An official website of the United States government
Traffic congestion has long been an ubiquitous problem that is exacerbating with the rapid growth of megac- ities. In this proof-of-concept work we study intrinsic motiva- tion, implemented via the empowerment principle, to control autonomous car behavior to improve traffic flow. In standard models of traffic dynamics, self-organized traffic jams emerge spontaneously from the individual behavior of cars, affecting traffic over long distances. Our novel car behavior strategy improves traffic flow while still being decentralized and using only locally available information without explicit coordination. Decentralization is essential for various reasons, not least to be able to absorb robustly substantial levels of uncertainty. Our scenario is based on the well-established traffic dynamics model, the Nagel-Schreckenberg cellular automaton. In a fraction of the cars in this model, we substitute the default behavior by empowerment, our intrinsic motivation-based method. This proposed model significantly improves overall traffic flow, mitigates congestion, and reduces the average traffic jam time.
more »
« less
This content will become publicly available on December 1, 2025
Kinetic Monte Carlo simulations of 1D and 2D traffic flows: Nonlocal models with generalized look-ahead rules
This paper presents a study on traffic flow models in one-dimensional (1D) and two-dimensional (2D) lattices. The models incorporate generalized look-ahead rules that consider nonlocal slowdown effects. The proposed cellular automata (CA) models use stochastic rules to determine the movement of cars based on the traffic configuration ahead of each car. Specifically, a look-ahead rule is used that considers both the car density ahead and a generalized interaction function based on the distance between cars. The CA models are simulated using an efficient kinetic Monte Carlo (KMC) algorithm. The numerical results in 1D demonstrate that the flows from the KMC simulations align with the macroscopic averaged fluxes for the look-ahead rule, across various parameter settings. In the 2D results, a sharp phase transition is observed from freely flowing traffic to global jamming, depending on the initial density of cars.
more »
« less
- PAR ID:
- 10546286
- Publisher / Repository:
- Elsevier Science
- Date Published:
- Journal Name:
- Transportation Research Part B: Methodological
- Volume:
- 190
- ISSN:
- 0191-2615
- Page Range / eLocation ID:
- 103083
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The traffic fundamental diagram (FD) describes the relationships among fundamental traffic variables of flow, density, and speed. FD represents fundamental properties of traffic streams, giving insights into traffic performance. This paper presents a theoretical investigation of dynamic FD properties, derived directly from vehicle car-following (control) models to model traffic hysteresis. Analytical derivation of dynamic FD is enabled by (i) frequency-domain representation of vehicle kinematics (acceleration, speed, and position) to derive vehicle trajectories based on transfer function and (ii) continuum approximation of density and flow, measured along the derived trajectories using Edie’s generalized definitions. The formulation is generic: the derivation of dynamic FD is possible with any analytical car-following (control) laws for human-driven vehicles or automated vehicles (AVs). Numerical experiments shed light on the effects of the density-flow measurement region and car-following parameters on the dynamic FD properties for an AV platoon.more » « less
-
Autonomous vehicles (AV) hold great potential to increase road safety, reduce traffic congestion, and improve mobility systems. However, the deployment of AVs introduces new liability challenges when they are involved in car accidents. A new legal framework should be developed to tackle such a challenge. This paper proposes a legal framework, incorporating liability rules to rear-end crashes in mixed-traffic platoons with AVs and human-propelled vehicles (HV). We leverage a matrix game approach to understand interactions among players whose utility captures crash loss for drivers according to liability rules. We investigate how liability rules may impact the game equilibrium between vehicles and whether human drivers’ moral hazards arise if liability is not designed properly. We find that compared to the no-fault liability rule, contributory and comparative rules make road users have incentives to execute a smaller reaction time to improve road safety. There exists moral hazards for human drivers when risk-averse AV players are in the car platoon.more » « less
-
null (Ed.)The successful synthesis of two-dimensional (2D) boron sheets typically relies on the utilization of a silver surface, which acts as a gated substrate compensating for the electron-deficiency of boron. However, how the structures of one-dimensional (1D) boron are affected by the gating effect remains unclear. By means of an unbiased global minimum structure search and density functional theory (DFT) computations, we discovered the coexistence of 2D boron sheets and 1D ribbons triggered by electrostatic gating. Specifically, at a low excess charge density level (<0.1 e per atom), 2D boron sheets dominate the low energy configurations. As the charge density increases (>0.3 e per atom), more 1D boron ribbons emerge, while the number of 2D layers is reduced. Additionally, a number of low-lying 1D boron ribbons were discovered, among which a flat borophene-like ribbon (FBR) was predicted to be stable and possess high mechanical strength. Moreover, the electride Ca 2 N was identified as an ideal substrate for the fabrication of the FBR because of its ability to supply a strong electrostatic field. This work bridges the gap between 2D and 1D boron structures, reveals the polymorphism of 1D boron ribbons under the electrostatic gating effect, and in general provides broad implications for future synthesis and applications of low-dimensional boron materials.more » « less
-
Approaching periodic systems in ensemble density functional theory via finite one-dimensional modelsAbstract Ensemble density functional theory (EDFT) is a generalization of ground-state DFT, which is based on an exact formal theory of finite collections of a system’s ground and excited states. EDFT in various forms has been shown to improve the accuracy of calculated energy level differences in isolated model systems, atoms, and molecules, but it is not yet clear how EDFT could be used to calculate band gaps for periodic systems. We extend the application of EDFT toward periodic systems by estimating the thermodynamic limit with increasingly large finite one-dimensional ‘particle in a box’ systems, which approach the uniform electron gas (UEG). Using ensemble-generalized Hartree and local spin density approximation exchange-correlation functionals, we find that corrections go to zero in the infinite limit, as expected for a metallic system. However, there is a correction to the effective mass, with results comparable to other calculations on 1D, 2D, and 3D UEGs, which indicates promise for non-trivial results from EDFT on periodic systems.more » « less
