Automatic Vehicle Location Research Articles

Introduction of Reserved Bus Lane

This paper evaluates the impact of adding a reserved bus lane on the running times and on-time performance of two parallel bus routes, one of them a limited-stop bus service and the other a regular bus service. By means of automatic vehicle location and automatic passenger count data, statistical models were built to estimate running time and on-time performance. The reserved bus lane yielded savings of 1.3% to 2.2% in total running time, and benefits were more significant for northbound afternoon peak trips than for southbound morning peak trips because of congestion levels northbound. The introduction of a reserved lane increased the odds of being on time by 65% for both routes. A decline in the variability of running time and delay at the end was noticed after implementation of the reserved lane; the decline indicated that the reliability of the service being offered along the corridor had improved. The analysis showed that the more affected a bus service was by adverse traffic conditions, the more it benefitted in running time from improvements introduced by reserved lanes while keeping schedules constant. Reserved lanes had a substantial effect on both service reliability and on-time performance, two key variables in customer satisfaction that justified such implementation. This study will help transit planners and schedulers to understand the effects of implementing reserved lanes on running time, on-time performance, and transit schedules.

Bus running time prediction using a statistical pattern recognition technique

Given that real-time bus arrival information is viewed positively by passengers of public transit, it is useful to enhance the methodological basis for improving predictions. Specifically, data captured and communicated by intelligent systems are to be supplemented by reliable predictive travel time. This paper reports a model for real-time prediction of urban bus running time that is based on statistical pattern recognition technique, namely locally weighted scatter smoothing. Given a pattern that characterizes the conditions for which bus running time is being predicted, the trained model automatically searches through the historical patterns which are the most similar to the current pattern and on that basis, the prediction is made. For training and testing of the methodology, data retrieved from the automatic vehicle location and automatic passenger counter systems of OC Transpo (Ottawa, Canada) were used. A comparison with other methodologies shows enhanced predictive capability.

소방용 AVL 시스템 개발

무선 통신과 모바일 단말기의 발달로 언제 어디서든 무선 통신을 할 수 있게 되었다. 이로 인하여 AVL 시스템의 활용의 폭이 넓어져 상황관제, 물류관리, 택배, 택시, ITS(Intelligent Transportation Systems) 등에 활용되고 있다. 본 논문에서는 구조, 구급 등과 같은 소방 활동에서 활용하기 위한 AVL 시스템을 설계 및 구현하고자 한다. 세부적으로 AVL 관련 기존 연구 및 시스템을 분석한 후에 긴급구조, 구급에 이용할 수 있는 AVL 시스템을 설계하고 구현한다. 이를 위하여 먼저 AVL 서버와 클라이언트를 구현하여 무선 통신을 이용하여 서버와 클라이언트의 안정적인 통신을 실현하고자 한다. 그리고 AVL 시스템을 이용하여 출동차량이 신속하게 재난 위치까지 찾아갈 수 있도록 설계하며, 차량의 위치정보를 이용하여 본부 상황실에서 차량 위치를 실시간으로 확인하여 효율적인 관제가 이루어질 수 있도록 개발한다. It is possible to use wireless communication any time in every place because of well-developed wireless networks and mobile devices. The AVL(Automatic Vehicle Location) system, therefore, has made practical use in situation control, distribution industry, home delivery service, and ITS(Intelligent Transportation System) area. In this paper, we design and implement an AVL system in order to use for fire fighting activities such as emergency rescue and relief. To do this, first, we investigate and analyze the existing researches and systems related to AVL system. In details, we develop an AVL server and clients to support stable communication each other using wireless networks. Using AVL system, calling cars find the position of accidents quickly and the fire defense headquarters control unforeseen accidents efficiently because the state of calling cars are confirmed in real time by their GPS data.

Global Positioning System Integrated with Personalized Real-Time Transit Information from Automatic Vehicle Location

Navigation of a transit system can be a major obstacle to new riders, especially special-needs populations and tourists. For those with cognitive disabilities (approximately 14.3 million Americans, or 6% of the population), it is challenging to plan and execute a trip without assistance. A travel assistance device (TAD) software prototype for Global Positioning System–enabled phones was developed to aid new transit riders, especially those who are cognitively disabled. When riders approach their stops, the TAD vibrates and delivers audio and visual messages to the riders to request a stop and exit the vehicle. This paper reports the results of a study that integrated communication with an automatic vehicle location (AVL) system on transit vehicles into TAD, with new features, including personalized notices of estimated vehicle arrival time and of vehicle arrival. Implementation issues addressed include the limitations of accessing AVL data for real-time consumer use, integration of different transit agency data sources, and consideration of the effects of software applications (e.g., wireless data communication) on mobile phone functionality (e.g., battery life).

Identifying Causes of Performance Issues in Bus Schedule Adherence with Automatic Vehicle Location and Passenger Count Data

Automatic vehicle location (AVL) and automatic passenger counting (APC) systems can provide rich archived databases for analysis. Previous work has focused on using AVL–APC data to evaluate system performance using various quantitative performance measures and data visualization methods. Given the large volume of data, there is a benefit to automating the creation of performance measures and data visualizations and “pushing” interesting information to users, rather than requiring users to create the performance measures and figures and sift through them on their own. This paper presents a methodology for identifying bus stops that are not meeting performance standards for schedule adherence and the factors that cause inadequate performance. The methodology is designed to be automated and therefore can be applied efficiently to AVL–APC data for an entire transit network. Use of this proposed method will enable transit agencies to identify service quality issues and their root causes more efficiently.

Costs and Benefits of Tools to Maintain Winter Roads

Some of the most useful data available to winter road maintenance managers and others charged with decision making are the costs, benefits, and effectiveness associated with winter maintenance of practices, equipment, and operations. However, significant effort may be required to track down this information, and access to published reports and papers is not guaranteed. This paper presents recent research results to assist practitioners in understanding the current state of the practice related to specific items. The information presented here focuses on the top 10 winter maintenance practices, equipment, and procedures as identified by practitioners, including anti-icing, deicing, front and underbody blades, automatic vehicle location and Global Positioning System technologies, pavement temperature sensors, road weather information system (RWIS), maintenance decision support system, carbide blades, air temperature sensors, and zero velocity spreaders. A review of the literature pertaining to these items indicated that, depending on the item of interest, significant data gaps might exist. This was less true for items such as RWIS and more true of items such as temperature sensors and material placement systems. Overall, quantified costs and benefits related to many items are still needed. In addition, further investigation is necessary to quantify the dollar values of costs and benefits associated with many items considered intangible at present. The determination of the values of such costs and benefits would assist in the conduct of cost–benefit studies and decision making.

Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring

Traditional technologies, such as inductive loop detectors, do not usually produce measurements of the quality required by real-time applications. Therefore, one wonders what could be expected from newer information and communication technologies, such as automatic vehicle location, license plate recognition, and detection of mobile devices. The main objectives of this paper are to explore the quality of the data produced by Bluetooth detection of mobile devices that equip vehicles for travel time forecasting and its use in estimating time-dependent origin-destination matrices. Ad hoc procedures based on Kalman filtering have been designed and implemented successfully, and the numerical results of the computational experiments are presented and discussed.

Role of automatic vehicle location systems and localisation accuracy in freight transport: an analytical estimation of gained operational times

This study concerns the application of automatic vehicle location systems (AVLSs) for the control and management of fleet of vehicles whose regular routes are random, that is, with origins and destinations so numerous and variable that they cannot be predefined. Typical examples include road shipments, pick-up and delivery services and express couriers, demand responsive transport services and public utility services (gas, water etc.). Specific reference is made to transport of goods but analogous observations may be valid for passenger transport. The average response time of the mobile unit depends on (i) the accuracy of the AVLS adopted; (ii) the configuration of the fleet within the territory where it operates; (iii) a number of operative parameters, among which are the size of the operative area, the number of vehicles employed, the average time that they are in use, their average speed and the average time taken to perform the service. The results of two specific models provide average response times which can be compared in transport operations carried out with and without the use of an AVLS. If we abstract the equations derived from these, we obtain a quantity Δt, which measures the reduction in response time resulting from the adoption of an AVLS. The relevance of the results is related to the role of accuracy, integrity and continuity of the future Galileo system for transport location services.

Augmenting Transit Trip Characterization and Travel Behavior Comprehension

Trips need to be described and have always been characterized by various levels of abstraction. It varies from a simple label such as home-based work to complete itinerary with sociodemographic characteristics of the trip maker and household. The rationale behind such classifications is that planners and modelers recognize that the demand of transportation is highly differentiated. It is hoped that additional attributes would provide a more complete portrait of the demand and an improved understanding of the underlying travel behavior. Passive data collection technologies bring an extra dimension to travel data acquisition. Multiday data, which are difficult to collect, become accessible. In public transit, a smart card automatic fare collection system with automatic vehicle location capability provides high-resolution longitudinal data on travel pattern but also suffers from the inherent limitations of passive methods. This paper proposes a methodology to enhance transit trip characterization by adding a multiday dimension to a month of smart card transactions. On the basis of an individual, anchor points—precise to an exact address—are detected. Boarding and alighting locations are described with respect to those anchors. The enhancement allows in-depth travel behavior analysis on a subgroup sharing a common anchor or an individual. The paper demonstrates the use of spatial statistics, spatial analyses with geographic information system, visualizations, and data mining to describe activity space and locations and departure time dynamics, and to derive monthly trip table, activity schedule, and behavioral rules for cardholders. The results offer promising insights to transit planning and the understanding of travel behavior.

Dynamic multi-interval bus travel time prediction using bus transit data

The objective of this research is to develop a dynamic model to forecast multi-interval path travel times between bus stops of origin and destination. The research also intends to test the proposed model using real-world data. This research was brought about by the shortcomings of the existing real-time based short-term-prediction models, which have been widely utilised for single interval predictions. The developed model is based on the Nearest Neighbour Non-Parametric Regression using historical and current data collected by the Automatic Vehicle Location technology. In a test with real-world bus data in Seoul, Korea, the proposed multi-interval-prediction model performed effectively in terms of both prediction accuracy and computing time.

A Multi-Constellations Satellite Selection Algorithm for Integrated Global Navigation Satellite Systems

The U.S. Global Positioning System (GPS) is currently the only fully operational global navigation satellite system (GNSS) that has been widely utilized in navigation and data collection, among other applications. In the near future, there will be other GNSSs such as the Russian GLONASS, the European Galileo, and the Chinese Compass that provide compatible services with GPS and will be available to all users. Besides operating in the single GNSS mode, future GNSS receivers will have the capability to operate in an integrated GNSS mode where they will be able to couple satellites from all available constellations for positioning solutions. However, tracking all visible satellites simultaneously increases the computational load of the receivers. This is particularly true with low-cost and compact receivers, which have limited computational resources and are commonly used in real-time intelligent transportation system (ITS) applications such as automatic vehicle location, route guidance, fleet management, vehicle dispatch, traveler information, and car navigation. These real-time applications also impose time constraints on positional updates (maximum required time interval between two epochs) while requiring high accuracy positioning solutions. To mitigate such burdens while maintaining benefits of the combined system, this article presents a new heuristic algorithm called a multi-constellations satellite selection algorithm (MCSSA). The algorithm allows an integrated GNSS receiver to track only a smaller set of visible satellites that can provide acceptable positioning solutions in the required time intervals. The MCSSA considers the geometric arrangements of visible satellites and selects the ones that spread evenly over the observed sky view. The performance of the MCSSA was validated by simulating the combined GPS and Galileo constellations. The accuracy and computation time of the MCSSA were compared with selected existing satellite selection algorithms. The results indicate that the MCSSA provides the set of satellites with near-optimal geometries giving high positional accuracy in a reasonably small computation time and thus is suitable for real-time applications.

Passengers' perceptions and effects of bus‐holding strategy using automatic vehicle location technology

AbstractThis study reports bus passengers' behavior and perceptions related to the use of potential features of an automatic vehicle location (AVL) system in bus transit through conducting an attitudinal on‐board survey in Bangkok. A passenger waiting‐time survey conducted as part of this study revealed that passengers perceive waiting‐time at bus stops to be greater than actually experienced. The other aim of this study is to examine the potential benefits of bus‐holding using an AVL technology, in terms of waiting‐time, through minimizing bus bunching under different congestion levels. The results are obtained using PARAMICS, and reveal a significant reduction in average waiting‐time.

Effects of Controlling Parameters on Performance of a Decision-Rule Map-Matching Algorithm

Advanced map-matching algorithms resolve spatial ambiguities between differential global positioning system (DGPS) and roadway centerline data. Most of these algorithms need further research to assess their performances with respect to their controlling parameters and their relationships with spatial data and temporal resolution. This paper presents an analysis of the effects of three parameters controlled by the user and two variables dominated externally through simulated data on the performance of a postprocessing decision-rule map-matching algorithm previously developed by the writers. The algorithm is tested against three different digital roadway map scales from counties in Wisconsin and Iowa, and two automatic vehicle location (AVL)/DGPS technologies mounted on intelligent winter maintenance vehicles. Sensitivity analyses indicate that the algorithm is sensitive to controlling parameter values depending on the data being tested. The algorithm satisfactorily resolves spatial ambiguities given different spatial data qualities, AVL/DGPS technologies, and temporal resolutions. Statistical analysis suggests a direct relationship between data collection frequency and spatial mismatch resolution. Parameter values are presented for minimizing false negatives and maximizing solved cases, thus enhancing the performance of the map-matching algorithm.

Measuring Freeway Traffic Conditions with Transit Vehicles

Many public transit agencies have equipped their fleet with automatic vehicle location (AVL) systems, which periodically provide the location of each vehicle in the fleet. Although the AVL is deployed for transit operations, the vehicles also provide valuable information about the traffic stream throughout the road network. This study developed a methodology to mine the transit AVL data to find all trips that use any portion of a prespecified freeway segment. These trips are then used to measure travel time and average speed over the freeway and thereby quantify conditions on the facility. The results are validated against concurrent loop detector data from a corridor. The greatest benefits, however, are in areas without fixed vehicle detection, so the methodology is also demonstrated on such a freeway corridor. The study corridors typically have fewer than 50 observations per day per kilometer per direction, so this paper includes a process for selecting those segments with at least one observation per hour. Even with this low density of observations, the data are aggregated to show clearly the recurring congestion patterns. Nonrecurring events are also evident, but they take longer to detect. With a higher frequency of observations (e.g., from other fleet AVL systems, cell phone tracking, or vehicle–infrastructure integration probe data), the methodology should also be effective for rapidly identifying nonrecurring congestion.

Automatic vehicle location tracking system based on GIS environment

Recently, automatic vehicle location (AVL) has become more widely used, affordable and popular than ever before. AVL is used for different tracking purposes, especially for those related to tracking one vehicle or a fleet of vehicles. Tracking system technology was made possible by the integration of three new technologies: navigational technologies such as global positioning system (GPS), database technologies such as geographic information system (GIS) and communication technology such as general packet radio service (GPRS). The proposed software design ‘tracking system’ is used to pinpoint the position, ground speed and fuel level of a given vehicle. This improves fleet management by making it secure and more efficient. The system has the ability to detect the optimal path between source and destination, depending on many factors such as travel time, jam, topography and number of traffic lights. The authors applied greedy techniques (GT) such as Dijkstra's and Kruskal's algorithms to a graph weight depending on the proposed cost function (CF). The geofencing technique is applied to the system based on real coordinates and grants security and safety to the fleet of vehicles. The designed software offers more flexibility in loading digital maps. This proposed software has the ability to visualise the real position of vehicles on maps and to take decisions according to real-time information.

Probability-based bus headway regularity measure

In frequently serviced bus routes passengers are more concerned about bus headway regularity than actual punctuality of bus arrival to the schedule. Buses arriving within very small (bus bunching) or very large headways are of particular concern and much less desirable. In this study, a time-point (stop) level probability-based headway regularity metric to measure bus service reliability is first formulated as a function of bus dwell time, number of stops into the trip, passenger activities (i.e. arrival, boarding and alighting) and expectation (or tolerance) of bus headways. The proposed metric is then applied to evaluate a Chicago Transit Authority bus route by using automatic vehicle location (AVL) data. It is found that headway regularity during a bus trip is closely impacted by dispatching headway. Furthermore, the time-point level service reliability declines as passenger activity levels increase or as the maximum passenger anticipated headway decreases (i.e. passengers become more demanding of frequent bus services). The case study demonstrates that the proposed probability-based headway regularity measure provides an operationable metric to transit agencies in terms of improving the transit service to meet passengers' expectation and thus increase ridership. Lastly, this study demonstrates another important application of the AVL/APC data.

Beyond Generating Transit Performance Measures

In recent years, the use of performance measures for transit planning and operations has gained a great deal of attention, particularly as transit agencies are required to provide service under increasing demand and with diminishing resources. The widespread application of the technologies of intelligent transportation systems to transit encourages automating the generation of comprehensive performance measures. In Portland, Oregon, the local transit provider, Tri-County Metropolitan Transportation District of Oregon (TriMet), has been on the leading edge of the transit industry since it implemented its bus dispatch system (BDS) in 1997. The BDS comprises automatic vehicle location on all buses, a radio communications system, automatic passenger counters on most vehicles, and a central dispatch center. Most significant, TriMet developed a system to archive all its stop-level data, which are then available for conversion to performance indicators. In the past decade, TriMet has used this system extensively to generate performance indicators through monthly, quarterly, and annual reporting. TriMet generates a wide range of performance indicators, yet an opportunity remains to explore metrics beyond general transit performance measures (TPMs). On the basis of an analysis of 1 year of archived BDS data for all routes and stops, the power of using visualization tools to understand the abundance of BDS data is demonstrated. In addition, several statistical models are generated to demonstrate the power of statistical analysis in conveying valuable and new TPMs beyond what is currently generated at TriMet or in the transit industry in general. It is envisioned that systematic use of these new methods and TPMs can help TriMet and other transit agencies improve the quality and reliability of their service.

Prototype for Data Fusion Using Stationary and Mobile Data

Arterial performance measurement is a critical issue for transportation system management, traveler information, and real-time situation-aware routing. In many urban areas current information on freeway conditions is available, appropriately given the large amount of travel that occurs on these facilities. However, because nearly 40% of the vehicle miles traveled in the United States occur on arterials, there is a need to provide similar information that can be used not only by travelers but also by traffic engineers and managers. Because many arterials are equipped with actuated traffic signals, the use of already installed sensors has been explored as one source of traffic volume, occupancy, or speed data to inform an arterial performance system. Coupled with this, there is a potential to exploit the availability of mobile probe geolocation data from sources such as automatic vehicle location systems for fleets of buses or taxis, or from cellular phone or other Global Positioning System–type devices. To demonstrate the potential value of fusing data from fixed and mobile surveillance systems toward improved arterial performance reporting, this paper describes the results of a case study from Portland, Oregon, that extracted improved arterial performance measures by combining data from traffic signal system detectors and from buses acting as probe vehicles. In particular, graphical techniques are developed that trace the boundaries of the congested regime in time and space along an arterial corridor. The paper includes recommendations for expanding the techniques to other corridors, using higher resolution, real-time transit location data, and online implementation of an arterial travel time information system.

Quantifying Impacts of Transit Reliability on User Costs

Transportation modeling frameworks assume that travelers are economically rational; that is, they choose the lowest-cost alternative to complete a desired trip. The reliability of travel time is of critical importance to travelers. The ability to quantify reliability allows planners to estimate more accurately how system performance influences local travel behavior and to evaluate more appropriately potential investments in the transportation system infrastructure. This paper presents a methodology that makes use of automatic vehicle location data from the regional municipality of Waterloo, Ontario, Canada, to estimate the reliability of transit service. On the basis of these data, the impacts of unreliable service on generalized transit user costs are quantified by use of a simulation model of bus arrivals and passengers’ desired arrival times. It is shown that the increasing reliability of arrivals at a station can decrease transit users’ generalized costs significantly and by as much as 15% in a reasonably reliable network. It is further posited that the inclusion of uncertainty in the calculation of generalized costs may provide better estimates of mode splits in travel forecasting models. A description of future applications of the model concludes the paper.

User acceptance of automatic vehicle location system technology: a study of motor carriers in Taiwan

This paper aims to analyse the Automatic Vehicle Location System (AVLS) acceptance intentions of motor carriers. This study applies Structure Equation Modelling (SEM) to investigate the impact of three factors based on the Technology Acceptance Model (TAM): perceived usefulness, perceived ease of use and the social norm on the intention of motor carriers. Empirical results indicate that a revised TAM could explain the AVLS acceptance behaviour of local motor carriers. Perceived ease of use has a stronger effect on AVLS acceptance intention than perceived usefulness. Government policies and AVLS introduction by competitors also influence motor carriers' behavioural intentions.