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General Overview

EICS Framework


Region of Reference

  • AfricaAfrica
  • AsiaAsia
  • AustraliaAustralia
  • EuropeEurope
  • North-AmericaNorth-America
  • South-AmericaSouth-America
  • WorldWorld


This intervention refers to the development of mechanisms that aid in the decrease of waiting time at public transit stations. Public transport services are exposed to many sources of uncertainty linked to traffic conditions, public transport operations, and passenger demand. Passenger waiting time at stops is thus a randomised variable sensitive to day-to-day changes and the interactions between vehicle and passenger stochastic arrival processes [4].

Modern technologies can be used to ensure that services run to schedule but also to warn users about delays or system disruptions. Real-time passenger information involving expected vehicle arrival times is proven to lower the perceived waiting time, as well as the actual time passengers need to wait at stops [5,6].

It has been found that waiting time depends on many factors, such as the level of traffic along designated routes, the overall transit system speed (i.e. dedicated lanes) and the mobility of transit modes during the trip [1]. Improved service levels and reduced waiting times can bring travel time benefits without the need for capital investment [7].

Waiting at stops, especially at night is a key concern for women when travelling and they also value the reliability of service schedules highly. The delays and long waiting times can cause much financial loss for public transport users and increases the risk to be exposed to criminals, including the risk of experiencing sexual harassment. Managing the transport system in such a way that travel and waiting times are minimised, therefore improving the users' experience and reducing the risk of sexual harassment and assault.

Types of Impact

Area Impacted

  • To/from the stop/station/rank
  • Waiting for train/bus/paratransit
  • In the vehicle
  • At interchanges
This intervention would impact areas where users wait for public transport, this includes both formal and informal transport modes. Therefore, this intervention would not impact areas to and from stations and the in-vehicle experience.

Time of Day of Impact

  • Day-time travel
  • Night-time travel
  • Peak-time travel
  • Off peak-time travel
All travel time categories could be positively impacted by this intervention, depending on the scale of implementation. This is especially true for peak-hour travel, as this intervention has the potential to cut waiting and travel times.

Mode Impacted

  • Bus
  • Train
  • Rideshare
  • 4 wheelers informal
  • 3 wheelers informal
  • 2 wheelers informal
  • Cycling
  • Walking
Modes with formal and informal infrastructure and stations/stops will be impacted. Cycling and walking are transport modes that the user controls in terms of start time, therefore will not be impacted by interventions to reduce waiting time.

Demographic impacted

  • Girls
  • Boys
  • Adult Women
  • Men
  • Elderly Women
All public transport users could be positively impacted by this intervention, this could result in reduced travel time for all affected passengers, regardless of their demographic.

SWOT Analysis

  • Improvement in user experience, due to reduced waiting time

  • Convenient and fast to implement

  • reduce opportunities for any crime (not just sexual harassment)

  • As soon as implementation stops, the benefits stop

  • Budget restrictions may limit expenditure

  • Improved safety for women, spend less time at stops

  • Reduction in delays

  • High security and mental assurance to public transport users

  • Not addressing personal safety issues may lead to reduced attractiveness of the service, leading to a decline in patronage


This intervention can be very effective as it improves user safety, particularly at stops that may not be safe to use at certain times. Based on the literature, we are confident that females and governing bodies will be pleased with the improvements.

  • Perception by (female) passengers
  • Perception by governing bodies
  • Level of confidence in these ratings


Implementing this intervention may take time depending on the solution employed. Benefits arise while the intervention is carried out and continue to accumulate as passengers are exposed to it.

Implementation timeframe

  • 0-1 year
  • 1-3 years
  • >3 years

Timeframe to realise benefits

  • 0-1 year
  • 1-3 years
  • >3 years

Scale of Implementation

This intervention can be implemented at a station/suburb or city level.

Station or

Ease of Implementation

This intervention takes can take a significant amount of effort to implement, and it may take some time to implement and see the benefits.

List of References



1. Shtayat A, Abu Alfoul M, Moridpour S, Al-Hurr N, Magableh K, Harahsheh I. Waiting Time of Public Transport Passengers in Jordan: Magnitude and Cost. Open Transp J. 2020;13(1):227-235. doi:10.2174/1874447801913010227

2. Vanderschuren M., Phayane S. and Allen H. (2015), Is South Africa’s Transport System Constitutional? Analysis of transport demand and supply challenges, 1st South African Homicide Research Colloquium, Cape Town, 3-4 September 2015



3. Chowdhury S, van Wee B. Examining women’s perception of safety during waiting times at public transport terminals. Transp Policy. 2020;94(September 2019):102-108. doi:10.1016/j.tranpol.2020.05.009



4. Cats O, Gkioulou Z. Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty. EURO J Transp Logist. 2017;6(3):247-270. doi:10.1007/s13676-014-0070-4

5. Mishalani RG, McCord MM WJ. Passenger wait time perceptions at bus stops: empirical results and impacts on evaluating real-time bus arrival information. Public Transp. 2006;9(2):89-106.

6. Dziekan K KK. Dynamic at-stop real-time information displays for public transport: effects on customers. Transp Res Part A. 2007;(14):335-350.

7. Transport Research Board Standing Committee AME40 (2021), Challenges and Future Possibilities – Improving “Informal” Public Transport in Developing Countries, Virtual Workshop Report, 20 May 2021.