Control and Management of Urban Traffic Networks With Mixed Autonomy

Details

• Creators:
  Pedarsani, Ramtin
• Corporate Creators:
  University of California, Santa Barbara. Electrical and Computer Engineering Department
• Corporate Contributors:
  California. Dept. of Transportation. Division of Research, Innovation, and System Information ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  Adaptive Cruise Control Asymmetry Autonomous Intelligent Cruise Control Autonomy Bernoulli Capacity Congestion Cooperative Adaptive Cruise Control (CACC) HCM Headways Highway Capacity Laser Radar Model Networks Routing Semi-Autonomous Simulation Of Urban MObility (SUMO) TraCI Traffic Platooning Traffic Simulation Validation Vehicle Mix

  More +
• Publication/ Report Number:
  CA18-3140
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report, 3/1/2017 – 2/28/2018
• Corporate Publisher:
  California. Dept. of Transportation. Division of Research and Innovation
• Abstract:
  Automobiles are increasingly equipped with autonomous and semi-autonomous technologies such as adaptive cruise control and automated lane-keeping. It is apparent that increasing numbers of these smart vehicles will have a dramatic impact on network-level mobility factors such as traffic congestion and travel times. By enabling platooning of groups of smart vehicles along the roadway, these autonomous capabilities can improve mobility. A platoon is two or more vehicles which are able to maintain short headways between them using, e.g., adaptive cruise control (ACC) (which allows a vehicle to use radar or Light Detection and Ranging (LIDAR) to automatically maintain a specified distance to the preceding vehicle) or cooperative adaptive cruise control (CACC). This report describes the study of road capacity models and vehicle routing behavior in transportation networks with mixed autonomy. That is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities, such as adaptive cruise control, that enable vehicle reduced headways and increased road capacity. In this research, a mixed traffic profile was considered, where a fraction of vehicles are smart and able to form platoons, and the remaining are regular vehicles that are manually driven. Two models were developed for road capacity under mixed autonomy that are based on the fundamental behavior of autonomous technologies such as adaptive cruise control. This study included simulation and modeling of transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. The microscopic traffic simulator "Simulation of Urban MObility" (SUMO) was used to validate the models developed in this study.
• Format:
  PDF
• Funding:
  65A0529 TO 052.5
• Collection(s):
  US Transportation Collection Autonomous Vehicles
• Main Document Checksum:
  urn:sha-512:89949c3812af108f8f29f230b2cb24ad8c843c896673faeaadcc8df41f4d8448d4e27ff1315471ceb41da9a070d852e42e653c731abf388965c7707f74adadf8
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/63058/dot_63058_DS1.pdf
• File Type:
  [PDF - 812.06 KB ]