Showing papers on "Intelligent transportation system published in 2008"

A multiagent approach to autonomous intersection management

Abstract: Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology--traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.

Vehicle Ad Hoc networks: applications and related technical issues

Abstract: This article presents a comprehensive survey of the state-of-the-art for vehicle ad hoc networks. We start by reviewing the possible applications that can be used in VANETs, namely, safety and user applications, and by identifying their requirements. Then, we classify the solutions proposed in the literature according to their location in the open system interconnection reference model and their relationship to safety or user applications. We analyze their advantages and shortcomings and provide our suggestions for a better approach. We also describe the different methods used to simulate and evaluate the proposed solutions. Finally, we conclude with suggestions for a general architecture that can form the basis for a practical VANET.

Robust Lane Detection and Tracking in Challenging Scenarios

Abstract: A lane-detection system is an important component of many intelligent transportation systems. We present a robust lane-detection-and-tracking algorithm to deal with challenging scenarios such as a lane curvature, worn lane markings, lane changes, and emerging, ending, merging, and splitting lanes. We first present a comparative study to find a good real-time lane-marking classifier. Once detection is done, the lane markings are grouped into lane-boundary hypotheses. We group left and right lane boundaries separately to effectively handle merging and splitting lanes. A fast and robust algorithm, based on random-sample consensus and particle filtering, is proposed to generate a large number of hypotheses in real time. The generated hypotheses are evaluated and grouped based on a probabilistic framework. The suggested framework effectively combines a likelihood-based object-recognition algorithm with a Markov-style process (tracking) and can also be applied to general-part-based object-tracking problems. An experimental result on local streets and highways shows that the suggested algorithm is very reliable.

Trip-Based Optimal Power Management of Plug-in Hybrid Electric Vehicles

Abstract: Hybrid electric vehicles (HEVs) have demonstrated the capability to improve fuel economy and emissions. The plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of the HEV. The charge-depletion mode is more appropriate for the power management of PHEVs, i.e., the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the trip destination. Trip information has so far been considered as future information for vehicle operation and is thus not available a priori. This situation can be changed by the recent advancement in intelligent transportation systems (ITSs) based on the use of on-board global positioning systems (GPSs), geographical information systems (GISs), and advanced traffic flow modeling techniques. In this paper, a new approach to optimal power management of PHEVs in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the end of the driving cycle. The vehicle model was based on a hybrid electric sport utility vehicle (SUV). Only fuel consumption is considered for the current stage of the study. A simulation study was conducted for several standard driving cycles and two trip models using the proposed method, and the results showed significant improvement in fuel economy compared with a rule-based control and a depletion sustenance control for most cases. Furthermore, the results showed much better consistency in fuel economy compared with rule-based and depletion sustenance control.

Traffic Estimation And Prediction Based On Real Time Floating Car Data

Abstract: The knowledge of the actual current state of the road traffic and its short-term evolution for the entire road network is a basic component of ATIS (advanced traveler information systems) and ATMS (advanced traffic management system) applications. In this view the use of real-time floating-car data (FCD), based on traces of GPS positions, is emerging as a reliable and cost-effective way to gather accurate travel times/speeds in a road network and to improve short-term predictions of travel conditions. The purpose of this paper is to present a large-scale working application of FCD-system, developed and operated by OCTOTelematics, delivering real-time traffic speed information throughout the Italian motorway network and along some important arterial streets located in major Italian metropolitan areas. Traffic speed estimates are deduced at an interval of 3 minutes from GPS traces transmitted in real-time from a large number (and still growing) of privately owned cars (about 600.000) equipped with a specific device covering a range of insurance-related applications. This paper also proposes two algorithms, respectively based on artificial neural networks and pattern-matching, designed to on-line perform short-term (15 to 30 minutes) predictions of link travel speeds by using current and near-past link average speeds estimated by the OCTOTelematics FCD system. The Rome ring road (GRA-Grande Raccordo Anulare) was used for testing the feasibility of the two algorithms. Testing results showed that the proposed approaches for short-term predictions are very promising and effective.

A Position-Based Clustering Technique for Ad Hoc Intervehicle Communication

Abstract: Intervehicle communication is a key technique of intelligent transport systems. Ad hoc networking in the vehicular environment was investigated intensively. This paper proposes a new clustering technique for large multihop vehicular ad hoc networks. The cluster structure is determined by the geographic position of nodes and the priorities associated with the vehicle traffic information. Each cluster elects one node as its cluster head. The cluster size is controlled by a predefined maximum distance between a cluster head and its members. Clusters are independently controlled and dynamically reconfigured as nodes move. This paper presents the stability of the proposed cluster structure, and communication overhead for maintaining the structure and connectivity in an application context. The simulation is performed with comparative studies using CORSIM and NS-2 simulators.

Design of Secure and Application-Oriented VANETs

Abstract: Vehicular ad hoc networks (VANETs) are important components of Intelligent Transportation Systems. The main benefit of VANET communication is seen in active safety systems that increase passenger safety by exchanging warning messages between vehicles. Other applications and private services are also permitted in order to lower the cost and to encourage VANET deployment and adoption. Security is one of the major challenges that must be addressed before VANETs can be successfully deployed. Another crucial issue is support of different applications and services in VANETs. In this paper we propose a secure and application-oriented network design framework for VANETs. We consider both security requirements of the communications and other requirements of potential VANET applications and services. The proposed framework consists of two basic components: an application-aware control scheme and a unified routing scheme. We also study a number of key enabling technologies that are important to a practical VANET. Our study provides a guideline for the design of a more secure and practical VANET.

Intelligent Infrastructure: Neural Networks, Wavelets, and Chaos Theory for Intelligent Transportation Systems and Smart Structures

Abstract: Artificial Neural Networks Wavelets Chaos Theory Freeway Incident Detection Micro-Simulation Model for Traffic Delay and Queue Length Estimation in Freeway Work Zones Traffic Delay Estimation and Cost Optimization in Freeway Work Zones Neuro-Fuzzy Logic Model for Work Zone Capacity Estimation Clustering Neural Network Models for Work Zone Capacity Estimation and Parametric Study Object-Oriented Model for Work Zone Capacity and Delay Estimation Wavelet Analysis of Traffic Flow Time Series Wavelet Neural Network for Traffic Flow Forecasting Dynamic Fuzzy Wavelet Neural Network for Structural System Identification Nonlinear System Identification of High-Rising Building Structures Damage Detection and Health Monitoring of Structures Nonlinear Control of Smart Structures Neuro-Genetic Algorithm for Nonlinear Control of Smart Structures

Using Travel Time Reliability Measures to Improve Regional Transportation Planning and Operations

Abstract: Estimation of travel time is of increasing importance to travelers and transportation professionals alike as congestion worsens in major urban areas. In fact, the reliability of travel time estimates on a given corridor may be more important for travelers, shippers, and transport managers than the travel time itself. This paper examines the uses of measured travel time reliability indices for improving real-time transportation management and traveler information with the use of archived intelligent transportation system data. A literature review of travel time reliability and its value as a congestion measure is followed by a description of a content analysis of 20 regional transportation plans from across the nation. Results from the content analysis indicate that travel time reliability is not currently used as a congestion measure and that the most common measures of congestion are the volume-to-capacity ratio, vehicle hours of delay, and mean speed. As a case study using data from Portland, Oregon, se...

Next-Generation Automated Vehicle Location Systems: Positioning at the Lane Level

Abstract: The majority of today's automated vehicle location (AVL) systems use Global Positioning System (GPS) technology, which can provide position information with an accuracy of approximately 15 m. Recently, low-cost Differential GPS (DGPS) receivers, which have a positioning accuracy of approximate 2-3 m, have become available. With this increased accuracy, it is now possible to perform AVL down to specific roadway lanes. In this paper, a vehicle-lane-determining system is described, consisting of an onboard DGPS receiver that is connected with a wireless communications channel, a unique lane-level digital roadway database, a developed lane-matching algorithm, and a real-time vehicle location display. Lane-level positioning opens up the door for a number of new intelligent transportation system applications such as better fleet management, lane-based traffic measurements from probe vehicles, and lane-level navigation. The developed low-cost system has been tested on a number of roadways and has performed very well when used with accurately surveyed map data. Based on more than 100 000 s, it has correctly determined the lane 97% of the time.

Review of traffic data estimations extracted from cellular networks

Abstract: One of the main characteristics of modern society is the never-ending increase in mobility. This leads to a series of problems such as congestion and increased pollution. To resolve these problems, it is imperative to have a good road network management and planning. To efficiently identify the characteristics of traffic in the road network, it would be necessary to perform a permanent monitorisation of all roadway links. This would involve an excessive cost of installation and maintenance of road infrastructure. Hence, new alternatives are required which can characterise traffic in a real time with good accuracy at an acceptable price. Mobile telephone systems are considered as a promising technology for the traffic data collection system. Its extensive use in converting its subscribers in a broad sample to draw information from phones becomes anonymous probes to monitor traffic. It is reviewed how to obtain parameters related to traffic from cellular-network-based data, describing methods used in existing simulation works as well as field tests in the academic and industrial field.

Aggregation algorithms in a vehicle-to-vehicle-to-infrastructure (V2V2I) intelligent transportation system architecture

Abstract: In this paper, the vehicle-to-vehicle-to-infrastructure (V2V2I) architecture, which is a hybrid of the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) architectures is described. The V2V2I architecture leverages the benefits of fast queries and responses from the V2I architecture, but with the advantage of a distributed system with no single point-of-failure from the V2V architecture. In the V2V2I architecture, the transportation network is broken into zones in which a single vehicle is known as the Super Vehicle. Only Super Vehicles are able to communicate with the central infrastructure and all other vehicles can only communicate with the Super Vehicle responsible for the zone they are currently traversing. The Super Vehicle Detection (SVD) algorithm for how a vehicle can find or become a Super Vehicle of a zone is described and how Super Vehicles can aggregate the speed and location data from all of the vehicles within their zone to still ensure an accurate representation of the network is discussed. An analysis using FreeSim is performed to determine the trade-offs experienced between accuracy and bandwidth based on the number of edges that comprises a zone, in addition to describing the benefits of the V2V2I architecture over the pure V2I or V2V architectures. (a) For the covering entry of this conference, please see ITRD abstract no. E217226.

Vehicle-to-vehicle-to-infrastructure (V2V2I) intelligent transportation system architecture

Abstract: In this paper, I describe the vehicle-to-vehicle-to-infrastructure (V2V2I) architecture, which is a hybrid of the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) architectures. The V2V2I architecture leverages the benefits of fast queries and responses from the V2I architecture, but with the advantage of a distributed architecture not having a single point-of-failure from the V2V architecture. In the V2V2I architecture, the transportation network is broken into zones in which a single vehicle is known as the super vehicle. Only super vehicles are able to communicate with the central infrastructure or with other Super Vehicles, and all other vehicles can only communicate with the super vehicle responsible for the zone in which they are currently traversing. I describe the super vehicle detection (SVD) algorithm for how a vehicle can find or become a super vehicle of a zone and how super vehicles can aggregate the speed and location data from all of the vehicles within their zone to still ensure an accurate representation of the network. I perform an analysis using FreeSim to determine the trade-offs experienced based on the size and number of zones within a transportation network and describe the benefits of the V2V2I architecture over the pure V2I or V2V architectures.

RFID design principles

Abstract: This cutting-edge book serves as a comprehensive introduction to RFID, offering you a detailed understanding of design essentials and applications, and providing a thorough overview of management issues By comparing RFID with WLAN and Bluetooth, this practical resource shows you how RFID technology can help you overcome many design challenges and limitations in the field The book explains the design of electronic circuits, antennas, interfaces, data encoding schemes, and complete RFID systems Starting with the basics of RF and microwave propagation, you learn about major system components including tags and readers This hands-on reference distills the latest RFID standards, and examines RFID at work in supply chain management, intelligent buildings, intelligent transportation systems, and tracking animals RFID is controversial among privacy and consumer advocates, and this book looks at every angle concerning security, ethics, and protecting consumer data From design details to applications to socio-cultural implications, this authoritative volume offers the knowledge you need to create an optimal RFID system and maximize its performance

Connectivity Requirements for Self-Organizing Traffic Information Systems

Abstract: To facilitate the dissemination of a time-critical information in a vehicular ad hoc network (VANET), immediate network connectivity is needed. In other words, a time-critical message from a source should be able to propagate and reach all of the vehicles on the road segment without any delay due to the unavailability of the vehicles to forward the message. Clearly, this requires the road segment to have a certain number of vehicles equipped with communication devices. It is the task of a system designer to determine the minimum number of vehicles (i.e., the minimum penetration) necessary to form a connected network as well as the critical transmission range required to provide such connectivity. In this paper, we present an analytical framework for determining the connectivity requirements in distributing the traffic information in a self-organizing vehicular network. One- and two-way street scenarios are considered. In addition to the conventional perspective on connectivity, where the characteristics of the wireless channel are often neglected, our analysis offers a new view by taking important physical-layer parameters, such as fading, propagation path loss, transmit power, and transmission data rate, into consideration.

DynaCAS: Computational Experiments and Decision Support for ITS

Abstract: Accurate, reliable, and timely traffic information is critical for deployment and operation of intelligent transportation systems (ITSs). Traffic forecasting for travelers and traffic operators should become at least as useful and convenient as weather reports. In the US, the Federal Highway Administration (FHWA) has envisioned a real-time traffic estimation and prediction system (TrEPS) as an ITS support platform that resides at traffic management centers (TMCs) for dynamic route assignment (DRA) and other transportation operations.

The Heterogeneous Systems Integration Design and Implementation for Lane Keeping on a Vehicle

Abstract: In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN i TS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC)1 and extra-urban highways.

Cooperative Control and Active Interfaces for Vehicle Assitsance and Automation

Abstract: Enabled by scientific, technological and societal progress, and pulled by human demands, more and more aspects of our life can be assisted or automated by technical artefacts. One example is the transportation domain, where in the sky commercial aircraft are flying highly automated most of the times and where on the roads a gradual revolution takes place towards assisted, highly automated or even fully automated cars and trucks. Automobiles and mobility are changing gradually towards intelligent vehicles embedded in an integrated, intelligent transportation system. On the one hand, assistance and automation can have benefits like higher safety, lower workload, or a special fascination of use. On the other hand, assistance and automation come with a couple of challenges especially regarding the interplay between the driver and the assistance/automation. Some of these challenges can be addressed with a close coupling of assistance/automation and the driver, which leads to a shared or cooperative control of the vehicle. An early example of cooperative control in a car is the Lane Keeping Assistant System LKAS, where the automation delivers about 80% of the force required to keep the vehicle on the road, while the driver has to provide the missing 20% and therefore stays in the loop. A combination of LKAS and ACC (Adaptive Cruise Control) leads to highly automated driving, one level of automation on the automation spectrum between manual and fully automated driving. A close coupling between automation and driver can be achieved with active interfaces, e.g. force feedback steering wheels like in the LKAS or active sidesticks. After a brief overview on active interface technology, a prototype system developed in the H-Mode project by NASA, DLR and TU-Munich, and first data gained in driving simulators will be described.

Dynamic parking negotiation and guidance using an agent-based platform

Abstract: Modern prosperous cities strongly need advanced parking assistant systems, intelligent transportation systems providing drivers with parking information. Existing parking information systems usually ignore the parking price factor and do not automatically provide optimal car parks matching drivers' demand. Currently, the parking price has no negotiable space; consumers lose their bargaining position to obtain better and cheaper parking. This study uses an intelligent agent system, and considering negotiable parking prices, selects the optimal car park for the driver. The autonomous coordination activities challenge traditional approaches and call for new paradigms and supporting middleware. An agent-based coordination network is proposed to bring true benefit to drivers and car park operators. These modern intelligent agents have capabilities including planning, mobility, execution monitoring and coordination. These properties can be used to construct the integrated parking assistant system.

Telematic method and apparatus with integrated power source

Abstract: Telematic method and apparatus adaptively uses fuel cell power source in vehicle with integrated power system, electrical system, telematic system, and body/powertrain system. Telematic communications systems including internet, digital video broadcast entertainment, digital audio broadcast, digital multimedia broadcast, global positioning system navigation, safety services, intelligent transportation systems, and/or universal mobile telecommunications system. Network-accessible software enables integrated modular function for automated control and provision of fuel cell resources for telematic appliance and/or other vehicle electro-mechanical devices.

Research on Intelligent Transportation System Technologies and Applications

Abstract: ITS (intelligent transportation system) has been developed since the beginning of 1970s, which makes human, vehicles, roads united and harmonic and establishes a wider range, fully efficient, real-time and accurate information manage system. In the paper, intelligent transportation technologies such as wireless communications, computational technologies, and Sensing technologies have been proposed. Intelligent transportation applications are also introduced. This is a belief abstract for an invited talk at the workshop on power Electronics and Intelligent transportation system.

Intelligent Transport Systems Standards

Abstract: This comprehensive 848-page volume offers the first exhaustive coverage of existing and developing standards that support ITS services and their interoperability. It features up-to-the-minute listings for standards developing organizations (SDOs) at both national and international levels, and also provides extensive referencing to other generic standards that can be of use to ITS service provision. You find updates on the latest best practices worldwide, helping you prevent oversights that could prove costly. This total one-stop resource provides a state-of-the-art review of intelligent transport systems, services, and supporting technologies, and updates you on the latest ITS standards governing communications, technical support, information technology, and identification technology. You find details on standards covering everything from traveler information and traffic management, to weather monitoring and emergency response. The book also summarizes standards for national and regional architecture in the U.S., European Union, Japan, and other nations. You find strategies for effectively integrating standards in your ITS planning, development, deployment and operations. Further, the disc includes links to free downloads of standards (where legitimately available) and links to sites where you can purchase standards.

Dynamic micro-assignment modeling approach for integrated multimodal urban corridor management

Abstract: Development and analysis of demand management strategies for integrated multimodal urban corridor management requires application of a new generation of demand modeling and network analysis tools. This paper describes the development of a dynamic trip micro-assignment and (meso) simulation system that incorporates individual tripmaker choices of travel mode, departure time and route in multimodal urban transportation networks (with different travel modes such as drive alone, shared ride, bus rapid transit and metro rail). These travel choice dimensions are integrated in a stochastic utility maximization framework that considers multiple user decision criteria such as travel time, travel cost, schedule delay, as well as travel time reliability. A variational inequality model is first proposed to describe the general stochastic dynamic traffic user equilibrium problem. For a typical case that assumes the logit-based alternative choice model, this paper develops an equivalent gap function-based optimization formulation and a heuristic iterative solution procedure. Based on a multi-dimensional network representation, an efficient time-dependent least cost path algorithm is embedded to generate an intermodal route choice set that recognizes time-dependent mode transfer costs and feasible mode transfer sequences. A two-stage estimation procedure that can systematically utilize historical static demand information, time-dependent link counts, as well as empirically calibrated stochastic departure time choice models is proposed to infer commuters’ preferred arrival time distribution, which is important in modeling departure time choice dynamics. A case study based on a large-scale multimodal transportation network (adapted from the Baltimore–Washington corridor) is presented to illustrate the capabilities of the methodology and provide insight into the potential benefit of integrated multimodal corridor management.

Geometric connectivity of vehicular ad hoc networks : Analytical characterization

Abstract: Advances in wireless communications are facilitating the development of inter-vehicle communication systems that will benefit mobility and safety objectives. Recently, these systems, referred as vehicular ad hoc networks (VANETs), are gaining significant prominence from both government agencies and private organizations. VANETs are characterized by high vehicle mobility, unexpected driver behavior and variable traffic environment which bring forth challenges to maintain good connectivity. This study considers VANETs as a nominal system with disturbance. Under the nominal system, the traffic space headway is assumed to follow an approved traffic flow distributions, such as exponential distribution. Disturbance is then used to capture a set of uncertain traffic flow events caused by driver behavior and changes in traffic flow. In addition, robustness factor is incorporated to present the impact of probabilistic disturbance events that disrupt the node connectivity. Under constant disturbance conditions, the lower bound of reachable neighbors for each vehicle to maintain a high connectivity is analytically derived. Furthermore, we obtain the relationship between the number of nodes in a VANET and the reachable neighbors under which the network is asymptotically connected. Finally, in variable disturbance situations, the interaction between robustness factor and macroscopic traffic parameters are investigated based on the simulation data. The validation results demonstrate that the proposed analytical characterization can approximate VANET connectivity very well. Our results facilitate the understanding of VANET connectivity on a freeway segment under different traffic conditions.

Event-Driven Architecture for Decision Support in Traffic Management Systems

Abstract: Decision support systems for traffic management systems have to cope with a high volume of events continuously generated by sensors. Conventional software architectures do not explicitly target the efficient processing of continuous event streams. Recently, event-driven architectures (EDA) have been proposed as a new paradigm for event-based applications. In this paper we propose a reference architecture for event-driven traffic management systems, which enables the analysis and processing of complex event streams in real-time and is therefore well-suited for decision support in sensor-based traffic control systems. We will illustrate our approach in the domain of road traffic management. In particular, we will report on the redesign of an intelligent transportation management system (ITMS) prototype for the high-capacity road network in Bilbao, Spain.

Assessing Safety on Dutch Freeways with Data from Infrastructure-Based Intelligent Transportation Systems

Abstract: Most freeway traffic surveillance technologies deployed around the world remain infrastructure based, with underground loop detectors being the most common among them. A proactive application for traffic surveillance data recently explored for some freeways in the United States is the estimation of real-time crash risk. The application involves establishing relationships between historical crashes and archived traffic data collected before those crashes. In these studies, crash occurrence on freeway sections has been related to temporal—spatial variation in speed and high lane occupancy. Critical modeling questions that remain unanswered relate to transferability of such an approach. This study attempts to address the issues of such transfer through analysis of crash data and corresponding loop detector data from five freeways in the Utrecht region of the Netherlands. Traffic surveillance systems for these freeways include more detectors per kilometer than most U.S. freeways. Their real-time data are also...

Accident Modification Factors for Traffic Engineering and ITS Improvements

Abstract: This report presents the findings of a research project to develop accident modification factors (AMFs) for traffic engineering and Intelligent Transportation Systems (ITS) improvements. AMFs are a tool for quickly estimating the impact of safety improvements. The report will be of particular interest to safety practitioners responsible for programming and implementing highway safety improvements.

Examination of Traveler Responses to Real-Time Information about Bus Arrivals using Panel Data:

Abstract: In recent years, a considerable amount of money has been spent on intelligent transportation system projects for public transportation, most notably, real-time transit information systems. To date, strikingly few studies that have empirically investigated the effects of deployment of such a system have been completed. This paper examines the effects of real-time transit information on travelers' behavior and psychology. The 2006-2007 University of Maryland (College Park) campus transportation panel survey data were used to examine how travelers responded to the ShuttleTrac system, a newly implemented real-time bus arrival information system for the university's shuttle service. Two fixed-effects models and five random-effects-ordered probit models were estimated to sort out the causal relations between ShuttleTrac system information use and two behavioral and five psychological indicators, respectively. It was found that use of the real-time information significantly increased the riders' feelings of secu...