The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework to deliver real-time control actions that optimize travel time, energy, and safety. Hardware is an integral part of any practical implementation of CAVs, and as such, it should be incorporated in any validation method. However, high costs associated with full scale, field testing of CAVs have proven to be a significant barrier. In this paper, we present the implementation of a decentralized control framework, which was developed previously, in a scaled-city using robotic CAVs, and discuss the implications of CAVs on travel time. Supplemental information and videos can be found at this https URL.
The first approach utilizes connectivity and automation to form closely-coupled vehicular platoons to effectively reduce aerodynamic drag, especially at a high cruising speed. The concept of forming platoons of vehicles traveling at high speed was a popular system-level approach to address traffic congestion that gained momentum in the 1980s and 1990s @cite_43 @cite_36 . An automated transportation system can alleviate congestion, reduce energy use and emissions, and improve safety while increasing throughput significantly. The Japan ITS Energy Project @cite_10 , the Safe Road Trains for the Environment program @cite_1 , and the California Partner for Advanced Transportation Technology @cite_3 , are among the mostly-reported efforts in this area.
@cite_36 @cite_1 @cite_3 @cite_43 @cite_10
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Abstract This paper presents an overview on an automated truck platoon that has been developed within a national ITS project named “Energy ITS.” The project, started in 2008, aims at energy saving and global warming prevention with ITS technologies. A platoon of three fully-automated heavy trucks and also a fully-automated light truck currently drives at 80 km h with the gap of up to 4 m on a test truck and along an expressway before public use, under not only steady state driving but also lane changing. The lateral control is based on the lane marker detection by the computer vision, and the longitudinal control is based on the gap measurement by 76 GHz radar and lidar in addition to the inter-vehicle communications of 5.8 GHz DSRC and infrared. The radar and lidar also work as the obstacle detection. The feature of the technologies is the high reliability, aiming at the near future introduction. Fuel consumption measurement on a test track and along an expressway shows that the fuel can be saved by about 13 when the gap was 10 m. The evaluation simulation shows that the effectiveness of the platooning with the gap of 10 m when the 40 penetration in heavy trucks is 2.1 reduction of CO 2 along an expressway. The introduction scenario is also discussed. A unified platoon-based mathematical formulation called PAMSCOD is presented to perform arterial (network) traffic signal control while considering multiple travel modes in a vehicle-to-infrastructure communications environment. First, a headway-based platoon recognition algorithm is developed to identify pseudo-platoons given probe vehicles’ online information. It is assumed that passenger vehicles constitute a significant majority of the vehicles in the network. This algorithm identifies existing queues and significant platoons approaching each intersection. Second, a mixed-integer linear program (MILP) is solved to determine future optimal signal plans based on the current traffic controller status, online platoon data and priority requests from special vehicles, such as transit buses. Deviating from the traditional common network cycle length, PAMSCOD aims to provide multi-modal dynamical progression (MDP) on the arterial based on the probe information. Microscopic simulation using VISSIM shows that PAMSCOD can easily handle two common traffic modes, transit buses and automobiles, and significantly reduce delays for both modes under both non-saturated and oversaturated traffic conditions as compared to traditional state-of-practice coordinated-actuated signal control with timings optimized by SYNCHRO. The automation of driving tasks is of increasing interest for highway traffic management. The emerging technologies of global positioning and intervehicular wireless communications, combined with in-vehicle computation and sensing capabilities, can potentially provide remarkable improvements in safety and efficiency. We address the problem of designing intelligent in-tersections, where traffic lights and stop signs are removed, and cars negotiate the intersection through an interaction of centralized and distributed decision making. Intelligent intersections are representative of complex hybrid systems that are increasingly of interest, where the challenge is to design tractable distributed algorithms that guarantee safety and provide good performance. Systems of automatically driven vehicles will need an under lying collision avoidance system with provable safety properties to be acceptable. This condition raises several challenges. We need to ensure perpetual collision avoidance so that cars do not get into future problematic positions to avoid an immediate collision. The architecture needs to allow distributed freedom of action to cars yet should guard against worst-case behavior of other cars to guarantee collision avoidance. The algorithms should be tractable both computationally and in information requirements and robust to uncertainties in sensing and communication. To address these challenges, we propose a hybrid architecture with an appropriate interplay between centralized coordination and distributed freedom of action. The approach is built around a core where each car has an infinite horizon contingency plan, which is updated at each sampling instant and distributed by the cars, in a computationally tractable manner. We also define a dynamically changing partial-order relation between cars, which specifies, for each car, a set of cars whose worst-case behaviors it should guard against. The architecture is hybrid, involving a centralized component that coordinates intersection traversals. We prove the safety and liveness of the overall scheme. The mathematical challenge of accurately quantifying performance remains as a difficult challenge; therefore, we conduct a simulation study that shows the benefits over stop signs and traffic lights. It is hoped that our effort can provide methodologies for the design of tractable solutions for complex distributed systems that require safety and liveness guarantees. Under the Connected Vehicles (CV) environment, it is possible to create a Cooperative Vehicle Intersection Control (CVIC) system that enables cooperation between vehicles and infrastructure for effective intersection operations and management when all vehicles are fully automated. Assuming such a CVIC environment, this paper proposed a CVIC algorithm that does not require a traffic signal. The CVIC algorithm was designed to manipulate individual vehicles' maneuvers so that vehicles can safely cross the intersection without colliding with other vehicles. By eliminating the potential overlaps of vehicular trajectories coming from all conflicting approaches at the intersection, the CVIC algorithm seeks a safe maneuver for every vehicle approaching the intersection and manipulates each of them. An additional algorithm was designed to deal with the system failure cases resulting from inevitable trajectory overlaps at the intersection and infeasible solutions. A simulation-based case study implemented on a hypothetical four-way single-lane approach intersection under varying congestion conditions showed that the CVIC algorithm significantly improved intersection performance compared with conventional actuated intersection control: 99 and 33 of stop delay and total travel time reductions, respectively, were achieved. In addition, the CVIC algorithm significantly improved air quality and energy savings: 44 reductions of CO2 and 44 savings of fuel consumption.