Automatic Vehicle Location Systems Research Articles

Public-transit frequency setting using minimum-cost approach with stochastic demand and travel time

Common practice in public-transit planning is to determine the frequency of service based on accumulated hourly passenger counts, average travel time, given vehicle capacity, and the standard of minimum frequency by time of day. With the increased usage of automatic vehicle location (AVL) and automatic passenger counting (APC) systems, it is possible to construct the statistical distributions of passenger demand and travel time by time of day. This can give rise to improve the accuracy of the frequencies determined. This study presents a new approach of frequency setting by enabling the use of stochastic properties of the collected data and its associated costs within a supply chain optimization model. An optimization framework is constructed based on two main cost elements: (a) empty-seat driven (unproductive cost) and (b) overload and un-served demand (increased user cost). The objective function is to minimize the total cost incurred with decision variables of either frequency or vehicle capacity (vehicle size). That is, from the operator perspective it is desirable to utilize efficiently the fleet of vehicles which is related to the decisions of the vehicle size. From the authority perspective, the concern is to provide an adequate level of service in terms of frequency. The study contains sensitivity analysis of the cost elements involved for economic evaluation.

A New Approach for Co-Operative Bus Priority at Traffic Signals

Bus priority at traffic signals is a growing area of cooperative transport system applications. Interest in bus priority continues to grow as the cities pay more attention to the needs of buses to provide fast, frequent, and reliable services, thus contributing to a sustainable transport system. Bus priority at traffic signals is particularly favored at places where road space is limited and traffic signal density is high. With increasing the use of automatic vehicle location (AVL) systems, it is now possible to provide “differential” priority, where different levels of priority can be awarded to buses at traffic signals according to chosen criteria (e.g., to improve regularity). At present, common strategies are based on the comparison of the time headway of a bus with the scheduled headway. However, this paper shows that greater regularity benefits could be achieved through a strategy where priority for a bus is based not only on its own headway but also the headway of the bus behind (the following bus). This paper demonstrates the benefits of this on a theoretical basis and quantifies the benefits from simulation modeling of a high-frequency bus route. Such a strategy provides an opportunity to exploit the more detailed location information available from the growing number of AVL-based systems for buses being implemented around the world.

Data management and applications in a world-leading bus fleet

Automatic Vehicle Location (AVL) Systems are being introduced increasingly in many major cities around the world to improve the efficiency of our road-based passenger transport systems. Satellite-based location and communication systems, particularly the Global Positioning System (GPS) have been the platform for AVL systems which are now supporting real-time passenger information (RTPI), fleet management and operations (FMOs) and public transport priorities (PTPs), to name three key applications. The process of real-time on-board bus location can result in a substantial database where the progress of the bus is stored typically on a second-by-second basis. This is necessary for the primary real-time applications such as those listed above (e.g. RTPI, FMO and PTP). In addition, it is clear that such data could have an array of ‘secondary’ purposes, including use off-line for improving scheduling efficiency and for automatic performance monitoring, thus reducing or removing the need for manual on-street surveys. This paper looks at these and other innovative uses of AVL data for public transport, taking the recent iBus system in London as a current example of a modern AVL/GPS application in a capital city. It describes the data architecture and management in iBus and then illustrates two further examples of secondary data use – dwell time estimation and bus performance analysis. The paper concludes with a discussion of some key data management issues, including data quantity and quality, before drawing conclusions.

Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception

Transit agencies implement many strategies in order to provide an attractive transportation service. This article aims to evaluate the impacts of implementing a combination of strategies, designed to improve the bus transit service, on running time and passenger satisfaction. These strategies include using smart card fare collection, introducing limited-stop bus service, implementing reserved bus lanes, using articulated buses, and implementing transit signal priority (TSP). This study uses stop-level data collected from the Société de transport de Montréal (STM)’s automatic vehicle location (AVL) and automatic passenger count (APC) systems, in Montréal, Canada. The combination of these strategies has lead to a 10.5% decline in running time along the limited stop service compared to the regular service. The regular route running time has increased by 1% on average compared to the initial time period. The study also shows that riders are generally satisfied with the service improvements. They tend to overestimate the savings associated with the implementation of this combination of strategies by 3.5–6.0 min and by 2.5–4.1 min for both the regular route and the limited stop service, respectively. This study helps transit planners and policy makers to better understand the effects of implementing a combination of strategies to improve running time and passenger’s perception of these changes in service.

A Preliminary Study of Just-in-Time Methods for a Seamless Public Transportation Information Framework

A seamless multimodal transit system has been a goal for transportation planners and users. Owing to the developments of advanced public transportation and telecom technologies such as automatic vehicle location (AVL) and real-time passenger information system, key just-in-time (JIT) concepts can now be realized in process design and coordinated scheduling to shape a seamless multimodal transit system. JIT refers to a production system that times both movements of goods during production and delivery from suppliers together. It meets the same logic for seamless multimodal services. Therefore, this study innovatively analyzes possible public transportation technologies for JIT uses; moreover, to layout the possible application frame-work of a transportation technology based JIT multimodal transit system for main station area in Taipei city. With this innovative framework, multimodal transit services can deliver to the right place at right time.

Automatic Identification of Vehicles with Faulty Automatic Vehicle Location and Control Units in London Buses' iBus System

The accuracy of vehicle location plays a pivotal role in several applications for bus network operations such as service control, warnings about low bridges, accurate prediction of bus arrival times, and traffic signal priority, as well as when historical operational data are used to measure network performance. In the context of iBus, an automatic vehicle location and control system deployed on all 8,400 buses operated by London Bus Services Limited (London Buses), tests demonstrated that the solution based on the Global Positioning System (GPS) provides location accuracy within 10 to 12 m 95% of the time; this timing is sufficient to support operational needs. To meet that level of location accuracy, the system must operate with a high degree of availability and accuracy on all vehicles. The challenge is to install, maintain, and repair vehicles so that they can operate at the required levels of performance under harsh operating conditions. Buses have many components—including the odometer, gyrocompass, aerials, WiFi, and power units—that can fail. This paper presents three approaches that London Buses uses to identify vehicles that have faulty hardware. One technique has also proved to be beneficial in testing new navigation software releases and in identifying design and parameterization problems that affect the quality of the navigation solution. The results will interest those involved with testing, maintenance, and repair of GPS-based vehicle fleets. These methods have helped ensure that London Buses can successfully observe 98% of all operated bus stop visits.

ANDROID - A CLOUD COMPUTING FOR VEHICLE TRACKING SYSTEM USING GPS

Tracking systems were first developed for the shipping industry because they wanted to determine where each vehicle was at any given time. Passive systems were developed in the beginning to fulfill these requirements. For the applications which require real time location information of the vehicle, these systems can’t be employed because they save the location information in the internal storage and location information can only be accessed when vehicle is available. To achieve Automatic Vehicle Location system that can transmit the location information in real time, Active systems are developed. Real time vehicular tracking system incorporates a hardware device installed in the vehicle (In-Vehicle Unit) and a remote Tracking server. The information is transmitted to Tracking server using GSM/GPRS modem on GSM network by using SMS or using direct TCP/IP connection with Tracking server through GPRS. Tracking several so has GSM/GPRS modem that receives vehicle location information via GSM network and stores this information in database. This information is available to android users over the internet. Keywords—GSM, GPS, GPRS, ANDROID, GUI, Cloud Computing.

Social-demographics, driving experience and yearly driving distance in relation to a tour bus driver’s at-fault accident risk

This study explored the at-fault accident risk of tour bus drivers based on 2023 drivers in Taiwan. Of the observed drivers, 4.1% had at least one accident in a year period, of these, 68.7% were at-fault for the accident. The results of logistic regression model revealed that a driver’s driving experience was the most influential factor (Wald=32.291, p=0.000) leading to at-fault accident risk. Drivers whose driving experience was from 6 to 8 years possessed the lowest at-fault accident rate (0.9%), which was lower than the over-all average at-fault accident rate of 2.8%. Novice drivers whose driving experience less than 3 years had the highest at-fault accident rate (12.4%). The driver’s yearly driving distance and the use of an Automatic Vehicle Location (AVL) system were also significantly associated with a driver’s at-fault accident. However, a driver’s age and educational level were not significantly associated with at-fault accident.

Managing taxi service operations based on the automatic vehicle location and dispatch system and wireless communication technology

This paper explores taxi service operations management based on the automatic vehicle location and dispatch system and wireless communication technology. With the implementation of the system, the taxi companies have enhanced service operations in terms of the efficiency of processing taxi reservations and dispatching taxi vehicles. In particular, they are able to offer timely and quality service to many different customers who request for taxi services at different locations. The wireless communications and human-system interactions of the taxi dispatch process have been discussed. The findings have managerial implications for improving service operations of public transport in different contexts.

Estimating Signalized Intersection Delays to Transit Vehicles

Many transit agencies have deployed automatic vehicle location (AVL) systems, automatic passenger counting (APC) systems, or both on a portion of their transit vehicle fleets. Data from these systems are used for realtime system monitoring and control, and archived data are often used for service performance reporting and for service planning. This paper proposes and demonstrates a method by which these archived data can be used to estimate the mean and variance of transit vehicle delays caused by signalized intersections. The proposed method is suitable for application to most transit AVL-APC databases and is demonstrated with data from Grand River Transit, the public transit service provider in the region of Waterloo, Ontario, Canada. The results obtained from the application to field data indicated that the proposed method was able to explain 96% of the variation in observed mean transit vehicle delay at signalized intersections. These results suggest that the proposed method has practical application for the identification and prioritization of candidate measures for transit priority, including transit signal priority (green extension, early green, special transit phases) and queue jump lanes.

Automated Quality Assurance Methodology for Archived Transit Data from Automatic Vehicle Location and Passenger Counting Systems

Automatic vehicle location (AVL) and automatic passenger counting (APC) systems are powerful tools for transit agencies to archive large, detailed data sets for transit operations. Ensuring data quality is an important first step to exploiting these data sets. An automated quality assurance methodology is presented to identify unreliable archived AVL-APC data for exclusion from further operational analyses. The approach is based on observed or expected pattern limitations of travel and passenger activity, which are derived from archived data. Stop-level tests identify suspect data, which are then flagged at the trip level. A methodology case study is presented for AVL-APC data from Grand River Transit in the region of Waterloo, Ontario, Canada.

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.

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.

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.

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.

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.

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.