Estimation of Bus Dwell Times with Automatic Passenger Counter Information

2003 ◽  
Vol 1841 (1) ◽  
pp. 120-127 ◽  
Author(s):  
Rajat Rajbhandari ◽  
Steven I. Chien ◽  
Janice R. Daniel
Keyword(s):  
Travel Time ◽  
Dwell Time ◽  
Time Of Day ◽  
Descriptive Statistics ◽  
Fleet Size ◽  
Transit Service ◽  
Service Type ◽  
Vehicle Travel Time ◽  
The Impact

The average passenger boarding and alighting times and bus dwell times at stops are important information for estimating transit service capacities. Bus dwell time directly affects vehicle travel time, and thus the fleet size required to provide service based on scheduled headway is affected. Research focused on estimating bus dwell time and the impact of boarding and alighting passengers on dwell time. In addition, the effect of standees, time of day, and service type on bus dwell time was investigated. The data were recently collected from an archived database, within which automatic passenger counter information was recorded. The dwell times and passenger counts were recorded daily during 2001 and the first 6 months of 2002. The bus dwell time and average passenger boarding and alighting time at stops are explained using descriptive statistics.

scholarly journals Examining the Impact of Adverse Weather on Travel Time Reliability of Urban Corridors in Shanghai

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yajie Zou ◽  
Ting Zhu ◽  
Yifan Xie ◽  
Linbo Li ◽  
Ying Chen
Keyword(s):  
Travel Time ◽  
Weather Condition ◽  
Time Of Day ◽  
Weather Data ◽  
Time Variability ◽  
Travel Time Reliability ◽  
Time Data ◽  
Adverse Weather Condition ◽  
Adverse Weather ◽  
The Impact

Travel time reliability (TTR) is widely used to evaluate transportation system performance. Adverse weather condition is an important factor for affecting TTR, which can cause traffic congestions and crashes. Considering the traffic characteristics under different traffic conditions, it is necessary to explore the impact of adverse weather on TTR under different conditions. This study conducted an empirical travel time analysis using traffic data and weather data collected on Yanan corridor in Shanghai. The travel time distributions were analysed under different roadway types, weather, and time of day. Four typical scenarios (i.e., peak hours and off-peak hours on elevated expressway, peak hours and off-peak hours on arterial road) were considered in the TTR analysis. Four measures were calculated to evaluate the impact of adverse weather on TTR. The results indicated that the lognormal distribution is preferred for describing the travel time data. Compared with off-peak hours, the impact of adverse weather is more significant for peak hours. The travel time variability, buffer time index, misery index, and frequency of congestion increased by an average of 29%, 19%, 22%, and 63%, respectively, under the adverse weather condition. The findings in this study are useful for transportation management agencies to design traffic control strategies when adverse weather occurs.

Simulation Modeling of Pedestrian Performance in the New Synchronized and Milwaukee B Interchanges versus Existing Designs

2018 ◽  
Vol 2672 (35) ◽  
pp. 151-160 ◽  
Author(s):  
Amirarsalan Mehrara Molan ◽  
Joseph E. Hummer
Keyword(s):  
Travel Time ◽  
Negative Impact ◽  
Heavy Vehicles ◽  
Traffic Distribution ◽  
Significant Negative Impact ◽  
Pedestrian Travel ◽  
Safe Condition ◽  
Vehicle Travel Time ◽  
Traffic Operation ◽  
The Impact

Most U.S. highway agencies recognize the importance of designing safe, short, and comfortable paths for pedestrians. Providing such an acceptable condition for pedestrians requires specific attention at intersections and service interchanges due to their interaction with other modes of transportation. The main objective of this research was to analyze pedestrian operation at two new service interchanges—the synchronized and Milwaukee B interchanges—in comparison with four existing designs. The analysis consists of three main parts: (1) a general comparison among the designs for pedestrian performances in terms of safety, travel time, and the level of service; (2) investigation of the effects of vehicles on pedestrian performance; and (3) modeling the impact of pedestrians on the traffic operation of vehicles. A comprehensive series of simulation tests were run using VISSIM and Synchro to study the pedestrian performance of interchanges in various situations of traffic volume, turning traffic ratio, traffic distribution, and percentage of heavy vehicles. The results indicated that a relatively safe condition is expected for pedestrians in the proposed new designs in comparison with the existing interchanges; however, the pedestrians’ travel time was lower in all the existing designs than in the new designs except the diverging diamond interchange (DDI). The DDI, one of the most popular alternative interchanges, showed the worst performance in all the aspects of the pedestrian analysis. Despite the very good performance of conventional diamond interchange regarding pedestrian travel time and safety, pedestrians could have a significant negative impact on vehicle travel time through a diamond.

Designing Limited-Stop Transit Service with Fixed Fleet Size in Peak Hours by Exploiting Transit Data

2017 ◽  
Vol 2647 (1) ◽  
pp. 134-141
Author(s):  
Xiaoling Luo ◽  
Yangsheng Jiang ◽  
Zhihong Yao ◽  
Youhua Tang ◽  
Yuan Liu
Keyword(s):  
Travel Time ◽  
Heuristic Algorithm ◽  
Travel Demand ◽  
Fleet Size ◽  
Transit Service ◽  
User Costs ◽  
Passenger Flow ◽  
Line Structure ◽  
Total Travel Time ◽  
Travel Behaviors

Efficiently designed limited-stop transit service is an attractive way to respond to high commuter travel demand in which trips concentrate on a few origin–destination pairs during peak hours. Such service is redesigned in many metropolises in China. Some research has dealt with this situation; bus fleet size was assumed to be unlimited, and the research was concerned with the average daily passenger flow rather than the specific average peak hour travel demand. In contrast to previous work, this paper presents an approach to design limited-stop transit service with the existing available fleet size from current normal service and focuses only on peak hour travel demand extracted through exploitation of transit data. First, a model for limited-stop service was proposed to minimize user costs through existing fixed fleet size. A heuristic algorithm was developed to search the transit line structure for limited-stop service instead of selecting lines from the predefined set. Next, a case in Chengdu, China, was tested. The results indicate that up to 9.32% of total travel time can be saved with the fixed fleet size when limited-stop transit service is applied. Finally, different proportions of commuter flow and different travel behaviors are discussed to illustrate the performance of limited-stop service for different scenarios.

scholarly journals The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4163
Author(s):  
Jamil Hamadneh ◽  
Domokos Esztergár-Kiss
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Fleet Size ◽  
The Public ◽  
Levels Of Automation ◽  
Multi Agent ◽  
Transport Modes ◽  
The Impact

Introducing autonomous vehicles (AVs) on the market is likely to bring changes in the mobility of travelers. In this work, extensive research is conducted to study the impact of different levels of automation on the mobility of people, and full driving automation needs further study because it is still under development. The impacts of AVs on travel behavior can be studied by integrating AVs into activity-based models. The contribution of this study is the estimation of AVs’ impacts on travelers’ mobility when different travel demands are provided, and also the estimation of AVs’ impact on the modal share considering the different willingness of pay to travel by AVs. This study analyses the potential impacts of AVs on travel behavior by investigating a sample of 8500 travelers who recorded their daily activity plans in Budapest, Hungary. Three scenarios are derived to study travel behavior and to find the impacts of the AVs on the conventional transport modes. The scenarios include (1) a simulation of the existing condition, (2) a simulation of AVs as a full replacement for conventional transport modes, and (3) a simulation of the AVs with conventional transport modes concerning different marginal utilities of travel time in AVs. The simulations are done by using the Multi-Agent Transport Simulation (MATSim) open-source software, which applies a co-evolutionary optimization algorithm. Using the scenarios in the study, we develop a base model, determine the required fleet size of AVs needed to fulfill the demand of the different groups of travelers, and predict the new modal shares of the transport modes when AVs appear on the market. The results demonstrate that the travelers are exposed to a reduction in travel time once conventional transport modes are replaced by AVs. The impact of the value of travel time (VOT) on the usage of AVs and the modal share is demonstrated. The decrease in the VOT of AVs increases the usage of AVs, and it particularly decreases the usage of cars even more than other transport modes. AVs strongly affect the public transport when the VOT of AVs gets close to the VOT of public transport. Finally, the result shows that 1 AV can replace 7.85 conventional vehicles with acceptable waiting time.

scholarly journals Emergency ambulance speed characteristics: a case study of Lesser Poland voivodeship, southern Poland

2021 ◽  
Author(s):  
Michał Lupa ◽  
Monika Chuchro ◽  
Wojciech Sarlej ◽  
Katarzyna Adamek
Keyword(s):  
Travel Time ◽  
Time Of Day ◽  
Southern Poland ◽  
The Road ◽  
Emergency Ambulance ◽  
Invaluable Tool ◽  
Day Of The Week ◽  
Correct Estimation ◽  
The Impact

AbstractThe correct estimation of ambulance travel time is an extremely important issue from the perspective of healthcare and the security of citizens. In some events, the threat to the health or life of an injured person increases with each minute of waiting for an ambulance. The authors of this article analyzed how ambulances travel throughout the entire Lesser Poland voivodeship in southern Poland. Based on the analysis of 300 million GPS records that were collected over several years from 300 ambulances, real ambulance speed characteristics were compiled for the most important cities in the region. The obtained results regarding ambulance speed characteristics were used to understand the correlation between ambulance speed, the density of the road network, and the built-up areas of a given city. Furthermore, the impact on the speed of ambulances of traffic, time of day, day of the week, or the season was also examined. The influence of the use of ambulances’ lights/sirens on travel time was also examined. The culmination of the research was the presentation of the theoretical foundations of coverage maps and a method of implementing them based on the determined speed characteristics. The presented studies show that the speed at which ambulances move is a very local phenomenon. Also, a relatively constant average speed of ambulances throughout the whole week was found. Moreover, a difference in speed between signaled and non-signaled ambulance trips was observed. The speed characteristics that were obtained were used as input data for the development of dynamic coverage maps, which are an invaluable tool for supporting the decisions of ambulance dispatchers.

scholarly journals Improving Bus Operations through Integrated Dynamic Holding Control and Schedule Optimization

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Shuozhi Liu ◽  
Xia Luo ◽  
Peter J. Jin
Keyword(s):  
Numerical Simulation ◽  
Travel Time ◽  
Optimal Choice ◽  
Fleet Size ◽  
Slack Time ◽  
Proposed Model ◽  
Average Travel Time ◽  
Bus Bunching ◽  
Bus Services ◽  
The Impact

Bus bunching can lead to unreliable bus services if not controlled properly. Passengers will suffer from the uncertainty of travel time and the excessive waiting time. Existing dynamic holding strategies to address bus bunching have two major limitations. First, existing models often rely on large slack time to ensure the validity of the underlying model. Such large slack time can significantly reduce the bus operation efficiency by increasing the overall route travel times. Second, the existing holding strategies rarely consider the impact on the schedule planning. Undesirable results such as bus overloading issues arise when the bus fleet size is limited. This paper explores analytically the relationship between the slack time and the effect of holding control. The optimal slack time determined based on the derived relationship is found to be ten times smaller than in previous models based on numerical simulation results. An optimization model is developed with passenger-orient objective function in terms of travel cost and constraints such as fleet size limit, layover time at terminals, and other schedule planning factors. The optimal choice of control stops, control parameters, and slack time can be achieved by solving the optimization. The proposed model is validated with a case study established based on field data collected from Chengdu, China. The numerical simulation uses the field passenger demand, bus average travel time, travel time variance of road segments, and signal timings. Results show that the proposed model significantly reduce passengers average travel time compared with existing methods.

scholarly journals Using a Neural Network to Analyze the Impact of Passenger Activity on Bus Dwell Time and Travel Time

2010 ◽  
Author(s):  
Mei Chen ◽  
Xiaobo Liu
Keyword(s):  
Neural Network ◽  
Travel Time ◽  
Dwell Time ◽  
Sensitivity Analyses ◽  
Neural Network Modeling ◽  
Time Data ◽  
Relative Significance ◽  
Improvement Measures ◽  
Trained Neural Network ◽  
The Impact

This paper applies neural network modeling approach to analyze the impact of passenger activities on bus dwell time and station-to-station travel time. Data used to develop the model was collected by onboard AVL/APC devices. Sensitivity analyses based on a trained neural network were performed to evaluate the relative significance of each passenger activity variable to variation of dwell time and/or station-to-station travel time. Transit providers can use these methods to identify the causes of schedule deviation and to develop improvement measures that are most effective to transit service.

Modeling Arrival Flight Times within the Terminal Airspace

2021 ◽  
pp. 036119812110114
Author(s):  
Osama Alsalous ◽  
Susan Hotle
Keyword(s):  
United States ◽  
Travel Time ◽  
The United States ◽  
Time Of Day ◽  
Civil Aviation ◽  
Weather Data ◽  
Travel Times ◽  
International Airport ◽  
Area Of Interest ◽  
The Impact

Air traffic management efficiency in the descent phase of flights is a key area of interest in aviation research for the United States, Europe, and recently other parts of the world. The efficiency of arrival travel times within the terminal airspace is one of nineteen key performance indicators defined by the Federal Aviation Administration (FAA) and the International Civil Aviation Organization, typically within 100 nmi of arrival airports. This study models the relationship between travel time within the terminal airspace and contributing factors using a multivariate log-linear model to quantify the impact that these factors have on the total travel time within the last 100 nmi. The results were compared with the baseline set of variables that are currently used for benchmarking at the FAA. The analyzed data included flight and weather data from January 1, 2018 to March 31, 2018 for five airports in the United States: Chicago O’Hare International Airport, Hartsfield-Jackson Atlanta International, San Francisco International Airport, John F. Kennedy International Airport, and LaGuardia Airport. The modeling results showed that there is a significant improvement in prediction accuracy of travel times compared with the baseline methodology when additional factors, such as wind, meteorological conditions, demand and capacity, ground delay programs, market distance, time of day, and day of week, are included. Root mean squared error values from out-of-sample testing were used to measure the accuracy of the estimated models.

Sensitivity Analysis of the Transit Signal Priority Requesting Threshold and the Impact on Bus Performance and General Traffic

2021 ◽  
pp. 036119812098585
Author(s):  
Michael H. Sheffield ◽  
Grant G. Schultz ◽  
David Bassett ◽  
Dennis L. Eggett
Keyword(s):  
Travel Time ◽  
Short Range ◽  
Dwell Time ◽  
Convincing Evidence ◽  
Transit Signal Priority ◽  
Time Performance ◽  
Dedicated Short Range Communication ◽  
Negative Impacts ◽  
Day To Day Operations ◽  
The Impact

An analysis was performed to evaluate the impact of changing the transit signal priority (TSP) requesting threshold on bus performance and general traffic, using field-generated data exclusively. Route 217, a conventional bus route that uses a dedicated short-range communication (DSRC)-based TSP system as part of its normal day-to-day operations, was analyzed over a three-month period from May 2019 through August 2019. The requesting thresholds evaluated for Route 217 were 3, 2, and 0 min, which stipulate how far behind schedule the bus must be to request TSP. For each requesting threshold, bus performance was evaluated through on-time performance (OTP), schedule deviation, travel time, and dwell time, while the traffic analysis was performed by evaluating split failure, change in green time, and the frequency at which TSP was served. A combination of observational and statistical analyses concluded with convincing evidence that OTP, schedule deviation, and travel time improve as the requesting threshold approaches zero with negligible impacts on general traffic. As the requesting threshold changed from 3, to 2, to 0 min, OTP increased 2.0% and 2.5%, respectively; mean schedule deviation improved by 15.9 s and 20.9 s, respectively; and travel time decreased at 75% of timepoints. Meanwhile, negative impacts to traffic occurred if an increase in split failure was measured after TSP was served, a phenomenon observed a maximum of once every 43 min. Thus, it is concluded that bus performance improves as the requesting threshold approaches zero with inconsequential impacts on general traffic.

Dynamic Comparison of the Fruit Sector and the Pollution Associated to Agriculture

2018 ◽  
Vol 69 (10) ◽  
pp. 2776-2780
Author(s):  
Valentina Constanta Tudor ◽  
Ionela Mituko Vlad ◽  
Diana Zamfir Vasca
Keyword(s):  
Agricultural Production ◽  
Descriptive Statistics ◽  
The Public ◽  
Perennial Plants ◽  
National Statistics ◽  
The Impact

Pollution in agriculture plays a major role. One of the sector affected by this phenomenon is the perennial plants, such as fruits sector. This sector is an important part of agricultural production in Romania, mainly because of the areas that have been dedicated; that is why the sector should be reconsidered because it could be one of the engines of the agriculture. This have to led to important efforts and increased attention in managing the opportunities offered by the development of the associations and producer groups involved. The present paper aims to address certain aspects of the national, macro-regional and European aspects of these fruits productions and the impact of the degree of pollution in agriculture. In this respect, data derived from the public databases dedicated to this field, namely Eurostat, the National Statistics Institute, DG Agriculture / FADN database and the Ministry of Agriculture, were used. The methods used to analyze and interpret the results are descriptive statistics, dynamics and comparisons between target areas and indicators. The results highlighted in the first part of the paper the Romania�s position upon the European average in what concern the fruit sector but also upon a competing country on the fruit market, Poland, which is considered to have a European top position.

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