Impact of Travel Time Models on Quality of Real-Time Routing Instructions

2003 ◽  
Vol 1857 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Elise Miller-Hooks ◽  
Baiyu Yang
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Communication Systems ◽  
Service Providers ◽  
A Priori ◽  
Information Service ◽  
Small Neighborhood ◽  
Transportation Systems ◽  
Travel Times ◽  
Real Time Information

Mobile communication systems coupled with intelligent transportation systems technologies can permit information service providers to supply real-time routing instructions to suitably equipped vehicles as real-time travel times are received. Simply considering current conditions in updating routing decisions, however, may lead to suboptimal path choices, because future travel conditions likely will differ from that currently observed. Even with perfect and continuously updated information about current conditions, future travel times can be known a priori with uncertainty at best. Further, in congested transportation systems, conditions vary over time as recurrent congestion may change with a foreseeable pattern during peak driving hours. It is postulated that better, more robust routing instructions can be provided by explicitly accounting for this inherent stochastic and dynamic nature of future travel conditions in generating the routing instructions. It is further hypothesized that nearly equally good routing instructions can be provided by collecting real-time information from only a small neighborhood within the transportation system as from the entire system. Extensive numerical experiments were conducted to assess the validity of these two hypotheses.

scholarly journals Estimation of the Number of Passengers in a Bus Using Deep Learning

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2178
Author(s):  
Ya-Wen Hsu ◽  
Yen-Wei Chen ◽  
Jau-Woei Perng
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Occupancy Rate ◽  
Convolutional Autoencoder ◽  
Real Time Information ◽  
Time Information ◽  
Better Than

For the development of intelligent transportation systems, if real-time information on the number of people on buses can be obtained, it will not only help transport operators to schedule buses but also improve the convenience for passengers to schedule their travel times accordingly. This study proposes a method for estimating the number of passengers on a bus. The method is based on deep learning to estimate passenger occupancy in different scenarios. Two deep learning methods are used to accomplish this: the first is a convolutional autoencoder, mainly used to extract features from crowds of passengers and to determine the number of people in a crowd; the second is the you only look once version 3 architecture, mainly for detecting the area in which head features are clearer on a bus. The results obtained by the two methods are summed to calculate the current passenger occupancy rate of the bus. To demonstrate the algorithmic performance, experiments for estimating the number of passengers at different bus times and bus stops were performed. The results indicate that the proposed system performs better than some existing methods.

scholarly journals The UbiBus Project: Using Context and Ubiquitous Computing to build Advanced Public Transportation Systems to Support Bus Passengers

2012 ◽  
Author(s):  
Vaninha Vieira ◽  
Ana Carolina Salgado ◽  
Patricia Tedesco ◽  
Valeria Times ◽  
Carlos Ferraz ◽  
...  
Keyword(s):  
Ubiquitous Computing ◽  
Real Time ◽  
Public Transportation ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Time Factors ◽  
Transportation Systems ◽  
Urban Mobility ◽  
Public Transportation Systems ◽  
Real Time Information

Urban mobility is a problem that affects all cities. Providing real time information that can assist citizens on planning their trips by choosing times and itineraries more appropriate to their needs are essential on smart cities. Our project, named UbiBus, investigates how Computational Context and Ubiquitous Computing can be applied to Intelligent Transportation Systems to aid bus passengers mobility on cities, since dynamic real-time factors can affect transportation means. This paper describes the overall ideas concerning the UbiBus Project and presents some of the applications under development with their preliminary results.

Telecommunications- and Information Technology–Inspired Analyses: Review of an Intelligent Transportation Systems Experience

2017 ◽  
Vol 2658 (1) ◽  
pp. 44-55 ◽  
Author(s):  
Yupo Chan
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Real Time ◽  
Traffic Management ◽  
Transportation Systems ◽  
Lessons Learned ◽  
Connected Vehicles ◽  
Ongoing Research ◽  
Real Time Information ◽  
Time Information

This paper reviews both the author’s experience with managing highway network traffic on a real-time basis and the ongoing research into harnessing the potential of telecommunications and information technology (IT). On the basis of the lessons learned, this paper speculates about how telecommunications and IT capabilities can respond to current and future developments in traffic management. Issues arising from disruptive telecommunications technologies include the ready availability of real-time information, the crowdsourcing of information, the challenges of big data, and the need for information quality. Issues arising from transportation technologies include autonomous vehicles and connected vehicles and new taxi-like car- and bikesharing. Illustrations are drawn from the following core functions of a traffic management center: ( a) detecting and resolving an incident (possibly through crowdsourcing), ( b) monitoring and forecasting traffic (possibly through connected vehicles serving as sensors), ( c) advising motorists about routing alternatives (possibly through real-time information), and ( d) configuring traffic control strategies and tactics (possibly though big data). The conclusion drawn is that agility is the key to success in an ever-evolving technological scene. The solid guiding principle remains innovative and rigorous analytical procedures that build on the state of the art in the field, including both hard and soft technologies. The biggest modeling and simulation challenge remains the unknown, including such rapidly emerging trends as the Internet of things and the smart city.

scholarly journals Real-Time Adaptive Traffic Signals Using Rate-Monotonic Scheduling

2019 ◽  
Vol 29 ◽  
pp. 03002 ◽  
Author(s):  
Mãdãlin-Dorin Pop
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Signals ◽  
Fixed Time ◽  
Transportation Systems ◽  
Real Time Scheduling ◽  
Traffic Lights ◽  
Rate Monotonic ◽  
Rate Monotonic Scheduling

The studies and real situations shown that the traffic congestion is one of nowadays highest problems. This problem wassolved in the past using roundabouts and traffic signals. Taking in account the number of cars that is increasing continuously, we can see that past approaches using traffic lights with fixed-time controller for traffic signals timing is obsolete. The present and the future is the using of Intelligent Transportation Systems. Traffic lights systems should be aware about realtime traffic parameters and should adapt accordingly to them. The purpose of this paper is to present a new approach to control traffic signals using rate-monotonic scheduling. Obtained results will be compared with the results obtained by using others real-time scheduling algorithms.

Simulation of an Arterial Incident Environment with Probe Reporting Capability

1998 ◽  
Vol 1644 (1) ◽  
pp. 116-123 ◽  
Author(s):  
Natacha Thomas ◽  
Bader Hafeez
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Simulation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Incident Detection ◽  
Travel Times ◽  
Control Center ◽  
Microscopic Traffic Simulation ◽  
Arterial Streets ◽  
Detection Systems

Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.

A Real-Time Information Service Platform for High-Speed Train

2012 ◽  
Vol 7 (9) ◽  
Author(s):  
Ruidan Su ◽  
Tao Wen ◽  
Weiwei Yan ◽  
Kunlin Zhang ◽  
Dayu Shi ◽  
...  
Keyword(s):  
Real Time ◽  
High Speed ◽  
Information Service ◽  
High Speed Train ◽  
Service Platform ◽  
Real Time Information ◽  
Time Information

Assessment of Rural Intelligent Transportation System Wireless Communications Solutions

2000 ◽  
Vol 1739 (1) ◽  
pp. 51-58 ◽  
Author(s):  
Qingyan Yang ◽  
Virginia Sisiopiku ◽  
Jim A. Arnold ◽  
Paul Pisano ◽  
Gary G. Nelson
Keyword(s):  
Wireless Communications ◽  
Wireless Communication ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Communication Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Future Research ◽  
Wireless Communication Systems ◽  
Rural Environments

Rural transportation systems have different features and needs than their urban counterparts. To address safety and efficiency concerns in rural environments, advanced rural transportation systems (ARTS) test and deploy appropriate intelligent transportation systems (ITS) technologies, many of which require communication support. However, wireless communication systems that currently serve urban areas often are not available or suitable in rural environments. Thus, a need exists to identify communication solutions that are likely to address successfully the needs and features of ARTS applications. Current and emerging wireless communications systems and technologies have been systematically assessed with respect to rural ITS applications. Wireless communication functions associated with rural ITS functions are first identified. Then requirements for applicable communication technologies in the rural environment are defined. Existing and emerging wireless communication systems and technologies are reviewed and evaluated by a systematic process of assessing rural ITS wireless solutions. Finally, recommendations for future research and operational tests are offered. The analysis results are expected to benefit rural ITS planners by identifying suitable wireless solutions for different rural contexts.

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