Showing papers in "Transportation Research Part C-emerging Technologies in 1998"

A real-time computer vision system for vehicle tracking and traffic surveillance

Abstract: Increasing congestion on freeways and problems associated with existing detectors have spawned an interest in new vehicle detection technologies such as video image processing. Existing commercial image processing systems work well in free-flowing traffic, but the systems have difficulties with congestion, shadows and lighting transitions. These problems stem from vehicles partially occluding one another and the fact that vehicles appear differently under various lighting conditions. We are developing a feature-based tracking system for detecting vehicles under these challenging conditions. Instead of tracking entire vehicles, vehicle features are tracked to make the system robust to partial occlusion. The system is fully functional under changing lighting conditions because the most salient features at the given moment are tracked. After the features exit the tracking region, they are grouped into discrete vehicles using a common motion constraint. The groups represent individual vehicle trajectories which can be used to measure traditional traffic parameters as well as new metrics suitable for improved automated surveillance. This paper describes the issues associated with feature based tracking, presents the real-time implementation of a prototype system, and the performance of the system on a large data set. ©

Travel time studies with global positioning and geographic information systems: an integrated methodology

Abstract: The paper describes a new methodology for performing travel time studies using global positioning system (GPS) and geographic information system (GIS) technologies. It documents the data collection, data reduction, and data reporting procedures, as well as analyses that illustrate the capabilities of the GPS/GIS methodology. The data collection procedure uses GPS receivers to automatically collect time, local coordinates, and speed at regular sampling periods, for example every one second. The data reduction procedure filters and aggregates GPS data to compute travel time and speed along highway segments. The data reporting procedure uses a GIS-based management information system to define queries, tabular reports, and color coded maps to document travel time data along these highway segments. These procedures have been implemented in three metropolitan areas in Louisiana: Baton Rouge, Shreveport, and New Orleans. In these cities, more than 180,000 segment travel time and speed records were derived between 1995 and 1996 from nearly three million GPS data points collected on 30,000 miles of travel time runs along 300 miles of urban highways. The three analyses included in the paper to assist in the process of understanding the GPS/GIS methodology are the following: segment lengths, sampling rates, and central tendency. The segment length analysis examines the effect of using different highway segment lengths and shows that relatively short segments (0.2–0.5 miles long) are needed to detect localized traffic effects. These traffic disturbances become visible only when segment lengths are at most half the length of the associated disturbance. This means that traditional link-based segments, which are typically longer than 0.5 miles, are not sufficient to characterize localized effects properly. The sampling rate analysis addresses the effect of collecting GPS data at different sampling periods and shows that for a segment to have GPS data associated with it, the GPS sampling period should be smaller than half the shortest travel time associated with the segment. The analysis also shows a tradeoff between sampling rates and segment speed reliability, and emphasizes the need for even shorter GPS sampling periods (1–2 s) in order to minimize errors in the computation of segment speeds. The central tendency analysis compares harmonic mean speeds and median speeds and shows that median speeds are more robust estimators of central tendency than harmonic mean speeds.

Toward the design of intelligent traveler information systems

Abstract: The emergence of Intelligent Transportation Systems (ITS) has fostered the development of advanced traveler information systems (ATIS). These systems are designed to assist travelers in making pre-trip and enroute travel choice decisions. It is contended that while many traveler information systems are innovative and make use of cutting edge technologies, they lack real machine intelligence and therefore may be limited in their ability to service the traveling public over the long-run. The purpose of this paper is to present a vision of the next generation traveler information system, termed Intelligent Traveler Information Systems (ITIS) in which artificial intelligence techniques are drawn upon to create systems capable of providing travelers with more personalized planning assistance.

Perception updating and day-to-day travel choice dynamics in traffic networks with information provision

Abstract: A Bayesian updating model is developed to capture the mechanism by which travelers update their travel time perceptions from one day to the next in light of information provided by Advanced Traveler Information Systems (ATIS) and their previous experience. The availability and perceived quality of traffic information are explicitly modeled within the proposed framework. The uncertainty associated with a driver's travel time estimate is modeled in a stochastic dynamic framework and is incorporated in a travel choice model. Each driver uses a disutility function of perceived travel time and perceived schedule delay to evaluate the alternative travel choices, then selects an alternative based on the utility maximization principle. The perception updating model and the choice model are integrated with a dynamic traffic simulator (DYNASMART). Empirical results from the simulation experiments and their implications are also presented.

Safety and capacity analysis of automated and manual highway systems

Abstract: This paper compares safety of automated and manual highway systems with respect to resulting rear-end collision frequency and severity. Safety is related to driver, vehicle and highway operating characteristics. Our safety analysis method maps the variation in these operating characteristics, modeled by probability distributions, to the probability and severity of the first rear-end crash due to a hard braking disturbance on the highway. The results show that automated driving is safer than the most alert manual drivers, at similar speeds and capacities. We also present a detailed safety-capacity trade-off study for four different automated highway system concepts that differ in their information structure and separation policy. This study quantifies the impact of inter-vehicle cooperation and operating speed of the Automated Highway System (AHS). It also compares and contrasts the safety characteristics of individual vehicle and platoon based Automated Highway Systems.

Technological change and social forecasting: the case of telecommuting as a travel substitute

Abstract: Telecommuting, along with other telecommunications services, is often suggested to be a solution to congestion-related transportation problems. Forecasts of telecommuting and its impacts have typically overestimated the adoption of this arrangement. The paper reviews the problems of forecasting a complex solution to social problems. It critically assesses the wide range of forecasting approaches applied to telecommuting and the reasons for the upwards bias. The appeal of the concept, combined with various interests are among the reasons for the optimistic forecasts. Methodologically, forecasts of telecommuting tend to emphasize technological change while underestimating the social implications which determine the adoption of such technologies. A choice theory is suggested as an alternative approach which can address issues related to human behavior in the context of technological change. The explanatory power of choice models is demonstrated and suggested for future analysis of technologies which entail extensive adaptation for adopters and institutions.

Intelligent traffic signals for pedestrians: evaluation of trials in three countries

Abstract: The DRIVE II project VRU-TOO (Vulnerable Road User Traffic Observation and Optimization) carried out trials of innovative pedestrian signalized crossings that were designed to be more responsive to pedestrians needs and thereby improve pedestrian safety and comfort. These advanced crossings were installed at sites in three European countries and a comprehensive evaluation of the impacts was carried out, with particular emphasis on changes in pedestrian behaviour and safety. While there were important differences in the impacts at the various sites, partly reflecting differences in system implementation, there were general gains in safety and comfort for pedestrians. These improvements were obtained without major side effects on vehicle travel. ©

Statistical and neural classifiers to detect traffic operational problems on urban arterials

Abstract: This paper proposes using artificial neural networks in a modular architecture to assist in detecting different types of operational problems on signalized urban arterials. A traffic surveillance infrastructure that includes inductive loop detectors on intersection approaches as well as mid-block system loops for traffic monitoring is used. For arterials, problems that require the attention of a traffic management center operator include lane-blocking incidents, special event conditions, and detector malfunctioning. Problem detection depends on factors such as operating conditions, configuration of sensors within the network, and block or link length. The feasibility of training and testing neural network models as components of a modular architecture, with an appropriate model for each sub-problem of pattern recognition, is demonstrated. The performance of this modular architecture exceeded that of any single architecture applied to the detection of different types of operational problems. The paper also reports on the performance of each type of model considered and the effect traffic flow levels and detector configuration have on the performance of the incident detection model. The results show that with the selection of a suitable architecture, the modular neural classifier outperforms alternative discriminant analysis-based classifiers. This is demonstrated using cyclic data from microscopic simulation and field data from Urban Traffic Control System (UTCS) implementations in the Cities of Los Angeles and Anaheim, California.

Automatic control of variable message signs in the interurban Scottish highway network

Abstract: The paper presents the design, implementation, and evaluation work performed by a European consortium for the development of a Variable Message Sign (VMS) information and guidance system in the interurban Scottish highway network. The control strategy employed is based on simple automatic control concepts with both feedback and feedforward terms subject to user-optimum constraints. Feedforward terms are employed for the prediction of travel times and delays along long-distance interurban highway links. Simulation studies demonstrate the potential improvements achievable with these kinds of control measures and control strategies. The implementation concepts and field evaluation results are outlined. ©

Duration and frequency of telecenter use: once a telecommuter, always a telecommuter?

Abstract: The study of temporal patterns of telecommuting is essential in understanding the adoption of telecommuting and, hence, the impacts of telecommuting on the demand for equipment and services as well as the demand for travel. This research examines, in the context of center-based telecommuting, how often individuals telecommute, the duration of their telecommuting participation, and causes of attrition among telecommuters. It also presents related findings from previous studies of home-based telecommuting. Attrition at the telecenters studied was relatively high, with 50% of all telecommuters quitting within the first 9 months. The average telecommuting frequency across the sample was 22% or about 1.1 days per week. Nearly 64% of the participants telecommuted less than 1 day per week on average. The relationship between frequency and duration appears to be complex, with partially counteracting trends. The results suggest that there is a stable segment of the sample (stayers) who are committed higher-frequency telecommuters, but that within the segment having a propensity to quit, there is a slight but statistically significant tendency for higher-frequency telecommuters to quit sooner. The motivations of participants for quitting the program were investigated. The most frequent type of reason given was job-related (cited by more than a third of all quitters). Other important reasons were supervisor-related (16%) and closure of the center (12%). No one cited dissatisfaction with telecommuting as a reason for quitting, and most quitters expressed a desire to continue telecommuting from the center.

Multi-state and multi-sensor incident detection systems for arterial streets

Abstract: Incident detection systems typically emphasize incident presence and location over incident severity and incident recovery. Yet, Advanced Traveller Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) rely on the latter states to implement and terminate diversion, and its supportive control strategies. Further, incident detection systems directly benefit from processing measurement vectors rather than scalars. Vectors of lane measurements favor detection through lane imbalances and identification of incident host lanes. Intelligent Transportation Systems promise new sensor data to control centers, including the travel times experienced by probe vehicles. Vectors of new and old sensor inputs may possess enhanced discriminatory values. To accomodate added detection states and the fusion of multi-sensor input vectors, this paper reformulates the arterial incident detection problem as a multiple attribute decision making problem with Bayesian scores. This novel approach utilizes as input the combinations of simulated probe travel times, number of probe reports, lane specific detector occupancies and vehicle counts. Models based solely on probe data lack in performance due to excessive overlaps in class distributions. Models based on detector occupancies and vehicle counts by lane perform outstandingly. They display a propensity to detect through lane measurement imbalances. The probe data is shown to enhance the performance of detector data based models.

Evaluation of advanced transit alternatives using consumer welfare

Abstract: Various combinations of advanced public transportation systems (APTS), including advanced transit information, demand responsive transit, and personal rapid transit, are evaluated by applying traditional travel and emissions criteria as well as consumer welfare and equity criteria. A state-of-the-practice regional travel demand model is used to simulate the travel effects of the APTS technologies in the Sacramento region for the year 2015. A method of obtaining consumer welfare is applied to the mode choice models in the travel model. It was found that APTS technologies, which were simulated in this study to act as feeder service for light rail and bus transit, did not significantly reduce congestion and emissions in the region. This was primarily because the Sacramento region lacks extensive penetration by light rail and bus service. The consumer welfare evaluation, however, showed that all the APTS technology scenarios yielded an economic benefit and were generally equitable even when capital, operation, and maintenance costs were included in the analysis. Further, the analysis showed that advanced transit information service alone produced the greatest increase in consumer welfare. The total yearly difference in benefits among the scenarios would be significant. Thus, it is concluded that the method of obtaining consumer welfare used in this study is a useful analytical tool for identifying optimal bundles of APTS technologies.

User-equilibrium properties of fixed points in dynamic traffic assignment

Abstract: This paper considers the problem of dynamic traffic assignment under the principle that individual drivers will choose fastest paths, in the dynamic situation where path durations consist of time-dependent link travel times. Rather than constructing a unified model encompassing traffic dynamics and route choice, we decompose the model into an assignment mapping, which identifies the link travel times resulting from an input routing policy, and a routing mapping, which yields fastest-path routings associated with input link travel times. Since time-dynamic link travel times are influenced by route choice, this dynamic situation therefore encompasses predictive routing strategies. We establish that user-equilibrium routing policies are fixed points of the composition of the routing and assignment functions. After discussing difficulties associated with establishing existence of fixed points under discrete-time modeling and all-or-nothing routing, we present instead new iterative routing mappings for continuous-time multipath routing (the splitting of a single-class flow onto multiple paths), which adjust routing policies more incrementally. We provide sufficient conditions for existence of fixed points in various routing policy domains and offer some suggestions on the computation of these fixed-point policies.

Understanding the demand for access information

Abstract: In many cities Intelligent Transport Systems (ITS) offer drivers a wide range of information on the performance of the transport system. Parking Guidance and Information (PGI) systems provide drivers with information on the direction to and the availability of spaces at car parks. Advanced PGI systems also offer the possibility of presenting a range of real time information, including car park location, availability, waiting times and prices. It is important to investigate driver response to existing PGI systems since it is not clear what types of drivers are using them and how they are influencing parking choices. This paper describes the application of a number of statistical analysis techniques undertaken to estimate the impact of PGI systems in several cities in Japan. Major findings of a survey of drivers conducted in Shinjuku are presented. Models relating driver awareness, usage and understanding of PGI systems to various driver and trip characteristics were developed. Both driver awareness and usage were found to be strongly related to trip frequency and origin. Overall, it appears that many of the aims of the PGI systems studied are generally being achieved with only moderate awareness and usage levels. A study of the demand for specific types of traffic and parking was also undertaken in order to help understand the potential market for these systems as well as how they will affect transport choices. Drivers were found to be non-homogeneous with respect to their information needs. Several trip and personal characteristics affecting drivers desire for different types of information were identified. Many of these factors were found to be directly related to the drivers perceived knowledge of the traffic and parking system. The nature of these market segments should be helpful in designing future ITS and PGI systems. ©

Fuzzy-logic-based incident detection for signalized diamond interchanges

Abstract: This paper documents a fuzzy-logic-based incident detection algorithm for signalized urban diamond interchanges. The model is capable of detecting lane-blocking incidents whose effects are manifested by patterns of deterioration in traffic conditions that require adjustments in signal control strategies. As a component of a real-time traffic adaptive control system for signalized diamond interchanges, the algorithm feeds an incident report (i.e., the time, location, and severity of the incident) to the system's optimization manager, which uses that information to determine the appropriate signal control strategy. The performance of the model was studied using a simulation of an actual diamond interchange. The simulation study evaluated the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy-logic-based approach is considered promising.

A new methodology for incident detection and characterization on surface streets

Abstract: In this paper, a new methodology is presented for real-time detection and characterization of incidents on surface streets. The proposed automatic incident detection approach is capable of detecting incidents promptly as well as characterizing incidents in terms of time-varying lane-changing fractions and queue lengths in blocked lanes, lanes blocked due to incidents, and incident duration. The architecture of the proposed incident detection approach consists of three sequential procedures: (1) Symptom Identification for identification of incident symptoms, (2) Signal Processing for real-time prediction of incident-related lane traffic characteristics and (3) Pattern Recognition for incident recognition. Lane traffic counts and occupancy are the only two major types of input data, which can be readily collected from point detectors. The primary techniques utilized in this paper include: (1) a discrete-time, nonlinear, stochastic system with boundary constraints to predict real-time lane-changing fractions and queue lengths and (2) a pattern-recognition-based algorithm employing modified sequential probability ratio tests (MSPRT) to detect incidents. Off-line tests based on simulated as well as video-based real data were conducted to assess the performance of the proposed algorithm. The test results have indicated the feasibility of achieving real-time incident detection using the proposed methodology.

Modeling detection of incidents by drivers

Abstract: An analytical model was developed to assess the detection of freeway incidents by drivers using advanced communications technologies. Drivers can report incidents to a highway agency by voice or by digital messaging either directly or through roadside beacons using a fixed or portable wireless communications system such as a cellular telephone. A FRESIM model was used to simulate shoulder and lane-blocking incidents occurring under variable traffic flow rates. The proportion of drivers with an in-vehicle communication medium arriving upstream of an incident and the degree of the drivers’ reporting propensity were introduced as controlled variables. A discrete probability model was used to represent binary reporting decisions of drivers arriving upstream of an incident. The results showed that all incident types that were simulated could be detected in a short time with high probability of detection. The data indicated that all incident types, regardless of the prevailing traffic volume at the time of their occurrence, were detectable in less than one minute if one of five drivers on a freeway had an in-vehicle communication medium and was willing to use it to report the incident. Of special importance is that at the end of 1995 there was one cellular telephone user per five licensed drivers in the United States. The results of the modeling further showed that other factors affecting the detection performance of a driver-initiated incident detection process were the willingness of drivers to report incidents, the length of roadway within which an incident is visible to a driver, and the austerity of the highway agency’s procedure for mitigating false reporting.

Functional evaluation of the los angeles smart card field operational test

Abstract: This paper summarizes the functional evaluation of an Advanced Fare Payment System deployed in Los Angeles in the summer of 1994. The functional evaluation is part of a larger Field Operational Test evaluation (Chira-Chavala, T., and Coifman, B., 1996. Impacts of Smart Cards on Transit Operators: Evaluation of I–110 Corridor Smart Card Demonstration Project. UCB-ITS-PRR-96-17, Institute of Transportation Studies, California PATH Research Report, University of California, Berkeley, CA; Guliano, G. and Moore II, J. E. 1996. Evaluation of the I-110 Corridor Smart Card Demonstration Project. UCB-ITS-PRR-96-20, Institute of Transportation Studies, California PATH Research Report, University of California, Berkeley, CA) managed by the Partnership for Advanced Transit and Highways (PATH) for the California Department of Transportation (Caltrans) and the Federal Transit Administration (FTA). The demonstration project fielded two types of advanced fare cards incorporating very different technologies on three separate transit properties as part of a relatively low cost system constructed from components manufactured to commercial rather than industrial specifications. Overall, the system performed well. Radio Frequency (RF) Cards demonstrated extremely high reliability. Smart Cards performed less well then the RF Cards, but both systems greatly surpassed the standards for magnetic stripe cards. ©