4.7 Article

Evaluation and modelling of the traffic flow effects of truck platooning

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2019.05.019

Keywords

Truck platooning; Vehicle automation; Traffic flow simulation; Traffic flow

Funding

  1. Amsterdam Institute of Advanced Metropolitan Solutions (AMS)
  2. 'Meaningful Human Control of Automated Driving Systems' project as part of the Responsible Innovation programme of the Netherlands Organization for scientific research NWO

Ask authors/readers for more resources

With automated and cooperative driving making its breakthrough, and related systems in fast development, their future influence and impact on roads and traffic may be extensive. Truck platooning is such an application that relies on the development of Cooperative Adaptive Cruise Control (CACC) and is said to be practice ready. While the main advantages of truck platooning lie in emission and energy reduction, claims are also being made for the influence on traffic flow. In this paper, we pose hypotheses based on some of the main claims. We also attempt to substantiate and give quantitative proof of the potential effects of truck platooning on traffic flow performance. The simulation model LMRS-IDM+ is extended to encompass the main influencing dynamics related to potential effects of truck platooning, based on empirical findings. The effects of truck platooning were tested for the influence of traffic states, truck gap settings, platoon sizes, and the share of equipped trucks. This resulted in outcomes regarding the total traffic performance, the performance of traffic at ramps, and the ability of a platoon to remain platooning as part of a case experiment performed on a part of the Trans-European ITS Corridor. The results showed that truck platooning may have a small negative effect on the total non-saturated traffic flow, however with a much larger negative effect on saturated traffic flow. However, drivers may be reluctant to platoon in saturated traffic in any case. The ability of inflowing traffic to merge at on-ramps was found to be affected by truck platoons, with platoon disengagements occurring under various conditions. The applied gap settings for platooning trucks did not significantly affect the merge time, while a higher gap did lead to a higher number of disengagements. The ability of trucks to platoon was positively affected by a greater percentage of equipped trucks and by larger platoon sizes. Shorter gap times also slightly improved the ability of trucks to remain in platooning formation. Finally, recommendations are given to improve platoon strategies and for policymakers to only allow truck platooning outside of busy (near-) saturated traffic, even though drivers may be reluctant to use the system in these conditions. Also, recommendations are made to investigate potential differences in the effects between the European and American contexts for truck-platooning.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Computer Science, Interdisciplinary Applications

A hybrid spatial-temporal deep learning architecture for lane detection

Yongqi Dong, Sandeep Patil, Bart van Arem, Haneen Farah

Summary: Accurate and reliable lane detection is crucial for the safety of lane-keeping assistance and lane departure warning systems. Existing methods mostly rely on single image detection, which may not perform well under challenging circumstances. This study proposes a hybrid spatial-temporal deep learning architecture that incorporates information from multiple continuous image frames to accurately detect lane markings in the last frame.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2023)

Article Transportation

Herd immunity for traffic safety in mixed automated traffic: what if cars could not crash!?

Simeon C. Calvert, Bart van Arem, Jane Lappin

Summary: This paper presents the concept of Herd Immunity for Traffic Safety (HITS), which focuses on the increased safety achieved when Connected Automated Vehicles (CAV) and Human Driven Vehicles (HDV) coexist in mixed traffic. With higher levels of CAV penetration, traffic safety grows non-linearly.

TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH (2023)

Article Transportation

A flock-like two-dimensional cooperative vehicle formation model based on potential functions

Ruochen Hao, Meiqi Liu, Wanjing Ma, Bart van Arem, Meng Wang

Summary: Due to the complexity of manoeuvre, there is a lack of models in the literature that describe the platoon formation process on urban roads. Inspired by flocking behaviours in nature, this study proposes a two-dimensional model based on the potential theory to describe the dynamics of connected automated vehicle (CAV) groups, which can also be applied to human-driven vehicles in mixed traffic environments.

TRANSPORTMETRICA B-TRANSPORT DYNAMICS (2023)

Article Psychology, Applied

Behavioral adaptations of human drivers interacting with automated vehicles

Shubham Soni, Nagarjun Reddy, Anastasia Tsapi, Bart van Arem, Haneen Farah

Summary: This study conducted a field test in the Netherlands and found that human drivers accepted smaller critical gaps and maintained shorter headway when interacting with automated vehicles (AVs). Positive information about the AV behavior resulted in closer interactions and increased trust from drivers.

TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR (2022)

Article Computer Science, Artificial Intelligence

Realising Meaningful Human Control Over Automated Driving Systems: A Multidisciplinary Approach

Filippo Santoni de Sio, Giulio Mecacci, Simeon Calvert, Daniel Heikoop, Marjan Hagenzieker, Bart van Arem

Summary: This paper presents a framework for achieving meaningful human control over Automated Driving Systems. It is based on the results of a multidisciplinary research project conducted at Delft University of Technology from 2017 to 2021. The framework emphasizes the importance of human persons and institutions being in control of the potentially dangerous operation of driving in mixed traffic. The paper proposes specific requirements for meaningful human control and discusses the implications for human actors and their skills. Future research directions and applications are also suggested.

MINDS AND MACHINES (2022)

Article Engineering, Civil

Safety Assessment of the Interaction Between an Automated Vehicle and a Cyclist: A Controlled Field Test

Maria Oskina, Haneen Farah, Peter Morsink, Riender Happee, Bart van Arem

Summary: This study investigates the safety of cyclists when interacting with automated vehicles compared to conventional vehicles. The results show that automated following has similar risks to manual following, while automated overtaking has higher risks compared to manual overtaking. Furthermore, longer interaction time leads to an increase in cycling speed and a decrease in lateral distance to the curb.

TRANSPORTATION RESEARCH RECORD (2023)

Article Engineering, Civil

Hierarchical Optimal Maneuver Planning and Trajectory Control at On-Ramps With Multiple Mainstream Lanes

Na Chen, Bart van Arem, Meng Wang

Summary: This study proposes a hierarchical cooperative merging control approach that ensures collision-free and traffic-efficient merging through the interaction of a maneuver planner and an operational trajectory controller. Compared to traditional merging methods, the proposed approach consistently results in less disturbances during merging.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022)

Article Engineering, Civil

Exploring Users' Preferences for Automated Minibuses and Their Service Type: A Stated Choice Experiment in the Netherlands

Maryna Ozturker, Goncalo Homem de Almeida Correia, Arthur Scheltes, Marie-Jose Olde Kalter, Bart van Arem

Summary: This study investigates the deployment potential of automated minibuses (AmBs) in the first-mile part of public transport trips. The results show that current public transport users prefer flexible service types, while car and active mode users do not show a preference for either service type. A positive attitude towards riding in AmBs is an important factor for potential users in all segments.

JOURNAL OF ADVANCED TRANSPORTATION (2022)

Article Economics

Efficient evaluation of stochastic traffic flow models using Gaussian process approximation

Pieter Jacob Storm, Michel Mandjes, Bart van Arem

Summary: This paper studies a Gaussian process approximation for a class of stochastic traffic flow models and demonstrates its effectiveness in evaluating joint vehicle-density distributions in road traffic networks. It discusses the computational complexity and impact of the assumption regarding vehicles' headways on the approximation accuracy.

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2022)

Article Transportation Science & Technology

Ride acceptance behaviour of ride-sourcing drivers

Peyman Ashkrof, Goncalo Homem de Almeida Correia, Oded Cats, Bart van Arem

Summary: This study examines the determinants of ride acceptance behavior among ride-sourcing drivers and proposes customized matching and pricing strategies to improve system efficiency. The results reveal that employment status, experience level, and working shift are key factors influencing the decision to accept ride requests. The study also finds that pickup time has a negative impact on ride acceptance, while a guaranteed tip and additional income from surge pricing are valued higher than trip fare.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2022)

Article Engineering, Civil

Framework for Network-Constrained Tracking of Cyclists and Pedestrians

Alphonse Vial, Gustaf Hendeby, Winnie Daamen, Bart van Arem, Serge Hoogendoorn

Summary: The increase in perception capabilities of connected mobile sensor platforms enables the collection of extensive sensed features at different temporal and spatial scales. This paper proposes a new method for tracking moving targets, such as pedestrians or cyclists, constrained by a road network, using spatially distributed sensor platforms. The key contribution is the introduction of network bound targets into the multi-target tracking problem, resulting in a network-constrained multi-hypotheses tracker (NC-MHT) that utilizes road information. Simulation results demonstrate that the method performs well and highlights the advantages of considering network constraints.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2023)

Article Engineering, Civil

Characterizing Behavioral Differences of Autonomous Vehicles and Human-Driven Vehicles at Signalized Intersections Based on Waymo Open Dataset

Yiyun Wang, Haneen Farah, Rongjie Yu, Shuhan Qiu, Bart van Arem

Summary: Autonomous vehicles (AVs) are being introduced to the traffic system, but empirical data shows conflicting effects. This study analyzes the driving behavior of AVs and human-driven vehicles (HDVs) at signalized intersections using the Waymo open dataset. Significant differences in driving behavior between AVs and HDVs were found in three situations: vehicle approaching the red light/queue, vehicle responding to the green light (as the first vehicle), and vehicle responding to its preceding vehicle (in the queue). Behavioral adaptations of HDV drivers were also revealed.

TRANSPORTATION RESEARCH RECORD (2023)

Article Engineering, Civil

Prioritizing Cyclists at Signalized Intersections Using Observations from Connected Autonomous Vehicles

Alphonse Vial, Maria Salomons, Winnie Daamen, Bart van Arem, Sascha Hoogendoorn-Lanser, Serge Hoogendoorn

Summary: The main objective of this study is to enhance the situational awareness of traffic signal controllers by using observations from moving sensor platforms, in order to prioritize cyclists and reduce their idle time at signalized intersections.

TRANSPORTATION RESEARCH RECORD (2023)

Article Transportation

On the Relocation Behavior of Ride-sourcing Drivers

Peyman Ashkrof, Goncalo Homem de Almeida Correia, Oded Cats, Bart van Arem

Summary: As individual service suppliers, ride-sourcing drivers have the freedom to choose their own relocation strategies, such as waiting, cruising freely, or following platform recommendations. These decisions have significant impacts on supply and demand balance and overall system performance. Through a stated choice experiment using a unique dataset of 576 ride-sourcing drivers in the US, we examined the searching behavior of drivers and assessed the effects of different attributes on their decisions. The findings suggest that drivers' relocation strategies vary among different driver groups and are influenced by factors such as surge pricing and distance from high-demand areas.

TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH (2023)

Article Transportation Science & Technology

Managing connected and automated vehicles with flexible routing at lane-allocation-freeintersections

Ruochen Hao, Yuxiao Zhang, Wanjing Ma, Chunhui Yu, Tuo Sun, Bart van Arem

Summary: With the development of internet of vehicles and automated driving, individual-based trajectory control at intersections becomes possible. This study proposes a mixed-integer linear programming (MILP) model to optimize vehicle trajectories at an isolated signal-free intersection without lane allocation, denoted as lane-allocation-free (LAF) control. Vehicle routes and trajectories at the intersection are optimized in one unified framework for system optimality in terms of total vehicle delay.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2023)

Article Transportation Science & Technology

3-Strategy evolutionary game model for operation extensions of subway networks

Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro

Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2024)

Article Transportation Science & Technology

Integrated optimization of container allocation and yard cranes dispatched under delayed transshipment

Hongtao Hu, Jiao Mob, Lu Zhen

Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2024)

Article Transportation Science & Technology

Range-constrained traffic assignment for electric vehicles under heterogeneous range anxiety

Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu

Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2024)

Article Transportation Science & Technology

Demand forecasting and predictability identification of ride-sourcing via bidirectional spatial-temporal transformer neural processes

Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen

Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2024)

Article Transportation Science & Technology

Partial trajectory method to align and validate successive video cameras for vehicle tracking

Benjamin Coifman, Lizhe Li

Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2024)

Article Transportation Science & Technology

Dynamic routing for the Electric Vehicle Shortest Path Problem with charging station occupancy information

Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli

Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2024)