Variable Speed Limits Control in an Urban Road Network to Reduce Environmental Impact of Traffic

Abstract

The problem of improving traffic sustainability and traffic efficiency in an urban road network, by implementing variable speed limits (VSL), is addressed in this paper. A nonlinear model predictive control (NMPC) design based on a first-order macroscopic traffic flow model is proposed for the speed limits optimization in each segment of the road network. Simulation results show the effectiveness of the proposed control approach, compared to reference cases in which the speed limits are constantly set to 30 km/h or 50 km/h. In the particular case of congested traffic conditions, the controller is capable of reducing both energy consumption and travel time, without delaying users waiting at the network boundaries.

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

“…Many VSL approaches can be found in the literature. Some of them aim at improving safety (Levin et al, 2019;Wu et al, 2019;Robinson et al, 2000), increasing road capacity and traffic flow (Frejo et al, 2019;Hadiuzzaman & Qiu, 2013;Hegyi et al, 2008), reducing pollution (S. K. Zegeye et al, 2012), and improving the energy efficiency (Othman et al, 2020). Usually, all these approaches consist in harmonizing the traffic speed.…”

“…However, special attention must be paid to the computation time to make it tractable for real-time operation, especially when the control inputs are very numerous. To address this issue, MPC approaches can be parameterized to reduce the number of control inputs (Othman et al, 2020;S. K. Zegeye et al, 2012).…”

“…Usually, these strategies are based on multi-criteria objective functions in order to improve both the energy efficiency and the traffic performance, and avoid trivial solutions, e.g., minimum or maximum speed limits everywhere. Othman et al (2020) propose to optimize the weighted sum of energy consumption and total distance traveled by road users, De Nunzio and Gutman (2017) minimize the energy consumption and the total time spent by vehicles by implementing a method based on shock waves theory, and Tajali and Hajbabaie (2018) harmonize the speed and maximize the outflow. Similarly, Van den Berg et al (2007) propose a hybrid MPC framework aiming at minimizing the travel time in mixed urban and highway networks.…”

“…Instead of using a physical model, another possibility is to use a data-driven model (S. Zegeye et al, 2013;Qi et al, 2004;Z. Xu et al, 2017;Othman et al, 2020). Basically, it consists in measuring fuel consumption or CO2 emissions and deducing look-up tables, regression models, or machine learning approaches to estimate the energy consumption from the vehicle dynamics.…”

Urban Road Traffic Fuel Consumption Optimization via Variable Speed Limits or Signalized Access Control: A Comparative Study

“…Although most variable speed limit (VSL) approaches in urban areas are not energy-efficiency oriented [5], [6], [7], speed limits have a strong impact on energy consumption and pollutant emission because of their impact on traffic dynamics [8]. In this sense, ecological VSL strategies are promising in urban environments as they can adapt to the traffic demand [9], [10]. However, studies that focus on the control of urban networks usually overlook the performance in the peri-urban areas.…”