Intelligent Transportation Systems

Human-In-The-Loop Classification of Adaptive Cruise Control at a Freeway Scale

Wang, Xia
Nice, Matthew
Bunting, Matt
Wu, Fangyu
Maria Laura Delle Monache
Lee, Jonathan W.
Piccoli, Benedetto
Seibold, Benjamin
Alexandre Bayen
Work, Daniel B.
Sprinkle, Jonathan
2025

The goal of this paper is to estimate whether a human or Adaptive Cruise Control (ACC) is managing a vehicle's speed control, based on observations by external sensors. The driving characteristics of individual vehicles---whether human-driven or ACC-controlled---play a crucial role in shaping overall traffic flow. To enable advanced traffic control strategies tailored to specific vehicle behaviors, this paper introduces a time-series deep learning classifier that leverages multiple models, including One-Dimensional Convolutional Neural Networks (1D-CNN), Recurrent Neural Networks (RNN),...

Strategizing Equitable Transit Evacuations: A Data-driven Reinforcement Learning Approach

Tang, Fang
Wang, Han
Maria Laura Delle Monache
2025

As natural disasters become increasingly frequent, the need for efficient and equitable evacuation planning has become more critical. This paper proposes a data-driven, reinforcement learning (RL)-based framework to optimize public transit operations for bus-based evacuations in transportation networks with an emphasis on improving both efficiency and equity. We model the evacuation problem as a Markov Decision Process (MDP) solved by RL, using real-time transit data from General Transit Feed Specification (GTFS) and transportation networks extracted from OpenStreetMap (OSM). The RL agent...

Preliminary Study of the Application of Synthetic Vision for Obstacle Avoidance on Highways

Misener, James A.
Raja Sengupta
Godbole, Datta N.
1997

Understanding and characterizing the forward environment of a ground vehicle is a pivotal element in determining the appropriate maneuver-response strategy while under varied degrees of vehicle automation. Potential degrees of automation span the probable near-term adoption of longitudinal crash countermeasure warning devices all the way through the longer-term objective of full vehicle automation. Between these extremes lies partially automated longitudinal crash avoidance, a potentially rich area of application for synthetic vision. This paper addresses the application of synthetic...

Benefit Evaluation of Crash Avoidance Systems

Godbole, Datta N.
Raja Sengupta
Misener, James
Kourjanskaia, Natasha
Michael, James B.
1998

A five-layer hierarchy to integrate models, data, and tools is proposed for benefits assessment and requirements development for crash avoidance systems. The framework is known as HARTCAS: Hierarchical Assessment and Requirements Tools for Crash Avoidance Systems. The analysis problem is multifaceted and large-scale. The driving environment is diverse and uncertain, driver behavior and performance are not uniform, and the range of applicable collision avoidance technologies is wide. Considerable real-world data are becoming available on certain aspects of this environment, although the...

Geographical Routing Using Partial Information for Wireless Ad Hoc Networks

Jain, Rahul
Puri, Anuj
Raja Sengupta
2001

In this paper, we present an algorithm for routing in wireless ad hoc networks using information about geographical location of the nodes. We assume each node knows its geographical position and the position of the node to which it wants to send a packet. Initially, the nodes only know their neighbors but over time they discover other nodes in the network. The routing table at a node S is a list ((pi, Si)) where pi is a geographical position and Si is a neighbor of node 5’. When node S receives a packet for a node D at position pos(D), it finds the pi in its routing table which is closest...

Modular Composition of Synchronous Programs: Applications to Traffic Signal Control

Zennaro, Marco
Raja Sengupta
2006

This paper describes a modular compilation scheme for distributed synchronous programming. The approach is first described mathematically and then implemented as a library to distribute Simulink (59). Application of the scheme is illustrated by developing a control system to coordinate traffic signals.

Kalman Filter-Based Integration of DGPS and Vehicle Sensors for Localization

Rezaei, Shahram
Raja Sengupta
2007

We present a position estimation scheme for cars based on the integration of global positioning system (GPS) with vehicle sensors. The aim is to achieve enough accuracy to enable in vehicle cooperative collision warning, i.e., systems that provides warnings to drivers based on information about the motions of neighboring vehicles obtained by wireless communications from those vehicles, without use of ranging sensors. The vehicle sensors consist of wheel speed sensors, steering angle encoder, and a fiber optic gyro. We fuse these in an extended Kalman filter. The process model is a dynamic...

Decentralized Error-Dependent Transmission Control for Model-Based Estimation Over a Multi-Access Network

Huang, Ching-Ling
Raja Sengupta
2008

This paper is motivated by the estimation problem and active safety design for ITS. We investigate the performance of model-based estimation over a multi-access network and emphasizes on asymptotic time-averaged MSE while using error-dependent transmission control. The performance of this decentralized policy is analyzed and an improved policy is also proposed to achieve robustness in a shared channel. Our results suggest that, while designing communication logic for vehicular safety applications, dynamics of the system and channel congestion should be considered at the same time.

A Bounded Real Lemma for Jump Systems

Seiler, P.
Raja Sengupta
2009

This note presents a bounded real lemma for discrete-time Markovian jump linear systems (MJLSs). We show that the linear matrix inequality in the bounded real lemma is both necessary and sufficient for this class of systems. For the case of one plant mode, this condition reduces to the standard necessary and sufficient condition for discrete-time systems. We envision this lemma being used to construct necessary and sufficient analysis and synthesis conditions for MJLSs.

3/2–Approximation Algorithm for Two Variants of a 2-Depot Hamiltonian Path Problem

Rathinam, Sivakumar
Raja Sengupta
2010

We consider two variants of a 2-depot Hamiltonian path problem and show that they have an algorithm with an approximation ratio of 32 if the costs are symmetric and satisfy the triangle inequality. This improves the 2-approximation algorithm already available for the problem.