Intelligent Transportation Systems

Cities as Complex Systems—Collection Overview

Rybski, Diego
Marta Gonzalez
2022

This collection provides a contemporary excerpt of “Cities as complex systems”. The contributions have been submitted between April and October 2020. We briefly discuss example papers addressing the themes “urban scaling”, “urban mobility”, “flows in cities”, “spatial analysis”, “information technology and cities”, and “cities in time”. After motivating the intersection of cities and complexity, we provide an introduction and additional thoughts on urban scaling.

Intelligent Transport Systems

Elizabeth Deakin
Karen Trapenberg Frick
Alexander Skabardonis
2009

If you've seen an electronic message sign alongthehighwaythattells you how long it will take to get downtown or to the airport, or paid your toll or your parking fees with an electronic tag, or ridden a bus that triggered the traffic lights to turn green as it approached them, then you have experienced some of the benefits of Intelligent Transportation Systems (ITS)—an...

Background Paper: The General Transit Feed Specification (GTFS) Makes Trip-Planning Easier — Especially During a Pandemic — Yet its Use by California Agencies is Uneven

Karen Trapenberg Frick
Kumar, Tanu
Post, Alison
2020

The General Transit Feed Specification (GTFS) is an open source data format public transportation agency use to share information about routes and vehicle arrival and departure times. A variety of trip-planning applications, including Google Maps, rely on GTFS feeds to incorporate public transit information. In April 2020, the California Integrated Travel Project conducted a Feasibility Study that called for the widespread adoption of GTFS-static (GTFS-s) and GTFS-realtime (GTFS-r) to make transit simpler for California residents; however, there is little research on patterns of...

Design of a Machine Vision-based, Vehicle Actuated Traffic Signal Controller

Michael Cassidy
Coifman, Benjamin
1998

This project presents a signal controller algorithm to capitalize on the extended information provided by wide-area detection at isolated intersections. Using computer simulation, different control strategies are evaluated and the performance of the proposed wide-area detection system with conventional signal controllers is compared. The results indicate that wide-area vehicle actuated (VA) control can yield significant improvements over conventional VA control strategies.

Vehicle Reidentification and Travel Time Measurement on Congested Freeways

Coifman, Benjamin
Michael Cassidy
2002

The paper presents an algorithm for matching individual vehicles measured at a freeway detector with the vehicles’ corresponding measurements taken earlier at another detector located upstream. Although this algorithm is potentially compatible with many vehicle detector technologies, the paper illustrates the method using existing dual-loop detectors to measure vehicle lengths. This detector technology has seen widespread deployment for velocity measurement. Since the detectors were not developed to measure vehicle length, these measurements can include significant errors. To overcome this...

Region-Wide Congestion Prediction and Control Using Deep Learning

Mohanty, Sudatta
Pozdnukhov, Alexey
Michael Cassidy
2020

Traffic congestion is forecast for neighborhoods within a region using a deep learning model. The model is based on Long Short-Term Memory (LSTM) neural network architecture. It forecasts a congestion score, defined as the ratio of the vehicle accumulation inside a neighborhood to its trip completion rate. Inputs include congestion scores measured at earlier times in neighborhoods within a region, and three other real-time measures of regional traffic. The ideas are tested using Newell’s simplified theory of kinematic waves. Simplified street networks are featured first. Initial tests...

Guaranteed Bounds on Highway Travel Times Using Probe and Fixed Data

Claudel, Christian G.
Alexandre Bayen
2009

This article investigates the problem of incorporating mobile probe data collected from GPS equipped cell phones into estimation algorithms for travel time. We use kinematic wave theory to create a modeling framework capable of incorporating trajectory data into the model. The problem of including loop detector data in this model is performed using a standard approach available in the literature. The problem of fusing this data with probe data is formulated using the Moskowitz function, which results from kinematic wave theory. Using this formulation, two linear programs are posed to...

Optimal Sensor Placement for Freeway Travel Time Estimation

Ban, Xuegang (Jeff)
Alexandre Bayen
Herring, Ryan
2009

This article presents a modeling framework and a polynomial solution algorithm for determining optimal locations of point detectors used to compute freeway travel times. First, an objective function is introduced to minimize the deviation of estimated and actual travel times of all individual sub-segments of a freeway route. By discretizing the problem in both time and space, we formulate it as a dynamic programming model, which can be solved via a shortest path search in an acyclic graph. Numerical examples are provided to illustrate the model and algorithm using microscopic traffic...

An Ensemble Kalman Filtering Approach to Highway Traffic Estimation Using GPS Enabled Mobile Devices

Work, Daniel B.
Tossavainen, Olli‐Pekka
Blandin, Sébastien
Alexandre Bayen
Iwuchukwu, Tochukwu
Tracton, Kenneth
2008

Traffic state estimation is a challenging problem for the transportation community due to the limited deployment of sensing infrastructure. However, recent trends in the mobile phone industry suggest that GPS equipped devices will become standard in the next few years. Leveraging these GPS equipped devices as traffic sensors will fundamentally change the type and the quality of traffic data collected on large scales in the near future. New traffic models and data assimilation algorithms must be developed to efficiently transform this data into usable traffic information. In this work, we...

Using Mobile Phones to Forecast Arterial Traffic through Statistical Learning

Herring, Ryan
Hofleitner, Aude
Amin, Saurabh
Abou Nasr, Tania
Khalek, Amin Abdel
Abbeel, Pieter
Alexandre Bayen
2010

This article introduces the new component of Mobile Millennium dedicated to arterial traffic. Mobile Millennium is a pilot system for collecting, processing and broadcasting real-time traffic conditions through the use of global position system (GPS) equipped smartphones. Two algorithms that use data from GPS equipped smartphones to estimate arterial traffic conditions are presented, analyzed and compared. The algorithms are based on Logistic Regression and Spatio-Temporal Auto Regressive Moving Average (STARMA), respectively. Each algorithm contains a learning component, which...