Yunjie Zhao

Assessing the Mobility and Environmental Benefits of Reservation-Based Intelligent Intersections Using an Integrated Simulator

The connected vehicle research program is a multimodal research initiative in the U.S. that envisions a fully connected transportation system with wireless communications linking vehicles, the infrastructure, and handheld smart devices. This paper designs and evaluates a reservation-based approach to intersection control that is designed to take full advantage of the unprecedented connectivity that the connected vehicle initiative promises to provide. The control approach, which is referred to herein as the “intelligent intersection” approach, builds on the previous work by Dresner and Stone by introducing new features to better account for several aspects of the real-world driving environment. To design and evaluate the “intelligent intersection,” a novel simulation test bed for connected vehicle applications is developed. The test bed integrates a microscopic traffic simulator with a network simulator and an emission analyzer. Using the integrated simulator, the mobility and environmental benefits of the intelligent intersection approach, compared with those of traditional control methods, are evaluated on two case studies: 1) an isolated intersection and 2) a real-world transportation network with multiple intersections. Results show that the proposed control approach offers significant mobility and environmental benefits. For example, for the second test case and using observed traffic volumes, the intelligent intersection reduced the average vehicle delay by 85%, fuel consumption by 50%, and emissions by 39%-50%. The study also demonstrates the utility of using the simulator test bed in the design and evaluation of connected vehicle applications.

Integrated Traffic-Driving-Networking Simulator for the Design of Connected Vehicle Applications: Eco-Signal Case Study

This article first develops an integrated traffic-driving-networking simulator (ITDNS) intended for the design and evaluation of cyber transportation systems (CTS) and connected vehicle (CV) applications. The ITDNS allows a human driver to control a subject vehicle, in a virtual environment, that is capable of communicating with other vehicles and the infrastructure with CTS messages. The challenges associated with the integration of the three simulators, and how those challenges were overcome, are discussed. As an application example, an eco-signal system, which recommends the approach speed for vehicles approaching the intersection so as to minimize fuel consumption and emissions, was implemented in the ITDNS. Test drivers were then asked to virtually drive through a signalized corridor twice, one time with the eco-signal system in place and another without the system. Thanks to the human-in-the-loop component of ITDNS, the research was able to evaluate the likely benefits of the eco-signal system, while accounting for the response of human drivers to the recommended speed profiles. Moreover, the study compared the energy consumption and emission production rates of human-controlled vehicles’ approach trajectories to the rates associated with “idealistic” trajectories that may be attainable via vehicle automation. With respect to ITDNS, the study demonstrates the unique advantages of the simulator and the broad range of applications it can address. Regarding the eco-signal application example, preliminary results demonstrate the potential of the concept to result in tangible reductions of around 9% for energy consumption, 18% for carbon monoxide, and 25% for nitrogen oxides emissions. Moreover, the application eliminated hard accelerations and decelerations maneuvers, and thus may have an additional positive safety impact.

Towards efficient vacant taxis Cruising Guidance

Different from the conventional operation mode in existing taxi dispatch systems, in this paper, we envision a new cyber-technology enabled taxi dispatch system which can efficiently provide vacant taxis with cruising route suggestions, not to respond to any specific pick-up request but instead, hoping to find prospective customers (such system is also complementary to the conventional operation mode). We address the Taxi Cruising Guidance (TCG) problem with the objective being to minimize the Global Vacant Rate (GVR), which is defined as the ratio of traveling miles with no passenger onboard, to the total traveling miles in a given time period. We propose a number of heuristic solutions and conduct comprehensive performance evaluations based on large-scale simulations. A case study is also presented by utilizing real traces collected from taxis in the city of Shanghai. As part of our research, we leverage a well-known microscopic traffic simulator (called TRANSIMS) to demonstrate that the application of TCG is also beneficial to traffic management.

On-road ads delivery scheduling and bandwidth allocation in vehicular CPS

We consider a promising application in Vehicular Cyber-Physical Systems (VCPS) called On-road Ad Delivery (OAD), where targeted advertisements are delivered via roadside APs to attract commuters to nearby shops. Different from most existing works on VANETs which only focused on a single technical area, this work on OAD involves technical elements from human factors, cyber systems and transportation systems since a commuters shopping decision depends on e.g. the attractiveness of the ads, the induced detour, and traffic conditions on different routes. In this paper, we address a new optimization problem in OAD whose goal is to schedule ad messages and allocate a limited amount of AP bandwidth so as to maximize the system-wide performance in terms of total realized utilities (TRU) of the delivered ads. A number of efficient heuristics are proposed to deal with ad message scheduling and AP bandwidth allocation. Besides largescale simulations, we also present a case study in a more realistic scenario utilizing real traces collected from taxis in the city of Shanghai. In addition, we use a commercial traffic simulator (PARAMICS) to show that our proposed solutions are also useful for traffic management in terms of balancing vehicular traffic and alleviating congestion.

Modeling the Impact of Inclement Weather on Freeway Traffic Speed at Macroscopic and Microscopic Levels

Inclement weather conditions, such as snowy and icy conditions, could have major impacts on driver behavior and on the performance of surface transportation systems. Recently, researchers have had an increased interest in understanding this impact better as well as in modeling it. This study contributes to the emerging literature in the impact of snowy and icy conditions on traffic and driver behavior by modeling the impact of inclement weather on freeway traffic speed, at both the macroscopic and microscopic levels, with data from Buffalo, New York. At the macroscopic level, freeway speed data observed on a Buffalo section of the New York State Thruway were correlated to a set of weather indices introduced by the study; the result was a regression model that could be used to estimate the average freeway speed as a function of weather conditions. At the microscopic level, the study was the first attempt to calibrate a cellular-automata traffic simulation model, specifically, the TRANSIMS model, to inclement weather (i.e., snowy) conditions. For the calibration of TRANSIMS, a vehicle equipped with a Global Positioning System collected second-by-second vehicle dynamics information during both normal and snowy weather conditions. The collected information was the basis for the adjustment of several of the TRANSIMS model parameters. The adjusted parameters enabled the model to closely replicate observed traffic flow parameters at both the macroscopic and microscopic scales.

Large-scale Agent-based Traffic Micro-simulation: Experiences with Model Refinement, Calibration, Validation and Application

Abstract This paper describes the authors’ continued efforts toward the development, calibration, validation and application of a large-scale, agent-based model of the Buffalo-Niagara metropolitan area. The model is developed using the TRansportation ANalysis SIMulation System (TRANSIMS), an open-source, agent-based suite of transportation models originally developed by Los Alamos National Lab (LANL). Following the network error-checking, calibration and validation phases of the model development cycle, the model was used to evaluate the impact of significant snow storm events on the performance of surface transportation network. This was done by modifying the behavior of the agents (i.e. the drivers) in the model to reflect more conservative driving behavior and vehicle dynamics limitations (such as maximum acceleration and deceleration) imposed by the impaired road surface condition. The study demonstrates that the development of regional agent-based models is technically feasible, but one that requires significant efforts in terms of network accuracy checking, model calibration and validation. Moreover, it is shown that inclement weather events reduce the ability of transportation networks to handle the travel demand, which in turn underscores the importance of effective travel demand management during such events.

Computationally-efficient Approaches to Integrating the MOVES Emissions Model with Traffic Simulators

Abstract This paper investigates different approaches to integrating the MOtor Vehicle Emission Simulator model (MOVES) with microscopic traffic simulators to allow for project-level emissions analysis. The integration methodology is based on using the second-by-second vehicle trajectory output from the traffic simulator to define the link drive schedule required to run MOVES. This raises the question of how to define a representative vehicle trajectory for each link, because tracking the emissions for individual vehicles is computationally intractable. In this study, the accuracy of two aggregation methods and one sampling method, for defining the representative trajectory, are compared for both freeway and arterial links. The results indicate that the sampling method outperforms either one of the aggregation methods, and that using as few as five probes can achieve over 95% accuracy in a timely manner.

Simulation-Based Testing and Evaluation Tools for Transportation Cyber–Physical Systems

Transportation cyber-physical systems (TCPSs) require simulation-based testing and evaluation due to the prohibitive cost of building realistic test beds. Given the transdisciplinary nature of TCPSs, various simulation models and frameworks have been proposed in civil engineering, computer science, and related fields. Traditionally, researchers in different areas have developed their own set of simulation tools, which provide limited capability for TCPS research. In recent years, we have witnessed a growing interest of combining two or more features of traditional simulators to capture the unique characteristics of TCPSs. In this paper, we describe several mainstream simulation models used in transportation, communication, and human-factor studies in TCPS research. Moreover, we present our unique design and implementation of an integrated traffic-driving-network simulator (ITDNS). Finally, we discuss future enhancements that will promote best simulation practices for TCPS research.

Integrated Traffic-Driving-Networking Simulator: A Unique RaD Tool for Connected Vehicles

This paper describes on-going research aimed at developing a 3-in-1 integrated traffic-driving-networking simulator (ITDNS) for the design and evaluation of Cyber Transportation Systems (CTS) and Connected Vehicle (CV) applications. This unique simulator allows a human driver to control a subject vehicle in a virtual environment, this vehicle is capable of communicating with other vehicles and the infrastructure via CTS messages. The challenges associated with the integration of the three simulators, and how those challenges were overcome, are discussed.

A Partial Reality Experimental System for Human-in-the-Loop Testing of Connected and Automated Vehicle Applications: Development, Validation and Applications

This chapter describes a trans-disciplinary research initiative currently underway at the University at Buffalo, the State University of New York, which aims at developing next generation testing and evaluation platform for emerging Cyber Transportation Systems (CTS). Specifically, the work is developing an integrated traffic-driving-networking simulator (ITDNS), which allows for human-in-the-loop testing of Connected Vehicle (CV) and Automated Vehicle (AV) applications and their interactions. Following a brief discussion of ITDNS, its design rationale and unique advantages, the chapter proceeds to describe some of the on-going research designed to validate and extend ITDNS. The chapter also briefly describes our recent research which is taking advantage of the human-in-the-loop testing capabilities of ITDNS to evaluate a number of CV and AV applications such as eco-signals, Adaptive Cruise Control (ACC), and Co-operative, Integrated Vehicle Infrastructure Control (CIVIC).