Optimal speed advisory for connected vehicles in arterial roads and the impact on mixed traffic

2016 ◽  
Vol 69 ◽  
pp. 548-563 ◽  
Author(s):  
Nianfeng Wan ◽  
Ardalan Vahidi ◽  
Andre Luckow
Keyword(s):  
Connected Vehicles ◽  
Mixed Traffic ◽  
Optimal Speed ◽  
The Impact

Parameter Sensitivity Analysis of a Cooperative Dynamic Bus Lane System With Connected Vehicles

2021 ◽  
pp. 036119812110357
Author(s):  
Meng Xie ◽  
Michael Winsor ◽  
Tao Ma ◽  
Andreas Rau ◽  
Fritz Busch ◽  
...  
Keyword(s):  
Travel Time ◽  
Transition Period ◽  
Penetration Rate ◽  
Simulation Models ◽  
Driving Behavior ◽  
Connected Vehicles ◽  
Microscopic Simulation ◽  
Communication Range ◽  
Bus Lane ◽  
The Impact

This paper aims to evaluate the sensitivity of the proposed cooperative dynamic bus lane system with microscopic traffic simulation models. The system creates a flexible bus priority lane that is only activated on demand at an appropriate time with advanced information and communication technologies, which can maximize the use of road space. A decentralized multi-lane cooperative algorithm is developed and implemented in a microscopic simulation environment to coordinate lane changing, gap acceptance, and car-following driving behavior for the connected vehicles (CVs) on the bus lane and the adjacent lanes. The key parameters for the sensitivity study include the penetration rate and communication range of CVs, considering the transition period and gradual uptake of CVs. Multiple scenarios are developed and compared to analyze the impact of key parameters on the system’s performance, such as total saved travel time of all passengers and travel time variation among buses and private vehicles. The microscopic simulation models showed that the cooperative dynamic bus lane system is significantly sensitive to the variations of the penetration rate and the communication range in a congested traffic state. With a CV system and a communication range of 150 m, buses obtain maximum benefits with minimal impacts on private vehicles in the study simulation. The safety concerns induced by cooperative driving behavior are also discussed in this paper.

scholarly journals EVALUATING THE EFFECT OF HEAVY VEHICLES ON TRAFFIC PARAMETERS BY USING HEAVY VEHICLE FACTOR

2018 ◽  
Vol 6 (4) ◽  
pp. 95-104
Author(s):  
Parthkumar Patel ◽  
H.R. Varia
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Freight Transport ◽  
Heavy Vehicle ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Highway Traffic ◽  
Ideal Situation ◽  
The Impact

Safe, convenient and timely transportation of goods and passengers is necessary for development of nation. After independence road traffic is increased manifold in India. Modal share of freight transport is shifted from Railway to roadways in India. Road infrastructures continuously increased from past few decades but there is still need for new roads to be build and more than three forth of the roads having mixed traffic plying on it. The impact of freight vehicles on highway traffic is enormous as they are moving with slow speeds. Nature of traffic flow is dependent on various traffic parameters such as speed, density, volume and travel time etc. As per ideal situation these traffic parameters should remain intact, but it is greatly affected by presence of heavy vehicle in mixed traffic due to Svehicles plying on two lane roads. Heavy vehicles affect the traffic flow because of their length and size and acceleration/deceleration characteristics.  This study is aimed to analyse the impact of heavy vehicles on traffic parameters.

An Extended Intelligent Driver Model to Describe the Impact of Cyberattacks on Connected Vehicles

CICTP 2019 ◽  
2019 ◽  
Author(s):  
Sifeng Wang ◽  
Haer Gao ◽  
Guizhen Yu ◽  
Pengcheng Wang ◽  
Honggang Li
Keyword(s):  
Driver Model ◽  
Connected Vehicles ◽  
The Impact

Bridge Surface Roughness Identified from the Displacement Influence Lines of the Contact Points by Two Connected Vehicles

2020 ◽  
pp. 2043003
Author(s):  
Y. B. Yang ◽  
B. Q. Wang ◽  
Z. L. Wang ◽  
K. Shi ◽  
H. Xu ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Surface Roughness ◽  
Dynamic Properties ◽  
Surface Profile ◽  
Connected Vehicles ◽  
The Finite Element Method ◽  
Contact Points ◽  
Continuous Beams ◽  
Static Correlation ◽  
The Impact

In this study, a new, effective procedure is proposed for identifying the surface roughness from the responses recorded of two connected test vehicles moving over the bridge. Central to this study is the proposal of a simple static correlation formula for relating the dynamic deflections of the two vehicles’s contact points on the bridge, via the displacement influence lines (DILs). With the aid of this relation, the roughness formula for estimating the bridge surface profile is derived using the responses of the leading and following vehicles. It does not require any prior knowledge of the dynamic properties of the bridge. The efficacy of the proposed procedure is validated for both the simple and three-span continuous beams by the finite element method (FEM). Also, a parametric study is conducted for various physical properties of the test vehicles. It is confirmed that the roughness profiles back-calculated from the proposed formula agree excellently with the assumed ones for both the simple and continuous beams. For use in practice, the two connected test vehicles should not be designed too heavy and not to move at too fast speeds, in order to reduce the impact on the bridge.

scholarly journals Traffic Simulation Analysis on Running Speed in a Connected Vehicles Environment

2019 ◽  
Vol 16 (22) ◽  
pp. 4373 ◽  
Author(s):  
Bin Yu ◽  
Miyi Wu ◽  
Shuyi Wang ◽  
Wen Zhou
Keyword(s):  
Travel Time ◽  
Delay Time ◽  
Traffic Simulation ◽  
Road Traffic ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Connected Vehicles ◽  
Running Speed ◽  
Traffic Characteristics ◽  
The Impact

Connected vehicles (CVs) exchange a variety of information instantly with surrounding vehicles and traffic facilities, which could smooth traffic flow significantly. The objective of this paper is to analyze the effect of CVs on running speed. This study compared the delay time, travel time, and running speed in the normal and the connected states, respectively, through VISSIM (a traffic simulation software developed by PTV company in German). The optimization speed model was established to simulate the decision-makings of CVs in MATLAB, considering the parameters of vehicle distance, average speed, and acceleration, etc. After the simulation, the vehicle information including speed, travel time, and delay time under the normal and the connected states were compared and evaluated, and the influence of different CV rates on the results was analyzed. In a two-lane arterial road, running speed in the connected state increase by 4 km/h, and the total travel time and delay time decrease by 5.34% and 16.76%, respectively, compared to those in the normal state. The optimal CV market penetration rate related to running speed and delay time is 60%. This simulation-based study applies user-defined lane change and lateral behavior rules, and takes different CV rates into consideration, which is more reliable and practical to estimate the impact of CV on road traffic characteristics.

Saturation Flow Model for Signalized Intersection under Mixed Traffic Condition

2018 ◽  
Vol 2672 (15) ◽  
pp. 55-65 ◽  
Author(s):  
Sabyasachi Biswas ◽  
Souvik Chakraborty ◽  
Indrajit Ghosh ◽  
Satish Chandra
Keyword(s):  
Conventional Method ◽  
Detailed Comparison ◽  
Heterogeneous Traffic ◽  
Signalized Intersection ◽  
Percentage Error ◽  
Mixed Traffic ◽  
Kriging Method ◽  
Traffic Condition ◽  
Saturation Flow ◽  
The Impact

Saturation flow is one of the most important functional parameters at signalized intersections. It is to be noted that saturation flow is a functional measure of the intersection operation, which indicates the probable capacity if working in an ideal situation. However, determination of the saturation flow is a challenging task in developing countries like India where vehicles with diverse static and dynamic characteristics use the same carriageway. At the same time, it is influenced by several other factors. In this context, the present research is carried out to examine the effects of traffic composition, approach width and right-turning movements on saturation flow under heterogeneous traffic conditions. This paper proposes a model for computing saturation flow at the signalized intersection under mixed traffic condition based on Kriging approach. A detailed comparison of the mean saturation flow values obtained by the conventional method, regression method, and Kriging method has also been presented. Low mean absolute percentage error values (<5%) have been obtained for saturation flow by Kriging method with respect to the conventional method. Finally, the proposed models are used to evaluate the impact of right-turning vehicles on saturation flow under shared lane condition.

scholarly journals SDAE+Bi-LSTM-Based Situation Awareness Algorithm for the CAN Bus of Intelligent Connected Vehicles

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Lei Chen ◽  
Mengyao Zheng ◽  
Zhaohua Liu ◽  
Mingyang Lv ◽  
Lv Zhao ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Can Bus ◽  
Threat Assessment ◽  
Assessment Model ◽  
Risk Level ◽  
Connected Vehicles ◽  
Area Network ◽  
Network Attacks ◽  
The Future ◽  
The Impact

With a deep connection to the internet, the controller area network (CAN) bus of intelligent connected vehicles (ICVs) has suffered many network attacks. A deep situation awareness method is urgently needed to judge whether network attacks will occur in the future. However, traditional shallow methods cannot extract deep features from CAN data with noise to accurately detect attacks. To solve these problems, we developed a SDAE+Bi-LSTM based situation awareness algorithm for the CAN bus of ICVs, simply called SDBL. Firstly, the stacked denoising auto-encoder (SDAE) model was used to compress the CAN data with noise and extract the deep spatial features at a certain time, to reduce the impact of noise. Secondly, a bidirectional long short-term memory (Bi-LSTM) model was further built to capture the periodic features from two directions to enhance the accuracy of the future situation prediction. Finally, a threat assessment model was constructed to evaluate the risk level of the CAN bus. Extensive experiments also verified the improved performance of our SDBL algorithm.

scholarly journals Connected Vehicle as a Mobile Sensor for Real Time Queue Length at Signalized Intersections

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2059 ◽  
Author(s):  
Kai Gao ◽  
Farong Han ◽  
Pingping Dong ◽  
Naixue Xiong ◽  
Ronghua Du
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Bp Neural Network ◽  
Queue Length ◽  
Penetration Rate ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Mixed Traffic ◽  
Model Based ◽  
Sensing Model

With the development of intelligent transportation system (ITS) and vehicle to X (V2X), the connected vehicle is capable of sensing a great deal of useful traffic information, such as queue length at intersections. Aiming to solve the problem of existing models’ complexity and information redundancy, this paper proposes a queue length sensing model based on V2X technology, which consists of two sub-models based on shockwave sensing and back propagation (BP) neural network sensing. First, the model obtains state information of the connected vehicles and analyzes the formation process of the queue, and then it calculates the velocity of the shockwave to predict the queue length of the subsequent unconnected vehicles. Then, the neural network is trained with historical connected vehicle data, and a sub-model based on the BP neural network is established to predict the real-time queue length. Finally, the final queue length at the intersection is determined by combining the sub-models by variable weight. Simulation results show that the sensing accuracy of the combined model is proportional to the penetration rate of connected vehicles, and sensing of queue length can be achieved even in low penetration rate environments. In mixed traffic environments of connected vehicles and unconnected vehicles, the queuing length sensing model proposed in this paper has higher performance than the probability distribution (PD) model when the penetration rate is low, and it has an almost equivalent performance with higher penetration rate while the penetration rate is not needed. The proposed sensing model is more applicable for mixed traffic scenarios with much looser conditions.

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