2 User and Other Road User Requirements -- 3.2.1 Truck Driver-Related Requirements -- 3.2.2 Other Road User-Related Requirements -- 3.3 Road Safety Requirements -- 3.4 Technical Requirements Related to C-ITS -- 3.5 Conclusion -- References -- 4 Research Design and Evaluation Strategies for Automated Driving -- 4.1 Benefits of Automated Driving -- 4.1.1 Requirements Conflict Efficiency Versus Safety -- 4.1.2 Requirements Conflict Safety Versus Comfort -- 4.1.3 Requirements Conflict Comfort Versus Effectiveness -- 4.1.4 Requirements Conflict Comfort Versus Efficiency -- 4.1.5 Requirements Conflict Traffic Versus Vehicle Efficiency.

11 Fuel Efficiency Assessment -- 11.1 Road Infrastructure Assessment -- 11.1.1 Risk-Rated Map -- 11.2 Driving Behaviour Assessment -- 11.3 Efficiency Assessment -- 11.3.1 General Feasibility of Platooning on a Road Segment -- 11.3.2 Economic Viability of Platooning on a Road Segment -- 11.4 Conclusion -- 12 Application of Fuel Efficiency and Traffic Efficiency Assessment -- 12.1 Fuel Efficiency Assessment in a Fleet Operator Case -- 12.2 Traffic Efficiency Assessment -- 12.3 C-ITS Assessment for Dynamic Traffic Control -- 12.4 Conclusion -- Reference -- Part III Towards Cooperative Truck Platooning Deployment -- 13 Road Safety Issues Related to Truck Platooning Deployment -- 13.1 Introduction -- 13.2 Legal Aspects for Platooning in Austria -- 13.2.1 Acquiring a Test Permission According to the Austrian Regulation on Automated Driving -- 13.2.2 Does the Current Law Facilitate Testing of Platoons on Austrian Roads? -- 13.2.3 Requirements for Platooning Tests in Austria from a Legal Point of View -- 13.3 Considerations for the Safety Potential of Platooning -- 13.3.1 Safety Potential of Platooning Compared to Existing Safety Assistance Systems -- 13.4 Assessment of Road Infrastructure with Respect to Safe Platooning -- 13.4.1 Performance of the On-Road Assessment -- 13.4.2 Analysis of Road Segments and Considerations for Platooning -- 13.5 Gap Acceptance of Car Drivers for Merging Between Trucks -- 13.6 Discussion -- References -- 14 Business Models, Economy and Innovation -- 14.1 Key Aspects of a Truck Platooning Business Model from a Road Operator’s Perspective -- 14.2 Trend Monitoring as a Key Feature for Business Model Development and Innovation -- 14.2.1 Relevance of Trend Monitoring for Business Model Development -- 14.2.2 Applying Trend Monitoring in the Context of Logistics and Automated Driving.

4.2 Entities with Effects on Automated Driving Performance -- 4.3 Additional Sources of Complexity -- 4.4 Development Procedures -- 4.5 Solution Concept -- 4.5.1 Scenario-Based Approach and Stochastic Simulation -- 4.5.2 Big Data Analytics and Machine Learning -- 4.5.3 Incident and Anomalies Detection -- 4.5.4 Naturalistic Driving and Behavioural Models -- 4.5.5 Effectiveness Rating -- 4.5.6 Cosimulation and Virtual Sensors -- 4.5.7 Complexity and Robustness Management -- References -- Part II Assessment Methodologies and Their Application -- 5 Truck Platoon Slipstream Effects Assessment -- 5.1 Computational Setup -- 5.1.1 Model Geometry and Virtual Wind Tunnel -- 5.1.2 Boundary Conditions -- 5.1.3 Heat Exchanger Model -- 5.1.4 Mesh Generation for Simulation -- 5.1.5 Flow Field Computation -- 5.2 Simulation Results and Discussion -- 5.2.1 Drag Coefficients -- 5.2.2 Fuel Savings -- 5.2.3 Mass Flow Through Heat Exchangers -- 5.3 Conclusion -- References -- 6 Validation of Truck Platoon Slipstream Effects -- 6.1 Introduction -- 6.2 Materials and Methods -- 6.2.1 Proving Ground -- 6.2.2 Heavy-Duty Vehicles -- 6.2.3 Sensors -- 6.2.4 Measurement Campaigns -- 6.2.5 Static Pressure -- 6.2.6 Data Preprocessing -- 6.3 Results -- 6.3.1 Static Pressure -- 6.3.2 Fuel Consumption -- 6.3.3 Comparison to Simulation Results -- 6.4 Discussion -- 6.4.1 Instrumentation -- 6.4.2 Measurement Campaign -- 6.4.3 Lessons Learned -- References -- 7 Simulation of Platoon Dynamics, Optimisation and Traffic Effects -- 7.1 Methodology for Scenario-Based Analysis -- 7.1.1 Traffic Detection -- 7.1.2 Naturalistic Driving and Field Operational Tests -- 7.1.3 Traffic Modelling -- 7.1.4 Development of Functions by Scenario Management -- 7.1.5 Evaluation and Analysis of Key Performance Indicators (KPIs) -- 7.1.6 Adaptation and Learning.

Correction to: A. Schirrer et al. (eds.), Energy-Efficient and Semi-automated Truck Platooning, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-3-030-88682-0.

14.2.3 Implications for Business Model Development Related to Logistics and Automated Driving -- 14.3 Discussion and Conclusion -- References -- 15 Advanced Powertrain Systems for Platooning-Capable Trucks -- 15.1 Introduction -- 15.2 -Emission Reduction by Different Application Domains -- 15.3 Ultra-low Emissions on Highways and Zero Emissions in Cities -- 15.4 Get the Right Infrastructure for Vehicle Energy Supply -- 15.5 Different Topologies for Truck Drives -- 15.5.1 Truck Propulsion Systems for Highway Domain -- 15.5.2 Truck Propulsion Systems for Urban Domain -- 15.6 Importance of Thermal Management Concepts for Truck Drives -- 15.6.1 Motivation -- 15.6.2 Materials and Methods -- 15.6.3 Results -- 15.6.4 Discussion -- 15.7 Cooling Concepts on the Example of H 2 Driven Trucks -- 15.8 Outlook -- References -- 16 How Platooning Research Enhances the European Innovation System -- 16.1 Introduction -- 16.2 Digital Road Infrastructure Leveraging ITS Systems in Europe -- 16.2.1 Selected Elements of the Current Situation -- 16.2.2 Potential Drivers of Socio-technical Transitions Ahead -- 16.2.3 Particular Demanding Situations for a European Innovation System -- 16.2.4 New Roles for Stakeholders -- 16.2.5 Dynamically Evolving Legal Framework -- 16.3 Discrepancy Between Customer Requirements and Eco-friendly Transport Logistics -- 16.3.1 Technical, Legal, and Social Aspects of C-ITS -- 16.3.2 Critical Discussion of C-ITS and the Needs of Society -- 16.4 Jointly Building Absorptive Capacity in Europe’s Innovation System -- References -- 17 Discussion -- 17.1 Traffic Safety and Legal Issues -- 17.2 Sustainability -- 17.3 Truck Platooning Deployment -- 17.4 Some Limitations and Cultural Blind Spots -- Correction to: Energy-Efficient and Semi-automated Truck Platooning.

4.2 Entities with Effects on Automated Driving Performance -- 4.3 Additional Sources of Complexity -- 4.4 Development Procedures -- 4.5 Solution Concept -- 4.5.1 Scenario-Based Approach and Stochastic Simulation -- 4.5.2 Big Data Analytics and Machine Learning -- 4.5.3 Incident and Anomalies Detection -- 4.5.4 Naturalistic Driving and Behavioural Models -- 4.5.5 Effectiveness Rating -- 4.5.6 Cosimulation and Virtual Sensors -- 4.5.7 Complexity and Robustness Management -- References -- Part II Assessment Methodologies and Their Application -- 5 Truck Platoon Slipstream Effects Assessment -- 5.1 Computational Setup -- 5.1.1 Model Geometry and Virtual Wind Tunnel -- 5.1.2 Boundary Conditions -- 5.1.3 Heat Exchanger Model -- 5.1.4 Mesh Generation for Simulation -- 5.1.5 Flow Field Computation -- 5.2 Simulation Results and Discussion -- 5.2.1 Drag Coefficients -- 5.2.2 Fuel Savings -- 5.2.3 Mass Flow Through Heat Exchangers -- 5.3 Conclusion -- References -- 6 Validation of Truck Platoon Slipstream Effects -- 6.1 Introduction -- 6.2 Materials and Methods -- 6.2.1 Proving Ground -- 6.2.2 Heavy-Duty Vehicles -- 6.2.3 Sensors -- 6.2.4 Measurement Campaigns -- 6.2.5 Static Pressure -- 6.2.6 Data Preprocessing -- 6.3 Results -- 6.3.1 Static Pressure -- 6.3.2 Fuel Consumption -- 6.3.3 Comparison to Simulation Results -- 6.4 Discussion -- 6.4.1 Instrumentation -- 6.4.2 Measurement Campaign -- 6.4.3 Lessons Learned -- References -- 7 Simulation of Platoon Dynamics, Optimisation and Traffic Effects -- 7.1 Methodology for Scenario-Based Analysis -- 7.1.1 Traffic Detection -- 7.1.2 Naturalistic Driving and Field Operational Tests -- 7.1.3 Traffic Modelling -- 7.1.4 Development of Functions by Scenario Management -- 7.1.5 Evaluation and Analysis of Key Performance Indicators (KPIs) -- 7.1.6 Adaptation and Learning.

7.2 Integral Safety and Advanced Driver Assistance Systems (ISS/ADAS) -- 7.2.1 Use Case-Based Representation of Requirements -- 7.2.2 System and Component Rating -- 7.2.3 Data Mapping, Representativeness of Use Cases -- References -- 8 Platoon Control Concepts -- 8.1 Introduction -- 8.2 Methodology Overview -- 8.3 Co-simulation-Based Validation -- 8.3.1 String Stability Considerations -- 8.4 Trajectory Optimisation Methodology -- 8.4.1 Optimisation Problem Formulation -- 8.4.2 Trajectory Optimisation for Approaching a Hazardous Location -- 8.4.3 Trajectory Optimisation for Crossing an Intersection -- 8.5 Distributed Model-Predictive Platoon Control -- 8.5.1 Safe-by-Design Local MPC Formulation -- 8.5.2 Validation of Collision Safety via Co-simulation -- 8.5.3 Safe Reduction of Inter-vehicle Distances -- 8.5.4 Situation-Aware Platoon Behaviour via V2V-Communication -- 8.5.5 Consideration of Varying Road Conditions -- 8.6 Conclusion -- References -- 9 Scenario-Based Simulation Studies on Platooning Effects in Traffic -- 9.1 Intersection Scenarios -- 9.1.1 Green Time Extension -- 9.1.2 Coordinated Drive-Away -- 9.1.3 Optimisation of Speeds and Distances Inside the Platoon -- 9.2 Application of Analytic Approaches: Highway Throughput Based on Platooning Headway -- 9.2.1 Analytical Models for the Traffic Throughput -- 9.2.2 Stochastic Variations -- 9.3 Theoretical Lower Limits on Intra-platoon Distance -- 9.3.1 Scenario Definition -- 9.3.2 Evaluation of KPIs -- 10 Energy-Efficient Internet of Things Solution for Traffic Monitoring -- 10.1 Introduction -- 10.2 Low Energy Internet of Things Traffic Monitoring System -- 10.2.1 Real-Time Object Detection -- 10.2.2 Sensor Fusion and Object Tracking -- 10.2.3 Traffic Flow Estimation -- 10.3 Traffic Flow Measurement Result -- 10.4 Discussion -- 10.5 Conclusion and Outlook -- References.

Correction to: A. Schirrer et al. (eds.), Energy-Efficient and Semi-automated Truck Platooning, Lecture Notes in Intelligent Transportation and Infrastructure, https://doi.org/10.1007/978-3-030-88682-0.

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