Microscopic Modeling of the Effects of Autonomous Vehicles on Motorway Performance

2020 ◽  
Vol 2674 (11) ◽  
pp. 697-707
Author(s):  
George Mesionis ◽  
Mark Brackstone ◽  
Natalie Gravett
Keyword(s):  
Automotive Industry ◽  
Autonomous Vehicles ◽  
Behavioral Model ◽  
Cruise Control ◽  
Lane Changing ◽  
Positive Effects ◽  
Traffic Conditions ◽  
High Penetration ◽  
The Subject ◽  
Microscopic Modeling

Autonomous vehicles (AVs) have been the subject of extensive research in recent years and are expected to completely transform the operation of transport networks and revolutionize the automotive industry in the coming decades. Modeling detailed interactions among vehicles with varying levels of penetration rates is essential for evaluating the potential effects. One such investigation is being performed within the ‘HumanDrive’ Project in the U.K. This work has required the development of a behavioral model that incorporates microscopic level interactions and has been based on a pre-existing adaptive cruise control and lane-changing model that has been adapted to better replicate the limitations of AVs and allow the investigation of differing levels of intelligence or assertiveness. The model has been implemented on the M1 Motorway near Sheffield in the U.K. This has allowed the investigation of the effects of AVs on the operation of a real network under various traffic conditions where the overall effects may be revealed, both as advantages to AV drivers, and potentially disadvantages to non-AV traffic. Additionally, it has been possible to examine how these affect junction operations and net emissions. Preliminary results have allowed us to quantify the positive effects of AVs which increase with the penetration. However, it is clear that there are points of inflection where benefits start to slow. It is at these (high) penetration rates that initial operational assumptions may become increasingly stretched and additional infrastructure and cooperative systems are likely to have to become prevalent.

scholarly journals Target Vehicle Selection Algorithm for Adaptive Cruise Control Based on Lane-changing Intention of Preceding Vehicle

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Jun Yao ◽  
Guoying Chen ◽  
Zhenhai Gao
Keyword(s):  
Adaptive Cruise Control ◽  
Prediction Algorithm ◽  
Support Vector ◽  
Lane Change ◽  
Selection Algorithm ◽  
Cruise Control ◽  
Lane Changing ◽  
Target Vehicle ◽  
Preceding Vehicle ◽  
The Subject

AbstractTo improve the ride comfort and safety of a traditional adaptive cruise control (ACC) system when the preceding vehicle changes lanes, it proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention for the preceding vehicle. First, the Next Generation Simulation dataset is used to train a lane-changing intention prediction algorithm based on a sliding window support vector machine, and the lane-changing intention of the preceding vehicle in the current lane is identified by lateral position offset. Second, according to the lane-changing intention and collision threat of the preceding vehicle, the target vehicle selection algorithm is studied under three different conditions: safe lane-changing, dangerous lane-changing, and lane-changing cancellation. Finally, the effectiveness of the proposed algorithm is verified in a co–simulation platform. The simulation results show that the target vehicle selection algorithm can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels their lane change maneuver. In the case of a dangerous lane change, the target vehicle selection algorithm proposed in this paper can respond more rapidly to a dangerous lane change than the target vehicle selection method of the traditional ACC system; thus, it can effectively avoid collisions and improve the safety of the subject vehicle.

scholarly journals Target Vehicle Selection Algorithm Based on Lane-changing Intention of Preceding Vehicle for ACC

2021 ◽  
Author(s):  
Jun Yao ◽  
Guoying Chen ◽  
Zhenhai Gao
Keyword(s):  
Ride Comfort ◽  
Lateral Position ◽  
Prediction Algorithm ◽  
Lane Change ◽  
Selection Algorithm ◽  
Cruise Control ◽  
Lane Changing ◽  
Target Vehicle ◽  
Preceding Vehicle ◽  
The Subject

Abstract In order to improve the ride comfort and safety of the traditional adaptive cruise control (ACC) system when the preceding vehicle changes lanes, this paper proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention of the preceding vehicle. First, NGSIM dataset is used to train a lane-changing intention prediction algorithm based on sliding window SVM, and the lane-changing intent of the preceding vehicle in the current lane can be identified by lateral position offset. Secondly, according to the lane-changing intention and the collision threat of the preceding vehicle, the target vehicle selection algorithm is studied under three different conditions: safe lane-changing condition, dangerous lane-changing condition, and lane-changing cancellation condition. Finally, the effectiveness of the algorithm proposed in this paper is verified in the co-simulation platform. The simulation results show that the target vehicle selection algorithm proposed in this paper can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels the lane change. In the case of a dangerous lane change, the target vehicle selection algorithm proposed in this paper can respond to the dangerous lane change in advance compared with the target vehicle selection method of the traditional ACC system, which can effectively avoid collisions and improve the safety of the subject vehicle.

Social Force Control for Human-Like Autonomous Driving

2018 ◽  
Author(s):  
DoHyun Daniel Yoon ◽  
Beshah Ayalew
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Social Force ◽  
Cruise Control ◽  
Lane Changing ◽  
Safe Navigation ◽  
Proposed Model ◽  
The Social ◽  
Efficient Integration

An autonomous driving control system that incorporates notions from human-like social driving could facilitate an efficient integration of hybrid traffic where fully autonomous vehicles (AVs) and human operated vehicles (HOVs) are expected to coexist. This paper aims to develop such an autonomous vehicle control model using the social-force concepts, which was originally formulated for modeling the motion of pedestrians in crowds. In this paper, the social force concept is adapted to vehicular traffic where constituent navigation forces are defined as a target force, object forces, and lane forces. Then, nonlinear model predictive control (NMPC) scheme is formulated to mimic the predictive planning behavior of social human drivers where they are considered to optimize the total social force they perceive. The performance of the proposed social force-based autonomous driving control scheme is demonstrated via simulations of an ego-vehicle in multi-lane road scenarios. From adaptive cruise control (ACC) to smooth lane-changing behaviors, the proposed model provided a flexible yet efficient driving control enabling a safe navigation in various situations while maintaining reasonable vehicle dynamics.

Multi-Player Dynamic Game-Based Automatic Lane-Changing Decision Model under Mixed Autonomous Vehicle and Human-Driven Vehicle Environment

2020 ◽  
Vol 2674 (11) ◽  
pp. 165-183
Author(s):  
Yuewen Yu ◽  
Shikun Liu ◽  
Peter J. Jin ◽  
Xia Luo ◽  
Mengxue Wang
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Splitting Method ◽  
Dynamic Game ◽  
Cruise Control ◽  
Lane Changing ◽  
Bicycle Model ◽  
Decision Making Model

The lane-changing decision-making process is challenging but critical to ensure safe and smooth maneuvers for autonomous vehicles (AVs). Conventional Gipps-type algorithms lack the flexibility for practical use under a mixed autonomous vehicle and human-driven vehicle (AV-HV) environment. Algorithms based on utility ignore the reactions of surrounding vehicles to the lane-changing vehicle. Game theory is a good way to solve the shortcomings of current algorithms, but most models based on game theory simplify the game with surrounding vehicles to the game with the following vehicle in the target lane, which means that the lane-changing decision under a mixed environment is not realized. This paper proposes a lane-changing decision-making model which is suitable for an AV to change lanes under a mixed environment based on a multi-player dynamic game theory. The overtaking expectation parameter (OEP) is introduced to estimate the utility of the following vehicle, OEP can be calculated by the proposed non-lane-based full velocity difference model with the consideration of lateral move and aggressiveness. This paper further proposes a hybrid splitting method algorithm to obtain the Nash equilibrium solution in the multi-player game to obtain the optimal strategy of lane-changing decision for AVs. An adaptive cruise control simulation environment is developed with MATLAB’s Simulink toolbox using Next Generation Simulation (NGSIM) data as the background traffic flow. The classic bicycle model is used in the control of involved HVs. Simulation results show the efficiency of the proposed multi-player dynamic game-based algorithm for lane-changing decision making by AVs under a mixed AV-HV environment.

scholarly journals Kiberbiztonság a járműiparban

2020 ◽  
Vol 1 (1) ◽  
pp. 2-6
Author(s):  
László Palkovics
Keyword(s):  
Automotive Industry ◽  
Autonomous Vehicles ◽  
Transport Processes ◽  
Transport Systems ◽  
The Internet ◽  
Vehicle Communication ◽  
Positive Effects ◽  
Vehicle To Vehicle ◽  
The Future ◽  
Vehicle To Vehicle Communication

Összefoglalás. Jelen cikk célja a járműipar egyes területeit érintő kiberbiztonsági kockázatok vizsgálata. Fentiekkel összhangban a cikk első részében a járműipar kiberbiztonsági szempontból releváns területei kerülnek meghatározásra. Ezt követően megtörténik a 2018. évben rögzített járműipari kibertámadások kockázatalapú értékelő elemzése. Summary. Nowadays, cybersecurity has a critical impact to our lives. The Internet has also got a substantial role in our days since many people are constantly connected to the Internet (e.g., through online social networks) (Török et al. 2020a). Besides, numerous personal and individual devices are connected. The growing number of connected devices and cyberspace expansion make our lives easier. However, this affects our privacy, with the potential for unauthorized use of personal information. In summary, life in a networked world carries unknown dangers. In the future, many new risk factors are expected to occur, which will significantly increase the level of cybersecurity threats. Examining the aspects of the automotive industry, we should mention the summary of Cheng et al., which explores the field’s problems through novel theoretical solutions and related practical considerations. The book pays special attention to vehicle communication and networked systems. This book examines three main scientific directions for 5G-compliant vehicle-to-vehicle communication and cooperative vehicle control: modeling and testing capabilities for vehicle-to-vehicle communication, state-of-the-art technologies related to the physical layer, and MAC design procedures (Cheng et al. 2019). Cheng and colleagues (Cheng et al. 2019) examined the communication channels currently applied in the automotive industry or that are expected to be applied soon. Particular attention has been paid to examining the tasks and challenges that need to be addressed in order to support the spread of the connected transport systems in the future. The evaluation focused on the cooperation of connected vehicles. Their study also outlined the most important security risks and challenges associated with new communication solutions. In the light of the above-mentioned considerations, it can be said that the emergence of connected and autonomous vehicles can make a significant contribution to the positive effects of cyberspace, but can also have a disadvantageous impact on the vulnerability of transport processes. In line with this, it is important to examine and understand the vulnerabilities of connected and autonomous vehicles, the threats to vehicles. With this knowledge, automotive cybersecurity professionals’ responsibility is to develop appropriate security functions and capabilities for connected and autonomous vehicles and transport systems. This enables the systems to detect, evaluate, and, if necessary, treat different attacks and malicious interventions. Along with the above objectives, many research studies in the automotive segment have already focused on identifying cybersecurity assessment frameworks for motor vehicles. Among these, it is worth highlighting the projects “HEAling Vulnerabilities to ENhance Software Security and Safety” and “E-safety vehicle intrusion protected applications” (Cheah et al. 2018).

scholarly journals Target Vehicle Selection Algorithm Based on Lane-changing Intention of Preceding Vehicle for ACC

2020 ◽  
Author(s):  
Jun Yao ◽  
Guoying Chen ◽  
Zhenhai Gao
Keyword(s):  
Ride Comfort ◽  
Lateral Position ◽  
Prediction Algorithm ◽  
Lane Change ◽  
Selection Algorithm ◽  
Cruise Control ◽  
Lane Changing ◽  
Target Vehicle ◽  
Preceding Vehicle ◽  
The Subject

Abstract In order to improve the ride comfort and safety of the traditional adaptive cruise control (ACC) system when the preceding vehicle changes lanes, this paper proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention of the preceding vehicle. First, NGSIM dataset is used to train a lane-changing intention prediction algorithm based on sliding window SVM, and the lane-changing intent of the preceding vehicle in the current lane can be identified by lateral position offset. Secondly, according to the lane-changing intention and the collision threat of the preceding vehicle, the target vehicle selection algorithm is studied under three different conditions: safe lane-changing condition, dangerous lane-changing condition, and lane-changing cancellation condition. Finally, the effectiveness of the algorithm proposed in this paper is verified in the co-simulation platform. The simulation results show that the target vehicle selection algorithm proposed in this paper can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels the lane change. In the case of a dangerous lane change, the target vehicle selection algorithm proposed in this paper can respond to the dangerous lane change in advance compared with the target vehicle selection method of the traditional ACC system, which can effectively avoid collisions and improve the safety of the subject vehicle.

Developing the guidelines for managing autonomous vehicle flows on congested highways: A case study of MD-100

SIMULATION ◽  
2021 ◽  
pp. 003754972098687
Author(s):  
Ranteg S Rao ◽  
Sung Yoon Park ◽  
Gang-Len Chang
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Behavioral Patterns ◽  
Lane Changing ◽  
Traffic Conditions ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Negative Impacts ◽  
Behavioral Mechanisms ◽  
Measures Of Effectiveness

Recognizing the need for responsible highway agencies to effectively manage emerging autonomous vehicles (AV) flows in contending with daily recurrent congestion, this study presents a systematic procedure for understanding the impacts of AV flows on traffic conditions under different AV behavioral mechanisms (i.e., car-following and lane-changing), and different penetration rates. Research results show that the presence of AV flows, depending on their adopted behavioral mechanisms, may have significant (either positive or negative) impacts on the overall traffic conditions. Hence, it is essential for responsible highway agencies to have proper operational guidelines to manage and coordinate AV flows. To demonstrate the proposed methodology, this study has carried out extensive simulation experiments using a congested segment of the MD-100 network (a multilane highway segment located in Maryland) under various AV penetration rates and observable behavioral patterns. The collected Measures of Effectiveness highlight that at each AV penetration level there exists a set of optimal behavioral patterns for the AV flows to coordinate with non-AV flows via the Vehicle to Infrastructure or Vehicle to Vehicle infrastructure so as to maximize the roadway capacity and minimize the resulting highway congestion.

AUTOMOTIVE INDUSTRY DICTIONARY: “HALMOVYI” (“BRAKE”) OR “HALMIVNYI” (“BRAKING”)

2020 ◽  
pp. 19-20
Author(s):  
Valentyn Merzhyievskyi ◽  
Yuliya Ponomarova
Keyword(s):  
Automotive Industry ◽  
Motor Transport ◽  
Subject Line ◽  
The Subject

In order to improve the national terminology in the industry and simultaneously to coordinate it with international terms, we propose to the Ukrainian motor transport community to take part in compilation of specialized translation dictionary. The magazine «Avtoshliakhovyk Ukrainy», as indicated in the No 1 (253) 2018, have opened a new section, «Automotive Industry Dictionary», intended to publish our draft definitions of the most controversial terms in Ukrainian, with comments on their formation and scope and corresponding terms in other languages. Please, send your remarks and ideas by email indicating «Automotive Industry Dictionary» in the subject line to: [email protected].

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

The referendum as an institution in the Black Sea Region: Does it signal the rise or collapse of democracy?

2019 ◽  
Vol 17 (4) ◽  
pp. 161-185
Author(s):  
Małgorzata Podolak
Keyword(s):  
Black Sea ◽  
Direct Democracy ◽  
The Black Sea ◽  
Moral Issues ◽  
Black Sea Region ◽  
Positive Effects ◽  
The Subject ◽  
Democratic Systems ◽  
Important State ◽  
Constitutional Changes

Views on the institution of direct democracy have changed during the period of democratic transition. The various advantages and positive effects of direct democracy have been confirmed by the practice of some democratic countries. Its educational and political activation value for society was also noted, without which civil society cannot form. The referendum is especially treated as the purest form of correlation between the views of society and the decisions of its representatives. In a situation where two representative bodies are present – the parliament and the president – a referendum is considered a means of resolving disputes between them in important state affairs. The referendum is nowadays becoming more than just a binding or consultative opinion on a legislative act, especially a constitution. First and foremost, it is important to see the extension of the type and scope of issues that are subject to direct voting. Apart from the traditional, i.e., constitutional changes, polarising issues that raise considerable emotion have become the subject of referenda. Problems of this type include, in particular, moral issues, membership in international organisations, and so-called ‘New Policy’. This article presents the role and importance of the referendum as an institution shaping the democratic systems of the Black Sea Region.

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