Novel Cooperative Collision Avoidance Model for Connected Vehicles

2017 ◽  
Vol 2645 (1) ◽  
pp. 144-156 ◽  
Author(s):  
Pangwei Wang ◽  
WenXiang Wu ◽  
Xiaohui Deng ◽  
Lin Xiao ◽  
Li Wang ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Traffic Safety ◽  
Traffic Information ◽  
Connected Vehicles ◽  
Time Interval ◽  
Connected Vehicle ◽  
Emergency Braking ◽  
Acceleration Rate ◽  
Vehicle Platoon ◽  
Connected Vehicle Technology

Connected vehicle technology exchanges real-time vehicle and traffic information through vehicle-to-vehicle and vehicle-to-infrastructure communication. The technology has the potential to improve traffic safety applications such as collision avoidance. In this paper, a novel cooperative collision avoidance (CCA) model that could improve the effectiveness of the collision avoidance system of connected vehicles was developed. Unlike traditional collision avoidance models, which relied mainly on emergency braking, the proposed CCA approach avoided collision through a combination of following vehicle deceleration and leading vehicle acceleration. Through spacing policy theory and nonlinear optimization, the model calculated the desired deceleration rate for the following vehicle and the acceleration rate for the leading vehicle, respectively, at each time interval. The CCA approach was then tested on a scaled platform with hardware-in-the-loop simulation embedded with MATLAB/Simulink and a car simulator package, CarSim. Results show that the proposed model can effectively avoid rear-end collisions in a three-vehicle platoon.

scholarly journals Modelling and Simulation of Cooperative Control for Bus Rapid Transit Vehicle Platoon in a Connected Vehicle Environment

2017 ◽  
Vol 29 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Jiahui Liu ◽  
Peiqun Lin ◽  
Jing(Peter) Jin
Keyword(s):  
Cooperative Control ◽  
Control Model ◽  
Bus Rapid Transit ◽  
Time Interval ◽  
Connected Vehicle ◽  
Rapid Transit ◽  
Vehicle Platoon ◽  
Connected Vehicle Technology ◽  
Pass Through ◽  
Set Up

The aim of this paper is to develop a cooperative control model for improving the operational efficiency of Bus Rapid Transit (BRT) vehicles. The model takes advantage of the emerging connected vehicle technology. A connected vehicle centre is established to assign a specific reservation time interval and transmit the corresponding dynamic speed guidance to each BRT vehicle. Furthermore, a set of constraints have been set up to avoid bus queuing and waiting phenomena in downstream BRT stations. Therefore, many BRT vehicles are strategically guided to form a platoon, which can pass through an intersection with no impedance. An actual signalized intersection along the Guangzhou BRT corridor is employed to verify and assess the cooperative control model in various traffic conditions. The simulation-based evaluation results demonstrate that the proposed approach can reduce delays, decrease the number of stops, and improve the sustainability of the BRT vehicles.

scholarly journals A Dynamic Travel Time Estimation Model Based on Connected Vehicles

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Daxin Tian ◽  
Yong Yuan ◽  
Honggang Qi ◽  
Yingrong Lu ◽  
Yunpeng Wang ◽  
...  
Keyword(s):  
Travel Time ◽  
Estimation Method ◽  
Time Estimation ◽  
Traffic Information ◽  
Connected Vehicles ◽  
Travel Time Estimation ◽  
Route Guidance ◽  
Connected Vehicle ◽  
Estimation Model ◽  
Connected Vehicle Technology

With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.

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 Connected Vehicle Technology: An All Too Convenient Solution to Roadway Problems in the United States

2016 ◽  
Vol 16 (1) ◽  
pp. 101-115
Author(s):  
Victor Kustra
Keyword(s):  
United States ◽  
Traffic Safety ◽  
The United States ◽  
United States Department ◽  
Connected Vehicle ◽  
Highway Traffic ◽  
National Highway Traffic Safety ◽  
Automobile Accidents ◽  
Connected Vehicle Technology ◽  
Vehicle Technology

Automobile accidents and roadway infrastructure problems are increasing in the United States.  Specifically, 5.7 million automobile accidents were reported in 2013.  The number of automobile accidents caused by lane drifting has increased over the past fifteen years, given the increased number of drivers on the road.   The National Highway Traffic Safety Administration (NHTSA) and the United States Department of Transportation (USDOT) have developed a cumulative solution to these problems. Connected Vehicle  technology is part of the USDOT’s “Intelligent Transportation Systems” (ITS) initiative.  The ITS initiative targets automobile crash avoidance and better traffic flow through the use of automated technologies.[1] Id. at v. 

scholarly journals DSRC versus 4G-LTE for Connected Vehicle Applications: A Study on Field Experiments of Vehicular Communication Performance

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Zhigang Xu ◽  
Xiaochi Li ◽  
Xiangmo Zhao ◽  
Michael H. Zhang ◽  
Zhongren Wang
Keyword(s):  
Collision Avoidance ◽  
High Speed ◽  
Field Experiments ◽  
Traffic Information ◽  
Connected Vehicle ◽  
Vehicular Communication ◽  
Test Bed ◽  
Traffic Sign ◽  
Communication Performance ◽  
4G Lte

Dedicated short-range communication (DSRC) and 4G-LTE are two widely used candidate schemes for Connected Vehicle (CV) applications. It is thus of great necessity to compare these two most viable communication standards and clarify which one can meet the requirements of most V2X scenarios with respect to road safety, traffic efficiency, and infotainment. To the best of our knowledge, almost all the existing studies on comparing the feasibility of DRSC or LTE in V2X applications use software-based simulations, which may not represent realistic constraints. In this paper, a Connected Vehicle test-bed is established, which integrates the DSRC roadside units, 4G-LTE cellular communication stations, and vehicular on-board terminals. Three Connected Vehicle application scenarios are set as Collision Avoidance, Traffic Text Message Broadcast, and Multimedia File Download, respectively. A software tool is developed to record GPS positions/velocities of the test vehicles and record certain wireless communication performance indicators. The experiments have been carried out under different conditions. According to our results, 4G-LTE is more preferred for the nonsafety applications, such as traffic information transmission, file download, or Internet accessing, which does not necessarily require the high-speed real-time communication, while for the safety applications, such as Collision Avoidance or electronic traffic sign, DSRC outperforms the 4G-LTE.

scholarly journals Evaluating Connected Vehicles and Their Applications

2016 ◽  
Vol 138 (12) ◽  
pp. S12-S17 ◽  
Author(s):  
Mohd Azrin Mohd Zulkefli ◽  
Pratik Mukherjee ◽  
Yunli Shao ◽  
Zongxuan Sun
Keyword(s):  
Real Time ◽  
Energy Savings ◽  
Traffic Information ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
New Paradigm ◽  
Target Vehicle ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Research Platform

This article presents evaluation results of connected vehicles and their applications. Vehicle-to-vehicle communication (V2V) and vehicle-to-infrastructure communication (V2I) can enable a new paradigm of vehicle applications. The connected vehicle applications could significantly improve vehicle safety, mobility, energy savings, and productivity by utilizing real-time vehicle and traffic information. In the foreseeable future, connected vehicles need to operate alongside unconnected vehicles. This makes the evaluation of connected vehicles and their applications challenging. The hardware-in-the-loop (HIL) testbed can be used as a tool to evaluate the connected vehicle applications in a safe, efficient, and economic fashion. The HIL testbed integrates a traffic simulation network with a powertrain research platform in real time. Any target vehicle in the traffic network can be selected so that the powertrain research platform will be operated as if it is propelling the target vehicle. The HIL testbed can also be connected to a living laboratory where actual on-road vehicles can interact with the powertrain research platform.

Developing a Crash Warning System for the Bike Lane Area at Intersections with Connected Vehicle Technology

2019 ◽  
Vol 2673 (4) ◽  
pp. 47-58 ◽  
Author(s):  
Yina Wu ◽  
Mohamed Abdel-Aty ◽  
Ou Zheng ◽  
Qing Cai ◽  
Lishengsa Yue
Keyword(s):  
Traffic Safety ◽  
Warning System ◽  
Threshold Value ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
Trajectory Data ◽  
Vehicle Trajectories ◽  
Connected Vehicle Technology ◽  
Turning Maneuver ◽  
The Right

A common type of bike lane at intersections is between the through lane and the right lane. With such design, right-turning drivers need to cross the bike lane to merge into the right lane, which could cause conflicts with bicycles on the keyhole bike lane. This study aims to develop a warning system for drivers to avoid vehicle–bicycle crashes in the bike lane area under a connected vehicle environment. To propose a reasonable warning system, 118 right-turning vehicle trajectories were collected by an unmanned aerial vehicle. Drivers’ right-turning behaviors are investigated based on the trajectory data. Then, a vehicle–bicycle crash warning algorithm is proposed to calculate the post-encroachment time (PET) under different situations. By comparing the threshold value and the PET value, potential vehicle–bicycle crash locations in the bike lane area could be identified. The proposed algorithm is designed to be displayed on front windshields with an augmented reality display. The results suggested that the proposed algorithm could provide high prediction accuracy. Moreover, vehicle speed, vehicle location, bicycle speed, and bicycle location were found to have significant impact on the locations of dangerous areas. It is expected that the proposed warning system could be used to identify the dangerous areas and deliver warning information for right-turning drivers when they are approaching an intersection. The warning system could help drivers be more prepared for the upcoming right-turning maneuver, and thus improve traffic safety for both drivers and cyclists at intersections.

Development of Risk Predictive Collision Avoidance System and Its Impact on Traffic and Vehicular Safety

2019 ◽  
Vol 2673 (7) ◽  
pp. 454-465 ◽  
Author(s):  
Donghoun Lee ◽  
Sehyun Tak ◽  
Seongjin Choi ◽  
Hwasoo Yeo
Keyword(s):  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Traffic Information ◽  
Collision Risk ◽  
Microscopic Traffic Simulation ◽  
Emergency Braking ◽  
Critical Situation ◽  
Research Findings ◽  
The Subject ◽  
Negative Impacts

Various collision avoidance systems (CASs) have been developed and employed in human-operated vehicles as well as more recently in autonomous vehicles. Most of the existing CASs perform an override function to actuate automatic emergency braking in a critical situation based on the current traffic information obtained from in-vehicle sensors or short-range vehicular communications. These CASs focus on the critical situation in the vicinity of the subject vehicle, which means they may have negative influences on the subject vehicle and its following vehicles, particularly when the leader vehicle of a platoon with short headway applies harsh braking to mitigate an impending collision risk. This study proposes a risk predictive CAS (RPCAS) which executes predictive deceleration with mild braking in advance to prevent a potential rear-end collision by predicting the collision risk arising from a downstream site. To evaluate the performance of the RPCAS, the proposed system is compared with several existing CASs in various car-following cases based on a microscopic traffic simulation. The simulation results show that the RPCAS can effectively reduce the rear-end collision risk with less harsh braking compared with the existing CASs. Furthermore, the RPCAS enables vehicles arriving from upstream to anticipate a potential crash, which provides them with sufficient time to reduce their current speeds proactively. The research findings suggest that the proposed system can attenuate the negative impacts of the previous CASs in relation to traffic and vehicular safety.

Understanding the Highway Safety Benefits of Different Approaches of Connected Vehicles in Reduced Visibility Conditions

2018 ◽  
Vol 2672 (19) ◽  
pp. 91-101 ◽  
Author(s):  
Md Sharikur Rahman ◽  
Mohamed Abdel-Aty ◽  
Ling Wang ◽  
Jaeyoung Lee
Keyword(s):  
Standard Deviation ◽  
Traffic Safety ◽  
Risk Index ◽  
Flow Characteristics ◽  
Crash Risk ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Car Following ◽  
Real Time Traffic ◽  
Surrogate Measures

This study evaluated the effectiveness of connected vehicle (CV) technologies in adverse visibility conditions using microscopic traffic simulation. Traffic flow characteristics deteriorate significantly in reduced visibility conditions resulting in high crash risks. This study applied CV technologies on a segment of Interstate I-4 in Florida to improve traffic safety under fog conditions. Two types of CV approaches (i.e., connected vehicles without platooning (CVWPL) and connected vehicles with platooning (CVPL) were applied to reduce the crash risk in terms of three surrogate measures of safety: the standard deviation of speed, the standard deviation of headway, and rear-end crash risk index (RCRI). This study implemented vehicle-to-vehicle (V2V) communication technologies of CVs to acquire real-time traffic data using the microsimulation software VISSIM. A car-following model for both CV approaches was used with an assumption that the CVs would follow this car-following behavior in fog conditions. The model performances were evaluated under different CV market penetration rates (MPRs). The results showed that both CV approaches improved safety significantly in fog conditions as MPRs increase. To be more specific, the minimum MPR should be 30% to provide significant safety benefits in terms of surrogate measures of safety for both CV approaches over the base scenario (non-CV scenario). In terms of surrogate safety measures, CVPL significantly outperformed CVWPL when MPRs were equal to or higher than 50%. The results also indicated a significant improvement in the traffic operation characteristics in terms of average speed.

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