Afternoon Peak Period Research Articles

QUANTIFYING THE IMPACT OF TRAFFIC-RELATED EMISSIONS ON AIR QUALITY IN KANO CITY, NIGERIA

The aim of this study is to assess the concentration of traffic related air pollutants at some major traffic junctions in Kano metropolis, it comprised of carrying traffic count in the vicinities so as ascertain the sources of the pollution and identify the level of carbon monoxide (CO), nitrogen dioxide (NO 2), Sulphur dioxide (SO 2) for a period of six weeks. Traffic density was estimated via manual counting using tally sheet system. Crowcon gasman to air samplers ware used to measure the concentrations of gases emitted into the atmosphere at the selected locations. A total of 126 samples of air quality measurements were taken out for three hours, with each hour devoted to morning, afternoon and evening peak periods. Results obtained were compared with National Environmental Standard and Regulatory Enforcement Agency (NESREA) guideline limits. Data were analysed using statistical package IBM SPSS version 16.0 to compute descriptive statistics, Pearson correlation, regression analysis and one sample t-test. There was a correlation between CO, NO 2, SO 2 and traffic volume in the entire junctions, and most of the correlation obtained may be attributed to the high vehicular volume in the traffic jam. The result of this indicated that the mean concentration of CO, NO 2 and SO 2 emission at Kabuga, Kofar ruwa, Hotoro NNPC and Aminu Kano Teaching Hospital traffic junctions, gaseous emissions were within NESREA guideline limit for ambient conditions, except for CO concentration of 14.43 and 13.60 ppm at Bata and Kantin Kwari intersections were found to be much higher when compared with the NESREA guideline limits, respectively. This implies that transport-related pollution around Bata and Kantin Kwari is apparently unsafe. Similarly, it is likely that air quality will continue to deteriorate as the city continues to grow. Therefore, there is need for government to institute and enforce traffic emission control and air quality management programs as a priority. They should also work to prevent further environmental degradation by adopting effective policy in Nigeria.

Estimating network flow and travel behavior using day-to-day system-level data: A computational graph approach

To estimate network flow and travel behavior under recurrent traffic conditions, we leverage computational graphs and multi-source system-level data and solve a single-level optimization problem consistent with stochastic user equilibrium under logit assignment (SUELOGIT). Our model learns time-specific O-D matrices and utility functions and network flow parameters such as link flows, path flows, and travel times. To increase the model’s representational capacity for reproducing observed link flows and travel times, the parameters of the link performance functions are assumed link-specific. More importantly, the utility function in the route choice model is enriched with (i) link-specific parameters to capture the effect of unobserved attributes on route choices and (ii) period-specific parameters weighting the observed features in the utility function to capture the heterogeneity of travelers preferences among periods of the day. Experiments on synthetic data show that the parameters of the models can be consistently recovered and that the solution of the model satisfies the SUELOGIT conditions with high accuracy. The estimation procedure is also robust to random noise in both the observed traffic flow and travel time, and it requires very few hyperparameter tuning. Subsequently, the algorithm is deployed at a large scale using real-world multi-source data in Fresno, CA, with hourly data collected during the morning and afternoon peak periods of October 2019. The utility function includes link-specific effects and attributes such as travel time, the standard deviation of travel time, the number of traffic incidents, and socio-demographic information obtained from the US Census. We obtain estimates for the total trips and travelers’ utility function by hour of the day and for the average values of the link performance parameters that are reasonable and informative on the demand and supply characteristics of the transportation network.

A GIS Approach to Measuring Public Transport Travel Delay on Higher Order Roads in the City of Cape Town

Abstract. On a daily basis, hundreds of thousands of people in the City of Cape Town rely on road-based public transport as a means of commuting. A major factor that influences the passengers’ experience is the travel time to reach a desired destination. Due to various physical and operational factors, some sections of the road network experience high congestion and travel time delays during the morning and afternoon peak periods. Quantifying these delays, and the number of road-based public transport passengers exposed to the delay along a specific road section during a peak period allows informed decision-making and prioritisation. GIS and spatial data analysis are powerful tools to determine where and when such delays occur. Various spatial data sets exist that were jointly analysed to quantify the delay and the passenger volumes exposed to the delay on the city’s public transport network.

The impact of traffic mobility measures on vehicle emissions for heterogeneous traffic in Lagos City

Emissions from vehicular traffic are one of the key drivers of urban environmental air pollution, degrading the ambient air quality in many African cities and across the globe. This study sought to assess the impact of traffic mobility measures on the emission levels of air pollutants from vehicle exhaust in Lagos, Nigeria. Traffic flow and vehicle mix were collected daily during morning, afternoon, and evening peak periods along selected arterial and two-lane collector roadways. Simultaneously, five (5) air pollutants from vehicular traffic emissions were observed at distinct monitoring stations along the roadways using portable gas detectors. The traffic flow and mobility measures were inputted into a multiple exponential model to estimate the concentration of each pollutant. The result of the vehicle fleet composition revealed 3.5%, 4.5%, 57%, 32%, 1.5%, and 2% for motorcycles, tricycles, personal cars, minibuses, large buses, and heavy goods vehicles, respectively, on the two-lane road and 10%, 35%, 27%, 10%, and 18% for motorcycles, personal cars, minibuses, large buses, and heavy goods vehicles, respectively, on the arterial. The results of a multiple exponential regression model (MER) showed significant contributions from traffic flow, speed, vehicle fleet proportion, and pollutant concentration (p <0.05). However, the impact on ambient air quality revealed severe pollution levels for CO and PM2.5, while SO2, NO2, and PM10 showed moderate, poor, and poor pollution levels. This study has provided evidence on how pollutant emissions increase rapidly during peak traffic conditions in heterogeneous traffic on different classes of roads and recommended policies for managing vehicle fleets and traffic congestion with the aim of reducing the impact on the ambient air quality and health of the public on heavily trafficked roadways in sub-Saharan African cities.

Analysis of the June 2021 winter storm in Victoria with a catastrophic loss of large trees and major flooding

An extreme weather event which occurred in June 2021 stretched the rescue operations of Victorian Emergency Services due to major flooding and the unprecedented number of fallen large trees. The mechanisms which produced severe convection with gusts strong enough to bring down thousands of trees also produced the heaviest rainfall. The blocked roads and access to fallen power lines resulted in power outages lasting three weeks in some areas and some people were trapped in their houses for up to a week. The atmosphere around Melbourne was characterized by very strong vertical wind shear however convection was confined to mountainous areas southeast, east, and northwest of Melbourne. Overall, the region around Melbourne was in a stable atmosphere and convection was released by strong orographic lifting. Some of the heaviest rain fell on the Strzelecki Ranges and this drained into the city of Traralgon where near-record floods were reported. The event is compared with a Melbourne event in 2020 which caused three fatalities from fallen trees in the afternoon peak period. The fatalities were restricted with the current event due to it occurring just before and after midnight.

Modeling Sustainable Traffic Behavior: Avoiding Congestion at a Stationary Bottleneck

Sustainable traffic behaviour is increasing in importance as traffic volume rises due to population growth. In this paper, a model for traffic flow at a stationary bottleneck is developed to determine the parameters that cause congestion. Towards this goal, traffic density, speed, and delay were acquired during peak and off-peak periods in the morning and afternoon at a stationary bottleneck in Peshawar, KPK, Pakistan. The morning and afternoon peak periods have high densities, low speeds, and considerable delays. Regression models are developed using this data. These results indicate that there is a linear relationship between density and time at the stationary bottleneck and a negative linear relationship between density and speed. Thus, an increase in density increases the time delay and reduces the speed. I comprehensive traffic delay model is characterized by a stationary bottleneck. The Kolmogorov-Smirnov (KS) test and P-values were used to identify the best-fit distribution for speed and density. The binomial and generalized extreme values are considered the best fits for density and speed. The results presented can be used to develop accurate simulation models for stationary bottlenecks to reduce congestion. Doi: 10.28991/CEJ-2022-08-11-02 Full Text: PDF

Effectiveness of modified pedestrian crossing signs in an urban area

The District of Columbia currently uses the standard pedestrian warning signs and diagonal arrow plaques at a substantial number of uncontrolled crosswalks within the City. However, the widespread use of these measures appears to be ineffective in curbing the incidence of pedestrian involved crashes or pedestrian-vehicle conflicts. To compensate for the perceived lack of effectiveness of the standard pedestrian warning sign the District Department of Transportation developed a new side-of-street crossing sign to improve driver compliance based on pedestrian right-of-way laws. This study was aimed at determining the effectiveness (defined as the proportion of drivers approaching a crosswalk who stop or yield the right of way to a pedestrian in the crosswalk) of the experimental side-of-street pedestrian crossing sign compared to the standard sign, with and without rectangular rapid flashing beacons. Effectiveness of the side-of-street pedestrian sign and standard sign were observed at a total of 32 locations in the District over a one-year period using the “control” and “experimental” comparison approach. Video data for each location was obtained from March 2018 through February 2019 during typical weekdays for the morning and afternoon peak periods. The results of the study showed that the experimental signs with RRFBs provided higher driver compliance rates (yielding to pedestrians) compared to the standard signs for both the morning and afternoon peak periods. However, the differences in compliance rates for the experimental and standard signs were not statistically significant at a 95% confidence interval. Further evaluation of the signs is recommended using the “before” and “after” approach in addition to an assessment of crash statistics at the selected locations.

Roundabout Performance Analysis Using Connected Vehicle Data

There are over 8000 roundabouts in the United States. The current techniques for assessing their performance require field counts to provide inputs to analysis or simulation models. These techniques are labor-intensive and do not scale well. This paper presents a methodology to use connected vehicle (CV) trajectory data to estimate delay and level of service for roundabout approaches by adapting the Purdue Probe Diagram used for traffic signal analytics. By linear referencing vehicle trajectories with a particular movement based on the location and time they exit a roundabout, delay can be calculated. The scalability is demonstrated by applying these techniques to assess over 100 roundabouts in Carmel, IN during the weekday afternoon peak period in July 2021. Over 264,000 trajectories and 3,600,000 GPS points were analyzed to rank over 300 roundabout approaches by delay and summarize in Pareto-sorted graphics and maps. The paper concludes by discussing how these techniques can also be used to analyze queue lengths and origin-destination characteristics at roundabouts. The methodology presented in this study can be used by any agency that wants to assess the performance of all roundabouts in their system.

Simulation-Based Public Transport Priority Tailored to Passenger Conflict Flows: A Case Study of the City of Zagreb

Prioritizing public transport is one of the most effective measure to increase the attractiveness and competitiveness of public transport in relation to individual vehicles. The main goal of this study was to examine the possibilities for reducing the travel time of tram vehicles by giving priority at signalized intersections in terms of sharing the traffic lane with personal vehicles and under conditions of strong conflict flows with private transport. For this purpose, we used the simulation tool VISSIM and its module EPICS. A methodology for determining weighting factors for prioritizing public transport flows was developed based on conflicting passenger flows in public transport vehicles and passenger cars. Three scenarios were tested in the study area: (1) “do nothing”; (2) unconditional priority; and (3) conditional priority. The results showed that unconditional priority led to unsustainable traffic conditions for personal vehicles and public transport. In contrast, conditional priority reduced the travel time of public transport on certain corridors by between 7.64% and 18.76% in the morning peak period, and 5.60% to 22.50% in the afternoon peak period.

Longitudinal Performance Assessment of Traffic Signal System Impacted by Long-Term Interstate Construction Diversion Using Connected Vehicle Data

Local arterials can be significantly impacted by diversions from adjacent work zones. These diversions often occur on unofficial detour routes due to guidance received on personal navigation devices. Often, these routes do not have sufficient sensing or communication equipment to obtain infrastructure-based traffic signal performance measures, so other data sources are required to identify locations being significantly affected by diversions. This paper examines the network impact caused by the start of an 18-month closure of the I-65/70 interchange (North Split), which usually serves approximately 214,000 vehicles per day in Indianapolis, IN. In anticipation of some proportion of the public diverting from official detour routes to local streets, a connected vehicle monitoring program was established to provide daily performances measures for over 100 intersections in the area without the need for vehicle sensing equipment. This study reports on 13 of the most impacted signals on an alternative arterial to identify locations and time of day where operations are most degraded, so that decision makers have quantitative information to make informed adjustments to the system. Individual vehicle movements at the studied locations are analyzed to estimate changes in volume, split failures, downstream blockage, arrivals on green, and travel times. Over 130,000 trajectories were analyzed in an 11-week period. Weekly afternoon peak period volumes increased by approximately 455%, split failures increased 3%, downstream blockage increased 10%, arrivals on green decreased 16%, and travel time increase 74%. The analysis performed in this paper will serve as a framework for any agency that wants to assess traffic signal performance at hundreds of locations with little or no existing sensing or communication infrastructure to prioritize tactical retiming and/or longer-term infrastructure investments.

Logic-Based Traffic Flow Control for Ramp Metering and Variable Speed Limits—Part 2: Simulation and Comparison

This paper simulates, analyzes, and compares, for two case studies (one synthetic freeway and one real-life freeway), the behavior of Logic-Based Traffic Flow Control (LB-TFC), an integrated control strategy for Ramp Metering (RM) installations and Variable Speed Limits (VSLs) that was proposed and derivated in the first part of the work (‘Part 1: Controller’). For the first case study, which was presented in the first part of the work, the control performance of LB-TFC is compared with the ones obtained with the optimal solution and with the Mainstream Traffic Flow Control (MTFC) + PI-ALINEA algorithm. Moreover, the robustness of the considered controllers is analyzed for this case study concluding that LB-TFC is quite robust, specially when comparing with MTFC + PI-ALINEA. For the second study (a stretch of the ring-road freeway SE-30 in Seville, Spain), data from 10 different days have been used in order to simulate the performance of the considered controllers using real data for the afternoon peak period. In order to properly deal with a bottleneck with a dynamically changing number of lanes, the equations used for MTFC + PI-ALINEA have been slightly modified for the second case study. For both case studies, LB-TFC provides a robust performance that, in most cases, is close to the optimal one and that improves the reduction in the Total Time Spent (TTS) obtained with MTFC + PI-ALINEA. Moreover, this paper studies the tuning of the control parameters and the advantages and disadvantages of LB-TFC.

Estimating network travel time reliability with network partitioning

Network travel time reliability can be represented by a relationship between network space-mean travel time and the standard deviation of network travel time. The primary objective of this paper is to improve estimation of the network travel time reliability with network partitioning. We partition a heterogeneous large-scale network into homogeneous regions (clusters) with well-defined Network Fundamental Diagrams (NFD) using directional and non-directional partitioning approaches. To estimate the network travel time reliability, a linear relationship is estimated that relates the mean travel time with the standard deviation of travel time per unit of distance at the network level. The impact of different partitioning approaches, as well as the number of clusters, on the network travel time reliability relationship are also explored. To estimate individual vehicle travel times, we use two distinct approaches to allocate vehicle trajectories to different time intervals, namely trajectory and sub-trajectory methods. We apply the proposed framework to a large-scale network of Chicago using a 24-h dynamic traffic simulation. Partitioning and travel time reliability estimation are conducted for both morning and afternoon peak periods to demonstrate the impacts of travel demand pattern variations. The numerical results show that the sub-trajectory method for the network travel time reliability estimation and the directional partitioning with three clusters have the highest performance among other tested methods. The analyses also demonstrate that partitioning a heterogeneous network into homogeneous clusters may improve network travel reliability estimation by estimating an independent relationship for each cluster. Also, comparing morning and afternoon peak periods suggests that the estimated parameter for the linear network travel time reliability relationship is directly related to the coefficient of variation of density as a measure of spatial distribution of congestion across the network.

Have walking and bicycling increased in the US? A 13-year longitudinal analysis of traffic counts from 13 metropolitan areas

Local, state, and federal governments promote walking and bicycling in order to reduce emissions and improve public health. Tracking rates of bicycling and walking over time is important for assessing progress towards this goal. In the United States, most data are limited to cross-sectional self-report surveys (e.g., National Household Travel Surveys [NHTS]) or capture only the main commute mode (e.g., American Community Survey [ACS]). This study examines temporal trends (while controlling for spatial factors) of active travel in 13 US metropolitan areas between 2004 and 2016 (with 78% of counts occurring between 2010 and 2016) using repeated counts of bicycle and pedestrian traffic (n = 1319 count locations; 5554 bicycle and 5166 pedestrian counts). We used multilevel mixed-effects models to examine the multi-year trend in bicycling and walking during morning and afternoon peak periods. In the 5 out of 8 models where the temporal trend was statistically significant, we found that, on average, traffic volumes increased at a rate of 2–6% (bicycle) and 2–3% (pedestrian) per year among count locations, holding other variables constant. Presence of bicycle facilities (e.g., bicycle lanes, off-street trails) was positively associated with higher levels of bicycle traffic. Our results based on observed traffic patterns suggest larger increases in bicycling and walking as compared to the trends reported from the NHTS and ACS data. Quantifying the temporal trend from observed counts of traffic may aid policy makers and urban planners in assessing progress towards the goal of increasing bicycling and walking to reduce emissions and increase physical activity.

Evaluation of the Roundabout Capacity Model in HCM6 Edition and HCM 2010 on a Multilane Roundabout

This study evaluated the performance of the new Highway Capacity Manual 6th Edition (HCM6) roundabout capacity model at a multilane roundabout in Richfield, Minnesota. Traffic flow rates and gap acceptance data were collected during 20 hours of afternoon peak period traffic over four days. The observed critical headways for the left and right lanes was equal to 4.43 and 3.99 s while the observed follow-up headways were 3.05 and 2.96 s, respectively. Roundabout capacity curves for both lanes were built through the collected flow information, as well as through the observed headways and the HCM formula. As compared with the field observed results, the default model in HCM6 overestimated the capacity of the study roundabout. The default model in HCM 2010 closely estimated the capacity for the right lane, but overestimated the capacity of the left lane when the circulating flow rate was high. The HCM6 model was calibrated with the observed critical and follow-up headways, as well as by calibrating the intercept of the model using only the follow-up headway. The fully calibrated model overestimated the capacity of the right lane by 7–10% as the circulating flow decreases and overestimated the capacity of the left lane by 7% and 31%. The partially calibrated model overestimated the capacity of the left lane by 6% and overestimated the capacity of the right lane by at most 10% under low circulating flow rate, but it underestimated the capacity by at most 21% under high circulating flow rate.

Vehicle Emission Computation Through Microscopic Traffic Simulation Calibrated Using Genetic Algorithm

Abstract Vehicle emission calculation is critical for evaluating motor vehicle related environmental protection policies. Currently, many studies calculate vehicle emissions from integrating the microscopic traffic simulation model and the vehicle emission model. However, conventionally vehicle emission models are presented as a stand-alone software, requiring a laborious processing of the simulated second-by-second vehicle activity data. This is inefficient, in particular, when multiple runs of vehicle emission calculations are needed. Therefore, an integrated vehicle emission computation system is proposed around a microscopic traffic simulation model. In doing so, the relational database technique is used to store the simulated traffic activity data, and these data are used in emission computation through a built-in emission computation module developed based on the IVE model. In order to ensure the validity of the simulated vehicle activity data, the simulation model is calibrated using the genetic algorithm. The proposed system was implemented for a central urban region of Nanjing city. Hourly vehicle emissions of three types of vehicles were computed using the proposed system for the afternoon peak period, and the results were compared with those computed directly from the IVE software with a trivial difference in the results from the proposed system and the IVE software, indicating the validity of the proposed system. In addition, it was found for the study region that passenger cars are critical for controlling CO, buses are critical for controlling CO and VOC, and trucks are critical for controlling NOx and CO2. Future work is to test the proposed system in more traffic management and control strategies, and more vehicle emission models are to be incorporated in the system.

Harnessing the Potential of Automated Data to Simulate Emissions of an Interregional Bus Route in Toronto, Canada

This study made use of automated vehicle location and automated passenger counter data to simulate the greenhouse gas (GHG) emissions of an interregional bus route in Toronto, Ontario, Canada. The authors analyzed bus performance and emissions as well as quantified emissions under the effects of operational improvements (increasing speed and reducing idling) and different fuels (conventional diesel, compressed natural gas, and biodiesel). Average total trip emissions were 54 kg per bus, with emissions higher in the morning peak period than in the afternoon peak period. Emissions rates on the highway portion of the corridor were lower than emissions rates for the arterial portions, with mean values of 1,627 g/km and 1,993 g/km, respectively. The authors observed that the addition of each passenger influenced bus emissions per passenger differently; when the bus was less crowded, each additional passenger could decrease emissions per passenger by 7%, but that reduction becomes 1.3% when the bus is crowded. Finally, the study results estimated that operational improvements could reduce emissions by 22%, whereas switching to compressed natural gas without speed improvements could reduce emissions by 6%. The effects of emissions reduction strategies are highly dependent on the characteristics of the bus and drive cycle. These results are useful to transit planners in the selection of appropriate GHG reduction strategies as well as in the selection of candidate corridors (highway versus arterial routes) for fleet renewal.

Evaluating Off-Peak Pricing Strategies in Public Transportation with an Activity-Based Approach

Public transportation authorities across the world are implementing various peak and off-peak pricing strategies to manage travel demand and improve the overall system performance. In this study, an activity-based demand framework was used to evaluate two off-peak pricing strategies currently in use in Singapore. These strategies consisted of a free prepeak travel on mass rapid transit (MRT) and an off-peak discount for an integrated transit (public buses and MRT). Smart card data collected before and after the implementation of the first policy were used to calibrate the behavioral models involved, to capture travelers’ preferences and choices properly. To evaluate both pricing strategies, a comprehensive set of key performance indicators was considered and included the changes in peak ridership, average trip fare, operator’s revenue, the number of public transportation trips, and mode share. The results indicate that off-peak discount pricing strategies are a viable policy option for spreading demand peaks and that they are more effective during the afternoon peak period. This study also demonstrates the capabilities and the advantages of an agent-based modeling platform, SimMobility, as a tool for policy analysis.

A Before and After Analysis of the Impacts of the Inaguration of a New Metro Station in Naples

In this paper a before and after analysis of the impacts of the inauguration of a new metro station in Garibaldi square in Naples in Italy will be presented. This station is part of Line 1 and it was inaugurated in January 2014. Moreover, many interventions have been carried out in Garibaldi square, surrounding the station. Therefore a reorganization of the whole transportation system connecting this new strategic node was necessary. Two surveys have been undertaken with the objective of understanding these impacts. Indeed the first one aimed at identifying the present circulation scheme and the one induced by the inauguration of the station. The second one aimed at quantifying the entity of traffic flows in “critical points”, by counting the vehicles during peak periods. From these surveys, it has come out that in the peak morning period (7am-10am) 6,000 vehicles have been counted towards the rail node Garibaldi. This value decreases of almost 15% in the afternoon peak period (12am-3pm) as well as in the evening one (5pm-8pm). A simulation model has been implemented as well in order to estimate future scenarios promoted by the local administration. Indeed the access to the square and to the surrounding areas (where the CBD and the historical centre are placed) changes completely.

Traffic lanes for vehicles of mass public passenger transport on city streets

Some of the basic measures of regulating public mass passenger transport in a city network are the introduction and management of traffic lanes reserved for the public transportation. These traffic lanes are important for several reasons: faster moving and shorter travelling time for the vehicles, reducing operating costs, improving the safety, increasing passenger comfort, maintaining of the timetable quality, etc. In most cities, an intensive use of the public transport is concentrated in the morning and the afternoon peak period. The state of the public transport system during these periods is reflected in the crowds inside the vehicles, long vehicle queues at intersections and at bus stops, which cause congestion on the streets and result in delays of public transport vehicles. This paper provides an overview of the current situation on an example in the city of Belgrade. The capacity and the quality of service for the street surfaces reserved for the public transportation vehicles were analysed on the aforementioned example.

Travel Patterns of Urban Linear Ferry Passengers

Urban linear ferry systems are an emerging form of public transport in cities worldwide. The travel behavior of passengers who used CityCat ferries in Brisbane, Queensland, Australia, was investigated with data from 1,675,821 smart card fare transactions for ferry trips made over a 6-month period. Although services used small vessels and had only one main route, about 2.3% of all paid public transport journeys in Brisbane were made on CityCat and the related cross-river ferries. The ferries were used more for commuting and university trips on weekdays with significant patronage in the morning and afternoon peak periods. Use was consistent on weekend days. Although use was strong, most users were infrequent patrons; this use suggested that leisure travel was a significant component of the system. Key terminals with high use rates included those where transfer to cross-river ferry services was possible. The system offered single-stop cross-river travel at many points. However, only 15.8% of paid trips in March 2013 were made this way; 84.2% of trips continued farther up- or downriver. Integration with other buses and trains was significant; about 15% of all ferry journeys were linked to another mode of public transport. Additional investigation into how users access terminals and interact with other public transport modes is suggested. With expansion planned, the CityCat system could increase its contribution to public transport in Brisbane. Increasing the use frequency of the large pool of infrequent riders could increase patronage of the system.