Quantifying the Impact of Cellular Vehicle-to-Everything (C-V2X) on Transportation System Efficiency, Energy and Environment

69A43551747123As communication technology develops at a rapid pace, connected vehicles (CVs) can potentially enhance vehicle safety while reducing energy consumption and emissions via data sharing. Many researchers have attempted to quantify the impacts of such CV applications and cellular vehicle-to-everything (C-V2X) communication. Highly efficient information interchange in a CV environment can provide timely data to enhance the transportation system\u2019s capacity, and it can support applications that improve vehicle safety and minimize negative impacts on the environment. This study summarizes existing literature on the safety, mobility, and environmental impacts of CV applications; gaps in current CV research; and recommended directions for future CV research. The study investigates a C-V2X eco-routing application that considers the performance of the C-V2X communication technology (mainly packet loss). The performance of the C-V2X communication is dependent on the vehicular traffic density, which is affected by traffic mobility patterns and vehicle routing strategies. As a case study of C-V2X applications, we developed an energy-efficient dynamic routing application using C-V2X Vehicle-to-Infrastructure (V2I) communication technology. Specifically, we developed a Connected Energy-Efficient Dynamic Routing (C-EEDR) application and used it in an integrated vehicular traffic and communication simulator (INTEGRATION). The results demonstrate that the C-EEDR application achieves fuel savings of up to 16.6% and 14.7% in the IDEAL and C-V2X communication cases, respectively, for a peak hour demand on the downtown Los Angeles network considering a 50% level of market penetration of connected vehicles

An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

Providing Real-time Driver Advisories in Connected Vehicles: A Data-Driven Approach Supported by Field Experimentation

Approximately 94\% of the annual transportation crashes in the U.S. involve driver errors and violations contributing to the $1 Trillion losses in the economy. Recent V2X communication technologies enabled by Dedicated Short Range Communication (DSRC) and Cellular-V2X (C-V2X) can provide cost-effective solutions for many of these transportation safety applications and help reduce crashes up to 85%. This research aims towards two primary goals. First, understanding the feasibility of deploying V2V-based safety critical applications under the constraints of limited communication ranges and adverse roadway conditions. Second, to develop a prototype application for providing real-time advisories for hazardous driving behaviors and to notify neighboring vehicles using available wireless communication platform. Towards accomplishing the first goal, we have developed a mathematical model to quantify V2V communication parameters and constraints pertaining to a DSRC-based “Safe pass advisory” application and validated the theoretical model using field experiments by measuring the communication ranges between two oncoming vehicles. We also investigated the impacts of varying altitudes, vehicle-interior obstacles, and OBU placement on V2V communication reliability and its implications. Along the direction of the second goal, we derived a data-driven model to characterize the acceleration/deceleration profile of a regular passenger vehicle with respect to speed and throttle position. As a proof of concept demonstration, we implemented an IoT-based communication architecture for disseminating the hazardous driving alerts to vulnerable drivers through cellular and/or V2X communication infrastructure

VNetIntSim: An Integrated Simulation Platform to Model Transportation and Communication Networks

The paper introduces a Vehicular Network Integrated Simulator (VNetIntSim) that integrates transportation modelling with Vehicular Ad Hoc Network (VANET) modelling. Specifically, VNetIntSim integrates the OPNET software, a communication network simulator, and the INTEGRATION software, a microscopic traffic simulation software. The INTEGRATION software simulates the movement of travellers and vehicles, while the OPNET software models the data exchange through the communication system. Information is exchanged between the two simulators as needed. As a proof of concept, the VNetIntSim is used to quantify the impact of mobility parameters (traffic stream speed and density) on the communication system performance, and more specifically on the data routing (packet drops and route discovery time)