Dynamic Cooperative Speed Optimization at Signalized Arterials with Various Platoons

2019 ◽  
Vol 2673 (5) ◽  
pp. 528-537 ◽  
Author(s):  
Xia Wu ◽  
Xiangmo Zhao ◽  
Qi Xin ◽  
Qiaoli Yang ◽  
Shaowei Yu ◽  
...  
Keyword(s):  
Traffic Signals ◽  
Programming Algorithm ◽  
Connected Vehicles ◽  
Driving Behaviors ◽  
Optimum Trajectories ◽  
Speed Optimization ◽  
The Status ◽  
Driving Model ◽  
Optimum Approach ◽  
Multiple Vehicles

Aggressive and inappropriate driving behaviors will lead to excessive fuel consumption. Both the Signal Phase and Timing (SPaT) and the status of preceding vehicles have significant impacts on driving behaviors. Drivers can obtain accurate SPaT information and the status of preceding vehicles via V2X communications. Many speed advisory strategies have been presented based on the consideration of this information. However, existing studies do not consider the cooperative optimization of multiple intersections and various platoons. Once connected vehicles travel through intersections with their own fuel-optimum trajectories, the following vehicles could be adversely affected by the preceding vehicles, leading to the following vehicles being stopped at the intersection. To address these problems, this paper presents an improved cooperative eco-driving model for when a vehicle passes two successive traffic signals during the green phase; a dynamic nonlinear programming algorithm is used to generate the optimal speed profile for various platoons considering the SPaT and the preceding vehicles’ status. Numerous simulations on VISSIM for uninformed and connected vehicles haves been conducted to make comparison analysis. It is apparent that the proposed eco-driving model produces a significant fuel saving. In addition, cooperative optimization for the various platoons and separate optimization of multiple vehicles were performed to seek the most effective solution. The results indicated that systematic optimization (cooperative optimization of the all vehicles) is identified as the fuel-optimum approach in comparison to the separate optimization.

scholarly journals Influences of Single-Lane Automatic Driving Systems on Traffic Efficiency and CO2 Emissions on China’s Motorways

2021 ◽  
Vol 11 (22) ◽  
pp. 11032
Author(s):  
Haokun Song ◽  
Fuquan Zhao ◽  
Zongwei Liu
Keyword(s):  
Co2 Emissions ◽  
Penetration Rate ◽  
Connected Vehicles ◽  
Driving System ◽  
Traffic Efficiency ◽  
Automatic Driving ◽  
Driving Behaviors ◽  
Road Capacity ◽  
Long Time ◽  
Carbon Dioxide Co2

There are big differences between the driving behaviors of intelligent connected vehicles (ICVs) and traditional human-driven vehicles (HVs). ICVs will be mixed with HVs on roads for a long time in the future. Different intelligent functions and different driving styles will affect the condition of traffic flow, thereby changing traffic efficiency and emissions. In this paper, we focus on China’s expressways and secondary motorways, and the impacts of the ‘single-lane automatic driving system’ (SLADS) on traffic delay, road capacity and carbon dioxide (CO2) emissions were studied under different ICV penetration rates. Driving styles were regarded as important factors for scenario analysis. We found that with higher volume input, SLADS has an optimizing effect on traffic efficiency and CO2 emissions generally, which will be more significant as the ICV penetration rate increases. Additionally, enhancing the aggressiveness of driving behavior appropriately is an effective way to amplify the benefits of SLADS.

scholarly journals Microscopic Estimation of Freeway Vehicle Positions from the Behavior of Connected Vehicles

2020 ◽  
Author(s):  
Noah J. Goodall ◽  
Brian L. Smith ◽  
Byungkyu Brian Park
Keyword(s):  
Traffic Signals ◽  
The United States ◽  
Traffic Information ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Travel Time Prediction ◽  
High Penetration ◽  
Initial Penetration ◽  
Car Following Model ◽  
Status Data

Given the current connected vehicles program in the United States, as well as other similar initiatives in vehicular networking, it is highly likely that vehicles will soon wirelessly transmit status data, such as speed and position, to nearby vehicles and infrastructure. This will drastically impact the way traffic is managed, allowing for more responsive traffic signals, better traffic information, and more accurate travel time prediction. Research suggests that to begin experiencing these benefits, at least 20% of vehicles must communicate, with benefits increasing with higher penetration rates. Because of bandwidth limitations and a possible slow deployment of the technology, only a portion of vehicles on the roadway will participate initially. Fortunately, the behavior of these communicating vehicles may be used to estimate the locations of nearby noncommunicating vehicles, thereby artificially augmenting the penetration rate and producing greater benefits. We propose an algorithm to predict the locations of individual noncommunicating vehicles based on the behaviors of nearby communicating vehicles by comparing a communicating vehicle's acceleration with its expected acceleration as predicted by a car-following model. Based on analysis from field data, the algorithm is able to predict the locations of 30% of vehicles with 9-m accuracy in the same lane, with only 10% of vehicles communicating. Similar improvements were found at other initial penetration rates of less than 80%. Because the algorithm relies on vehicle interactions, estimates were accurate only during or downstream of congestion. The proposed algorithm was merged with an existing ramp metering algorithm and was able to significantly improve its performance at low connected vehicle penetration rates and maintain performance at high penetration rates.

scholarly journals Toward an Intelligent Driving Behavior Adjustment Based on Legal Personalized Policies Within the Context of Connected Vehicles

2021 ◽  
Vol 7 ◽  
Author(s):  
Fatma Outay ◽  
Nafaa Jabeur ◽  
Hedi Haddad ◽  
Zied Bouyahia ◽  
Hana Gharrad
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Self Regulation ◽  
Field Tests ◽  
Transportation Systems ◽  
Connected Vehicles ◽  
Consumer Privacy ◽  
Road Traffic Safety ◽  
Fair Competition ◽  
Driving Behaviors

The advent of Connected Vehicles (CVs) is creating new opportunities within the transportation sector. It is, indeed, expected to improve road traffic safety, enhance mobility, reduce fuel consumption and gas emissions, as well as foster economic growth via investments and jobs. However, to motivate the deployment of CVs and maximize their related benefits, policymakers must create appropriate neutral legal frameworks. These frameworks should promote the innovation of current road infrastructures, support cooperation and interoperability between transportation systems, and encourage fair competition between companies while upholding consumer privacy as well as data protection. We argue that policymakers should also support innovative mobility services toward a better accommodation of individual drivers and vehicles. Within this scope, we are proposing in this paper an intelligent approach that promotes the implementation of personalized road policies based on driving behaviors, driving performance, and the ongoing road traffic situation. These policies, which are dynamic in space and time, ultimately aim to increase drivers’ awareness by encouraging behavioral self-regulation. To meet our goals, we are using software agents that autonomously manage the driving behaviors according to well-defined transitions between driving states while enabling appropriate message exchanges between CVs. We run software simulations as well as field tests and obtained promising results that would reflect the relevance of implementing our vision of personalized policies.

Using Difference Images to Detect Pedestrian Signal Changes

2017 ◽  
Vol 29 (4) ◽  
pp. 706-711 ◽  
Author(s):  
Tetsuo Tomizawa ◽  
◽  
Ryunosuke Moriai
Keyword(s):  
Traffic Signals ◽  
Image Sequences ◽  
Traffic Light ◽  
Lighting Conditions ◽  
The Status ◽  
Pedestrian Traffic ◽  
Signal Changes ◽  
Time Changes ◽  
Difference Images ◽  
Pedestrian Signals

This paper describes a method of using camera images to detect changes in the display status of pedestrian traffic signals. In much of the research previously done on signal detection, the color or shape of images or machine learning has been used to estimate the signal status. However, it is known that these methods are greatly affected by occlusion and changes in illumination. We propose a method of detecting, using multiple image sequences captured over time, changes in appearance that occur when a signal changes. If this method is used, the position and the status of the traffic light can be accurately detected as long as it appears in the image, even if its relative position or the lighting conditions in the area changes. In this paper, we first describe how pedestrian signals are seen when difference images are used, and we propose an algorithm for detecting when a signal changes. Then, the effectiveness of the proposed method is confirmed through verification tests.

Two-Step Algorithm to Detect Cyber-Attack Over the Can-Bus: A Preliminary Case Study in Connected Vehicles

2021 ◽  
Author(s):  
Marco Lombardi ◽  
Francesco Pascale ◽  
Domenico Santaniello
Keyword(s):  
Can Bus ◽  
Detection System ◽  
Detection Algorithm ◽  
Connected Vehicles ◽  
Cyber Attack ◽  
Multimedia Services ◽  
Control Units ◽  
The Status ◽  
Step Algorithm

Abstract Modern vehicles are connected to the network and between each other through smart sensors and smart objects commonly present on board. This situation has allowed manufacturers to send over-the-air updates, receive diagnostic information, and offer various multimedia services. More generally, at present, all this is indicated by the term 'Vehicle to Everything' (V2X), which indicates a system of communication between a vehicle to any entity that may influence the vehicle and vice versa. However, it introduces problems regarding the vehicle's IT security. It is possible, for example, by tampering with one of the Electronic Control Units (ECUs) to take partial or total control of the vehicle. In this paper, we introduce a preliminary study case to guarantee cybersecurity inside connected vehicles. In particular, an Intrusion Detection System over the CAN-Bus to allow the possible malicious massages. In particular, through the use of a two-step detection algorithm that exploits both the variation of the status parameters of the various ECUs over time and the Bayesian networks can identify a possible attack. The first experimental results seem encouraging.

scholarly journals The status, challenges, and trends: an interpretation of technology roadmap of intelligent and connected vehicles in China (2020)

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qing Xu ◽  
Keqiang Li ◽  
Jianqiang Wang ◽  
Quan Yuan ◽  
Yanding Yang ◽  
...  
Keyword(s):  
Industrial Revolution ◽  
Rapid Development ◽  
Connected Vehicles ◽  
Content Type ◽  
Technology Roadmap ◽  
Technical Content ◽  
The Status ◽  
Technical Architecture ◽  
The Impact ◽  
International Strategies

Purpose The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied. Design/methodology/approach This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies. Findings The technical architecture of ICVs as the “three rows and two columns” structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed. Originality/value This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.

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