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A case study for the implementation of an integrated variable speed limit (VSL) control strategy in a freeway section of I-80 based on SUMO simulations

Citation

Gao, Hang; Zhang, Michael (2021), A case study for the implementation of an integrated variable speed limit (VSL) control strategy in a freeway section of I-80 based on SUMO simulations, Dryad, Dataset, https://doi.org/10.25338/B8QD04

Abstract

This project aims at reducing fuel consumption and greenhouse gas emission by applying variable speed control (VSL) strategies to the traffic corridors with multi-segment and multi-bottleneck. The dataset is composed of inputs and outputs of the SUMO simulation model via TraCI API. SUMO is a microscopic traffic simulation platform which allows to simulate a given traffic demand through a given network. Namely, the inputs consist of the vehicle trip data obtained from the PeMS database in a 10-mile long freeway section of Interstate-80 Eastbound where the outputs are simulation results of the aggregated average travel time, fuel consumption and carbon emissions under different VSL strategies with different optimal speed limit.

Methods

The input data consists of the corridor structure and the traffic demand data:

  • The traffic demand data is obtained based on the public database from PeMS. Details can be found in http://pems.dot.ca.gov/.
  • The road network is constructed and modified by netedit. A 10-mile-long freeway section of Interstate-80 Eastbound, with 6 junctions across the city of Davis, CA is selected to evaluate our VSL control strategies. This section has a series of recurrent bottlenecks and severe congestion occurs almost every day in the afternoon peak hours. These multiple bottlenecks are all “critical” along the path. Junction 70 is interconnected with SR-113, another freeway from the north. It introduces heavy merging traffic without metering. A vast lane drop from 6 to 3 lanes exists between Junction 71 and 72. With saturated mainline flow and extra ramp demand at Junction 75 and 78, the downstream traffic flow is sensitive to breakdown even with ramp metering activated in peak hours. Details can be found in https://sumo.dlr.de/docs/netedit.html.

The output data is generated through the SUMO simulation. In this simulation, traffic control interface(TraCI) uses a TCP based client/server architecture to build connection with sumo, which is accessible to retrieve values of vehicles and detectors and then construct the VSL control models to get simulation results analysis. Details can be found in https://sumo.dlr.de/docs/TraCI.html.

Usage Notes

Input Data:

  1. vsl_I-80.net.xml: Definition of the 10-mile-long freeway section of Interstate-80 Eastbound network file connecting the city of Davis and West Sacrameto in California
  2. vsl_I-80.additionals.xml: Definition of induction loop detectors to capture the vehicle data in every simulation step
  3. vsl_I-80.flow.xml: Definition of 5 hours' traffic demand data(OD pairs) with three typical demand sets(light, medium and heavy)
  4. vsl_I-80.rou.xml: Vehicle routes and trip information using shortest path computation via duarouter function
  5. vsl_I-80.sumocfg.xml: Configuration file glues input files and makes it executable by SUMO

Output Data:

  1. emissions_no_vsl.xml: The output which contains aggregated travel time, fuel consumption and pollutants without control strategy
  2. emissions_static.xml: Output based on the flow-based control strategy
  3. emissions_lqr.xml: Output based on the density-based LQR control strategy

Funding

Pacific Southwest Region University Transportation Center, Award: UCD-18-21