Effects of behavioral characteristics of taxi drivers on safety and capacity of signalized intersections

Xu, Chengcheng; Liu, Pan; Wang, Wei; Jiang, Xuan; Chen, Yuguang

doi:10.1007/s11771-014-2392-7

Cited by 12 publications

(6 citation statements)

References 12 publications

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“…Though often very professional, taxi drivers depend to a large extent on the number of passengers they carry to determine their income. That is why they are pressed to attract more passengers and drive faster than they should, which can tremendously affect their risky behaviours [ 7 ]. A body of related research also reported a high rate of risky behaviours, unauthorized speeding, overtaking, stopping mid-street for passengers, giving a lift to passengers while moving, fast and recurrent changing of lanes and unauthorized distance from the car ahead of them [ 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of safe driving Behaviours based on health belief model: the case of taxi drivers in Bandar Abbas, Iran

et al. 2018

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BackgroundRoad accidents are among the main causes of mortality. As safe and secure driving is a key strategy to reduce car injuries and offenses, the present research aimed to explore safe driving behaviours among taxi drivers based on the Health Belief Model (HBM).MethodsThis study was conducted on 184 taxi drivers in Bandar Abbas who were selected based on a multiple stratified sampling method. Data were collected by a questionnaire comprised of a demographic information section along with the constructs of the HBM. Data were analysed by SPSS ver19 via a Pearson’s correlation coefficient and multiple regressions.ResultsThe mean age of the participants was 45.1 years (SD = 11.1). They all had, on average, 10.3 (SD = 7/5) years of taxi driving experience. Among the HBM components, cues to action and perceived benefits were shown to be positively correlated with safe driving behaviours, while perceived barriers were negatively correlated. Cues to action, perceived barriers and perceived benefits were shown to be the strongest predictors of a safe drivers’ behaviour.ConclusionsBased on the results of this study in designing health promotion programmes to improve safe driving behaviours among taxi drivers, cues to action, perceived benefits and perceived barriers are important. Therefore, advertising, the design of information campaigns, emphasis on the benefits of safe driving behaviours and modification barriers are recommended.

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Section: Introductionmentioning

confidence: 99%

Prediction of safe driving Behaviours based on health belief model: the case of taxi drivers in Bandar Abbas, Iran

et al. 2018

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“…The earlier literature discussed the problems of informal operations, including poor safety, environmental, and passenger comfort track records, and various ways of regulating or formalising them (e.g. Cervero and Golub, 2007;EMBARQ, 2014). However more recently much more focus has been put on gradual efforts at paratransit upgrading, leading to the idea of hybrid public transport systems where formal and informal systems co-exist even while incremental improvements are sought (Salazar Ferro et al, 2013).…”

Section: Hybrid Public Transport Operationsmentioning

confidence: 99%

Mixing the formal with the informal in shared right-of-way systems: A simulation-based case study in Tshwane, South Africa

preez¹,

Venter²

2022

Case Studies on Transport Policy

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“…Taxis have a significant effect on traffic, as shown in the following references. In [18], a study in Nanjing, China, identifies the percentage of taxis and cars that were involved in one of the following risk-taking behaviors: failure to yield the right-of-way, sudden lane change, inadequate stop, unnecessary passing, and failure to stay in lane. In these five situations, taxis' percentage was greater than that of cars.…”

Section: Taxismentioning

confidence: 99%

Impact of Buses, Taxis, Passenger Cars, and Traffic Infrastructure on Average Travel Speed

Carrillo-González

Ortega

Sandoval-Gutierrez

et al. 2021

Journal of Advanced Transportation

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It is known that many variables influence traffic, yet very little is known about the weight of each factor in the dynamics of traffic in cities of developing countries, in many cases due to their peculiar traffic regulations. In this work, we search for the variables that have the most significant impact on the average travel speed of three distinct types of vehicles: passenger cars, taxis, and buses. First, we developed a tool featuring algorithms that simulate ordinary overtaking and car-following behaviors, along with controls for setting vehicles’ actions, particularly buses’ and taxis’ stops. Then, we chose a particular zone to study, based on its common geometry and the particular traffic infrastructure (speed bumps, traffic lights, and bus stops) inside it. Later on, three experiments were carried out, with the following results. (1) Both the buses’ arrival frequency and curbside bus stops affect the passenger cars’ average travel speed. The buses’ response was affected by the bus bay and curbside bus stops. The buses’ speed tendency influenced neither the passenger cars’ nor buses’ response. (2) Taxis’ arrival frequency, stopping frequency, and speed tendency were found to influence the passenger cars’ response. Taxis’ response was altered by taxis’ speed tendency, while buses’ response was affected by taxis’ arrival frequencies. (3) The number of speed bumps, the arrival frequency of passenger cars, and their speed conditions (homogeneous and heterogeneous) affect the passenger cars’ response. We expect that the findings presented in this study, along with the recommendations made from the results, may pave the way for better road design public policies.

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Effects of behavioral characteristics of taxi drivers on safety and capacity of signalized intersections

Cited by 12 publications

References 12 publications

Prediction of safe driving Behaviours based on health belief model: the case of taxi drivers in Bandar Abbas, Iran

Prediction of safe driving Behaviours based on health belief model: the case of taxi drivers in Bandar Abbas, Iran

Mixing the formal with the informal in shared right-of-way systems: A simulation-based case study in Tshwane, South Africa

Impact of Buses, Taxis, Passenger Cars, and Traffic Infrastructure on Average Travel Speed

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