Bus Travel Time Reliability Incorporating Stop Waiting Time and In-vehicle Travel Time with AVL Data

Improving bus operation quality can attract more commuters to use bus transit, and therefore reduces the share of car and alleviates traffic congestion. One important index of bus operation quality is the bus travel time reliability, which in this paper is defined to be the probability when the sum of bus stop waiting time and in-vehicle travel time is less than a certain threshold. We formulate the bus travel time reliability by the convolution of independent events’ probabilities, and elaborate the calculation method using Automatic Vehicle Location (AVL) data. Next, the No.63 Bus Line in Harbin City is used to test the applicability of the proposed method, and analyze the influence factors of the bus travel time reliability. The numerical results show that factors such as weather, workday, departure time, travel distance, and the distance from the boarding stop to the bus departure station will significantly affect the travel time reliability. At last, some general conclusions and future research are summarized.

STUDI WAKTU PERJALANAN DAN TUNDAAN DENGAN APLIKASI VISSIM PADA RUAS JALAN A.H. NASUTION

A.H Nasution Street is one of the primary arterial roads that connect between Cileunyi to East Bandung. East Bandung region is one of the areas that chosen by people at Bandung to settle. Therefore during rush hour there is congestion at A.H Nasution Street. The goal of this research is to identify vehicle travel time on A.H Nasution Street, and evaluate each intersection that is one of the major delays on A.H Nasution Street and provide alternative solutions using PTV Vissim. The road sections that reviewed ini this research started from the A.H nasution – Ahmad Yani Intersection until Ditbintekjatan, (Direktorat Bina Teknik Jalan dan Jembatan) with data collection time on Monday, 9th Mar 2020 at 06.00 am – 07.00 am. The existing analysis on A.H Nasution street from West to East has LoS F with vehicle travel time taken for 22 minutes 10 seconds with a delay of 410 seconds, while from East to West has LoS F with vehicle travel time taken for 23 minutes 47 seconds with a delay of 345 seconds. If repairs are made by widening the lane at Sta (0+000) – Sta (0+500) and the the prohibition of turning right at each unsignalized intersection on the section that reviewed, the A.H Nasution street from West to East has a LoS C with vehicle travel time faster with a shorter delay, while from East to West has a LoS D with vehicle travel time faster with a shorter delay.

Identifying and Quantifying Factors Determining Dynamic Vanpooling Use

Nowadays, the growth of traffic congestion and emissions has led to the emergence of an innovative and sustainable transportation service, called dynamic vanpooling. The main aim of this study is to identify factors affecting the travel behavior of passengers due to the introduction of dynamic vanpooling in the transportation system. A web-based mode choice survey was designed and implemented for this scope. The stated-preference experiments offered respondents binary hypothetical scenarios with an ordered choice between dynamic vanpool and the conventional modes of transport, private car and public transportation. In-vehicle travel time, total travel cost and walking and waiting time or searching time for parking varies across the choice scenarios. An ordered probit model, a multinomial logit model and two binary logit models were specified. The model estimation results indicate that respondents who are aged between 26 and 35 years old, commute with PT or are members of bike-sharing services were significantly more likely to choose dynamic vanpool or PT than private car. Moreover, respondents who are worried about climate change and are willing to spend more for environmentally friendly products are significantly more likely to use dynamic vanpool in comparison with private cars. Finally, to indicate the model estimation results for dynamic vanpool, the value of in-vehicle travel time is found to be 12.2€ per hour (13.4€ for Munich subsample).

Diagnosing Obstacles to Speed and Reliability with High-Resolution Automatic Vehicle Locator Data: Bus Time Budgets

Transit riders consistently rate speed and reliability of service as primary drivers of satisfaction, and transit agencies can help retain and grow ridership by improving these components of service. The challenge for transit agency staff is to identify when and where they should focus efforts to improve service quality. Here we propose an approach to data analysis that identifies and isolates specific aspects of service that are limiting speed and reliability. In-vehicle travel time can be decomposed into time spent in motion and time stopped. Time in motion is often dependent on factors common to general traffic, whereas time stopped has some features in common with general traffic (i.e., traffic signals) and some unique to buses (i.e., passenger dwell). Other sources of delay from serving a bus stop include deceleration, acceleration, and signal delay. To improve overall travel time, transit agencies must prioritize interventions that will contribute the most to improving speed and reliability. We used high-resolution automatic vehicle locator data to assign components of speed and reliability within a trip-level “time budget.” We compared typical time budget components across service types, and used the time budget approach to evaluate local service and Rapid bus service operating simultaneously on the same alignment. Results of the delay and variability quantifications suggested particular interventions, as well as the expected size of the resulting effect. With limited resources, the bus time budget approach could aid understanding and prioritization of transit agency efforts to improve speed and reliability.

Freight Vehicle Travel Time Analysis: A Case Study of Birgunj Nagdhunga Corridor

This study covers the freight vehicle, which clears the custom clearance process for Kathmandu and transports the same goods to Kathmandu from Birgunj. In this study average travel time for freight vehicles from Birgunj to Nagdhunga has been studied, along with the factors affecting the travel time from Birgunj to Nagdhunga. License plate monitoring method of the freight vehicles was done to find the average travel time and a questionnaire survey was done to identify the factors affecting travel time of the freight vehicle. The travel time from Birgunj to Nagdhunga is different for different types of, vehicle and good. The fastest average travel time is of fixed container of 40 feet size with 23.2 hours and longest average time is for fixed container of 20 feet size with 28.95 hours. The average travel time for non-degradable goods is 26.5 hours and for degradable goods is 22.38 hours. Major factors affecting the travel time are traffic congestion along the route, bad road condition along the route and hilly road with sharp bends, turns and grade.

Analysis on Link Travel Time Estimation considering Time Headway Based on Urban Road RFID Data

In this paper, the calculation method of the link travel time is firstly analysed in the continuous traffic flow by using the detection data collected when vehicles pass through urban links, and a theoretical derivation formula for estimating link travel time is proposed by considering the typical vehicle travel time and the time headway deviation upstream and downstream of the links as the main parameters. A typical vehicle analysis method based on link travel time similarity is proposed, and the theoretical formula is optimized, respectively. Then, an estimation formula based on maximum travel time similarity and an estimation formula based on maximum travel time confidence interval similarity are proposed, respectively. Finally, when analysing the fitting conditions, the collected data from urban roads in Nanjing are used to verify the proposed travel time estimation method based on the radio frequency identification devices. The results show that time headway deviation converges to zero when the hourly vehicle volume is more than 20 veh/h in the certain flow direction, and there are more positive and negative fluctuations when the hourly vehicle volume is less than 10 veh/h in the certain flow direction. The accuracy of the proposed improved method based on typical vehicle travel time estimation is significantly improved by considering the typical vehicle travel time, and typical vehicles on the road segment mainly exist at the tail of the traffic platoon in the corresponding period.

Estimation of Travel Time Spending by Urban Transport Passengers

The objective of the article is to obtain dependencies linking time spent by passengers on travel by public transport with the main factors that form the elements of this time spending. The research used methods of analytical modelling, mathematical and transport statistics, survey, analytical and logical analysis, methodology of transport research.Mathematical models for estimating passenger travel time in cities using public transport are considered. Attention is drawn to formation of each of the elements of travel time and to the relationship of these elements with each other. Such elements comprise time of walking to the stopping point of departure and of walking from the stopping point of arrival to the destination of the trip; waiting time for boarding a vehicle; travel time spent in a vehicle along the route. The dependences of these elements on the factors that form time spending have been identified. The increase in time spent waiting for boarding a vehicle is investigated depending on reduction in the planned number of vehicles due to breakdowns. The above models can be used in transport planning and assessing quality o f public transportation in terms of passenger travel time.