scholarly journals Travel Time Reliability of Bus Operation in Heterogeneous Traffic Conditions of Dar es Salaam City, Tanzania

2020 ◽  
Vol 11 (2) ◽  
pp. 44-55
Author(s):  
Prosper S. Nyaki ◽  
Hannibal Bwire ◽  
Nurdin K. Mushule

AbstractThe assessment of travel time reliability enables precise prediction of travel times, better activity scheduling and decisions for all users of the road network. Furthermore, it helps to monitor traffic flow as a crucial strategy for reducing traffic congestion and ensuring high-quality service in urban roads. Travel time reliability is a useful reference tool for evaluating transport service quality, operating costs and system efficiency. However, many analyses of travel time reliability do not provide true travel variation under heterogeneous traffic flow conditions where traffic flow is a mixture of motorized and non-motorized transport. This study analysed travel time reliability under heterogeneous traffic conditions. The travel reliabilities focused on passenger waiting time at bus stops, in-vehicle travel time, and delay time at intersections which were analysed using buffer time, standard deviation, coefficient of variation, and planning time. The data used were obtained from five main bus routes in Dar es Salaam. The results indicate low service reliability in the outbound directions compared to inbound directions. They also intend to raise awareness of policy-makers about the situation and to make them shift from expanding road networks towards optimising road operations.

2021 ◽  
Author(s):  
Swapneel R. Kodupuganti ◽  
Sonu Mathew ◽  
Srinivas S. Pulugurtha

The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.


Author(s):  
Whoibin Chung ◽  
Mohamed Abdel-Aty ◽  
Ho-Chul Park ◽  
Qing Cai ◽  
Mdhasibur Rahman ◽  
...  

A new decision support system (DSS) using travel time reliability was developed for integrated active traffic management (IATM) including freeways and arterials. The DSS consists of recommendation and evaluation of response plans. The DSS also includes three representative traffic management strategies: variable speed limits, queue warning, and ramp metering. The recommendation of response plans for recurring traffic congestion was generated from the logics of the three strategies. The evaluation of response plans was conducted by travel time reliability through the prediction of traffic conditions with response plans. The near-future prediction of traffic conditions with control strategies was conducted through METANET for freeways and arterials. The developed DSS was evaluated under three types of traffic congestion: extreme, heavy, and moderate. According to the evaluation results, the developed DSS recommended an IATM strategy with the highest synergistic relationships in real time and contributed to enhancing the effectiveness of the IATM strategies. It was confirmed that arterials should have the allowable residual capacity for the improvement of traffic flow of the entire corridor network. Furthermore, the DSS demonstrated a more balanced traffic condition between freeways and arterials.


Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.


The traffic flow conditions in developing countries are predominantly heterogeneous. The early developed traffic flow models have been derived from fluid flow to capture the behavior of the traffic. The very first two-equation model derived from fluid flow is known as the Payne-Whitham or PW Model. Along with the traffic flow, this model also captures the traffic acceleration. However, the PW model adopts a constant driver behavior which cannot be ignored, especially in the situation of heterogeneous traffic.This research focuses on testing the PW model and its suitability for heterogeneous traffic conditions by observing the model response to a bottleneck on a circular road. The PW model is mathematically approximated using the Roe Decomposition and then the performance of the model is observed using simulations.


2017 ◽  
Vol 2643 (1) ◽  
pp. 139-159 ◽  
Author(s):  
Shu Yang ◽  
Chengchuan An ◽  
Yao-Jan Wu ◽  
Jingxin Xia

Travel time reliability (TTR) is an important performance indicator for transportation systems. TTR can be generally categorized as either segment based or origin–destination (O-D) based. A primary difference between the two TTR estimations is that route information is implied in segment-based TTR estimations. Segment-based TTR estimations have been widely studied in previous research; however, O-D–based TTR estimations are used infrequently. This paper provides detailed insight into O-D–based TTR estimations and raises three new issues: ( a) How many routes do travelers usually take and what are the TTR values associated with these routes? ( b) Do statistical differences exist between route-specific and non-route-specific (NRS) TTR values? ( c) How can O-D–based TTR information be delivered? Two processes were proposed to address the issues. Three TTR measures—standard deviation, coefficient of variation, and buffer index—were calculated. The bootstrapping technique was used to measure the accuracy of the TTR measures. Approximate confidence intervals were used to investigate statistically the differences between route-specific and NRS TTR measures. A large quantity of taxicab GPS-based data provided data support for estimating O-D–based TTR measures. The results of O-D–based TTR measures showed that no statistically significant differences existed between route-specific and NRS TTR measures for most of the time periods examined. Statistically significant differences could still be found in some time periods. Travelers may take advantage of these differences to choose a more reliable route. Access to both numeric TTR values and route preference, instead of just to TTR information on segments of interest, can be beneficial to travelers in planning an entire trip.


2011 ◽  
Vol 97-98 ◽  
pp. 952-955
Author(s):  
Xiong Fei Zhang ◽  
Rui Min Li ◽  
Min Liu ◽  
Qi Xin Shi

Travel time reliability, as a measure of performance, is attracting more and more attention because unreliable transportation information hinders travelers’ decision making and creates difficulties for authorities to manage network operations. Since travel time reliability is closely related to the stochastic properties of the day-to-day travel time distribution, several statistical measures have been proposed, including standard deviation, coefficient of variation, buffer index, misery index and so on. Each of these measures is derived from travel time distribution but captures only one or two characteristics of travel time. In this paper, an effort is made to evaluate travel time reliability incorporating as many characteristics of travel time as possible based on fuzzy logic. The basic rules are: (1) the larger the variance is, the more unreliable the travel time is; (2) the larger the travel times of unlucky travelers are, the more unreliable the travel time is; (3) the larger the distribution skews to the left, the more unreliable the travel time is. The proposed methodology has been tested and analyzed with field data.


Author(s):  
Raunak Mishra ◽  
Pallav Kumar ◽  
Shriniwas S. Arkatkar ◽  
Ashoke Kumar Sarkar ◽  
Gaurang J. Joshi

This research was aimed at developing an area occupancy–based method for estimating passenger car unit (PCU) values for vehicle categories under heterogeneous traffic conditions on multilane urban roads for a wide range of traffic flow levels. First, PCU values of vehicle categories were determined according to the Transport and Road Research Laboratory definition and replaced the commonly considered measure of performance speed with area occupancy using simulation. The PCU values obtained were found to be significantly different for different volume-to-capacity ratios; this result shows that the PCU value is dynamic in nature. While the dynamic nature of PCU values is well appreciated, practitioners may prefer a single set of optimized PCU values (unique for each vehicle category). Hence, a new method with a matrix solution was proposed to estimate the optimized or unique set of PCU values with area occupancy as the performance measure. To check the credibility of the proposed method, the estimated PCU values were compared from existing guidelines regulated by the Indian Roads Congress (IRC) and values estimated with the widely accepted dynamic PCU concept of speed–area ratio. Results show that the PCU values suggested by IRC and the dynamic PCU concept using the speed–area ratio underestimate and overestimate the flows, respectively, at different traffic volumes. However, the values obtained with the area-occupancy concept were found to be consistent with the traffic flow in a cars-only traffic situation at different flow conditions. The derived set of optimized PCU values proposed can be useful for traffic engineers, researchers, and practitioners for capacity and level-of-service analysis under heterogeneous traffic conditions.


2017 ◽  
Vol 22 (2) ◽  
pp. 106-120 ◽  
Author(s):  
Fangfang Zheng ◽  
Jie Li ◽  
Henk van Zuylen ◽  
Xiaobo Liu ◽  
Hongtai Yang

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