Bus transit travel time reliability evaluation based on automatic vehicle location data

In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed and evaluated based on automatic vehicle location （AVL） data. Based on the statistical analysis of the bus transit travel time, six indices including the coefficient of variance, the width of travel time distribution, the mean commercial speed, the congestion frequency, the planning time index and the buffer time index are proposed. Moreover, a framework for evaluating bus transit travel time reliability is constructed. Finally, a case study on a certain bus route in Suzhou is conducted. Results show that the proposed evaluation index system is simple and intuitive, and it can effectively reflect the efficiency and stability of bus operations. And a distinguishing feature of bus transit travel time reliability is the temporal pattern. It varies across different time periods.

Vision-based long-distance lane perception and front vehicle location for full autonomous vehicles on highway roads

A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.

Bus travel time reliability incorporating stop waiting time and in‑vehicle travel time with AVL data

Improving bus travel time reliability can attract more commuters to use bus transit,and therefore reduces the share of cars and alleviates trafc congestion.This paper formulates a new bus travel time reliability metric that jointly considers two stochastic processes:the in-stop waiting process and in-vehicle travel time process,and the bus travel time reliability function is calculated by the convolution of independent events’probabilities.The new reliability metric is defned as the probability when bus travel time is less than a certain threshold and can be used in both conditions with and without bus transfer.Next,Automatic Vehicle Location(AVL)data of the city of Harbin is used to demonstrate the applicability of the proposed method.Results show that factors such as weather,day of the week,departure time,travel distance,and the distance from the boarding stop to the bus departure station can signifcantly afect the travel time reliability.Then,a case with low bus departure frequency is analyzed to show the impact of travelers’arrival distribution on their bus travel time reliability.Further,it is demonstrated that the travel time reliabilities of two bus transfer schemes of the same Origin–Destination(O–D)pair can have signifcantly diferent patterns.Understanding the bus travel time reliability pattern of the alternative bus routes can help passengers to choose a more reliable bus route under diferent conditions.The proposed bus travel time reliability metric is tested to be sensitive to the efect of diferent factors and can be applied in bus route recommendation,bus service evaluation,and optimization.

Design and Implementation of Mobile Terminal Monitoring System based on GIS

This paper presents a vehicle navigation and monitoring system scheme based on GIS/GPS/GPRS. The whole system consists of vehicle terminal and monitoring center, the monitoring center and the monitoring terminal comprises a communication server, communication server is only responsible for data storage and forwarding, the monitoring functions are completed by the monitoring terminal. Therefore, after the map matching, control terminal is performed on the device display to achieve real-time monitoring of vehicle location. The monitoring terminal can also be parameters of the moving vehicle accurate location, velocity and state the necessary query and transmission scheduling control instruction to carry out scientific scheduling and management, and improve operation efficiency. If the vehicle encountered an unexpected condition, harm or left the restricted area, it also can send alarm information to the monitoring terminal, and then the terminal can receive assistance and support in time.

"Weather" transit is reliable? Using AVL data to explore tram performance in Melbourne,Australia

This paper uses automatic vehicle location （AVL） records to investigate the effect of weather conditions on the travel time reliability of on-road rail transit, through a case study of the Melbourne streetcar （tram） network. The datasets available were an extensive historica; AVL dataset as well as weather observations. The sample size used in the analysis included all trips made over a period of five years （2006-2010 inclusive）, during the morning peak （7 am-9 am） for fifteen randomly selected radial tram routes, all traveling to the Melbourne CBD create a linear model Ordinary least square （OLS） regression analysis was conducted to with tram travel time being the dependent variable. An alternative formulation of the model is also compared. Travel time was regressed on various weather effects including precipitation, air temperature, sea level pressure and wind speed; as well as indicator variables for weekends, public holidays and route numbers to investigate a correlation between weather condition and the on-time performance of the trams. The results indicate that only precipitation and air temperature are significant in their effect on tram travel time. The model demonstrates that on average, an additional millimeter of precipitation during the peak period adversely affects the average travel time during that period by approximately 8 s, that is, rainfall tends to increase the travel time. The effect of air temperature is less intuitive, with the model indicating that trams adhere more closely to schedule when the temperature is different in absolute terms to the mean operating conditions （taken as 15 ℃）.