Identification and prioritization of connected vehicle technologies for sustainable development in Iran

2021 ◽  
pp. 101829
Author(s):  
Maedeh Nasrollahi ◽  
Rohollah Ghasemi ◽  
Abdolhamid Safaei Ghadikolaei ◽  
Morteza Sheykhizadeh ◽  
Mehdi Abdi
Keyword(s):  
Sustainable Development ◽  
Connected Vehicle ◽  
Vehicle Technologies

scholarly journals Safety improvements by intelligent connected vehicle technologies: A meta-analysis considering market penetration rates

2021 ◽  
Vol 159 ◽  
pp. 106234
Author(s):  
Guiming Xiao ◽  
Jaeyoung Lee ◽  
Qianshan Jiang ◽  
Helai Huang ◽  
Mohamed Abdel-Aty ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Vehicle Technologies

User Acceptance and Willingness to Pay for Connected Vehicle Technologies: Adaptive Choice-Based Conjoint Analysis

2015 ◽  
Vol 2531 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Hyeon-Shic Shin ◽  
Michael Callow ◽  
Seyedehsan Dadvar ◽  
Young-Jae Lee ◽  
Z. Andrew Farkas
Keyword(s):  
Willingness To Pay ◽  
Online Survey ◽  
Connected Vehicle ◽  
Purchasing Decisions ◽  
Important Constraint ◽  
Trade Offs ◽  
Collision Prevention ◽  
Adaptive Choice ◽  
The Difference ◽  
Vehicle Technologies

The preferences of drivers and their willingness to pay (WTP) for connected vehicle (CV) technologies were estimated with the use of adaptive choice-based conjoint (ACBC) analysis, the newest such method available. More than 500 usable surveys were collected through an online survey. Respondents were asked to choose from variously priced CV technology bundles (e.g., collision prevention, roadway information system). The study found that the acceptance level of the CV technologies was high, given that an absolute majority of survey respondents had the highest preferences for the most comprehensive technology bundle in each attribute. However, a comparison of the average importance of each attribute, including bundle prices, implied that price would be an important constraint and would influence CV deployment rates. At the attribute level, collision prevention technology received the highest importance score (i.e., the safety benefits most appealed to drivers). The ACBC analysis seemed to mimic well the trade-offs that people would consider in their actual purchasing decisions. The difference between WTP and self-explicated prices obtained before preferences were estimated was statistically significant (i.e., participants chose bundles after they considered product attributes and prices). This finding also affirmed that the ACBC analysis was a more appropriate method than the direct questioning methods used in past studies. Finally, certain socioeconomic characteristics were positively related to WTP. Those respondents that were knowledgeable about CV technologies and showed more innovativeness had higher WTP as well.

Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies

2018 ◽  
Vol 52 (6) ◽  
pp. 1299-1326 ◽  
Author(s):  
Hyoshin (John) Park ◽  
Ali Haghani ◽  
Song Gao ◽  
Michael A. Knodler ◽  
Siby Samuel
Keyword(s):  
Location Problems ◽  
Connected Vehicle ◽  
Sensor Location ◽  
Dynamic Traffic ◽  
Vehicle Technologies

scholarly journals Review of Usage of Real-World Connected Vehicle Data

2020 ◽  
Vol 2674 (10) ◽  
pp. 939-950
Author(s):  
Yun Zhou ◽  
Raj Bridgelall
Keyword(s):  
Real World ◽  
Large Scale ◽  
The United States ◽  
Connected Vehicles ◽  
United States Department ◽  
Connected Vehicle ◽  
Pilot Model ◽  
Vehicle Data ◽  
World Information ◽  
Vehicle Technologies

GPS loggers and cameras aboard connected vehicles can produce vast amounts of data. Analysts can mine such data to decipher patterns in vehicle trajectories and driver–vehicle interactions. Ability to process such large-scale data in real time can inform strategies to reduce crashes, improve traffic flow, enhance system operational efficiencies, and reduce environmental impacts. However, connected vehicle technologies are in the very early phases of deployment. Therefore, related datasets are extremely scarce, and the utility of such emerging datasets is largely unknown. This paper provides a comprehensive review of studies that used large-scale connected vehicle data from the United States Department of Transportation Connected Vehicle Safety Pilot Model Deployment program. It is the first and only such dataset available to the public. The data contains real-world information about the operation of connected vehicles that organizations are testing. The paper provides a summary of the available datasets and their organization, and the overall structure and other characteristics of the data captured during pilot deployments. Usage of the data is then classified into three categories: driving pattern identification, development of surrogate safety measures, and improvements in the operation of signalized intersections. Finally, some limitations experienced with the existing datasets are identified.

scholarly journals Multilane Spatiotemporal Trajectory Optimization Method (MSTTOM) for Connected Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Pangwei Wang ◽  
Yunfeng Wang ◽  
Hui Deng ◽  
Mingfang Zhang ◽  
Juan Zhang
Keyword(s):  
Traffic Management ◽  
Trajectory Optimization ◽  
Fuel Efficiency ◽  
Optimization Method ◽  
Connected Vehicles ◽  
Full Potential ◽  
Connected Vehicle ◽  
Vehicle Technologies ◽  
Vehicle Fuel Efficiency ◽  
Trajectory Problem

It is agreed that connected vehicle technologies have broad implications to traffic management systems. In order to alleviate urban congestion and improve road capacity, this paper proposes a multilane spatiotemporal trajectory optimization method (MSTTOM) to reach full potential of connected vehicles by considering vehicular safety, traffic capacity, fuel efficiency, and driver comfort. In this MSTTOM, the dynamic characteristics of connected vehicles, the vehicular state vector, the optimized objective function, and the constraints are formulated. The method for solving the trajectory problem is optimized based on Pontryagin’s maximum principle and reinforcement learning (RL). A typical scenario of intersection with a one-way 4-lane section is measured, and the data within 24 hours are collected for tests. The results demonstrate that the proposed method can optimize the traffic flow by enhancing vehicle fuel efficiency by 32% and reducing pollutants emissions by 17% compared with the advanced glidepath prototype application (GPPA) scheme.

scholarly journals Modeling and simulation of vehicle group lane-changing behaviors in upstream segment of ramp areas under a connected vehicle environment

2019 ◽  
Vol 1 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Haijian Li ◽  
Zhufei Huang ◽  
Lingqiao Qin ◽  
Shuo Zheng ◽  
Yanfang Yang
Keyword(s):  
Traffic Congestion ◽  
Road Safety ◽  
Design Methodology ◽  
Vehicle Group ◽  
Connected Vehicle ◽  
Lane Changing ◽  
Content Type ◽  
Traffic Capacity ◽  
Simulation Results ◽  
Vehicle Technologies

Purpose The purpose of this study is to effectively optimize vehicle lane-changing behavior and alleviate traffic congestion in ramp area through the study of vehicle lane-changing behaviors in upstream segment of ramp areas. Design/methodology/approach In the upstream segment of ramp areas under a connected vehicle environment, different strategies of vehicle group lane-changing behaviors are modeled to obtain the best group lane-changing strategy. The traffic capacity of roads can be improved by controlling group lane-changing behavior and continuously optimizing lane-changing strategy through connected vehicle technologies. This paper constructs vehicle group lane-changing strategies in upstream segment of ramp areas under a connected vehicle environment. The proposed strategies are simulated by VISSIM. Findings The results show that different lane-changing strategies are modeled through vehicle group in the upstream segment of ramp areas, which can greatly reduce the delay of ramp areas. Originality/value The simulation results verify the validity and rationality of the corresponding vehicle group lane-changing behavior model strategies, effectively standardize the driver's lane-changing behavior, and improve road safety and capacity.

scholarly journals Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies

2021 ◽  
Vol 18 (17) ◽  
pp. 9228
Author(s):  
Hong Tan ◽  
Fuquan Zhao ◽  
Han Hao ◽  
Zongwei Liu
Keyword(s):  
Communication Systems ◽  
Road Traffic ◽  
High Tech ◽  
Connected Vehicle ◽  
Driver Assistance Systems ◽  
Road Traffic Crashes ◽  
Vehicle Communication ◽  
Advantages And Disadvantages ◽  
Crash Avoidance ◽  
Vehicle Technologies

The Intelligent and Connected Vehicle (ICV) is regarded as a high-tech solution to reducing road traffic crashes in many countries across the world. However, it is not clear how effective these technologies are in avoiding crashes. This study sets out to summarize the evidence for the crash avoidance effectiveness of technologies equipped on ICVs. In this study, three common methods for safety benefit evaluation were identified: Field operation test (FOT), safety impact methodology (SIM), and statistical analysis methodology (SAM). The advantages and disadvantages of the three methods are compared. In addition, evidence for the crash avoidance effectiveness of Advanced Driver Assistance Systems (ADAS) and Vehicle-to-Vehicle communication Systems (V2V) are presented in the paper. More specifically, target crash scenarios and the effectiveness of technologies including FCW/AEB, ACC, LDW/LDP, BSD, IMA, and LTA are different. Overall, based on evidence from the literature, technologies on ICVs could significantly reduce the number of crashes.

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