Traffic Impact Analysis Of Capacity And Safety Evaluation For Bus Stop

Urban public transportation systems perform an essential function in the mobility of passengers in metropolitan areas around the world.Many studies have found that the performance of bus stops has an important effect on bus service level.In high demand situations,especially for commuting,the performance of transit system is controlled by bus stops.In light of these,this research study focus on the traffic impact analysis for bus stops including capacity,safety,and empirical analysis,which are closely related to bus service.The primary objectives are to obtain and analyze the characteristics of bus arrivals and bus service based on data collection and analysis;study the bus stop capacity modeling using diffusion approximation method and ququing theory;calculate the capacity reduction coefficients for motor vehicle lanes and non-motorized vehicle lanes;and conduct level-of-safety modeling for bus stops based on the traffic conflict analysis.Specifically,the following main contributions are made in this thesis.(1)Analysis of bus dwelling characteristics at bus stopsAccoeding to the location,right-of-way,form,and cross-section,seven types of bus stop designs are commonly observed in China.In order to analyze and forecast the number of passengers at bus stops,a hybrid method of ARIMA-EGARCH-M-GED(AEMG)was introduced in this section.In addition,a quantitative approach was developed to estimate bus dwell time and time lost serving stop,which included acceleration and deceleration time,dead time,and time for serving boarding and alighting passengers.A case study was conducted to show the applicability of the proposed model.R-square and Mean Absolute Percentage Error values indicated the method was well validated and could be practically used in China.(2)Modeling bus capacity for bus stopsThis section explored the distributions for bus arrivals and bus service time.The results showed that bus arrivals at stops followed Poisson process,and bus service time at stops followed lognormal distribution.Based on the above testing results,a stochastic queuing model M/G-L/1(S)for single-berth and multi-berth stops were developed to estimate bus stop capacity.In addition,a model incorporating a diffusion approximation method was proposed to explore the correlation between failure rate and bus-stop operation,which included bus arrival rate,service time,variation coefficient of service time,variation coefficient of bus arrival headway,and bus stop capacity.The results found that it was not efficient to build bus stops with more than three adjacent berths.If more than 3 berths were necessary,the stop should be split in two multi-berth stops(e.g.,a 4-berth stop can be split in two 2-berth stops).(3)Effects of bus stops on the traffic operation of non-bus motor vehicles and non-motorized vehiclesTo explore the effects of dwelling buses on motor vehicles and non-motorized vehicles,generalized event count(GEC)and propensity score matching(PSM)methods were developed to analyze traffic conflicts beteween buses and non-motorized vehicles and evaluate the effects of dwelling buses on the reductions of motor vehicle speeds at stops.According to the calculations,the estimated treatment effect was 7.2km/h.In addition,this section utilized a reduction coefficient of capacity to evaluate the impact of bus stops on the traffic operation of motor vehicle lanes and non-motorized vehicle lanes.The results showed that as the number of berths increased,the capacity reduction coefficients decreased.(4)Traffic safety evaluation for bus stopsIn China,it is quite difficult to obtain traffic crash data or conflict data mainly due to the lack of traffic data management and organizational issues.In light of this,the concept of level-of-safety for bus stops was introduced and corresponding models were proposed to quantify safety levels,which considered conflict points,traffic factors,geometric characteristics,traffic signs and markings,pavement conditions,and lighting conditions.Principal component analysis and k-means clustering method were used to model and quantify safety levels for bus stops including six levels,i.e.,level A(best)to level F(worst).