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Effects of ACC heavy-duty vehicles in mixed traffic: environmental effects PowerPoint PPT Presentation

Effects of ACC heavy-duty vehicles in mixed traffic: environmental effects by Margareta Stefanovic and Petros Ioannou Center for Advanced Transportation Technologies University of Southern California Los Angeles, CA 90089 http://www.usc.edu/dept/ee/catt OUTLINE OF PRESENTATION Motivation

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Effects of ACC heavy-duty vehicles in mixed traffic: environmental effects

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Effects of ACC heavy-duty vehicles in mixed traffic: environmental effects

by

Margareta Stefanovic and Petros Ioannou

Center for Advanced Transportation Technologies

University of Southern California

Los Angeles, CA 90089

http://www.usc.edu/dept/ee/catt

PATH Annual Conference October 2002


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OUTLINE OF PRESENTATION

  • Motivation

  • Truck model

  • ACC control law

  • Human Driver Model

  • Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

  • Lane Change Effects

  • Conclusions

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  • Motivation

  • Several controllers for speed tracking and vehicle following for HDV’s have been designed and tested recently (e.g. by UCLA research group). They demonstrated local and string stability and close vehicle following even in the case of large actuator delays.

  • The controllers were tested for performance in HDV platoons, designed to operate in dedicated lanes. Of interest here is the impact of the mixed manual/ACC passenger car/HDV traffic on traffic flow characteristics.

  • What is the effect of ACC HDV’s on environmental pollution and fuel efficiency? Similar study for passenger cars was conducted under MOU 392 and TO 4217.

  • Large gap formed in front of the truck (both ACC and manual) in high acceleration maneuvers gives rise to cut-ins in front of the truck and potentially dangerous situations. What is the impact on traffic flow characteristics and emission when trucks are ACC equipped?

  • * D.Yanakiev, J. Eyre and I. Kanellakopoulos: “Analysis, Design, and Evaluation of AVCS for Heavy-Duty Vehicles with Actuator Delays: Final Report for MOU 240”, California PATH Research Report UCB-ITS_PRR-98-18

PATH Annual Conference October 2002


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Truck model

Complex nonlinear model of the longitudinal truck dynamics was compiled by the UCLA group. After linearization and neglecting of fast modes a simple 1st order linear model is obtained:

- truck longitudinal speed

- fuel / brake control input

d - disturbance

parameters a, bdepend on the operating point (steady state speed and the load torque) around which the system dynamics is linearized.

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- Based on the linearized model, various longitudinal controllers for vehicle following had been developed and tested for stability and performance.

- Among several such controllers we select a simple fixed gain PID controller, as it was shown that, with the appropriate choice of control parameters and spacing policies, stability and good performance of vehicle following are achieved, while the controller complexity is greatly reduced..

Control objective

Regulate to zero relative velocity vr and separation error :

- desired inter-vehicle spacing

This is achieved by satisfying:

(k - design parameter (constant or varying) tuned according to the performance requirements.

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ACC controller

-We select a fixed gain PID control law with the approximate derivative term:

Spacing policies:

- variable time headway:

if

introduced to reduce the steady state inter-vehicle spacing and to smooth the control action, and :

- variable position error gain:

included to limit the acceleration/deceleration that results from the large spacing error. Note that exponential term in k has a quadratic dependence on the position error δ.

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Truck Human Driver Model

  • There exists a variety of human driver vehicle following models for the passenger vehicles.

  • Very few of them are designed for heavy vehicles.

  • The Bando* vehicle following model:

V(x) is the desired safe velocity, determined by the following distance from the preceding vehicle, and has a sigmoid shape:

in ** this model is modified to be used for trucks in the following sense: lower sensitivity of the HDD vehicle due to its lower actuation-to-weight ratio is accounted for in the smaller sensitivity constant a (typically 0.8 or less vs. 1.5 – 5 for cars).

* M. Bando et al: “Dynamical Model of Traffic Congestion and numerical simulation”, Physical Review E, Vol. 51, N0 2, February 1995

** A.Mason and A.Woods: “Car-Following Model of Multi-species Systems of Road Traffic”, Physical Review E, Vol. 55, N0 3, March 1997.

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- We modify Bando model further, to account for the fact that the truck driver can see further away when he follows the passenger cars ahead of him:

Instead of depending on the following distance from the immediately preceding vehicle only, the desired safe velocity is assumed to depend on two (or more) vehicles ahead, e.g.:

The proportionality constant  (0 <  <1) is chosen so that the sensitivity with regards to the immediately preceding vehicle has the highest weight ( > 0.5 in the above equation).

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

Consider a fleet of ten vehicles in a single lane, nine of which are manual passenger cars, and one is ACC truck.

Proposed parameters from UCLA group *:

ck = 0.1, k0 = 1, σ = 0.1, H0 = 0.1, ch=0.2

Kp =150, Ki=3, Kd=20

Our tuned parameters:

ck = 0.01, k0 = 0.2, σ = 1, H0 = 0.4, ch=0.2

Kp=110, Ki=1, Kd=100

Exponential term in position error gain is chosen to have a parabolical dependence on the position error, as proposed in *.

For low accelerations of the preceding vehicles, the actuator of the ACC truck does not saturate, and the control action that is commanded results in a stable truck behavior, with close vehicle following, as seen from the figures below:

* D.Yanakiev, J. Eyre and I. Kanellakopoulos: “Analysis, Design, and Evaluation of AVCS for Heavy-Duty Vehicles with Actuator Delays: Final Report for MOU 240”, California PATH Research Report UCB-ITS_PRR-98-18

PATH Annual Conference October 2002


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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

Speed responses for the mixed manual/ACC traffic (4thvehicle is ACC truck, the

rest are manual passenger cars)

Position error vs. time for the ACC truck

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

Speed responses for the 100% manual traffic (4th vehicle is manually driven truck)

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

- This choice of functional dependence of position error gain k on the position error is justified for relatively low acceleration rates of the lead vehicle, as well as for the case of truck platooning.

  • Here we do not consider platooning of HDVs, but the mixing of passenger cars and trucks on highways, when vehicles in front may attempt to accelerate at the rates higher that those attainable by the heavy vehicle dynamics.

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

Speed responses for the mixed manual/ACC traffic (4th vehicle is ACC truck, the

rest are manual passenger cars). Parameter k depends on position error squared.

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

where the position error of the ACC truck is…

Position error vs. time for the ACC truck

Note the collision between the truck and the passenger car in front.

For the purposes of vehicle following in high acceleration scenarios, we modify the expression for the position error gain to have the exponential term linearly dependent on the position error.

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

With this modification, the above scenario is simulated again:

Clearly, the ACC truck keeps a safe distance from the vehicle ahead at all times.

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

The performance of the 100% manual traffic in the same scenario is now simulated. Bando model for the truck driver is used, with the safe desired speed dependent on the two vehicles immediately ahead:

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

-Environmental Evaluation

  • Compare the accumulative pollution levels and fuel economy of the 100% manual traffic (passenger cars and trucks) vs. mixed traffic (manual cars and ACC trucks).

  • Environmental evaluation model used: For passenger cars: CMEM - Comprehensive Modal Emissions Model (UC Riverside, 1998): high fidelity model, sensitive to transients. For trucks: Heavy-Duty Diesel Modal Emissions and Fuel Consumption Model (being developed by UC Riverside group, TO 4215).

  • Tailpipe emissions of unburnt hydrocarbons HC, carbon monoxide (CO), oxides of nitrogen (NOx), CO2 and fuel consumption are calculated and compared for mixed vs. manual traffic.

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Vehicle Following in Mixed Manual/ACC Passenger Cars/HDV Traffic

For the last shown speed scenario in a single lane vehicle following, the calculated benefits are given below:

However, due to the low acceleration capabilities of the HDVs, there is a very large position error formed in both mixed and manual traffic case. In multilane highway situations, this will undoubtedly give rise to (multiple) lane cut-ins in front of the truck.

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Lane Change Effects

Consider the same speed scenario; now vehicles from the adjacent lanes cut in front of the truck, using the gap formed in front of it:

Speed responses in mixed traffic: 4th vehicle is ACC truck.

Position error vs. time of the ACC truck.

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Lane Change Effects

- When ACC truck is replaced with the manually driven one, less cut-ins are expected in front of it, due to the less smooth speed response of the truck human driver. We assume one cut-in from the neighboring lane:

Speed responses in 100% manual traffic: 4th vehicle is manual truck.

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Lane Change Effects

The environmental effects?

Due to more traffic flow disturbances in the mixed case (two cut-ins instead of one) the benefits are correspondingly reduced:

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Lane Change Effects

- How are the benefits affected when the cut-in vehicle is an ACC equipped passenger car?

Speed responses in mixed traffic: 4th vehicle is ACC truck, cut-in vehicle is an ACC passenger car.

- Due to smooth acceleration of the cut-in passenger car, we assume less cut-ins in front of ACC truck.

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Lane Change Effects

Calculated environmental effects:

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Conclusions

  • ACC equipped trucks mixed with passenger cars in a vehicle following with no lane change result in moderately improved traffic flow characteristics as well as emission levels and fuel efficiency.

  • Due to low acceleration capabilities of HD vehicles, frequent cut-ins in front of the trucks are expected in high acceleration maneuvers performed downstream. This is particularly so when the truck is ACC equipped.

  • Lane cut-ins result in reduced benefits on the mixed traffic side.

  • A conclusion to be verified is that higher benefits are obtainable if trucks are platooned instead of mixed individually with other vehicles on the road.

  • Further investigation and design of new ACC control laws to achieve higher benefits for mixed manual/ACC truck/passenger cars traffic is underway.

PATH Annual Conference October 2002


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