A linear Lagrangian model predictive controller of macro- and micro- variable speed limits to eliminate freeway jam waves

2021 ◽  
Vol 128 ◽  
pp. 103121
Author(s):  
Yu Han ◽  
Meng Wang ◽  
Ziang He ◽  
Zhibin Li ◽  
Hao Wang ◽  
...  
Keyword(s):  
Lagrangian Model ◽  
Variable Speed ◽  
Model Predictive Controller ◽  
Speed Limits ◽  
Variable Speed Limits ◽  
Predictive Controller

scholarly journals Homogenization Effects of Variable Speed Limits

2014 ◽  
Vol 15 (2) ◽  
pp. 130-143 ◽  
Author(s):  
Alvaro Garcia-Castro ◽  
Andres Monzon
Keyword(s):  
Weather Conditions ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Speed Limits ◽  
Key Indicator ◽  
Variable Speed Limits ◽  
Performance And Emissions ◽  
Speed Management ◽  
Road Performance

Abstract Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) - as opposed to fixed limits - have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results This study also presents a key indicator which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain). It also presents the relation between this indicator and road performance and emissions values.

An integrated control method based on the priority of ways in a freeway network

2016 ◽  
Vol 40 (3) ◽  
pp. 843-852 ◽  
Author(s):  
Minghui Ma ◽  
Shidong Liang
Keyword(s):  
Traffic Congestion ◽  
Control Method ◽  
Integrated Control ◽  
Adaptive Controller ◽  
Ramp Metering ◽  
Traffic Density ◽  
Variable Speed ◽  
Speed Limits ◽  
Variable Speed Limits ◽  
Freeway Networks

Traffic congestion is a common problem in merging regions of freeway networks. An adaptive integrated control method involving variable speed limits and ramp metering is presented with the aim of easing traffic congestion at merging regions. The problem of the imbalanced rights of ways of the upstream mainline and on-ramp at the merging region is solved by constructing the evaluation indices of congestion degree. Specifically, the traffic density and queue length of the upstream mainline and on-ramp are selected for use in the evaluation indices. Then, an adaptive controller is designed, integrating variable speed limits and ramp metering. The proposed method is tested in simulations considering a real freeway network in China calibrated by real traffic variables. The results show that the proposed adaptive integrated control method can prevent traffic flow breakdown and maintain a high outflow at the merging region during peak periods. The adaptive integrated control may lead to a 17% improvement in traffic delay.

scholarly journals Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Y. Bello ◽  
T. Azib ◽  
C. Larouci ◽  
M. Boukhnifer ◽  
N. Rizoug ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Consumption Rate ◽  
Driver Behavior ◽  
Optimal Controller ◽  
Model Predictive Controller ◽  
Speed Limits ◽  
Additional Information ◽  
Predictive Controller ◽  
The Cost ◽  
Energy Consumption Rate

The eco-driving profiles are algorithms able to use additional information in order to create recommendations or limitation over the driver capabilities. They increase the autonomy of the vehicle but currently their usage is not related to the autonomy required by the driver. For this reason, in this paper, the eco-driving challenge is translated into two-layer optimal controller designed for pure electric vehicles. This controller is oriented to ensure that the energy available is enough to complete a demanded trip, adding speed limits to control the energy consumption rate. The mechanical and electrical models required are exposed and analyzed. The cost function is optimized to correspond to the needs of each trip according to driver behavior, vehicle, and traject information. The optimal controller proposed in this paper is a nonlinear model predictive controller (NMPC) associated with a nonlinear unidimensional optimization. The combination of both algorithms allows increasing around 50% the autonomy with a limitation of the 30% of the speed and acceleration capabilities. Also, the algorithm is able to ensure a final autonomy with a 1.25% of error in the presence of sensor and actuator noise.

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