Minimum-violation scLTL motion planning for mobility-on-demand

Vasile, Cristian-Ioan; Tůmová, Jana; Karaman, Sertaç; Belta, Călin; Rus, Daniela

doi:10.1109/icra.2017.7989177

Cited by 66 publications

(56 citation statements)

References 13 publications

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“…Recent work such as [10][11][12] investigated verifying reachand-avoid tasks 1 or routing tasks in linear temporal logic (LTL). LTL is a formal language that combines boolean and temporal operators.…”

Section: Related Workmentioning

confidence: 99%

From Specifications to Behavior: Maneuver Verification in a Semantic State Space

Esterle

Aravantinos

Knoll

2019

2019 IEEE Intelligent Vehicles Symposium (IV)

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To realize a market entry of autonomous vehicles in the foreseeable future, the behavior planning system will need to abide by the same rules that humans follow. Product liability cannot be enforced without a proper solution to the approval trap. In this paper, we define a semantic abstraction of the continuous space and formalize traffic rules in linear temporal logic (LTL). Sequences in the semantic state space represent maneuvers a high-level planner could choose to execute. We check these maneuvers against the formalized traffic rules using runtime verification. By using the standard model checker NuSMV, we demonstrate the effectiveness of our approach and provide runtime properties for the maneuver verification. We show that high-level behavior can be verified in a semantic state space to fulfill a set of formalized rules, which could serve as a step towards safety of the intended functionality.• an LTL representation corresponding to the partitioning method of [9], arXiv:1905.00708v1 [cs.RO]

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Section: Related Workmentioning

confidence: 99%

From Specifications to Behavior: Maneuver Verification in a Semantic State Space

Esterle

Aravantinos

Knoll

2019

2019 IEEE Intelligent Vehicles Symposium (IV)

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“…In our prior work, we explored similar motion planning problems for a single vehicle with conflicting rules of the road [1], [2], [3]. The notion of level of violation of rules was introduced in [1], [2] for the design of minimum-violation planners, where the vehicle was tasked to arrive at a goal location.…”

Section: Introductionmentioning

confidence: 99%

“…1 routing over topological models of road networks with the goal of minimizing delays of demands that could not be serviced within their desired deadlines. An integrated route and motion planning algorithm was proposed in [3] for a single vehicle with limited sensing tasked with servicing rich demands and obeying the rules of the road in a minimumviolating way. The approach overcomes spatial and temporal scalability issues, allowing the methods to handle large road networks with time-varying estimated travel times available to the vehicle.…”

Section: Introductionmentioning

confidence: 99%

“…Based on our previous work, we formulate a motion planning problem for multivehicle systems with the objective of minimizing the social cost. We propose a receding horizon solution, that leverages our previous planning method [3] when no collision between vehicles are encountered. However, when possible collisions are detected, we resolve the situations locally within socalled bubble spaces enclosing the conflict, and performing joint planning to overcome them.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, an RRT * -based approach tailored for finding minimum-violation motion plans was proposed in [1], but it did not consider sensing, all information was available off-line. In previous work, we proposed an integrated route and motion planning framework [3] that minimized specification violation, but only for a single vehicle.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Vehicle Motion Planning for Social Optimal Mobility-on-Demand

Karlsson

Vasile

Tůmová

et al. 2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

Self Cite

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The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters.Abstract-In this paper we consider a fleet of self-driving cars operating in a road network governed by rules of the road, such as the Vienna Convention on Road Traffic, providing rides to customers to serve their demands with desired deadlines. We focus on the associated motion planning problem that tradesoff the demands' delays and level of violation of the rules of the road to achieve social optimum among the vehicles. Due to operating in the same environment, the interaction between the cars must be taken into account, and can induce further delays. We propose an integrated route and motion planning approach that achieves scalability with respect to the number of cars by resolving potential collision situations locally within so-called bubble spaces enclosing the conflict. The algorithms leverage the road geometries, and perform joint planning only for lead vehicles in the conflict and use queue scheduling for the remaining cars. Furthermore, a framework for storing previously resolved conflict situations is proposed, which can be use for quick querying of joint motion plans. We show the mobility-on-demand setup and effectiveness of the proposed approach in simulated case studies involving up to 10 selfdriving vehicles.

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A Differentially Private and Truthful Incentive Mechanism for Traffic Offload to Public Transportation

Niu

Clark

2018

Lecture Notes in Computer Science

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Increasingly large trip demands have strained urban transportation capacity, which consequently leads to traffic congestion. In this work, we focus on mitigating traffic congestion by incentivizing passengers to switch from private to public transit services. We address the following challenges. First, the passengers incur inconvenience costs when participating in traffic offload due to delay and discomfort, and thus need to be reimbursed. The inconvenience cost, however, is unknown to the government when choosing the incentives. Furthermore, participating in traffic offload raises privacy concerns from passengers. An adversary could infer personal information, (e.g., daily routine, region of interest, and wealth), by observing the decisions made by the government, which are known to the public. We adopt the concept of differential privacy and propose privacy-preserving incentive designs under two settings, denoted as two-way communication and one-way communication. Under two-way communication, we focus on how the government should reveal passengers' inconvenience costs to properly incentivize them while preserving differential privacy. We formulate the problem as a mixed integer linear program, and propose a polynomial-time approximation algorithm. We show the proposed approach achieves truthfulness, individual rationality, social optimality, and differential privacy. Under one-way communication, we focus on how the government should design the incentives without revealing passengers' inconvenience costs while still preserving differential privacy. We formulate the problem as a convex program, and propose a differentially private and near-optimal solution algorithm. A numerical case study using Caltrans Performance Measurement System (PeMS) data source is presented as evaluation. arXiv:1906.01683v1 [cs.CY] 4 Jun 2019integer linear program. We propose an efficient approximation algorithm to reduce the computation complexity. • We prove that the proposed mechanism design under two-way communication achieves approximate optimal social welfare, truthfulness, individual rationality, and differential privacy. • For the one-way communication, we formulate the problem as an online convex program. We give a polynomialtime algorithm to solve for the mechanism design. We prove that the proposed mechanism is differentially private and Hannan consistent. • We present a numerical case study with real-world trace data as evaluation. The results show that the proposed approach achieves individual rationality and non-negative social welfare, and is privacy preserving. The remainder of this paper is organized as follows. We discuss the related works in Section II. In Section III, we present the problem formulation under two-way and one-way communication settings, respectively. We present the proposed incentive mechanism design in Section IV for the two-way communication setting. Section V gives the proposed solution for one-way communication setting. The proposed approaches are demonstrated using a numerical case study in Sectio...

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Minimum-violation scLTL motion planning for mobility-on-demand

Cited by 66 publications

References 13 publications

From Specifications to Behavior: Maneuver Verification in a Semantic State Space

From Specifications to Behavior: Maneuver Verification in a Semantic State Space

Multi-Vehicle Motion Planning for Social Optimal Mobility-on-Demand

A Differentially Private and Truthful Incentive Mechanism for Traffic Offload to Public Transportation

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